From 94e151c5a4fb43b0df63e198dd09fdf15c8a54f8 Mon Sep 17 00:00:00 2001 From: "github-classroom[bot]" <66690702+github-classroom[bot]@users.noreply.github.com> Date: Fri, 1 Mar 2024 01:05:08 +0000 Subject: [PATCH 1/8] Setting up GitHub Classroom Feedback From d52859c9dd8b76f4663516e5fe6217f94654ffb4 Mon Sep 17 00:00:00 2001 From: Samikshya Pantha Date: Sun, 3 Mar 2024 14:01:27 -0600 Subject: [PATCH 2/8] Imported cloud data and created subsets --- Assignment1.ipynb | 2813 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 2813 insertions(+) create mode 100644 Assignment1.ipynb diff --git a/Assignment1.ipynb b/Assignment1.ipynb new file mode 100644 index 0000000..8f2ed3c --- /dev/null +++ b/Assignment1.ipynb @@ -0,0 +1,2813 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 142, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a dataset that contains the monthly means of Sea Surface Temperature anomalies and total column water vapor from Jan 1979-Dec 2023 over the Pacific Basin (65°N to 65°S, 120°E to 60°W)\n", + " #masked out over land - save this to your computer.\n", + " #Plot maps of the mean SST and mean total column water vapor for the entire period of record." + ] + }, + { + "cell_type": "code", + "execution_count": 143, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\spantha\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\distributed\\node.py:182: UserWarning: Port 5555 is already in use.\n", + "Perhaps you already have a cluster running?\n", + "Hosting the HTTP server on port 62564 instead\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 143, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from dask.distributed import Client, progress\n", + "client = Client(dashboard_address=':5555') \n", + "client" + ] + }, + { + "cell_type": "code", + "execution_count": 144, + "metadata": {}, + "outputs": [], + "source": [ + "# Import libraries\n", + "\n", + "import xarray as xr\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": 145, + "metadata": {}, + "outputs": [], + "source": [ + "filename = 'era5data_pacificbasin_sst_vapor.nc'\n", + "\n", + "if os.path.exists(filename):\n", + " # Read saved data\n", + " ds= xr.open_dataset(filename)\n", + "\n", + "else:\n", + " # Pull the data only if not available locally\n", + " ds = xr.open_dataset('https://thredds.rda.ucar.edu/thredds/dodsC/aggregations/g/ds633.1/2/TP',\n", + " chunks={'time':'500MB'})\n", + "\n", + " variables = ['Total_column_water_vapour_surface_Mixed_intervals_Average',\n", + " 'Sea_surface_temperature_surface_Mixed_intervals_Average']\n", + " #select the two needed variables every 4th point to get 1 degree resolution\n", + " ds = ds[variables].sel(lat=slice(65, -65, 4), lon=slice(120, 300, 4))\n", + " ds.to_netcdf(filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 146, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "Dimensions:                                                    (time: 516,\n",
+       "                                                                lat: 130,\n",
+       "                                                                lon: 181)\n",
+       "Coordinates:\n",
+       "  * lat                                                        (lat) float32 ...\n",
+       "  * lon                                                        (lon) float32 ...\n",
+       "  * time                                                       (time) datetime64[ns] ...\n",
+       "    reftime                                                    (time) datetime64[ns] ...\n",
+       "Data variables:\n",
+       "    Total_column_water_vapour_surface_Mixed_intervals_Average  (time, lat, lon) float32 ...\n",
+       "    Sea_surface_temperature_surface_Mixed_intervals_Average    (time, lat, lon) float32 ...\n",
+       "Attributes:\n",
+       "    Originating_or_generating_Center:     European Centre for Medium Range We...\n",
+       "    Originating_or_generating_Subcenter:  0\n",
+       "    GRIB_table_version:                   0,128\n",
+       "    file_format:                          GRIB-1\n",
+       "    Conventions:                          CF-1.6\n",
+       "    history:                              Read using CDM IOSP GribCollection v3\n",
+       "    featureType:                          GRID\n",
+       "    _CoordSysBuilder:                     ucar.nc2.dataset.conv.CF1Convention
" + ], + "text/plain": [ + "\n", + "Dimensions: (time: 516,\n", + " lat: 130,\n", + " lon: 181)\n", + "Coordinates:\n", + " * lat (lat) float32 ...\n", + " * lon (lon) float32 ...\n", + " * time (time) datetime64[ns] ...\n", + " reftime (time) datetime64[ns] ...\n", + "Data variables:\n", + " Total_column_water_vapour_surface_Mixed_intervals_Average (time, lat, lon) float32 ...\n", + " Sea_surface_temperature_surface_Mixed_intervals_Average (time, lat, lon) float32 ...\n", + "Attributes:\n", + " Originating_or_generating_Center: European Centre for Medium Range We...\n", + " Originating_or_generating_Subcenter: 0\n", + " GRIB_table_version: 0,128\n", + " file_format: GRIB-1\n", + " Conventions: CF-1.6\n", + " history: Read using CDM IOSP GribCollection v3\n", + " featureType: GRID\n", + " _CoordSysBuilder: ucar.nc2.dataset.conv.CF1Convention" + ] + }, + "execution_count": 146, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ds" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Jan 1979-Dec 2023" + ] + }, + { + "cell_type": "code", + "execution_count": 147, + "metadata": {}, + "outputs": [], + "source": [ + "ds_mean = ds.mean(dim=['time'])" + ] + }, + { + "cell_type": "code", + "execution_count": 148, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.Dataset>\n",
+       "Dimensions:                                                    (lat: 130,\n",
+       "                                                                lon: 181)\n",
+       "Coordinates:\n",
+       "  * lat                                                        (lat) float32 ...\n",
+       "  * lon                                                        (lon) float32 ...\n",
+       "Data variables:\n",
+       "    Total_column_water_vapour_surface_Mixed_intervals_Average  (lat, lon) float32 ...\n",
+       "    Sea_surface_temperature_surface_Mixed_intervals_Average    (lat, lon) float32 ...
" + ], + "text/plain": [ + "\n", + "Dimensions: (lat: 130,\n", + " lon: 181)\n", + "Coordinates:\n", + " * lat (lat) float32 ...\n", + " * lon (lon) float32 ...\n", + "Data variables:\n", + " Total_column_water_vapour_surface_Mixed_intervals_Average (lat, lon) float32 ...\n", + " Sea_surface_temperature_surface_Mixed_intervals_Average (lat, lon) float32 ..." + ] + }, + "execution_count": 148, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ds_mean" + ] + }, + { + "cell_type": "code", + "execution_count": 149, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Dimensions: (latitude: 721, longitude: 1440, time: 1)\n", + "Coordinates:\n", + " * latitude (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n", + " * longitude (longitude) float64 0.0 0.25 0.5 0.75 ... 359.0 359.2 359.5 359.8\n", + " * time (time) datetime64[ns] 1979-01-01\n", + "Data variables:\n", + " utc_date (time) int32 ...\n", + " LSM (time, latitude, longitude) float32 ...\n", + "Attributes:\n", + " _NCProperties: version=1|netcdflibversion=4.6.1|hdf5lib...\n", + " DATA_SOURCE: ECMWF: https://cds.climate.copernicus.eu...\n", + " NETCDF_CONVERSION: CISL RDA: Conversion from ECMWF GRIB1 da...\n", + " NETCDF_VERSION: 4.6.1\n", + " CONVERSION_PLATFORM: Linux casper04 3.10.0-693.21.1.el7.x86_6...\n", + " CONVERSION_DATE: Mon May 13 18:10:35 MDT 2019\n", + " Conventions: CF-1.6\n", + " NETCDF_COMPRESSION: NCO: Precision-preserving compression to...\n", + " history: Mon May 13 18:10:35 2019: ncks -4 --ppc ...\n", + " NCO: netCDF Operators version 4.7.4 (http://n...\n", + " DODS_EXTRA.Unlimited_Dimension: time\n" + ] + } + ], + "source": [ + "\n", + "\n", + "url = \"https://thredds.rda.ucar.edu/thredds/dodsC/files/g/ds633.0/e5.oper.invariant/197901/e5.oper.invariant.128_172_lsm.ll025sc.1979010100_1979010100.nc\"\n", + "\n", + "ds_lsm = xr.open_dataset(url)\n", + "print(ds_lsm)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 150, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "Dimensions:    (latitude: 721, longitude: 1440, time: 1)\n",
+       "Coordinates:\n",
+       "  * latitude   (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n",
+       "  * longitude  (longitude) float64 0.0 0.25 0.5 0.75 ... 359.0 359.2 359.5 359.8\n",
+       "  * time       (time) datetime64[ns] 1979-01-01\n",
+       "Data variables:\n",
+       "    utc_date   (time) int32 ...\n",
+       "    LSM        (time, latitude, longitude) float32 ...\n",
+       "Attributes:\n",
+       "    _NCProperties:                   version=1|netcdflibversion=4.6.1|hdf5lib...\n",
+       "    DATA_SOURCE:                     ECMWF: https://cds.climate.copernicus.eu...\n",
+       "    NETCDF_CONVERSION:               CISL RDA: Conversion from ECMWF GRIB1 da...\n",
+       "    NETCDF_VERSION:                  4.6.1\n",
+       "    CONVERSION_PLATFORM:             Linux casper04 3.10.0-693.21.1.el7.x86_6...\n",
+       "    CONVERSION_DATE:                 Mon May 13 18:10:35 MDT 2019\n",
+       "    Conventions:                     CF-1.6\n",
+       "    NETCDF_COMPRESSION:              NCO: Precision-preserving compression to...\n",
+       "    history:                         Mon May 13 18:10:35 2019: ncks -4 --ppc ...\n",
+       "    NCO:                             netCDF Operators version 4.7.4 (http://n...\n",
+       "    DODS_EXTRA.Unlimited_Dimension:  time
" + ], + "text/plain": [ + "\n", + "Dimensions: (latitude: 721, longitude: 1440, time: 1)\n", + "Coordinates:\n", + " * latitude (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n", + " * longitude (longitude) float64 0.0 0.25 0.5 0.75 ... 359.0 359.2 359.5 359.8\n", + " * time (time) datetime64[ns] 1979-01-01\n", + "Data variables:\n", + " utc_date (time) int32 ...\n", + " LSM (time, latitude, longitude) float32 ...\n", + "Attributes:\n", + " _NCProperties: version=1|netcdflibversion=4.6.1|hdf5lib...\n", + " DATA_SOURCE: ECMWF: https://cds.climate.copernicus.eu...\n", + " NETCDF_CONVERSION: CISL RDA: Conversion from ECMWF GRIB1 da...\n", + " NETCDF_VERSION: 4.6.1\n", + " CONVERSION_PLATFORM: Linux casper04 3.10.0-693.21.1.el7.x86_6...\n", + " CONVERSION_DATE: Mon May 13 18:10:35 MDT 2019\n", + " Conventions: CF-1.6\n", + " NETCDF_COMPRESSION: NCO: Precision-preserving compression to...\n", + " history: Mon May 13 18:10:35 2019: ncks -4 --ppc ...\n", + " NCO: netCDF Operators version 4.7.4 (http://n...\n", + " DODS_EXTRA.Unlimited_Dimension: time" + ] + }, + "execution_count": 150, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ds_lsm" + ] + }, + { + "cell_type": "code", + "execution_count": 151, + "metadata": {}, + "outputs": [], + "source": [ + "ds_lsm = ds_lsm.sel(latitude=slice(65, -65, 4), longitude=slice(120, 300, 4))\n", + "\n", + "ds_lsm = ds_lsm.mean(dim=['time'])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 155, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "Dimensions:                                                    (lat: 130,\n",
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+       "  * lat                                                        (lat) float32 ...\n",
+       "  * lon                                                        (lon) float32 ...\n",
+       "Data variables:\n",
+       "    Total_column_water_vapour_surface_Mixed_intervals_Average  (lat, lon) float32 ...\n",
+       "    Sea_surface_temperature_surface_Mixed_intervals_Average    (lat, lon) float32 ...
" + ], + "text/plain": [ + "\n", + "Dimensions: (lat: 130,\n", + " lon: 181)\n", + "Coordinates:\n", + " * lat (lat) float32 ...\n", + " * lon (lon) float32 ...\n", + "Data variables:\n", + " Total_column_water_vapour_surface_Mixed_intervals_Average (lat, lon) float32 ...\n", + " Sea_surface_temperature_surface_Mixed_intervals_Average (lat, lon) float32 ..." + ] + }, + "execution_count": 153, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ds_mean" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "a =ds_mean.iloc[::4,'Total_column_water_vapour_surface_Mixed_intervals_Average', ]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ds_mean_lsm = ds_mean.where(ds_lsm.LSM ==0)\n", + "\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From d7b71c3991462befe84dd836096c382428b7da93 Mon Sep 17 00:00:00 2001 From: Samikshya Pantha Date: Fri, 8 Mar 2024 23:17:20 -0600 Subject: [PATCH 3/8] Plot maps of the mean SST and mean total column water vapor --- Module4_Question1.ipynb | 2952 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 2952 insertions(+) create mode 100644 Module4_Question1.ipynb diff --git a/Module4_Question1.ipynb b/Module4_Question1.ipynb new file mode 100644 index 0000000..ce0a0a2 --- /dev/null +++ b/Module4_Question1.ipynb @@ -0,0 +1,2952 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a dataset that contains the monthly means of Sea Surface Temperature anomalies and total column water vapor from Jan 1979-Dec 2023 over the Pacific Basin (65°N to 65°S, 120°E to 60°W)\n", + " #masked out over land - save this to your computer.\n", + " #Plot maps of the mean SST and mean total column water vapor for the entire period of record." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from dask.distributed import Client, progress\n", + "client = Client(dashboard_address=':5555') \n", + "client" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# Import libraries\n", + "\n", + "import xarray as xr\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "degree_step_size= 4" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "filename = 'era5data_pacificbasin_sst_vapor.nc'\n", + "\n", + "if os.path.exists(filename):\n", + " # Read saved data\n", + " ds= xr.open_dataset(filename)\n", + "\n", + "else:\n", + " # Pull the data only if not available locally\n", + " ds = xr.open_dataset('https://thredds.rda.ucar.edu/thredds/dodsC/aggregations/g/ds633.1/2/TP',\n", + " chunks={'time':'500MB'})\n", + "\n", + " #variables = ['Total_column_water_vapour_surface_Mixed_intervals_Average','Sea_surface_temperature_surface_Mixed_intervals_Average']\n", + " \n", + " #select the two needed variables every 4th point to get 1 degree resolution\n", + " #ds = ds[variables].sel(lat=slice(65, -65, degree_step_size), lon=slice(120, 300, degree_step_size))\n", + " ds.to_netcdf(filename)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sst_avg= ds[\"Sea_surface_temperature_surface_Mixed_intervals_Average\"]/10\n", + "sst_avg" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The 95%-value is -- 29.196896\n" + ] + } + ], + "source": [ + "#Finding Sea Surface Temp anomalies\n", + "#import pandas as pd\n", + "\n", + "sst_avg_mean_along_lat_lon = sst_avg.mean(dim= ['lon','lat'])\n", + "\n", + "sst_avg_mean_along_lat_lon.to_pandas()\n", + "ninety_five_percentile_sst = np.percentile(sst_avg_mean_along_lat_lon.to_pandas().to_numpy(), 95, method=\"inverted_cdf\")\n", + "print(\"The 95%-value is --\", ninety_five_percentile_sst)" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "Coordinates:\n",
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+       "  * lon      (lon) float64 1kB 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n",
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sst_avg_mean_along_time.where(ds_lsm <1, drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 138, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "lonW = 120\n", + "lonE = 300\n", + "latS = -65\n", + "latN = 65\n", + "\n", + "\n", + "crs0 = ccrs.PlateCarree(central_longitude=0)\n", + "crs_pacific = ccrs.PlateCarree(central_longitude=-150)\n", + "\n", + "res = '110m'\n", + "fig = plt.figure(figsize=(11, 8.5))\n", + "ax = plt.subplot(1, 1, 1, projection=crs_pacific)\n", + "ax.set_title('Sea Surface Temperature Anomalies(°C) along Pacific Basin')\n", + "gl = ax.gridlines(\n", + " draw_labels=True, linewidth=2, color='gray', alpha=0.5, linestyle='--'\n", + ")\n", + "ax.set_extent([lonW, lonE, latS, latN], crs=crs0)\n", + "ax.coastlines(resolution=res, color='black')\n", + "lon, lat = np.meshgrid(sst_avg_lsm[\"lon\"].to_numpy(),\n", + " sst_avg_lsm[\"lat\"].to_numpy())\n", + "data = sst_avg_lsm.to_dataframe().to_numpy().reshape(lat.shape)\n", + "# print(lat.shape)\n", + "# print(lon.shape)\n", + "\n", + "dataplot = ax.contourf(lon, lat, data, transform=crs0, levels=20)\n", + "plt.colorbar(dataplot, orientation=\"horizontal\")" + ] + }, + { + "cell_type": "code", + "execution_count": 135, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "total_column_water_vapor = ds['Total_column_water_vapour_surface_Mixed_intervals_Average']\n", + "total_column_water_vapor= total_column_water_vapor.mean(dim=['time'])\n", + "total_column_water_vapor_lsm = total_column_water_vapor.where(ds_lsm<0.05, drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.Dataset> Size: 95kB\n",
+       "Dimensions:  (lat: 130, lon: 181)\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n",
+       "  * lon      (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n",
+       "Data variables:\n",
+       "    LSM      (lat, lon) float32 94kB nan nan nan nan nan ... nan nan nan nan nan
" + ], + "text/plain": [ + " Size: 95kB\n", + "Dimensions: (lat: 130, lon: 181)\n", + "Coordinates:\n", + " * lat (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n", + " * lon (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n", + "Data variables:\n", + " LSM (lat, lon) float32 94kB nan nan nan nan nan ... nan nan nan nan nan" + ] + }, + "execution_count": 136, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "total_column_water_vapor_lsm" + ] + }, + { + "cell_type": "code", + "execution_count": 141, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 141, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + " Comm: tcp://127.0.0.1:61037\n", + " \n", + " Total threads: 3\n", + "
\n", + " Dashboard: http://127.0.0.1:61041/status\n", + " \n", + " Memory: 3.95 GiB\n", + "
\n", + " Nanny: tcp://127.0.0.1:61019\n", + "
\n", + " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-x2edej9a\n", + "
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Worker: 1

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\n", + " Comm: tcp://127.0.0.1:61044\n", + " \n", + " Total threads: 3\n", + "
\n", + " Dashboard: http://127.0.0.1:61046/status\n", + " \n", + " Memory: 3.95 GiB\n", + "
\n", + " Nanny: tcp://127.0.0.1:61021\n", + "
\n", + " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-yqgyxc_j\n", + "
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Worker: 2

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\n", + " Comm: tcp://127.0.0.1:61036\n", + " \n", + " Total threads: 3\n", + "
\n", + " Dashboard: http://127.0.0.1:61039/status\n", + " \n", + " Memory: 3.95 GiB\n", + "
\n", + " Nanny: tcp://127.0.0.1:61023\n", + "
\n", + " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-zkv640vg\n", + "
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Worker: 3

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\n", + " Comm: tcp://127.0.0.1:61038\n", + " \n", + " Total threads: 3\n", + "
\n", + " Dashboard: http://127.0.0.1:61043/status\n", + " \n", + " Memory: 3.95 GiB\n", + "
\n", + " Nanny: tcp://127.0.0.1:61025\n", + "
\n", + " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-waxujn41\n", + "
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" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-03-08 19:55:54,103 - distributed.scheduler - WARNING - Worker failed to heartbeat within 300 seconds. Closing: \n", + "2024-03-08 19:55:54,107 - distributed.scheduler - WARNING - Worker failed to heartbeat within 300 seconds. Closing: \n", + "2024-03-08 19:55:54,112 - distributed.scheduler - WARNING - Received heartbeat from unregistered worker 'tcp://127.0.0.1:61038'.\n", + "2024-03-08 19:55:54,116 - distributed.scheduler - WARNING - Received heartbeat from unregistered worker 'tcp://127.0.0.1:61036'.\n", + "2024-03-08 23:58:05,816 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:61037 (pid=15720) exceeded 95% memory budget. Restarting...\n", + "2024-03-08 23:58:06,412 - distributed.nanny - WARNING - Restarting worker\n", + "2024-03-09 00:00:53,700 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:63507 (pid=15596) exceeded 95% memory budget. Restarting...\n", + "2024-03-09 00:00:54,255 - distributed.nanny - WARNING - Restarting worker\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "Task exception was never retrieved\n", + "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", + "Traceback (most recent call last):\n", + " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", + " raise AllExit()\n", + "distributed.client.AllExit\n", + "2024-03-09 00:05:46,443 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:61044 (pid=10144) exceeded 95% memory budget. Restarting...\n", + "2024-03-09 00:05:47,021 - distributed.nanny - WARNING - Restarting worker\n", + "2024-03-09 00:08:24,494 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:63557 (pid=13660) exceeded 95% memory budget. Restarting...\n", + "2024-03-09 00:08:25,249 - distributed.nanny - WARNING - Restarting worker\n", + "2024-03-09 00:11:08,814 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:63650 (pid=1488) exceeded 95% memory budget. Restarting...\n", + "2024-03-09 00:11:09,346 - distributed.nanny - WARNING - Restarting worker\n", + "2024-03-09 00:13:44,486 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:63675 (pid=16624) exceeded 95% memory budget. Restarting...\n", + "2024-03-09 00:13:45,150 - distributed.nanny - WARNING - Restarting worker\n" + ] + } + ], + "source": [ + "from dask.distributed import Client, progress\n", + "client = Client(dashboard_address=':5555') \n", + "client" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Import libraries\n", + "\n", + "import xarray as xr\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "degree_step_size= 4" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "filename = 'era5data_pacificbasin_sst_vapor.nc'\n", + "\n", + "if os.path.exists(filename):\n", + " # Read saved data\n", + " ds= xr.open_dataset(filename)\n", + "\n", + "else:\n", + " # Pull the data only if not available locally\n", + " ds = xr.open_dataset('https://thredds.rda.ucar.edu/thredds/dodsC/aggregations/g/ds633.1/2/TP',\n", + " chunks={'time':'500MB'})\n", + "\n", + " variables = ['Total_column_water_vapour_surface_Mixed_intervals_Average','Sea_surface_temperature_surface_Mixed_intervals_Average']\n", + " \n", + " #select the two needed variables every 4th point to get 1 degree resolution\n", + " ds = ds[variables].sel(lat=slice(65, -65, degree_step_size), lon=slice(120, 300, degree_step_size))\n", + " ds.to_netcdf(filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "Dimensions:                                                    (time: 516,\n",
+       "                                                                lat: 130,\n",
+       "                                                                lon: 181)\n",
+       "Coordinates:\n",
+       "  * lat                                                        (lat) float32 520B ...\n",
+       "  * lon                                                        (lon) float32 724B ...\n",
+       "  * time                                                       (time) datetime64[ns] 4kB ...\n",
+       "    reftime                                                    (time) datetime64[ns] 4kB dask.array<chunksize=(516,), meta=np.ndarray>\n",
+       "Data variables:\n",
+       "    Total_column_water_vapour_surface_Mixed_intervals_Average  (time, lat, lon) float32 49MB dask.array<chunksize=(120, 130, 181), meta=np.ndarray>\n",
+       "    Sea_surface_temperature_surface_Mixed_intervals_Average    (time, lat, lon) float32 49MB dask.array<chunksize=(120, 130, 181), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    Originating_or_generating_Center:     European Centre for Medium Range We...\n",
+       "    Originating_or_generating_Subcenter:  0\n",
+       "    GRIB_table_version:                   0,128\n",
+       "    file_format:                          GRIB-1\n",
+       "    Conventions:                          CF-1.6\n",
+       "    history:                              Read using CDM IOSP GribCollection v3\n",
+       "    featureType:                          GRID\n",
+       "    _CoordSysBuilder:                     ucar.nc2.dataset.conv.CF1Convention
" + ], + "text/plain": [ + " Size: 97MB\n", + "Dimensions: (time: 516,\n", + " lat: 130,\n", + " lon: 181)\n", + "Coordinates:\n", + " * lat (lat) float32 520B ...\n", + " * lon (lon) float32 724B ...\n", + " * time (time) datetime64[ns] 4kB ...\n", + " reftime (time) datetime64[ns] 4kB dask.array\n", + "Data variables:\n", + " Total_column_water_vapour_surface_Mixed_intervals_Average (time, lat, lon) float32 49MB dask.array\n", + " Sea_surface_temperature_surface_Mixed_intervals_Average (time, lat, lon) float32 49MB dask.array\n", + "Attributes:\n", + " Originating_or_generating_Center: European Centre for Medium Range We...\n", + " Originating_or_generating_Subcenter: 0\n", + " GRIB_table_version: 0,128\n", + " file_format: GRIB-1\n", + " Conventions: CF-1.6\n", + " history: Read using CDM IOSP GribCollection v3\n", + " featureType: GRID\n", + " _CoordSysBuilder: ucar.nc2.dataset.conv.CF1Convention" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ds" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.DataArray 'Sea_surface_temperature_surface_Mixed_intervals_Average' (\n",
+       "                                                                             time: 10,\n",
+       "                                                                             lat: 10,\n",
+       "                                                                             lon: 10)> Size: 4kB\n",
+       "dask.array<getitem, shape=(10, 10, 10), dtype=float32, chunksize=(10, 10, 10), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float32 40B 64.75 63.75 62.75 61.75 ... 57.75 56.75 55.75\n",
+       "  * lon      (lon) float32 40B 120.0 121.0 122.0 123.0 ... 127.0 128.0 129.0\n",
+       "  * time     (time) datetime64[ns] 80B 1979-01-16T12:00:00 ... 1979-10-16T12:...\n",
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+       "Attributes: (12/15)\n",
+       "    long_name:                       Sea surface temperature (Mixed_intervals...\n",
+       "    units:                           K\n",
+       "    description:                     v-component of wind\n",
+       "    grid_mapping:                    LatLon_Projection\n",
+       "    Grib_Statistical_Interval_Type:  Average\n",
+       "    Grib_Variable_Id:                VAR_98-0-128-34_L1_Imixed_S123\n",
+       "    ...                              ...\n",
+       "    Grib1_Parameter:                 34\n",
+       "    Grib1_Parameter_Name:            sst\n",
+       "    Grib1_Level_Type:                1\n",
+       "    Grib1_Level_Desc:                Ground or water surface\n",
+       "    Grib1_Interval_Type:             123\n",
+       "    Grib1_Interval_Name:             Average of N uninitialized analyses, int...
" + ], + "text/plain": [ + " Size: 4kB\n", + "dask.array\n", + "Coordinates:\n", + " * lat (lat) float32 40B 64.75 63.75 62.75 61.75 ... 57.75 56.75 55.75\n", + " * lon (lon) float32 40B 120.0 121.0 122.0 123.0 ... 127.0 128.0 129.0\n", + " * time (time) datetime64[ns] 80B 1979-01-16T12:00:00 ... 1979-10-16T12:...\n", + " reftime (time) datetime64[ns] 80B dask.array\n", + "Attributes: (12/15)\n", + " long_name: Sea surface temperature (Mixed_intervals...\n", + " units: K\n", + " description: v-component of wind\n", + " grid_mapping: LatLon_Projection\n", + " Grib_Statistical_Interval_Type: Average\n", + " Grib_Variable_Id: VAR_98-0-128-34_L1_Imixed_S123\n", + " ... ...\n", + " Grib1_Parameter: 34\n", + " Grib1_Parameter_Name: sst\n", + " Grib1_Level_Type: 1\n", + " Grib1_Level_Desc: Ground or water surface\n", + " Grib1_Interval_Type: 123\n", + " Grib1_Interval_Name: Average of N uninitialized analyses, int..." + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sst_avg= ds[\"Sea_surface_temperature_surface_Mixed_intervals_Average\"]\n", + "#sst_avg= sst_avg/10\n", + "sst_avg.head(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The 95%-value is -- 291.96896\n" + ] + } + ], + "source": [ + "#Finding Sea Surface Temp anomalies\n", + "#import pandas as pd\n", + "\n", + "sst_avg_mean_along_lat_lon = sst_avg.mean(dim= ['lon','lat'])\n", + "\n", + "sst_avg_mean_along_lat_lon.to_pandas()\n", + "ninety_five_percentile_sst = np.percentile(sst_avg_mean_along_lat_lon.to_pandas().to_numpy(), 95, method=\"inverted_cdf\")\n", + "print(\"The 95%-value is --\", ninety_five_percentile_sst)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Sea Surface Temp Along time\n", + "sst_avg_mean_along_time = sst_avg.mean(dim= ['time'])\n", + "sst_anomalies = sst_avg_mean_along_time.where(sst_avg_mean_along_time>= ninety_five_percentile_sst, drop =True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.Dataset> Size: 97kB\n",
+       "Dimensions:  (lat: 130, lon: 181)\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float64 1kB 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n",
+       "  * lon      (lon) float64 1kB 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n",
+       "Data variables:\n",
+       "    LSM      (lat, lon) float32 94kB 0.982 0.9716 0.9474 ... 0.1706 0.533 1.0
" + ], + "text/plain": [ + " Size: 97kB\n", + "Dimensions: (lat: 130, lon: 181)\n", + "Coordinates:\n", + " * lat (lat) float64 1kB 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n", + " * lon (lon) float64 1kB 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n", + "Data variables:\n", + " LSM (lat, lon) float32 94kB 0.982 0.9716 0.9474 ... 0.1706 0.533 1.0" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Land Sea Mask\n", + "\n", + "url = \"https://thredds.rda.ucar.edu/thredds/dodsC/files/g/ds633.0/e5.oper.invariant/197901/e5.oper.invariant.128_172_lsm.ll025sc.1979010100_1979010100.nc\"\n", + "\n", + "ds_lsm = xr.open_dataset(url)[[\"LSM\"]]\n", + "ds_lsm = ds_lsm.rename({\"latitude\": \"lat\", \"longitude\": \"lon\"})\n", + "\n", + "ds_lsm = ds_lsm.sel(lat=slice(64.9, -65, degree_step_size), lon=slice(120, 300, degree_step_size))\n", + "ds_lsm = ds_lsm.mean(dim=['time'])\n", + "ds_lsm" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "#Plotting the Anamalies\n", + "\n", + "import warnings\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import cartopy\n", + "from cartopy import crs as ccrs, feature as cfeature" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Jan 1979-Dec 2023" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Land Sea Mask\n", + "\n", + "url = \"https://thredds.rda.ucar.edu/thredds/dodsC/files/g/ds633.0/e5.oper.invariant/197901/e5.oper.invariant.128_172_lsm.ll025sc.1979010100_1979010100.nc\"\n", + "\n", + "ds_lsm = xr.open_dataset(url)[[\"LSM\"]]\n", + "ds_lsm = ds_lsm.rename({\"latitude\": \"lat\", \"longitude\": \"lon\"})\n", + "\n", + "ds_lsm = ds_lsm.sel(lat=slice(64.9, -65, degree_step_size), lon=slice(120, 300, degree_step_size))\n", + "ds_lsm = ds_lsm.mean(dim=['time'])\n", + "ds_lsm[\"lat\"] = sst_avg_mean_along_time[\"lat\"]\n", + "ds_lsm[\"lon\"] = sst_avg_mean_along_time[\"lon\"]\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "Data variables:\n",
+       "    LSM      (lat, lon) float32 94kB 0.982 0.9716 0.9474 ... 0.1706 0.533 1.0
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+       "                                                                             lat: 721,\n",
+       "                                                                             lon: 1440)> Size: 4MB\n",
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"execution_count": 138, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "lonW = 120\n", + "lonE = 300\n", + "latS = -65\n", + "latN = 65\n", + "\n", + "\n", + "crs0 = ccrs.PlateCarree(central_longitude=0)\n", + "crs_pacific = ccrs.PlateCarree(central_longitude=-150)\n", + "\n", + "res = '110m'\n", + "fig = plt.figure(figsize=(11, 8.5))\n", + "ax = plt.subplot(1, 1, 1, projection=crs_pacific)\n", + "ax.set_title('Sea Surface Temperature Anomalies(°C) along Pacific Basin')\n", + "gl = ax.gridlines(\n", + " draw_labels=True, linewidth=2, color='gray', alpha=0.5, linestyle='--'\n", + ")\n", + "ax.set_extent([lonW, lonE, latS, latN], crs=crs0)\n", + "ax.coastlines(resolution=res, color='black')\n", + "lon, lat = np.meshgrid(sst_avg_lsm[\"lon\"].to_numpy(),\n", + " sst_avg_lsm[\"lat\"].to_numpy())\n", + "data = sst_avg_lsm.to_dataframe().to_numpy().reshape(lat.shape)\n", + "# print(lat.shape)\n", + "# print(lon.shape)\n", + "\n", + "dataplot = ax.contourf(lon, lat, data, transform=crs0, levels=20)\n", + "plt.colorbar(dataplot, orientation=\"horizontal\")" + ] + }, + { + "cell_type": "code", + "execution_count": 135, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "total_column_water_vapor = ds['Total_column_water_vapour_surface_Mixed_intervals_Average']\n", + "total_column_water_vapor= total_column_water_vapor.mean(dim=['time'])\n", + "total_column_water_vapor_lsm = total_column_water_vapor.where(ds_lsm<0.05, drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.Dataset> Size: 95kB\n",
+       "Dimensions:  (lat: 130, lon: 181)\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n",
+       "  * lon      (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n",
+       "Data variables:\n",
+       "    LSM      (lat, lon) float32 94kB nan nan nan nan nan ... nan nan nan nan nan
" + ], + "text/plain": [ + " Size: 95kB\n", + "Dimensions: (lat: 130, lon: 181)\n", + "Coordinates:\n", + " * lat (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n", + " * lon (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n", + "Data variables:\n", + " LSM (lat, lon) float32 94kB nan nan nan nan nan ... nan nan nan nan nan" + ] + }, + "execution_count": 136, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "total_column_water_vapor_lsm" + ] + }, + { + "cell_type": "code", + "execution_count": 141, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 141, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "lonW = 120\n", + "lonE = 300\n", + "latS = -65\n", + "latN = 65\n", + "\n", + "\n", + "crs0 = ccrs.PlateCarree(central_longitude=0)\n", + "crs_pacific = ccrs.PlateCarree(central_longitude=-150)\n", + "\n", + "res = '110m'\n", + "fig = plt.figure(figsize=(11, 8.5))\n", + "ax = plt.subplot(1, 1, 1, projection=crs_pacific)\n", + "ax.set_title('Total Column Water Vapour (kgm-2) Along Pacific Basin')\n", + "gl = ax.gridlines(\n", + " draw_labels=True, linewidth=2, color='gray', alpha=0.5, linestyle='--'\n", + ")\n", + "ax.set_extent([lonW, lonE, latS, latN], crs=crs0)\n", + "ax.coastlines(resolution=res, color='black')\n", + "lon, lat = np.meshgrid(total_column_water_vapor_lsm[\"lon\"].to_numpy(),\n", + " total_column_water_vapor_lsm[\"lat\"].to_numpy())\n", + "data = total_column_water_vapor_lsm.to_dataframe().to_numpy().reshape(lat.shape)\n", + "# print(lat.shape)\n", + "# print(lon.shape)\n", + "\n", + "dataplot = ax.contourf(lon, lat, data, transform=crs0, levels=20)\n", + "plt.colorbar(dataplot, orientation=\"horizontal\")" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
<xarray.DataArray 'Sea_surface_temperature_surface_Mixed_intervals_Average' (\n",
+       "                                                                             time: 516,\n",
+       "                                                                             lat: 130,\n",
+       "                                                                             lon: 181)> Size: 49MB\n",
+       "dask.array<getitem, shape=(516, 130, 181), dtype=float32, chunksize=(120, 130, 181), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n",
+       "  * lon      (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n",
+       "  * time     (time) datetime64[ns] 4kB 1979-01-16T12:00:00 ... 2021-12-16T12:...\n",
+       "    reftime  (time) datetime64[ns] 4kB dask.array<chunksize=(516,), meta=np.ndarray>\n",
+       "Attributes: (12/15)\n",
+       "    long_name:                       Sea surface temperature (Mixed_intervals...\n",
+       "    units:                           K\n",
+       "    description:                     v-component of wind\n",
+       "    grid_mapping:                    LatLon_Projection\n",
+       "    Grib_Statistical_Interval_Type:  Average\n",
+       "    Grib_Variable_Id:                VAR_98-0-128-34_L1_Imixed_S123\n",
+       "    ...                              ...\n",
+       "    Grib1_Parameter:                 34\n",
+       "    Grib1_Parameter_Name:            sst\n",
+       "    Grib1_Level_Type:                1\n",
+       "    Grib1_Level_Desc:                Ground or water surface\n",
+       "    Grib1_Interval_Type:             123\n",
+       "    Grib1_Interval_Name:             Average of N uninitialized analyses, int...
" + ], + "text/plain": [ + " Size: 49MB\n", + "dask.array\n", + "Coordinates:\n", + " * lat (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n", + " * lon (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n", + " * time (time) datetime64[ns] 4kB 1979-01-16T12:00:00 ... 2021-12-16T12:...\n", + " reftime (time) datetime64[ns] 4kB dask.array\n", + "Attributes: (12/15)\n", + " long_name: Sea surface temperature (Mixed_intervals...\n", + " units: K\n", + " description: v-component of wind\n", + " grid_mapping: LatLon_Projection\n", + " Grib_Statistical_Interval_Type: Average\n", + " Grib_Variable_Id: VAR_98-0-128-34_L1_Imixed_S123\n", + " ... ...\n", + " Grib1_Parameter: 34\n", + " Grib1_Parameter_Name: sst\n", + " Grib1_Level_Type: 1\n", + " Grib1_Level_Desc: Ground or water surface\n", + " Grib1_Interval_Type: 123\n", + " Grib1_Interval_Name: Average of N uninitialized analyses, int..." + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sst_avg" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "metadata": {}, + "outputs": [], + "source": [ + "sst_avg= sst_avg/10" + ] + }, + { + "cell_type": "code", + "execution_count": 117, + "metadata": {}, + "outputs": [], + "source": [ + "#Finding Analomies Jan 1979-Dec 2023 \n", + "clm = (sst_avg.sel(time=slice('1979-01-01','2021-12-31')).groupby('time.month').mean(dim='time'))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 118, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\xarray\\core\\indexing.py:1430: PerformanceWarning: Slicing with an out-of-order index is generating 43 times more chunks\n", + " return self.array[key]\n" + ] + } + ], + "source": [ + "anm = (sst_avg.groupby('time.month')-clm)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.DataArray 'Sea_surface_temperature_surface_Mixed_intervals_Average' (\n",
+       "                                                                             time: 516,\n",
+       "                                                                             lat: 130,\n",
+       "                                                                             lon: 181)> Size: 49MB\n",
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+       "  * time     (time) datetime64[ns] 4kB 1979-01-16T12:00:00 ... 2021-12-16T12:...\n",
+       "    reftime  (time) datetime64[ns] 4kB dask.array<chunksize=(516,), meta=np.ndarray>\n",
+       "    month    (time) int64 4kB 1 2 3 4 5 6 7 8 9 10 11 ... 3 4 5 6 7 8 9 10 11 12
" + ], + "text/plain": [ + " Size: 49MB\n", + "dask.array\n", + "Coordinates:\n", + " * lat (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n", + " * lon (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n", + " * time (time) datetime64[ns] 4kB 1979-01-16T12:00:00 ... 2021-12-16T12:...\n", + " reftime (time) datetime64[ns] 4kB dask.array\n", + " month (time) int64 4kB 1 2 3 4 5 6 7 8 9 10 11 ... 3 4 5 6 7 8 9 10 11 12" + ] + }, + "execution_count": 119, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "anm" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": {}, + "outputs": [], + "source": [ + "# Detrending function definition\n", + "def detrend_dim(da, dim, deg=1):\n", + " # detrend along a single dimension\n", + " p = da.polyfit(dim=dim, deg=deg)\n", + " fit = xr.polyval(da[dim], p.polyfit_coefficients)\n", + " return da - fit\n", + "\n", + "# Your dataset is called anm\n", + "# Perform detrending\n", + "detrended_anm = detrend_dim(anm, dim='time', deg=1)\n", + "detrended_anm_SD = detrended_anm/detrended_anm.std(dim='time').compute()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [], + "source": [ + "3) Perform an EOF analysis (with cosine latitude weighting) on the SST anomalies and plot a map of the first 5 EOFs.\n", + "from eofs.xarray import Eof\n", + "from eofs.examples import example_data_path" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Create an EOF solver to do the EOF analysis. Square-root of cosine of\n", + "# latitude weights are applied before the computation of EOFs.\n", + "coslat = np.cos(np.deg2rad(detrended_anm_SD.coords['lat'].values))\n", + "wgts = np.sqrt(coslat)[..., np.newaxis]\n", + "solver = Eof(detrended_anm_SD, weights=wgts)\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.2" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From e2d1355db8fb7f169c0f3ca3827bb28d265f8ed3 Mon Sep 17 00:00:00 2001 From: Samikshya Pantha Date: Sat, 9 Mar 2024 11:11:42 -0600 Subject: [PATCH 5/8] Performed EOFs Analysis on SST Anomalies --- Module4_Part2.ipynb | 628 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 628 insertions(+) create mode 100644 Module4_Part2.ipynb diff --git a/Module4_Part2.ipynb b/Module4_Part2.ipynb new file mode 100644 index 0000000..dcd2117 --- /dev/null +++ b/Module4_Part2.ipynb @@ -0,0 +1,628 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "import cartopy.crs as ccrs\n", + "import cartopy.feature as cfeature\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import xarray as xr\n", + "import warnings\n", + "\n", + "from eofs.xarray import Eof\n", + "warnings.filterwarnings(\"ignore\")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.DataArray (time: 516, lat: 130, lon: 181)> Size: 97MB\n",
+       "[12141480 values with dtype=float64]\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n",
+       "  * lon      (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n",
+       "  * time     (time) datetime64[ns] 4kB 1979-01-16T12:00:00 ... 2021-12-16T12:...\n",
+       "    reftime  (time) datetime64[ns] 4kB ...\n",
+       "    month    (time) int64 4kB ...
" + ], + "text/plain": [ + " Size: 97MB\n", + "[12141480 values with dtype=float64]\n", + "Coordinates:\n", + " * lat (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n", + " * lon (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n", + " * time (time) datetime64[ns] 4kB 1979-01-16T12:00:00 ... 2021-12-16T12:...\n", + " reftime (time) datetime64[ns] 4kB ...\n", + " month (time) int64 4kB ..." + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sst= xr.open_dataarray(\"detrended_anm_SD.nc\")\n", + "sst\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Create an EOF solver to do the EOF analysis. Square-root of cosine of\n", + "# latitude weights are applied before the computation of EOFs.\n", + "coslat = np.cos(np.deg2rad(sst.coords['lat'].values))\n", + "wgts = np.sqrt(coslat)[..., np.newaxis]\n", + "solver = Eof(sst, weights=wgts)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "# Retrieve the leading EOF, expressed as the correlation between the leading\n", + "# PC time series and the input SST anomalies at each grid point, and the\n", + "# leading PC time series itself.\n", + "eofs5 = solver.eofsAsCorrelation(neofs=5)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(30, 24))\n", + "\n", + "for ieof in range(5):\n", + " ax = plt.subplot(2, 3, ieof+1, projection=ccrs.PlateCarree(central_longitude=-150))\n", + " fill = eofs5[ieof].plot.contourf(ax=ax, levels=10, cmap=plt.cm.RdBu_r,\n", + " add_colorbar=False, transform=ccrs.PlateCarree())\n", + " ax.add_feature(cfeature.COASTLINE, color='k', edgecolor='k')\n", + " cb = plt.colorbar(fill, orientation='horizontal')\n", + " cb.set_label('correlation coefficient', fontsize=12)\n", + " ax.set_title(f'EOF{ieof+1} expressed as correlation', fontsize=16)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "varfrac = solver.varianceFraction()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(1.913573448681996e-33, 0.1928202755470871)" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the fraction of variance explained by each EOF\n", + "plt.figure(figsize=(11,6))\n", + "eof_num = range(1, 11)\n", + "plt.plot(eof_num, varfrac[0:10], linewidth=2)\n", + "plt.plot(eof_num, varfrac[0:10], linestyle='None', marker=\"o\", color='r', markersize=8)\n", + "plt.axhline(0, color='k')\n", + "plt.xticks(range(1, 11))\n", + "plt.title('Fraction of the total variance represented by each EOF')\n", + "plt.xlabel('EOF #')\n", + "plt.ylabel('Variance Fraction')\n", + "plt.xlim(1, 10)\n", + "plt.ylim(np.min(varfrac), np.max(varfrac)+0.01)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#help(solver.reconstructedField)\n", + "reconstruction = solver.reconstructedField(5)\n", + "reconstruction" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.2" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 1cb9a60db44fddc417b72bda1b9f576c9ccb36d5 Mon Sep 17 00:00:00 2001 From: Samikshya Pantha Date: Sat, 9 Mar 2024 13:25:39 -0600 Subject: [PATCH 6/8] Completed Part 6 + compiled scripts into one notebook --- Module4_Assignment.ipynb | 8736 ++++++++++++++++++++------------------ 1 file changed, 4595 insertions(+), 4141 deletions(-) diff --git a/Module4_Assignment.ipynb b/Module4_Assignment.ipynb index e56fdc6..635992a 100644 --- a/Module4_Assignment.ipynb +++ b/Module4_Assignment.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -13,7 +13,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -23,7 +23,7 @@ "
\n", "
\n", "

Client

\n", - "

Client-c1e54ded-ddac-11ee-9828-a4b1c14bb2ab

\n", + "

Client-d0297954-de42-11ee-94e0-a4b1c14bb2ab

\n", " \n", "\n", " \n", @@ -54,7 +54,7 @@ " \n", "
\n", "

LocalCluster

\n", - "

3e97a11f

\n", + "

b7a21870

\n", "
\n", " \n", "
\n", @@ -91,11 +91,11 @@ "
\n", "
\n", "

Scheduler

\n", - "

Scheduler-3452c35e-ccd4-4f66-9767-285e4b2514cd

\n", + "

Scheduler-ba858858-b15e-45af-b203-deffb43af750

\n", " \n", " \n", " \n", "
\n", - " Comm: tcp://127.0.0.1:61016\n", + " Comm: tcp://127.0.0.1:54828\n", " \n", " Workers: 4\n", @@ -137,7 +137,7 @@ " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -182,7 +182,7 @@ "
\n", - " Comm: tcp://127.0.0.1:61037\n", + " Comm: tcp://127.0.0.1:54848\n", " \n", " Total threads: 3\n", @@ -145,7 +145,7 @@ "
\n", - " Dashboard: http://127.0.0.1:61041/status\n", + " Dashboard: http://127.0.0.1:54853/status\n", " \n", " Memory: 3.95 GiB\n", @@ -153,13 +153,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:61019\n", + " Nanny: tcp://127.0.0.1:54831\n", "
\n", - " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-x2edej9a\n", + " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-891xglkw\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -227,7 +227,7 @@ "
\n", - " Comm: tcp://127.0.0.1:61044\n", + " Comm: tcp://127.0.0.1:54850\n", " \n", " Total threads: 3\n", @@ -190,7 +190,7 @@ "
\n", - " Dashboard: http://127.0.0.1:61046/status\n", + " Dashboard: http://127.0.0.1:54857/status\n", " \n", " Memory: 3.95 GiB\n", @@ -198,13 +198,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:61021\n", + " Nanny: tcp://127.0.0.1:54833\n", "
\n", - " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-yqgyxc_j\n", + " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-flt7ds7w\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -272,7 +272,7 @@ "
\n", - " Comm: tcp://127.0.0.1:61036\n", + " Comm: tcp://127.0.0.1:54847\n", " \n", " Total threads: 3\n", @@ -235,7 +235,7 @@ "
\n", - " Dashboard: http://127.0.0.1:61039/status\n", + " Dashboard: http://127.0.0.1:54851/status\n", " \n", " Memory: 3.95 GiB\n", @@ -243,13 +243,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:61023\n", + " Nanny: tcp://127.0.0.1:54835\n", "
\n", - " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-zkv640vg\n", + " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-7uiw72vc\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -321,3130 +321,12 @@ "" ], "text/plain": [ - "" + "" ] }, - "execution_count": 1, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-03-08 19:55:54,103 - distributed.scheduler - WARNING - Worker failed to heartbeat within 300 seconds. Closing: \n", - "2024-03-08 19:55:54,107 - distributed.scheduler - WARNING - Worker failed to heartbeat within 300 seconds. Closing: \n", - "2024-03-08 19:55:54,112 - distributed.scheduler - WARNING - Received heartbeat from unregistered worker 'tcp://127.0.0.1:61038'.\n", - "2024-03-08 19:55:54,116 - distributed.scheduler - WARNING - Received heartbeat from unregistered worker 'tcp://127.0.0.1:61036'.\n", - "2024-03-08 23:58:05,816 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:61037 (pid=15720) exceeded 95% memory budget. Restarting...\n", - "2024-03-08 23:58:06,412 - distributed.nanny - WARNING - Restarting worker\n", - "2024-03-09 00:00:53,700 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:63507 (pid=15596) exceeded 95% memory budget. Restarting...\n", - "2024-03-09 00:00:54,255 - distributed.nanny - WARNING - Restarting worker\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "Task exception was never retrieved\n", - "future: .wait() done, defined at c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py:2209> exception=AllExit()>\n", - "Traceback (most recent call last):\n", - " File \"c:\\ATMS523\\time-series-and-eofs-samikshyapantha\\.venv\\Lib\\site-packages\\distributed\\client.py\", line 2218, in wait\n", - " raise AllExit()\n", - "distributed.client.AllExit\n", - "2024-03-09 00:05:46,443 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:61044 (pid=10144) exceeded 95% memory budget. Restarting...\n", - "2024-03-09 00:05:47,021 - distributed.nanny - WARNING - Restarting worker\n", - "2024-03-09 00:08:24,494 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:63557 (pid=13660) exceeded 95% memory budget. Restarting...\n", - "2024-03-09 00:08:25,249 - distributed.nanny - WARNING - Restarting worker\n", - "2024-03-09 00:11:08,814 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:63650 (pid=1488) exceeded 95% memory budget. Restarting...\n", - "2024-03-09 00:11:09,346 - distributed.nanny - WARNING - Restarting worker\n", - "2024-03-09 00:13:44,486 - distributed.nanny.memory - WARNING - Worker tcp://127.0.0.1:63675 (pid=16624) exceeded 95% memory budget. Restarting...\n", - "2024-03-09 00:13:45,150 - distributed.nanny - WARNING - Restarting worker\n" - ] } ], "source": [ @@ -3455,7 +337,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ @@ -3464,12 +346,19 @@ "import xarray as xr\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", - "import os" + "import os\n", + "\n", + "import cartopy.crs as ccrs\n", + "import cartopy.feature as cfeature\n", + "import warnings\n", + "\n", + "from eofs.xarray import Eof\n", + "warnings.filterwarnings(\"ignore\")" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -3478,7 +367,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -3502,7 +391,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -3879,10 +768,10 @@ " * lat (lat) float32 520B ...\n", " * lon (lon) float32 724B ...\n", " * time (time) datetime64[ns] 4kB ...\n", - " reftime (time) datetime64[ns] 4kB dask.array<chunksize=(516,), meta=np.ndarray>\n", + " reftime (time) datetime64[ns] 4kB ...\n", "Data variables:\n", - " Total_column_water_vapour_surface_Mixed_intervals_Average (time, lat, lon) float32 49MB dask.array<chunksize=(120, 130, 181), meta=np.ndarray>\n", - " Sea_surface_temperature_surface_Mixed_intervals_Average (time, lat, lon) float32 49MB dask.array<chunksize=(120, 130, 181), meta=np.ndarray>\n", + " Total_column_water_vapour_surface_Mixed_intervals_Average (time, lat, lon) float32 49MB ...\n", + " Sea_surface_temperature_surface_Mixed_intervals_Average (time, lat, lon) float32 49MB ...\n", "Attributes:\n", " Originating_or_generating_Center: European Centre for Medium Range We...\n", " Originating_or_generating_Subcenter: 0\n", @@ -3891,7 +780,7 @@ " Conventions: CF-1.6\n", " history: Read using CDM IOSP GribCollection v3\n", " featureType: GRID\n", - " _CoordSysBuilder: ucar.nc2.dataset.conv.CF1Convention
\n", - " Comm: tcp://127.0.0.1:61038\n", + " Comm: tcp://127.0.0.1:54849\n", " \n", " Total threads: 3\n", @@ -280,7 +280,7 @@ "
\n", - " Dashboard: http://127.0.0.1:61043/status\n", + " Dashboard: http://127.0.0.1:54855/status\n", " \n", " Memory: 3.95 GiB\n", @@ -288,13 +288,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:61025\n", + " Nanny: tcp://127.0.0.1:54837\n", "
\n", - " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-waxujn41\n", + " Local directory: C:\\Users\\SAMIKS~1\\AppData\\Local\\Temp\\dask-scratch-space\\worker-r3emoh9c\n", "
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Array Chunk
Bytes 4.03 kiB 4.03 kiB
Shape (516,) (516,)
Dask graph 1 chunks in 2 graph layers
Data type datetime64[ns] numpy.ndarray
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    • Total_column_water_vapour_surface_Mixed_intervals_Average
      (time, lat, lon)
      float32
      dask.array<chunksize=(120, 130, 181), meta=np.ndarray>
      long_name :
      Total column water vapour (Mixed_intervals Average) @ Ground or water surface
      units :
      kg m**-2
      grid_mapping :
      LatLon_Projection
      Grib_Statistical_Interval_Type :
      Average
      Grib_Variable_Id :
      VAR_98-0-128-137_L1_Imixed_S123
      Grib1_Center :
      98
      Grib1_Subcenter :
      0
      Grib1_TableVersion :
      128
      Grib1_Parameter :
      137
      Grib1_Parameter_Name :
      tcwv
      Grib1_Level_Type :
      1
      Grib1_Level_Desc :
      Ground or water surface
      Grib1_Interval_Type :
      123
      Grib1_Interval_Name :
      Average of N uninitialized analyses, intervals = (refTime, refTime + i * P2)
      \n", - " \n", - " \n", - " \n", - " \n", - "
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      Array Chunk
      Bytes 46.32 MiB 10.77 MiB
      Shape (516, 130, 181) (120, 130, 181)
      Dask graph 5 chunks in 3 graph layers
      Data type float32 numpy.ndarray
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    • Sea_surface_temperature_surface_Mixed_intervals_Average
      (time, lat, lon)
      float32
      dask.array<chunksize=(120, 130, 181), meta=np.ndarray>
      long_name :
      Sea surface temperature (Mixed_intervals Average) @ Ground or water surface
      units :
      K
      description :
      v-component of wind
      grid_mapping :
      LatLon_Projection
      Grib_Statistical_Interval_Type :
      Average
      Grib_Variable_Id :
      VAR_98-0-128-34_L1_Imixed_S123
      Grib1_Center :
      98
      Grib1_Subcenter :
      0
      Grib1_TableVersion :
      128
      Grib1_Parameter :
      34
      Grib1_Parameter_Name :
      sst
      Grib1_Level_Type :
      1
      Grib1_Level_Desc :
      Ground or water surface
      Grib1_Interval_Type :
      123
      Grib1_Interval_Name :
      Average of N uninitialized analyses, intervals = (refTime, refTime + i * P2)
      \n", - " \n", - " \n", - " \n", - " \n", - "
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      Array Chunk
      Bytes 46.32 MiB 10.77 MiB
      Shape (516, 130, 181) (120, 130, 181)
      Dask graph 5 chunks in 3 graph layers
      Data type float32 numpy.ndarray
      \n", - "       		\n", - " \n", - "\n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - "\n", - " \n", - " 181\n", - " 130\n", - " 516\n", - "\n", - "
    • lat
      PandasIndex
      PandasIndex(Index([ 64.75000762939453,  63.75000762939453,  62.75000762939453,\n",
+       "      dtype='datetime64[ns]')
    • reftime
      (time)
      datetime64[ns]
      ...
      standard_name :
      forecast_reference_time
      long_name :
      GRIB reference time
      _CoordinateAxisType :
      RunTime
      [516 values with dtype=datetime64[ns]]
    • Total_column_water_vapour_surface_Mixed_intervals_Average
      (time, lat, lon)
      float32
      ...
      long_name :
      Total column water vapour (Mixed_intervals Average) @ Ground or water surface
      units :
      kg m**-2
      grid_mapping :
      LatLon_Projection
      Grib_Statistical_Interval_Type :
      Average
      Grib_Variable_Id :
      VAR_98-0-128-137_L1_Imixed_S123
      Grib1_Center :
      98
      Grib1_Subcenter :
      0
      Grib1_TableVersion :
      128
      Grib1_Parameter :
      137
      Grib1_Parameter_Name :
      tcwv
      Grib1_Level_Type :
      1
      Grib1_Level_Desc :
      Ground or water surface
      Grib1_Interval_Type :
      123
      Grib1_Interval_Name :
      Average of N uninitialized analyses, intervals = (refTime, refTime + i * P2)
      [12141480 values with dtype=float32]
    • Sea_surface_temperature_surface_Mixed_intervals_Average
      (time, lat, lon)
      float32
      ...
      long_name :
      Sea surface temperature (Mixed_intervals Average) @ Ground or water surface
      units :
      K
      description :
      v-component of wind
      grid_mapping :
      LatLon_Projection
      Grib_Statistical_Interval_Type :
      Average
      Grib_Variable_Id :
      VAR_98-0-128-34_L1_Imixed_S123
      Grib1_Center :
      98
      Grib1_Subcenter :
      0
      Grib1_TableVersion :
      128
      Grib1_Parameter :
      34
      Grib1_Parameter_Name :
      sst
      Grib1_Level_Type :
      1
      Grib1_Level_Desc :
      Ground or water surface
      Grib1_Interval_Type :
      123
      Grib1_Interval_Name :
      Average of N uninitialized analyses, intervals = (refTime, refTime + i * P2)
      [12141480 values with dtype=float32]
    • lat
      PandasIndex
      PandasIndex(Index([ 64.75000762939453,  63.75000762939453,  62.75000762939453,\n",
        "        61.75000762939453,  60.75000762939453,  59.75000762939453,\n",
        "        58.75000762939453,  57.75000762939453,  56.75000762939453,\n",
        "        55.75000762939453,\n",
@@ -4166,10 +828,10 @@
        "       -58.24999237060547, -59.24999237060547, -60.24999237060547,\n",
        "       -61.24999237060547, -62.24999237060547, -63.24999237060547,\n",
        "       -64.24999237060547],\n",
-       "      dtype='float32', name='lat', length=130))
    • lon
      PandasIndex
      PandasIndex(Index([120.0, 121.0, 122.0, 123.0, 124.0, 125.0, 126.0, 127.0, 128.0, 129.0,\n",
+       "      dtype='float32', name='lat', length=130))
    • lon
      PandasIndex
      PandasIndex(Index([120.0, 121.0, 122.0, 123.0, 124.0, 125.0, 126.0, 127.0, 128.0, 129.0,\n",
        "       ...\n",
        "       291.0, 292.0, 293.0, 294.0, 295.0, 296.0, 297.0, 298.0, 299.0, 300.0],\n",
-       "      dtype='float32', name='lon', length=181))
    • time
      PandasIndex
      PandasIndex(DatetimeIndex(['1979-01-16 12:00:00', '1979-02-15 00:00:00',\n",
+       "      dtype='float32', name='lon', length=181))
    • time
      PandasIndex
      PandasIndex(DatetimeIndex(['1979-01-16 12:00:00', '1979-02-15 00:00:00',\n",
        "               '1979-03-16 12:00:00', '1979-04-16 00:00:00',\n",
        "               '1979-05-16 12:00:00', '1979-06-16 00:00:00',\n",
        "               '1979-07-16 12:00:00', '1979-08-16 12:00:00',\n",
@@ -4180,7 +842,7 @@
        "               '2021-07-16 12:00:00', '2021-08-16 12:00:00',\n",
        "               '2021-09-16 00:00:00', '2021-10-16 12:00:00',\n",
        "               '2021-11-16 00:00:00', '2021-12-16 12:00:00'],\n",
-       "              dtype='datetime64[ns]', name='time', length=516, freq=None))
  • Originating_or_generating_Center :
    European Centre for Medium Range Weather Forecasts (ECMWF) (RSMC)
    Originating_or_generating_Subcenter :
    0
    GRIB_table_version :
    0,128
    file_format :
    GRIB-1
    Conventions :
    CF-1.6
    history :
    Read using CDM IOSP GribCollection v3
    featureType :
    GRID
    _CoordSysBuilder :
    ucar.nc2.dataset.conv.CF1Convention
    • " + " dtype='datetime64[ns]', name='time', length=516, freq=None))
  • Originating_or_generating_Center :
    European Centre for Medium Range Weather Forecasts (ECMWF) (RSMC)
    Originating_or_generating_Subcenter :
    0
    GRIB_table_version :
    0,128
    file_format :
    GRIB-1
    Conventions :
    CF-1.6
    history :
    Read using CDM IOSP GribCollection v3
    featureType :
    GRID
    _CoordSysBuilder :
    ucar.nc2.dataset.conv.CF1Convention
    • " ], "text/plain": [ " Size: 97MB\n", @@ -4191,10 +853,10 @@ " * lat (lat) float32 520B ...\n", " * lon (lon) float32 724B ...\n", " * time (time) datetime64[ns] 4kB ...\n", - " reftime (time) datetime64[ns] 4kB dask.array\n", + " reftime (time) datetime64[ns] 4kB ...\n", "Data variables:\n", - " Total_column_water_vapour_surface_Mixed_intervals_Average (time, lat, lon) float32 49MB dask.array\n", - " Sea_surface_temperature_surface_Mixed_intervals_Average (time, lat, lon) float32 49MB dask.array\n", + " Total_column_water_vapour_surface_Mixed_intervals_Average (time, lat, lon) float32 49MB ...\n", + " Sea_surface_temperature_surface_Mixed_intervals_Average (time, lat, lon) float32 49MB ...\n", "Attributes:\n", " Originating_or_generating_Center: European Centre for Medium Range We...\n", " Originating_or_generating_Subcenter: 0\n", @@ -4206,7 +868,7 @@ " _CoordSysBuilder: ucar.nc2.dataset.conv.CF1Convention" ] }, - "execution_count": 9, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -4217,7 +879,52 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "sst_avg= ds[\"Sea_surface_temperature_surface_Mixed_intervals_Average\"]\n", + "sst_avg= sst_avg/10\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The 95%-value is -- 29.196896\n" + ] + } + ], + "source": [ + "#Finding Sea Surface Temp anomalies\n", + "#import pandas as pd\n", + "\n", + "sst_avg_mean_along_lat_lon = sst_avg.mean(dim= ['lon','lat'])\n", + "\n", + "sst_avg_mean_along_lat_lon.to_pandas()\n", + "ninety_five_percentile_sst = np.percentile(sst_avg_mean_along_lat_lon.to_pandas().to_numpy(), 95, method=\"inverted_cdf\")\n", + "print(\"The 95%-value is --\", ninety_five_percentile_sst)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "#Sea Surface Temp Along time\n", + "sst_avg_mean_along_time = sst_avg.mean(dim= ['time'])\n", + "sst_anomalies = sst_avg_mean_along_time.where(sst_avg_mean_along_time>= ninety_five_percentile_sst, drop =True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -4587,255 +1294,129 @@ " fill: currentColor;\n", "}\n", "
    <xarray.DataArray 'Sea_surface_temperature_surface_Mixed_intervals_Average' (\n",
-       "                                                                             time: 10,\n",
-       "                                                                             lat: 10,\n",
-       "                                                                             lon: 10)> Size: 4kB\n",
-       "dask.array<getitem, shape=(10, 10, 10), dtype=float32, chunksize=(10, 10, 10), chunktype=numpy.ndarray>\n",
+       "                                                                             lat: 79,\n",
+       "                                                                             lon: 181)> Size: 57kB\n",
+       "array([[      nan,       nan,       nan, ..., 29.200706, 29.226988,\n",
+       "        29.24074 ],\n",
+       "       [      nan,       nan,       nan, ..., 29.436005, 29.44704 ,\n",
+       "        29.431862],\n",
+       "       [      nan,       nan,       nan, ..., 29.569479, 29.56108 ,\n",
+       "        29.549383],\n",
+       "       ...,\n",
+       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "              nan],\n",
+       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "              nan],\n",
+       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "              nan]], dtype=float32)\n",
        "Coordinates:\n",
-       "  * lat      (lat) float32 40B 64.75 63.75 62.75 61.75 ... 57.75 56.75 55.75\n",
-       "  * lon      (lon) float32 40B 120.0 121.0 122.0 123.0 ... 127.0 128.0 129.0\n",
-       "  * time     (time) datetime64[ns] 80B 1979-01-16T12:00:00 ... 1979-10-16T12:...\n",
-       "    reftime  (time) datetime64[ns] 80B dask.array<chunksize=(10,), meta=np.ndarray>\n",
-       "Attributes: (12/15)\n",
-       "    long_name:                       Sea surface temperature (Mixed_intervals...\n",
-       "    units:                           K\n",
-       "    description:                     v-component of wind\n",
-       "    grid_mapping:                    LatLon_Projection\n",
-       "    Grib_Statistical_Interval_Type:  Average\n",
-       "    Grib_Variable_Id:                VAR_98-0-128-34_L1_Imixed_S123\n",
-       "    ...                              ...\n",
-       "    Grib1_Parameter:                 34\n",
-       "    Grib1_Parameter_Name:            sst\n",
-       "    Grib1_Level_Type:                1\n",
-       "    Grib1_Level_Desc:                Ground or water surface\n",
-       "    Grib1_Interval_Type:             123\n",
-       "    Grib1_Interval_Name:             Average of N uninitialized analyses, int...
    " + " * lat (lat) float32 316B 40.75 39.75 38.75 37.75 ... -35.25 -36.25 -37.25\n", + " * lon (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0" ], "text/plain": [ " Size: 4kB\n", - "dask.array\n", + " lat: 79,\n", + " lon: 181)> Size: 57kB\n", + "array([[ nan, nan, nan, ..., 29.200706, 29.226988,\n", + " 29.24074 ],\n", + " [ nan, nan, nan, ..., 29.436005, 29.44704 ,\n", + " 29.431862],\n", + " [ nan, nan, nan, ..., 29.569479, 29.56108 ,\n", + " 29.549383],\n", + " ...,\n", + " [ nan, nan, nan, ..., nan, nan,\n", + " nan],\n", + " [ nan, nan, nan, ..., nan, nan,\n", + " nan],\n", + " [ nan, nan, nan, ..., nan, nan,\n", + " nan]], dtype=float32)\n", "Coordinates:\n", - " * lat (lat) float32 40B 64.75 63.75 62.75 61.75 ... 57.75 56.75 55.75\n", - " * lon (lon) float32 40B 120.0 121.0 122.0 123.0 ... 127.0 128.0 129.0\n", - " * time (time) datetime64[ns] 80B 1979-01-16T12:00:00 ... 1979-10-16T12:...\n", - " reftime (time) datetime64[ns] 80B dask.array\n", - "Attributes: (12/15)\n", - " long_name: Sea surface temperature (Mixed_intervals...\n", - " units: K\n", - " description: v-component of wind\n", - " grid_mapping: LatLon_Projection\n", - " Grib_Statistical_Interval_Type: Average\n", - " Grib_Variable_Id: VAR_98-0-128-34_L1_Imixed_S123\n", - " ... ...\n", - " Grib1_Parameter: 34\n", - " Grib1_Parameter_Name: sst\n", - " Grib1_Level_Type: 1\n", - " Grib1_Level_Desc: Ground or water surface\n", - " Grib1_Interval_Type: 123\n", - " Grib1_Interval_Name: Average of N uninitialized analyses, int..." + " * lat (lat) float32 316B 40.75 39.75 38.75 37.75 ... -35.25 -36.25 -37.25\n", + " * lon (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0" ] }, - "execution_count": 20, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "sst_avg= ds[\"Sea_surface_temperature_surface_Mixed_intervals_Average\"]\n", - "#sst_avg= sst_avg/10\n", - "sst_avg.head(10)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The 95%-value is -- 291.96896\n" - ] - } - ], - "source": [ - "#Finding Sea Surface Temp anomalies\n", - "#import pandas as pd\n", - "\n", - "sst_avg_mean_along_lat_lon = sst_avg.mean(dim= ['lon','lat'])\n", - "\n", - "sst_avg_mean_along_lat_lon.to_pandas()\n", - "ninety_five_percentile_sst = np.percentile(sst_avg_mean_along_lat_lon.to_pandas().to_numpy(), 95, method=\"inverted_cdf\")\n", - "print(\"The 95%-value is --\", ninety_five_percentile_sst)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#Sea Surface Temp Along time\n", - "sst_avg_mean_along_time = sst_avg.mean(dim= ['time'])\n", - "sst_anomalies = sst_avg_mean_along_time.where(sst_avg_mean_along_time>= ninety_five_percentile_sst, drop =True)\n" + "sst_anomalies" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -5210,7 +1791,7 @@ " * lat (lat) float64 1kB 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n", " * lon (lon) float64 1kB 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n", "Data variables:\n", - " LSM (lat, lon) float32 94kB 0.982 0.9716 0.9474 ... 0.1706 0.533 1.0
    • " ], "text/plain": [ " Size: 97kB\n", @@ -5271,7 +1852,7 @@ " LSM (lat, lon) float32 94kB 0.982 0.9716 0.9474 ... 0.1706 0.533 1.0" ] }, - "execution_count": 21, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -5291,7 +1872,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -5314,7 +1895,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -5334,7 +1915,7 @@ }, { "cell_type": "code", - "execution_count": 93, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -5703,31 +2284,38 @@ " stroke: currentColor;\n", " fill: currentColor;\n", "}\n", - "
    <xarray.Dataset> Size: 97kB\n",
+       "
    <xarray.Dataset> Size: 95kB\n",
        "Dimensions:  (lat: 130, lon: 181)\n",
        "Coordinates:\n",
-       "  * lat      (lat) float64 1kB 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n",
-       "  * lon      (lon) float64 1kB 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n",
+       "  * lat      (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n",
+       "  * lon      (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n",
        "Data variables:\n",
-       "    LSM      (lat, lon) float32 94kB 0.982 0.9716 0.9474 ... 0.1706 0.533 1.0
    • " ], "text/plain": [ - " Size: 97kB\n", + " Size: 95kB\n", "Dimensions: (lat: 130, lon: 181)\n", "Coordinates:\n", - " * lat (lat) float64 1kB 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n", - " * lon (lon) float64 1kB 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n", + " * lat (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n", + " * lon (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n", "Data variables:\n", " LSM (lat, lon) float32 94kB 0.982 0.9716 0.9474 ... 0.1706 0.533 1.0" ] }, - "execution_count": 93, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -5781,7 +2373,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -6151,58 +2743,108 @@ " fill: currentColor;\n", "}\n", "
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-       "                                                                             lat: 721,\n",
-       "                                                                             lon: 1440)> Size: 4MB\n",
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    <xarray.DataArray 'Sea_surface_temperature_surface_Mixed_intervals_Average' (\n",
-       "                                                                             time: 516,\n",
-       "                                                                             lat: 130,\n",
-       "                                                                             lon: 181)> Size: 49MB\n",
-       "dask.array<sub, shape=(516, 130, 181), dtype=float32, chunksize=(1, 130, 181), chunktype=numpy.ndarray>\n",
+       "
    <xarray.DataArray (time: 516, lat: 130, lon: 181)> Size: 97MB\n",
+       "[12141480 values with dtype=float64]\n",
        "Coordinates:\n",
        "  * lat      (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n",
        "  * lon      (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n",
        "  * time     (time) datetime64[ns] 4kB 1979-01-16T12:00:00 ... 2021-12-16T12:...\n",
-       "    reftime  (time) datetime64[ns] 4kB dask.array<chunksize=(516,), meta=np.ndarray>\n",
-       "    month    (time) int64 4kB 1 2 3 4 5 6 7 8 9 10 11 ... 3 4 5 6 7 8 9 10 11 12
    • " ], "text/plain": [ - " Size: 49MB\n", - "dask.array\n", + " Size: 97MB\n", + "[12141480 values with dtype=float64]\n", "Coordinates:\n", " * lat (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n", " * lon (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n", " * time (time) datetime64[ns] 4kB 1979-01-16T12:00:00 ... 2021-12-16T12:...\n", - " reftime (time) datetime64[ns] 4kB dask.array\n", - " month (time) int64 4kB 1 2 3 4 5 6 7 8 9 10 11 ... 3 4 5 6 7 8 9 10 11 12" + " reftime (time) datetime64[ns] 4kB ...\n", + " month (time) int64 4kB ..." ] }, - "execution_count": 119, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "anm" + "#Read the SST Anomalies data\n", + "sst_anm_preproc= xr.open_dataarray(\"detrended_standarized_SST_anm.nc\")\n", + "sst_anm_preproc\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Part 3 : EOF Analysis\n" ] }, { "cell_type": "code", - "execution_count": 121, + "execution_count": 43, "metadata": {}, "outputs": [], "source": [ - "# Detrending function definition\n", - "def detrend_dim(da, dim, deg=1):\n", - " # detrend along a single dimension\n", - " p = da.polyfit(dim=dim, deg=deg)\n", - " fit = xr.polyval(da[dim], p.polyfit_coefficients)\n", - " return da - fit\n", + "# Create an EOF solver to do the EOF analysis. Square-root of cosine of\n", + "# latitude weights are applied before the computation of EOFs.\n", + "coslat = np.cos(np.deg2rad(sst_anm_preproc.coords['lat'].values))\n", + "wgts = np.sqrt(coslat)[..., np.newaxis]\n", + "solver = Eof(sst_anm_preproc, weights=wgts)\n", "\n", - "# Your dataset is called anm\n", - "# Perform detrending\n", - "detrended_anm = detrend_dim(anm, dim='time', deg=1)\n", - "detrended_anm_SD = detrended_anm/detrended_anm.std(dim='time').compute()\n" + "# Retrieve the leading EOF, expressed as the correlation between the leading\n", + "# PC time series and the input SST anomalies at each grid point, and the\n", + "# leading PC time series itself.\n", + "eofs5 = solver.eofsAsCorrelation(neofs=5)\n" ] }, { "cell_type": "code", - "execution_count": 136, + "execution_count": 44, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "3) Perform an EOF analysis (with cosine latitude weighting) on the SST anomalies and plot a map of the first 5 EOFs.\n", - "from eofs.xarray import Eof\n", - "from eofs.examples import example_data_path" + "fig = plt.figure(figsize=(30, 24))\n", + "\n", + "for ieof in range(5):\n", + " ax = plt.subplot(2, 3, ieof+1, projection=ccrs.PlateCarree(central_longitude=-150))\n", + " fill = eofs5[ieof].plot.contourf(ax=ax, levels=10, cmap=plt.cm.RdBu_r,\n", + " add_colorbar=False, transform=ccrs.PlateCarree())\n", + " ax.add_feature(cfeature.COASTLINE, color='k', edgecolor='k')\n", + " cb = plt.colorbar(fill, orientation='horizontal')\n", + " cb.set_label('correlation coefficient', fontsize=12)\n", + " ax.set_title(f'EOF{ieof+1} expressed as correlation', fontsize=16)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Part 4: Plotting the percent of variance explained by the first 10 EOFs." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 45, "metadata": {}, "outputs": [], "source": [ - "# Create an EOF solver to do the EOF analysis. Square-root of cosine of\n", - "# latitude weights are applied before the computation of EOFs.\n", - "coslat = np.cos(np.deg2rad(detrended_anm_SD.coords['lat'].values))\n", - "wgts = np.sqrt(coslat)[..., np.newaxis]\n", - "solver = Eof(detrended_anm_SD, weights=wgts)\n" + "varfrac = solver.varianceFraction()\n", + "varperc =100*varfrac" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(1.9135734486819958e-31, 18.29202755470871)" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the fraction of variance explained by each EOF\n", + "plt.figure(figsize=(11,6))\n", + "eof_num = range(1, 11)\n", + "plt.plot(eof_num, varperc[0:10], linewidth=2)\n", + "plt.plot(eof_num, varperc[0:10], linestyle='None', marker=\"o\", color='r', markersize=8)\n", + "plt.axhline(0, color='k')\n", + "plt.xticks(range(1, 11))\n", + "plt.title('Percent of the total variance represented by each EOF')\n", + "plt.xlabel('EOF #')\n", + "plt.ylabel('Variance percent')\n", + "plt.xlim(1, 10)\n", + "plt.ylim(np.min(varperc), np.max(varperc)+0.01)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Reconstruct the SST field using the first 5 EOFs and plot a map of the Pearson's correlation coefficient " + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "sst_observed = sst_avg" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "# Create an EOF solver to do the EOF analysis. Square-root of cosine of\n", + "# latitude weights are applied before the computation of EOFs.\n", + "\n", + "coslat = np.cos(np.deg2rad(sst_observed.coords['lat'].values))\n", + "wgts = np.sqrt(coslat)[..., np.newaxis]\n", + "solver = Eof(sst_observed, weights=wgts)\n", + "\n", + "# Retrieve the leading EOF, expressed as the correlation between the leading\n", + "# PC time series and the input SST anomalies at each grid point, and the\n", + "# leading PC time series itself.\n", + "eofs5 = solver.eofsAsCorrelation(neofs=5)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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    <xarray.DataArray 'Sea_surface_temperature_surface_Mixed_intervals_Average' (\n",
+       "                                                                             time: 516,\n",
+       "                                                                             lat: 130,\n",
+       "                                                                             lon: 181)> Size: 49MB\n",
+       "array([[[        nan,         nan,         nan, ..., -0.09068224,\n",
+       "         -0.10087339, -0.11487187],\n",
+       "        [        nan,         nan,         nan, ..., -0.11625043,\n",
+       "         -0.14163439, -0.18867703],\n",
+       "        [        nan,         nan,         nan, ..., -0.15437521,\n",
+       "         -0.20674725, -0.25114238],\n",
+       "        ...,\n",
+       "        [ 0.16161048,  0.167361  ,  0.1658317 , ...,  0.15639858,\n",
+       "          0.1542428 ,  0.14014205],\n",
+       "        [ 0.1512748 ,  0.15169172,  0.15075645, ...,  0.11523686,\n",
+       "          0.12548049,  0.09397514],\n",
+       "        [ 0.11951568,  0.12127689,  0.12072147, ...,  0.04766271,\n",
+       "          0.04243768,         nan]],\n",
+       "\n",
+       "       [[        nan,         nan,         nan, ..., -0.10126364,\n",
+       "         -0.10956991, -0.12170956],\n",
+       "        [        nan,         nan,         nan, ..., -0.12230431,\n",
+       "         -0.14702304, -0.20423228],\n",
+       "        [        nan,         nan,         nan, ..., -0.15918203,\n",
+       "         -0.22351593, -0.2810314 ],\n",
+       "...\n",
+       "        [-0.06368165, -0.06889395, -0.06795529, ..., -0.02418233,\n",
+       "         -0.02104509, -0.00719749],\n",
+       "        [-0.05787777, -0.05722079, -0.05479576, ...,  0.00602739,\n",
+       "          0.01544668,  0.0353695 ],\n",
+       "        [-0.04466783, -0.04248886, -0.03907751, ...,  0.0805605 ,\n",
+       "          0.03446279,         nan]],\n",
+       "\n",
+       "       [[        nan,         nan,         nan, ..., -0.02736648,\n",
+       "         -0.04639189, -0.06119855],\n",
+       "        [        nan,         nan,         nan, ..., -0.06130467,\n",
+       "         -0.07817742, -0.07281475],\n",
+       "        [        nan,         nan,         nan, ..., -0.09474733,\n",
+       "         -0.09041134, -0.03881208],\n",
+       "        ...,\n",
+       "        [ 0.03805611,  0.03413324,  0.0345646 , ...,  0.07874626,\n",
+       "          0.0791669 ,  0.08376103],\n",
+       "        [ 0.03655944,  0.03791131,  0.04048203, ...,  0.08905116,\n",
+       "          0.09889851,  0.09732071],\n",
+       "        [ 0.02950617,  0.03345724,  0.0372605 , ...,  0.12864752,\n",
+       "          0.06576088,         nan]]], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * time     (time) datetime64[ns] 4kB 1979-01-16T12:00:00 ... 2021-12-16T12:...\n",
+       "  * lat      (lat) float32 520B 64.75 63.75 62.75 61.75 ... -62.25 -63.25 -64.25\n",
+       "  * lon      (lon) float32 724B 120.0 121.0 122.0 123.0 ... 298.0 299.0 300.0\n",
+       "    reftime  (time) datetime64[ns] 4kB 1979-01-01 1979-02-01 ... 2021-12-01\n",
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+       "    long_name:  Sea_surface_temperature_surface_Mixed_intervals_Average_recon...
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}, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the leading EOF expressed as correlation in the Pacific domain.\n", + "clevs = np.linspace(-3, 3, 21)\n", + "ax = plt.axes(projection=ccrs.PlateCarree(central_longitude=-150))\n", + "fill = cor_reconstructed_vs_observed.plot.contourf(ax=ax, levels=clevs, cmap=plt.cm.RdBu_r,\n", + " add_colorbar=False, transform=ccrs.PlateCarree())\n", + "ax.add_feature(cfeature.COASTLINE, color='k', edgecolor='k')\n", + "cb = plt.colorbar(fill, orientation='horizontal')\n", + "cb.set_label('Correlation between Reconstructed vs Observed SST', fontsize=12)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + " Compute a map of the Pearson's correlation coefficient \n", + "between SST EOF1 and monthly mean detrended, deseasonalized, and standardized monthly mean column water vapor anomalies \n", + "(don't mask these over land for the plot). See anything interesting?" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "                                                                               lat: 130,\n",
+       "                                                                               lon: 181)> Size: 94kB\n",
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+       "                                                                               time: 516,\n",
+       "                                                                               lat: 130,\n",
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2021-12-01\n", + " month (time) int64 4kB 1 2 3 4 5 6 7 8 9 10 11 ... 3 4 5 6 7 8 9 10 11 12" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "detrended_anm_SD_tcwv.mean()" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the leading EOF1 expressed as correlation in the Pacific domain.\n", + "\n", + "clevs = np.linspace(-3, 3, 21)\n", + "ax = plt.axes(projection=ccrs.PlateCarree(central_longitude=-150))\n", + "fill = cor_SST_EOF1_vs_tcwv.plot.contourf(ax=ax, levels=clevs, cmap=plt.cm.RdBu_r,\n", + " add_colorbar=False, transform=ccrs.PlateCarree())\n", + "ax.add_feature(cfeature.COASTLINE, color='k', edgecolor='k')\n", + "cb = plt.colorbar(fill, orientation='horizontal')\n", + "cb.set_label('Correlation between SST_EOF1 vs Preprocessed TCWV Anomalies', fontsize=8)" ] } ], From 1e3cfa35714a79d5eb07edbcc29b5ef3d04712be Mon Sep 17 00:00:00 2001 From: Samikshya Pantha Date: Mon, 11 Mar 2024 15:16:20 -0500 Subject: [PATCH 7/8] Created Readme file and added comments to improve readability. --- Module4_Assignment.ipynb | 566 ++++----------------------------------- ReadMe.txt | 14 + 2 files changed, 64 insertions(+), 516 deletions(-) create mode 100644 ReadMe.txt diff --git a/Module4_Assignment.ipynb b/Module4_Assignment.ipynb index 635992a..79ecb80 100644 --- a/Module4_Assignment.ipynb +++ b/Module4_Assignment.ipynb @@ -1,19 +1,31 @@ { "cells": [ { - "cell_type": "code", - "execution_count": 1, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "# Create a dataset that contains the monthly means of Sea Surface Temperature anomalies and total column water vapor from Jan 1979-Dec 2023 over the Pacific Basin (65°N to 65°S, 120°E to 60°W)\n", - " #masked out over land - save this to your computer.\n", - " #Plot maps of the mean SST and mean total column water vapor for the entire period of record." + "#### Read Me\n", + "\n", + "This notebook contains code to analyze Sea Surface Temperature Anomalies and Total Column Water Vapor over the Pacific Basin. Through maps users will be able to analyse climate variability in this region.\n", + "\n", + "For this study, ERA 5 data has been fetched through UCAR Thredds Data Server. ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather. It provides hourly estimates for a large number of atmospheric and land-surface variables.\n", + "\n", + "To run this code, the user has rely on several Python libraries such as\n", + "xarray for handling multi-dimensional arrays, matplotlib for plotting, cartopy for geographical visualization, and numpy for numerical computations. \n", + "\n", + "In Part one, the SST and TCWV anomalies were plotted to illustrate the variability within the Pacific Basin.\n", + "\n", + "In Part two, SST anomalies were calcuated by substracting climatological mean from the observed SST data for each month. Detrending was applied to the SST anomalies to remove any long-term trends by fitting a polynomial function to the data.\n", + "\n", + "In Part three, four and five, EOF analysis was done to decompose the spatial patterns of SST anomalies into orthogonal modes of variability. \n", + "\n", + "\n", + "\n" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -327,6 +339,20 @@ "execution_count": 2, "metadata": {}, "output_type": "execute_result" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-03-10 14:05:33,821 - distributed.scheduler - WARNING - Worker failed to heartbeat within 300 seconds. Closing: \n", + "2024-03-10 14:05:34,615 - distributed.scheduler - WARNING - Worker failed to heartbeat within 300 seconds. Closing: \n", + "2024-03-10 14:05:34,623 - distributed.scheduler - WARNING - Received heartbeat from unregistered worker 'tcp://127.0.0.1:54847'.\n", + "2024-03-10 14:05:34,629 - distributed.scheduler - WARNING - Received heartbeat from unregistered worker 'tcp://127.0.0.1:54849'.\n", + "2024-03-10 14:06:02,420 - distributed.nanny - WARNING - Worker process still alive after 3.199655456542969 seconds, killing\n", + "2024-03-10 14:06:02,443 - distributed.nanny - WARNING - Worker process still alive after 3.1999971008300783 seconds, killing\n", + "2024-03-11 09:09:19,042 - distributed.scheduler - WARNING - Worker failed to heartbeat within 300 seconds. Closing: \n", + "2024-03-11 09:09:19,157 - distributed.scheduler - WARNING - Received heartbeat from unregistered worker 'tcp://127.0.0.1:54848'.\n" + ] } ], "source": [ @@ -348,6 +374,7 @@ "import numpy as np\n", "import os\n", "\n", + "import cartopy\n", "import cartopy.crs as ccrs\n", "import cartopy.feature as cfeature\n", "import warnings\n", @@ -358,10 +385,11 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ + "#Degree step size\n", "degree_step_size= 4" ] }, @@ -883,8 +911,9 @@ "metadata": {}, "outputs": [], "source": [ - "sst_avg= ds[\"Sea_surface_temperature_surface_Mixed_intervals_Average\"]\n", - "sst_avg= sst_avg/10\n" + "# Fetching Sea Surfave Temp\n", + "sst_avg= ds[\"Sea_surface_temperature_surface_Mixed_intervals_Average\"]/10\n", + "sst_avg" ] }, { @@ -902,10 +931,9 @@ ], "source": [ "#Finding Sea Surface Temp anomalies\n", - "#import pandas as pd\n", - "\n", "sst_avg_mean_along_lat_lon = sst_avg.mean(dim= ['lon','lat'])\n", "\n", + "#Calculate the 95th percentile of SST\n", "sst_avg_mean_along_lat_lon.to_pandas()\n", "ninety_five_percentile_sst = np.percentile(sst_avg_mean_along_lat_lon.to_pandas().to_numpy(), 95, method=\"inverted_cdf\")\n", "print(\"The 95%-value is --\", ninety_five_percentile_sst)" @@ -1870,22 +1898,6 @@ "ds_lsm" ] }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "#Plotting the Anamalies\n", - "\n", - "import warnings\n", - "\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import cartopy\n", - "from cartopy import crs as ccrs, feature as cfeature" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -2859,6 +2871,7 @@ "metadata": {}, "outputs": [], "source": [ + "# Fetch SST points only at sea\n", "sst_avg_lsm = sst_avg_mean_along_time.where(ds_lsm <1, drop=True)" ] }, @@ -2889,7 +2902,8 @@ } ], "source": [ - "\n", + "# Plot Sea Surface Temperature Anomalies\n", + "#Define plotting parameters\n", "lonW = 120\n", "lonE = 300\n", "latS = -65\n", @@ -2924,7 +2938,7 @@ "metadata": {}, "outputs": [], "source": [ - "\n", + "# Plot Total Column Water Vapor\n", "total_column_water_vapor = ds['Total_column_water_vapour_surface_Mixed_intervals_Average']\n", "total_column_water_vapor= total_column_water_vapor.mean(dim=['time'])\n", "total_column_water_vapor_lsm = total_column_water_vapor.where(ds_lsm<0.05, drop=True)" @@ -3415,6 +3429,7 @@ } ], "source": [ + "# Plot Total Column Water Vapor\n", "lonW = 120\n", "lonE = 300\n", "latS = -65\n", @@ -4069,6 +4084,7 @@ ], "source": [ "#Finding Anomalies and Climatology date range: Jan 1979-Dec 2023 \n", + "# Compute climatology\n", "clm = (sst_avg.sel(time=slice('1979-01-01','2021-12-31')).groupby('time.month').mean(dim='time'))\n", "anm = (sst_avg.groupby('time.month')-clm)\n", "anm\n" @@ -4572,7 +4588,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Part 3 : EOF Analysis\n" + "#### Part 3 : EOF Analysis\n" ] }, { @@ -4626,7 +4642,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Part 4: Plotting the percent of variance explained by the first 10 EOFs." + "#### Part 4: Plotting the percent of variance explained by the first 10 EOFs." ] }, { @@ -4684,7 +4700,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Reconstruct the SST field using the first 5 EOFs and plot a map of the Pearson's correlation coefficient " + "#### Part 5: Reconstruct the SST field using the first 5 EOFs and plot a map of the Pearson's correlation coefficient " ] }, { @@ -5862,491 +5878,9 @@ "metadata": {}, "outputs": [], "source": [ - " Compute a map of the Pearson's correlation coefficient \n", - "between SST EOF1 and monthly mean detrended, deseasonalized, and standardized monthly mean column water vapor anomalies \n", - "(don't mask these over land for the plot). See anything interesting?" + " #Compute a map of the Pearson's correlation coefficient between SST EOF1 and monthly mean detrended, deseasonalized, and standardized monthly mean column water vapor anomalies \n" ] }, - { - "cell_type": "code", - "execution_count": 55, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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