[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -1,15 +1,15 @@
 repos:
   - repo: https://github.com/kynan/nbstripout
-    rev: 0.6.1
+    rev: 0.7.1
     hooks:
     - id: nbstripout
       files: ".ipynb"
   - repo: https://github.com/psf/black
-    rev: 23.9.1
+    rev: 24.4.2
     hooks:
     - id: black
   - repo: https://github.com/pycqa/flake8
-    rev: 6.1.0
+    rev: 7.0.0
     hooks:
     - id: flake8
   - repo: https://github.com/s-weigand/flake8-nb

moralization/analyse.py

@@ -1,6 +1,7 @@
 """
 Contains statistical analysis.
 """
+
 from collections import defaultdict
 import pandas as pd
 import numpy as np

moralization/input_data.py

@@ -1,6 +1,7 @@
 """
 Module that handles input reading.
 """
+
 from cassis import load_typesystem, load_cas_from_xmi, typesystem, Cas
 import pathlib
 import importlib_resources

moralization/plot.py

@@ -1,6 +1,7 @@
 """
 Contains plotting functionality.
 """
+
 import pandas as pd
 import seaborn as sns
 import matplotlib.pyplot as plt

notebooks/DemoNotebook_spacy_model.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "17ddce3f",
+   "id": "0",
    "metadata": {
     "id": "-tIt14wg_KRi"
    },
@@ -17,7 +17,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "dec6ba0b",
+   "id": "1",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -42,7 +42,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f7ce3ad0",
+   "id": "2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a0aa6775",
+   "id": "3",
    "metadata": {},
    "source": [
     "### Import training data using DataManager\n",
@@ -64,7 +64,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "fa65a7f6",
+   "id": "4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -81,7 +81,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d0ebdd8c",
+   "id": "5",
    "metadata": {},
    "source": [
     "You can provide the language in the model initialization, as well as the task that should be trained on. Default language is German, and the default task is task1: Training for labels in category 1. The available tasks are:\n",
@@ -97,7 +97,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5508ae9c",
+   "id": "6",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -118,7 +118,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "44031c8d",
+   "id": "7",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -128,7 +128,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a988aa6b",
+   "id": "8",
    "metadata": {},
    "source": [
     "### Create a new spacy model using ModelManager\n",
@@ -153,7 +153,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b868d3d7",
+   "id": "9",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -167,22 +167,22 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c7d2c783",
+   "id": "10",
    "metadata": {},
    "source": []
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a16b05d5",
+   "id": "11",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0ec9f981",
+   "id": "12",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -191,7 +191,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e6cb68cb",
+   "id": "13",
    "metadata": {},
    "source": [
     "### Edit metadata\n",
@@ -204,7 +204,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3769b760",
+   "id": "14",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -214,7 +214,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "9701fcdb",
+   "id": "15",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -230,7 +230,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5f5172b5",
+   "id": "16",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -240,7 +240,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "961d1d2f",
+   "id": "17",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -249,7 +249,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a0059ffd",
+   "id": "18",
    "metadata": {},
    "source": [
     "### Train the model\n",
@@ -261,7 +261,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "576bdb58",
+   "id": "19",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -270,7 +270,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a105a00a",
+   "id": "20",
    "metadata": {
     "tags": []
    },
@@ -284,7 +284,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6a10dd79",
+   "id": "21",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -293,7 +293,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "42d60f85",
+   "id": "22",
    "metadata": {},
    "source": [
     "### Test the model"
@@ -302,7 +302,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e6ed2d40",
+   "id": "23",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -311,7 +311,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f1c99e30",
+   "id": "24",
    "metadata": {},
    "source": [
     "### Publish model to hugging-face\n",
@@ -324,7 +324,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "18b270dd",
+   "id": "25",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -334,7 +334,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2f36af3f",
+   "id": "26",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -343,7 +343,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c0b7c1f0",
+   "id": "27",
    "metadata": {},
    "source": [
     "### Load an existing model\n",
@@ -354,7 +354,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d9706336",
+   "id": "28",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -365,7 +365,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "70f521ea",
+   "id": "29",
    "metadata": {},
    "outputs": [],
    "source": []