From 16ebb06112e5936c602b36cfe194139ced3422ff Mon Sep 17 00:00:00 2001 From: beckynevin Date: Sun, 21 Jul 2024 08:27:29 -0600 Subject: [PATCH] now setting sigma_x to values that propagate --- notebooks/fig1.ipynb | 209 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 209 insertions(+) create mode 100644 notebooks/fig1.ipynb diff --git a/notebooks/fig1.ipynb b/notebooks/fig1.ipynb new file mode 100644 index 0000000..462abc1 --- /dev/null +++ b/notebooks/fig1.ipynb @@ -0,0 +1,209 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "d2f97a7d-eed6-4d08-972e-4d179b14f459", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "from data.data import MyDataLoader, DataPreparation" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "id": "3d25d32f-32a6-45aa-8b0f-b144d367f932", + "metadata": {}, + "outputs": [], + "source": [ + "# lookup dict\n", + "noise_to_sigma = {\n", + " 'low': 1,\n", + " 'medium': 5,\n", + " 'high': 10,\n", + " 'vhigh': 100\n", + "}\n", + "inject_x_linear = {'low': 1/5, 'medium': 5/5, 'high': 10/5}\n", + "inject_x_image = {'low': 1/np.sqrt(32), 'medium': 5/np.sqrt(32), 'high': 10/np.sqrt(32)}\n", + "noise = 'high'" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "90f13884-f44d-493c-9f23-3652ca36679d", + "metadata": {}, + "outputs": [], + "source": [ + "data = DataPreparation()" + ] + }, + { + "cell_type": "code", + "execution_count": 118, + "id": "bb06c377-8398-45ec-8021-e560973821db", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "linear_homoskedastic simulation data generated, with noise injected type: feature.\n", + "linear_homoskedastic simulation data generated, with noise injected type: predictive.\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(10,4))\n", + "\n", + "data.params = np.array([[ 5, 4]])\n", + "ax0 = fig.add_subplot(141)\n", + "data.simulate_data(data.params,\n", + " inject_x_linear[noise], \n", + " simulation_name = 'linear_homoskedastic',\n", + " inject_type = 'feature'\n", + " )\n", + "ax0.plot(np.array(data.input).flatten(), np.array(data.output).flatten(), color = 'black')\n", + "ax0.scatter(np.array(data.input), np.array(data.output), color = 'black', s=0.25, zorder=-100)\n", + "ax0.set_title('Feature injection', size=15)\n", + "ax0.annotate(r'$\\sigma_x = $'+str(inject_x_linear[noise])+\n", + " ', $\\sigma_y = $'+str(inject_x_linear[noise]*data.params[0][0]),\n", + " xy=(0.02, 0.9),\n", + " xycoords='axes fraction'\n", + " )\n", + "ax0.set_xlabel(r'Feature, $x$')\n", + "ax0.set_ylabel(r'Prediction, $y$')\n", + "ax0.set_aspect(0.2, adjustable='box')\n", + "\n", + "ax1 = fig.add_subplot(142)\n", + "data.simulate_data(data.params,\n", + " noise_to_sigma[noise], \n", + " simulation_name = 'linear_homoskedastic',\n", + " inject_type = 'predictive'\n", + " )\n", + "ax1.plot(np.array(data.input), np.array(data.output).flatten(), color = 'black')\n", + "ax1.scatter(np.array(data.input), np.array(data.output), color = 'black', s=0.25, zorder=-100)\n", + "ax1.set_title('Predictive injection', size=15)\n", + "ax1.annotate(r'$\\sigma_y = $'+str(noise_to_sigma[noise]),\n", + " xy=(0.02, 0.9),\n", + " xycoords='axes fraction'\n", + " )\n", + "ax1.set_xlabel(r'Feature, $x$')\n", + "ax1.set_aspect(0.2, adjustable='box')\n", + "\n", + "# now doing 2D\n", + "data.params = np.array([[ 4.37086107, 9.55642876, 0.69598183]])\n", + "image_size = 32\n", + "\n", + "ax2 = fig.add_subplot(143)\n", + "\n", + "image_f, y_f = data.simulate_data_2d(\n", + " size_df,\n", + " data.params,\n", + " inject_type=\"feature\",\n", + " sigma=inject_x_image[noise]\n", + " )\n", + "ax2.imshow(image_f[0])\n", + "ax2.annotate('Pixel sum = ' + str(round(y_f[0], 2)),\n", + " xy=(0.02, 0.9),\n", + " xycoords='axes fraction',\n", + " color='white',\n", + " size=10)\n", + "ax2.annotate(r'$\\sigma_x = $' + str(round(inject_x_image[noise], 1)) \n", + " + ', $\\sigma_y = $' + str(round(inject_x_image[noise]*np.sqrt(32), 2)),\n", + " xy=(0.02, 0.8),\n", + " xycoords='axes fraction',\n", + " color='white',\n", + " size=10)\n", + "ax2.set_title('Feature injection', size=15)\n", + "\n", + "ax3 = fig.add_subplot(144)\n", + "\n", + "image_p, y_p = data.simulate_data_2d(\n", + " size_df,\n", + " data.params,\n", + " inject_type=\"predictive\",\n", + " sigma=noise_to_sigma[noise]\n", + " )\n", + "ax3.imshow(image_p[0])\n", + "ax3.annotate('Pixel sum = ' + str(round(y_p[0], 2)),\n", + " xy=(0.02, 0.9),\n", + " xycoords='axes fraction',\n", + " color='white',\n", + " size=10)\n", + "ax3.annotate(r'$\\sigma_y = $' + str(round(noise_to_sigma[noise])),\n", + " xy=(0.02, 0.8),\n", + " xycoords='axes fraction',\n", + " color='white',\n", + " size=10)\n", + "ax3.set_title('Predictive injection', size=15)\n", + "\n", + "\n", + "\n", + "plt.tight_layout()\n", + "plt.savefig('../../../Desktop/design.png', dpi=1000)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "757c13c8-5d05-4437-97d3-673a42695eff", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "79a3ab38-f987-4142-aad1-2ecbe5b6a388", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "51c2a1ea-b7ca-49c2-8551-66b5d39452c0", + "metadata": {}, + "outputs": [], + "source": [ + "data = DataPreparation()" + ] + } + ], + "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": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}