From 957a586b6648ba6095f8ebf4ae3dfe1b52b42c23 Mon Sep 17 00:00:00 2001 From: Wilder Wohns Date: Fri, 11 Feb 2022 14:27:13 -0500 Subject: [PATCH] add clustering notebook and encodings --- examples/clustering.ipynb | 223 +++++++++++ examples/explore-ts.ipynb | 630 ++++++++++++++++++++++++++++++++ scripts/empirical_evaluation.py | 170 +++++++++ tspyro/cluster.py | 77 +++- 4 files changed, 1099 insertions(+), 1 deletion(-) create mode 100644 examples/clustering.ipynb create mode 100644 examples/explore-ts.ipynb create mode 100644 scripts/empirical_evaluation.py diff --git a/examples/clustering.ipynb b/examples/clustering.ipynb new file mode 100644 index 0000000..e5545d7 --- /dev/null +++ b/examples/clustering.ipynb @@ -0,0 +1,223 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 6, + "id": "320e17d5", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: python-louvain in /opt/miniconda3/envs/tspyro/lib/python3.7/site-packages (0.16)\r\n", + "Requirement already satisfied: numpy in /opt/miniconda3/envs/tspyro/lib/python3.7/site-packages (from python-louvain) (1.20.3)\r\n", + "Requirement already satisfied: networkx in /opt/miniconda3/envs/tspyro/lib/python3.7/site-packages (from python-louvain) (2.6.3)\r\n" + ] + } + ], + "source": [ + "!pip install python-louvain" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "488b81d8", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import networkx as nx\n", + "import math\n", + "import collections\n", + "import torch\n", + "import numpy as np\n", + "\n", + "from community import community_louvain\n", + "import tskit\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "import cartopy\n", + "import cartopy.crs as ccrs" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "1e272296", + "metadata": {}, + "outputs": [], + "source": [ + "# Download the tree sequence from here: https://drive.google.com/drive/folders/15pvB_F0-hB4xYVKrTRhCVfeJymsZPSM9?usp=sharing\n", + "ts = tskit.load(\"/Users/anthonywohns/Downloads/hgdp_sgdp_high_cov_ancients_chr20.dated.trees\")" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "558c8e59", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "torch.Size([1206, 2])\n", + "torch.Size([2412, 2])\n" + ] + } + ], + "source": [ + "# Grab the locations of samples\n", + "modern_sample_locations = torch.as_tensor(ts.tables.individuals.location.reshape((ts.num_individuals-8, 2)))\n", + "print(modern_sample_locations.shape)\n", + "# Need to reshape because num_samples = 2 * num_individuals, and locations are stored per individual\n", + "modern_sample_locations = modern_sample_locations.reshape(-1, 1, 2).expand(-1, 2, 2).reshape(-1, 2)\n", + "print(modern_sample_locations.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "e4e5c2e6", + "metadata": {}, + "outputs": [], + "source": [ + "# Functions borrowed from https://github.com/tskit-dev/what-is-an-arg-paper\n", + "\n", + "def convert_nx(ts, mutation_rate=1e-8):\n", + " \"\"\"\n", + " Returns the specified tree sequence as an networkx directed graph.\n", + " Weights are the edge's total span * e^(-edge length * mutation_rate).\n", + "\n", + " Mutation rate is in units: probability of mutation per base pair per generation.\n", + " \"\"\"\n", + " G = nx.Graph()\n", + " edges = collections.defaultdict(list)\n", + " times = ts.tables.nodes.time\n", + " for edge in ts.edges():\n", + " edges[(edge.child, edge.parent)].append((edge.left, edge.right, times[edge.parent], times[edge.child]))\n", + " for node in ts.nodes():\n", + " G.add_node(node.id, time=node.time, flags=node.flags)\n", + " for edge, intervals in edges.items():\n", + " G.add_edge(*edge, weight=sum((right - left) * math.e**(-(top-bottom) * mutation_rate) for\n", + " (left, right, top, bottom) in intervals))\n", + "\n", + " return G" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "f5c0e45c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(443679, 2876017)" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "graph = convert_nx(ts)\n", + "graph.number_of_nodes(), graph.number_of_edges()" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "42de75c1", + "metadata": {}, + "outputs": [], + "source": [ + "partition = community_louvain.best_partition(graph, weight=\"weight\", resolution=1) # resolution > 1: fewer clusters. < 1: more clusters" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "22653875", + "metadata": {}, + "outputs": [], + "source": [ + "assignment = np.array(list(partition.values()))[ts.samples()][:-16] # hack since 8 individual ancient locations aren't included" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "9615001c", + "metadata": {}, + "outputs": [], + "source": [ + "# Make dictionary where key=community and value=nodes in community\n", + "partition_dict = collections.defaultdict(list)\n", + "for key, val in partition.items():\n", + " partition_dict[val].append(key)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "50193f69", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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TableRowsSizeHas Metadata
Edges313496783.7 MiB\n", + " \n", + "
Individuals1214406.4 KiB\n", + " ✅\n", + "
Migrations04 Bytes\n", + " \n", + "
Mutations311019186.0 MiB\n", + " \n", + "
Nodes44367921.0 MiB\n", + " ✅\n", + "
Populations1898.6 KiB\n", + " ✅\n", + "
Provenances1812.9 KiB\n", + " \n", + "
Sites138376999.4 MiB\n", + " ✅\n", + "
\n", + "
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\n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ts" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "# Plot the number of ancestral lineages at different points in time\n", + "def count_edges_at_time(t):\n", + " time = ts.tables.nodes.time\n", + " child = ts.tables.edges.child\n", + " parent = ts.tables.edges.parent\n", + " # Find edges that have children which live before time t\n", + " return np.sum(np.logical_and(time[child] <= t, time[parent] > t))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "log_scale = 2 ** np.arange(15.0)\n", + "log_scale = np.concatenate([[0], log_scale])" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "ancestors_at_t = []\n", + "for i in log_scale:\n", + " ancestors_at_t.append(count_edges_at_time(i))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(log_scale, ancestors_at_t)\n", + "plt.xscale(\"symlog\")\n", + "plt.yscale(\"log\")\n", + "plt.xlabel(\"Times (generations)\")\n", + "plt.ylabel(\"Number of ancestral lineages\")\n", + "plt.title(\"Number of ancestral lineages at different points in time\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This is reassuring because there are millions of internal nodes, but also millions of edges tethering those ancestors to the samples." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Where are samples located geographically?\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "locations = []\n", + "for indiv in ts.individuals():\n", + " if len(indiv.location) > 0:\n", + " locations.append(indiv.location)\n", + " locations.append(indiv.location)\n", + "locations = np.array(locations)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Geographic location of samples')" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(10, 10))\n", + "ax = plt.axes(projection=ccrs.Robinson(central_longitude=41))\n", + "ax.coastlines(linewidth=0.1)\n", + "ax.add_feature(cartopy.feature.LAND, facecolor=\"lightgray\")\n", + "ax.set_global()\n", + "plt.scatter(locations[:,1], locations[:,0], transform=ccrs.PlateCarree(),)\n", + "plt.title(\"Geographic location of samples\")" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "139" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# How many unique locations are there?\n", + "len(np.unique(locations, axis=0))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Ancient Samples Geographic Spread" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [], + "source": [ + "aadr_locations = pd.read_csv(\"/Users/anthonywohns/Downloads/v50.0_1240K_public.anno\", delimiter=\"\\t\")" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [], + "source": [ + "ancient_locations = aadr_locations[aadr_locations['Date mean in BP in years before 1950 CE [OxCal mu for a direct radiocarbon date, and average of range for a contextual date]'] != 0]" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/miniconda3/envs/tspyro/lib/python3.7/site-packages/pandas/core/indexing.py:723: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " iloc._setitem_with_indexer(indexer, value, self.name)\n" + ] + } + ], + "source": [ + "ancient_locations.loc[\"Lat.\"] = ancient_locations[\"Lat.\"].replace('..',np.NaN)\n", + "ancient_locations.loc[\"Long.\"] = ancient_locations[\"Long.\"].replace('..',np.NaN)" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "could not convert string to float: '..'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m/var/folders/0d/bpdnfw3x1gxg1zqc3c8yg3mc0000gn/T/ipykernel_39878/2695177950.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mancient_coords\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mancient_locations\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"Lat.\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_numpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mancient_locations\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"Long.\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_numpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfloat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mValueError\u001b[0m: could not convert string to float: '..'" + ] + } + ], + "source": [ + "ancient_coords = np.array([ancient_locations[\"Lat.\"].to_numpy(), ancient_locations[\"Long.\"].to_numpy()]).T.astype(float)" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Geographic location of ancient samples')" + ] + }, + "execution_count": 98, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(10, 10))\n", + "ax = plt.axes(projection=ccrs.Robinson(central_longitude=41))\n", + "ax.coastlines(linewidth=0.1)\n", + "ax.add_feature(cartopy.feature.LAND, facecolor=\"lightgray\")\n", + "ax.set_global()\n", + "plt.scatter(ancient_coords[:,1], ancient_coords[:,0], transform=ccrs.PlateCarree(),s=0.5)\n", + "plt.title(\"Geographic location of ancient samples\")" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1859" + ] + }, + "execution_count": 99, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# How many unique locations are there?\n", + "len(np.unique(ancient_coords, axis=0))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "How old are these samples?" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.hist(aadr_locations['Date mean in BP in years before 1950 CE [OxCal mu for a direct radiocarbon date, and average of range for a contextual date]'],\n", + " bins=np.concatenate([[0],2 ** np.arange(20.)]))\n", + "plt.yscale(\"log\")\n", + "plt.xscale(\"log\")\n", + "plt.xlabel(\"Date in years\")\n", + "plt.title(\"Age of samples in AADR Database\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## What's the overlap with the HGDP + SGDP?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The AADR dataset contains genotyping data from the \"1240k\" SNP array." + ] + }, + { + "cell_type": "code", + "execution_count": 126, + "metadata": {}, + "outputs": [], + "source": [ + "snps = pd.read_csv(\"~/Downloads/v50.0_1240K_public.snp\", header=None)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1233013\n" + ] + } + ], + "source": [ + "import os\n", + "from collections import Counter\n", + "fields = [\"id\", \"chromosome\", \"frequency\", \"position\", \"ref\", \"alt\"]\n", + "cols = {k: [] for k in fields}\n", + "with open(os.path.expanduser(\"~/Downloads/v50.0_1240K_public.snp\"), \"rt\") as f:\n", + " for line in f:\n", + " line = line.strip().split()\n", + " if len(line) == len(fields):\n", + " for k, v in zip(fields, line):\n", + " cols[k].append(v)\n", + "print(len(cols[\"id\"]))" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2 98657\n", + "1 93166\n", + "3 81416\n", + "6 78867\n", + "5 74004\n", + "4 71634\n", + "8 63916\n", + "7 62595\n", + "10 61131\n", + "11 57163\n", + "12 56133\n", + "9 52765\n", + "23 49704\n", + "13 40441\n", + "14 37903\n", + "16 36000\n", + "15 35991\n", + "18 35327\n", + "24 32670\n", + "17 30733\n", + "20 30377\n", + "19 19273\n", + "21 16727\n", + "22 16420\n" + ] + } + ], + "source": [ + "for c, count in Counter(cols[\"chromosome\"]).most_common():\n", + " print(c, count)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.8.12" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/scripts/empirical_evaluation.py b/scripts/empirical_evaluation.py new file mode 100644 index 0000000..b45d30f --- /dev/null +++ b/scripts/empirical_evaluation.py @@ -0,0 +1,170 @@ +import argparse +import os +import pickle + +import numpy as np +import torch +import tsdate +import tskit +from tspyro import models + + +def create_filename(args, prefix): + Ne = str(args.Ne) + mutation_rate = str(args.mutation_rate) + if args.euclidean_likelihood: + likelihood = "euclidean" + elif args.waypoint_likelihood: + likelihood = "waypoint" + if args.reparam_model: + model = "reparam" + elif args.meanfield_model: + model = "meanfield" + steps = str(args.steps) + ts_fn = os.path.basename(args.tree_sequence) + ts_fn = os.path.splitext(ts_fn)[0] + filename = ( + args.output_path + + ts_fn + + "_" + + prefix + + "_" + + Ne + + "_" + + mutation_rate + + "_" + + likelihood + + "_" + + model + + "_" + + steps + ) + return filename + + +def main(args): + """Main Entry Point""" + ts = tskit.load(args.tree_sequence) + # Simplify to modern samples + # TODO: Add locations to ancient samples + modern_samples = np.where(ts.tables.nodes.time == 0)[0] + ts = ts.simplify(samples=modern_samples) + ts = ts.simplify(np.arange(0, 10)) + ts = ts.keep_intervals([[0, 1e7]]) + # Get locations of samples from the tree sequence + locations = [] + for indiv in ts.individuals(): + if len(indiv.location) > 0: + # Bit of a hack, but the following is doubled as we + # need to record a location for each chromosome + locations.append(indiv.location) + locations.append(indiv.location) + locations = np.array(locations) + leaf_location = torch.as_tensor( + locations[: ts.num_samples, :], dtype=torch.get_default_dtype() + ) + if args.euclidean_likelihood: + likelihood = models.euclidean_migration + elif args.waypoint_likelihood: + raise NotImplementedError("Waypoint Model not implemented for world map yet") + else: + raise ValueError("Must specify a migration likelihood") + if args.reparam_model: + model = models.ReparamLocation(ts, leaf_location) + elif args.meanfield_model: + model = models.mean_field_location + else: + raise ValueError("Must specify a location model") + + # Create the priors for dates + priors = tsdate.build_prior_grid( + ts, Ne=args.Ne, approximate_priors=True, progress=args.progress + ) + + times, location, migration_scale, guide, losses = models.fit_guide( + ts, + leaf_location, + priors, + Ne=args.Ne, + mutation_rate=args.mutation_rate, + migration_likelihood=likelihood, + location_model=model, + steps=args.steps, + log_every=args.log_every, + Model=models.NaiveModel, + migration_scale_init=args.migration_scale_init, + learning_rate=args.learning_rate, + ) + pickle.dump(times, open(create_filename(args, "times"), "wb")) + pickle.dump(location, open(create_filename(args, "location"), "wb")) + pickle.dump(migration_scale, open(create_filename(args, "migration_scale"), "wb")) + # TODO: Why isn't this working? + # torch.save(guide, create_filename(args, "guide")) + # pickle.dump(guide, open(create_filename(args, "guide"), "wb")) + pickle.dump(losses, open(create_filename(args, "losses"), "wb")) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Runs tspyro on a tree sequence") + parser.add_argument( + "tree_sequence", + help="The path and name of the input tree sequence from which \ + we estimate node ages.", + ) + parser.add_argument( + "output_path", help="The path to the directory where output will be saved" + ) + parser.add_argument( + "Ne", type=int, help="The effective population size to use in the prior" + ) + parser.add_argument( + "mutation_rate", + type=float, + help="The estimated mutation rate per unit of genome per generation.", + ) + parser.add_argument( + "--reparam-model", + action="store_true", + help="use the reparameterized location model", + ) + parser.add_argument( + "--meanfield-model", + action="store_true", + help="use the reparameterized location model", + ) + parser.add_argument( + "--euclidean-likelihood", + action="store_true", + help="use the euclidean migration likelihood model", + ) + parser.add_argument( + "--waypoint-likelihood", + action="store_true", + help="use the waypoint migration likelihood model", + ) + parser.add_argument( + "--steps", type=int, default=1000, help="Number of steps to run inference" + ) + parser.add_argument( + "--migration-scale-init", + type=float, + default=1, + help="Initialization value for the migration scale", + ) + parser.add_argument( + "--learning-rate", + type=float, + default=0.1, + help="Learning rate value to use in ELBO inference", + ) + parser.add_argument( + "--log-every", + type=int, + default=100, + help="How often do we log our inference progress?", + ) + parser.add_argument( + "-p", "--progress", action="store_true", help="Show progress bar." + ) + args = parser.parse_args() + main(args) diff --git a/tspyro/cluster.py b/tspyro/cluster.py index cd37c13..a900aa4 100644 --- a/tspyro/cluster.py +++ b/tspyro/cluster.py @@ -1,3 +1,4 @@ +import numpy as np import torch import tqdm @@ -65,6 +66,80 @@ def make_fake_data(num_samples, num_variants): return data +def naive_encoder(ts): + """ + Make an encoding of the sparse genotype data naively: haplotype by haplotype. + Note this is very slow for large tree sequences. + + :returns: A Dict representing sparse genotypes. + :rtype: dict + """ + offsets = [] + index = [] + values = [] + for haplo in tqdm(ts.haplotypes(), total=ts.num_samples): + begin = len(index) + for i, g in enumerate(haplo): + assert g in "-01" + if g != "-": + index.append(i) + values.append(bool(int(g))) + end = len(index) + offsets.append([begin, end]) + return { + "offsets": torch.tensor(offsets, dtype=torch.long), + "index": torch.tensor(index, dtype=torch.long), + "values": torch.tensor(values, dtype=torch.bool), + } + + +def variant_encoder(ts): + """ + Encodes sparse genotype data variant by variant. This is faster + than the naive encoding but requires inverting to be compatible with + `make_clustering_gibbs()`. + + :returns: A Dict representing sparse genotypes in compressed sparse + column format. + :rtype: dict + """ + offsets = [] + index = [] + values = [] + for var in tqdm(ts.variants(), total=ts.num_sites): + geno = var.genotypes + begin = len(index) + + index.extend(np.where([geno != -1])[1]) + + non_missing = geno != -1 + values.extend(geno[non_missing] != 0) + end = len(index) + offsets.append([begin, end]) + return { + "offsets": torch.tensor(offsets, dtype=torch.long), + "index": torch.tensor(index, dtype=torch.long), + "values": torch.tensor(values, dtype=torch.bool), + } + + +def dense_encoder_genos(genos): + """ + Encodes a genotype matrix in the sparse genotype encoding format. + + :returns: A Dict representing sparse genotypes. + :rtype: dict + """ + n, p = genos.shape + print("n*p is {}".format(n * p)) + return { + "offsets": torch.arange(n, dtype=torch.long)[:, None] * p + + torch.tensor([0, p]), + "index": torch.arange(p).expand(n, p).reshape(-1), + "values": torch.as_tensor(genos).bool().reshape(-1), + } + + def make_clustering_gibbs( data: dict, num_clusters: int, @@ -131,7 +206,7 @@ def make_clustering_gibbs( assert (counts.sum() / expected).sub(1).abs() < 1e-6 clusters = (counts[..., 1] / counts.sum(-1)).round_().bool() - return clusters + return assignment, clusters def make_reproduction_tensor(