{ "cells": [ { "cell_type": "markdown", "source": [ "# Demo 3 (PS): Embedding of Pose Segmentation Data\n", "\n", "*Written and last updated July 19, 2025 by Sedona Ewbank, snewbank@stanford.edu*\n", "\n", "The purpose of this demo is to demonstrate how to load pose segmentation data and visualize it in various ways." ], "metadata": { "collapsed": false }, "id": "93f1de39db0a9692" }, { "cell_type": "code", "outputs": [ { "data": { "text/plain": "" }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import os\n", "import sys\n", "import importlib\n", "\n", "#This block only important for running as script\n", "#script_dir = os.path.dirname(os.path.abspath(__file__))\n", "mariposa_dir = \"/Users/snewbank/PycharmProjects/MARIPoSA\"\n", "utils_dir = os.path.join(mariposa_dir, 'utils')\n", "sys.path.append(utils_dir)\n", "sys.path.append(mariposa_dir)\n", "\n", "#import utils\n", "from utils import metadata, analyze, plot, simulate\n", "\n", "importlib.reload(metadata)\n", "importlib.reload(analyze)\n", "importlib.reload(plot)\n", "importlib.reload(simulate)" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-07-20T07:50:18.233758Z", "start_time": "2025-07-20T07:50:18.203881Z" } }, "id": "a53085614583f0a2", "execution_count": 17 }, { "cell_type": "code", "outputs": [], "source": [ "demo_dir=\"/Users/snewbank/Behavior/MARIPoSA_demo_data/\"\n", "config=metadata.load_project(demo_dir+\"250719_test/config_PS.yaml\")\n", "save=True\n", "save_path = demo_dir+\"demo_figures/\"\n", "if not os.path.exists(save_path):\n", " os.makedirs(save_path)" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-07-20T07:17:18.435966Z", "start_time": "2025-07-20T07:17:18.410085Z" } }, "id": "c1796a1ba8c3778f", "execution_count": 2 }, { "cell_type": "markdown", "source": [ "## 3.1: Embedding with PCA\n", "We can first try embedding our data agnostic to the subgroups with principal components analysis (PCA). Here we can make use here of the scaling function of module_usage and module_transitions - each can be scaled to unit variance with zero mean across features with .scale(), and scaling can be checked with .scaled. We can then use analyze.embed to embed and plot.plot_embeddings to visualize." ], "metadata": { "collapsed": false }, "id": "aacb9d6bded8a5fd" }, { "cell_type": "code", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on function embed in module utils.analyze:\n", "\n", "embed(module_feature_object, method='lda', n_components=2)\n", " Get dimensionally reduced space embeddings of the data with LDA or PCA\n", " \n", " :param module_feature_object: module feature object\n", " :param method: LDA or PCA; default LDA\n", " :param n_components: number of components\n", " :return:\n", "\n", "Help on function plot_embeddings in module utils.plot:\n", "\n", "plot_embeddings(module_feature_object, embeddings_object, figW=3, figH=3, cmap='viridis', title=None, legend=False, draw_ellipse=True, alt_legend=None)\n", " Plot embeddings\n", " \n", " :param module_feature_object: module feature object (ModuleUsage or ModuleTransitions) from analyze.get_module_{xx}\n", " :param embeddings_object: embeddings object (LDA or PCA) from analyze.embed\n", " :param figW: figure width\n", " :param figH: figure height\n", " :param cmap: matplotlib colormap\n", " :param title: title string, or None\n", " :param legend: True or False\n", " :return: fig\n" ] } ], "source": [ "help(analyze.embed)\n", "\n", "help(plot.plot_embeddings)" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-07-20T08:02:03.082522Z", "start_time": "2025-07-20T08:02:03.064959Z" } }, "id": "b95c941705b9a632", "execution_count": 24 }, { "cell_type": "code", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Is module usage scaled? False\n", "Is module usage scaled now?? True\n", "Ellipse only drawn for embeddings_object of class LDA, not \n", "Are module transitions scaled? False\n", "Are module transitions scaled now?? True\n", "Ellipse only drawn for embeddings_object of class LDA, not \n" ] }, { "data": { "text/plain": "
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" 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" }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Get and scale module usage\n", "labels_df = analyze.get_module_labels(config, 0, 1200, subgroups = [\"sal\",\"k1\",\"k5\",\"k10\"])\n", "module_usage = analyze.get_module_usage(config, labels_df, binsize=300)\n", "print(f\"Is module usage scaled? {module_usage.scaled}\")\n", "module_usage = module_usage.scale()\n", "print(f\"Is module usage scaled now?? {module_usage.scaled}\")\n", "\n", "#Embed module usage\n", "alt_legend={\"sal\":\"0\",\"k1\":\"1\",\"k5\":\"5\",\"k10\":\"10\"}\n", "emb = analyze.embed(module_usage,method=\"PCA\",n_components=2)\n", "fig = plot.plot_embeddings(module_usage, emb, figW=3.5, figH=2.5, cmap=\"viridis_r\", title=\"PCA usage\",legend=True,alt_legend=alt_legend)\n", "if save:\n", " fig.savefig(save_path+\"demo3-1_pca_embed_usage.png\",dpi=300)\n", " \n", "# Get and scale module transitions\n", "module_transitions = analyze.get_module_transitions(config, labels_df)\n", "print(f\"Are module transitions scaled? {module_transitions.scaled}\")\n", "module_transitions = module_transitions.scale()\n", "print(f\"Are module transitions scaled now?? {module_transitions.scaled}\")\n", " \n", "# Embed module transitions\n", "emb = analyze.embed(module_transitions,method=\"PCA\",n_components=2)\n", "fig = plot.plot_embeddings(module_transitions, emb, figW=3.5, figH=2.5, cmap=\"viridis_r\", title=\"PCA transitions\",legend=True,alt_legend=alt_legend)\n", "if save:\n", " fig.savefig(save_path+\"demo3-1_pca_embed_tx.png\",dpi=300)" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-07-20T07:58:25.742314Z", "start_time": "2025-07-20T07:58:14.916609Z" } }, "id": "9ad3d0b3195de983", "execution_count": 21 }, { "cell_type": "markdown", "source": [ "## 3.2: Embedding with LDA \n", "We can also embed based on class comparison (maximizing between-class distance and minimizing within-class distance) using linear discriminant analysis (LDA). Here again we make use of analyze.embed to embed and plot.plot_embeddings to visualize." ], "metadata": { "collapsed": false }, "id": "9e2d0a1952da5ce4" }, { "cell_type": "code", "outputs": [ { "data": { "text/plain": "
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" 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" }, "metadata": {}, "output_type": "display_data" } ], "source": [ "emb = analyze.embed(module_usage,method=\"LDA\",n_components=2)\n", "fig = plot.plot_embeddings(module_usage, emb, figW=3.5, figH=2.5, cmap=\"viridis_r\", title=\"LDA usage\",legend=True,draw_ellipse=True,alt_legend=alt_legend)\n", "if save:\n", " fig.savefig(save_path+\"demo3-2_lda_embed_usage.png\",dpi=300)\n", "\n", "emb = analyze.embed(module_transitions,method=\"LDA\",n_components=2)\n", "fig = plot.plot_embeddings(module_transitions, emb, figW=3.5, figH=2.5, cmap=\"viridis_r\", title=\"LDA transitions\",legend=True,draw_ellipse=True,alt_legend=alt_legend)\n", "if save:\n", " fig.savefig(save_path+\"demo3-2_lda_embed_tx.png\",dpi=300)" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-07-20T07:58:26.762025Z", "start_time": "2025-07-20T07:58:25.744895Z" } }, "id": "22161a6397325507", "execution_count": 22 }, { "cell_type": "code", "outputs": [], "source": [], "metadata": { "collapsed": false }, "id": "4bfc5be638bf74fa" } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.6" } }, "nbformat": 4, "nbformat_minor": 5 }