Topology in neuroscience
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"# Decoding population activity"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"**Imports**"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"from sym_model import Population\n",
"\n",
"import sys\n",
"import seaborn as sns\n",
"import umap\n",
"import numpy as np\n",
"import pandas as pd\n",
"from matplotlib import pyplot as plt\n",
"sys.path.insert(0, './model')\n",
"\n",
"from model import decoding\n",
"from model import persistence\n",
"from utils import get_orientation_phase_grid"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## Getting the data\n",
"\n",
"**Sampling the activity using the model**"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"limit = 1500\n",
"# n_theta, n_phi = 18, 24\n",
"n_theta, n_phi = 9, 12\n",
"step_phi, step_theta = 360 // n_phi, 180 // n_theta"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0. 0.] [160. 330.]\n"
]
}
],
"source": [
"grid = get_orientation_phase_grid(step_phi, step_theta)\n",
"grid = grid.reshape((-1, 2)) * 180 / np.pi\n",
"print(grid[0], grid[-1])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"res = Population.random(10).sample_responses(limit, custom_grid=grid, use_sigmoid=False)\n",
"res, phi_deg, theta_deg = res[:, :, 0], res[:, 0, 1], res[:, 0, 2]"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"import pickle\n",
"with open('res.pkl', 'wb') as f:\n",
" pickle.dump(res, f)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"phi_reorder = sorted(list(range(len(phi_deg[:limit]))), key=lambda x: phi_deg[x])\n",
"theta_reorder = sorted(list(range(len(theta_deg[:limit]))), key=lambda x: theta_deg[x])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": "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",
"text/latex": [
"$\\displaystyle \\left( 108, \\ 10\\right)$"
],
"text/plain": [
"(108, 10)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"res.shape"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"res_reshaped = res.reshape((n_phi, n_theta, -1))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/lib/python3.10/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
" warnings.warn(msg, FutureWarning)\n"
]
},
{
"data": {
"text/plain": [
"<AxesSubplot:ylabel='Density'>"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.distplot((res).ravel().clip(-0.1, 0.1))"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## Plotting joint tunings"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"phase_linspace = np.linspace(0, 360, n_phi)\n",
"orientation_linspace = np.linspace(0, 180, n_theta)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 432x288 with 6 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(3, 2)\n",
"ax = ax.flatten()\n",
"# set title\n",
"fig.suptitle('Joint Tunings - By Phase')\n",
"for i in range(6):\n",
" ax[i].plot(phase_linspace, res_reshaped.mean(1)[:, i])"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 432x288 with 6 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(3, 2)\n",
"ax = ax.flatten()\n",
"# set title\n",
"fig.suptitle('Joint Tunings - By Orientation')\n",
"for i in range(6):\n",
" ax[i].plot(orientation_linspace, res_reshaped.mean(0)[:, i])"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7f13229a8970>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAMUAAAD4CAYAAABc3CKDAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAAKs0lEQVR4nO3dXYic5RnG8evqrovJatBYW8wHTYRgm1psQvAjglATqVaphfYgUsVKS0+qRhFES1GQHvRARA9EkKgVDIYSAw0iRhuVUixbNQZMXCUhfmRNbFKDJmxbN4l3D2bSTu9ussm8T+Z9d/v/gWR3dnjmJuM/73y9+zgiBOA/vlT3AEDTEAWQEAWQEAWQEAWQ9Pfyxgb6psW0/hmV14mxgwWmwfHwwCnF1mrS/fZPjWosPvd4P+tpFNP6Z2jprB9XXufQBzsLTIPj0T9rbrG1mnS/DcXGo/6Mh09AQhRAQhRAQhRAUikK21faftf2dtt3lRoKqFPXUdjuk/SwpKskLZR0ne2FpQYD6lLlSHGhpO0RsSMixiStkXRtmbGA+lSJYrakzheeR9qX/RfbP7f9uu3Xxw7/o8LNAb1RJYrx3g38n5MzIuLRiFgSEUsG+qZVuDmgN6pEMSKp8+3OOZJ2VRsHqF+VKF6TtMD2fNsDklZIWl9mLKA+XX/2KSIO2b5Z0gZJfZIej4itxSYDalLpA4ER8Zyk5wrNAjQC72gDCVEACVEASU9PMoqxg4060aSknb9aWmSdub9+tcg6pUzV++tYOFIACVEACVEACVEACVEACVEACVEACVEACVEACVEACVEACVEACVEACVEACVEACVEACVEASU/PvBs7Z1A7f1b9DLWmnZ0mNXOmEvpenlVsrcPfmRy/K48jBZAQBZAQBZAQBZAQBZBU2d5rru2XbQ/b3mp7ZcnBgLpUeUn2kKQ7ImKT7dMlvWH7xYh4u9BsQC26PlJExO6I2NT++oCkYY2zvRcw2RR5TmF7nqRFkoZKrAfUqXIUtk+T9Iyk2yJi/zg///dGkIf/Plr15oCTrurm8qeoFcTqiFg33nU6N4Lsmz5Y5eaAnqjy6pMlPSZpOCIeKDcSUK8qR4pLJd0g6XLbm9v/fa/QXEBtqmwE+SeNv5c2MKnxjjaQEAWQEAWQOCJ6dmMzPDMu8rKe3V4vlTpDbbKcnTbZDcVG7Y994z4n5kgBJEQBJEQBJEQBJEQBJEQBJEQBJEQBJEQBJEQBJEQBJEQBJEQBJEQBJEQBJEQBJEQBJEQBJD3dCHLWt0Z1z/pNlde579zFBaYpa6qeRnrPjur31xFNvN/Gw5ECSIgCSIgCSIgCSIgCSEps2tJn+03bz5YYCKhbiSPFSrX2uwOmhKo7Gc2RdLWkVWXGAepX9UjxoKQ7JX1xtCt07nn36SdHvRrQGFW297pG0p6IeONY1+vc8+6Ms3hej+arur3X922/L2mNWtt8PVVkKqBGVTaXvzsi5kTEPEkrJL0UEdcXmwyoCY9ngKTIp2Qj4hVJr5RYC6gbRwogIQogIQogYSPIQjbs2lxkne/O+naRdXBsbAQJnACiABKiABKiABKiABKiABKiABKiABKiABKiABKiABKiABKiABKiABKiABKiABKiAJKennm35IJT4y8b5lZeh7PTemfNzleLrbVi7tJia1XFmXfACSAKICEKICEKICEKIKm6k9EZttfafsf2sO1LSg0G1KXqL1h+SNLzEfEj2wOSpheYCahV11HYniHpMkk/kaSIGJM0VmYsoD5VHj6dK2mvpCfaWwavsj2Yr9S5593eTw5XuDmgN6pE0S9psaRHImKRpFFJd+Urde55d/ZZfRVuDuiNKlGMSBqJiKH292vVigSY1KrsefexpJ22z2tftEzS20WmAmpU9dWnWyStbr/ytEPSTdVHAupVKYqI2CxpSZlRgGbgHW0gIQogIQogYc+7Qkqdodaks9OmMs68A04AUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQBJ1V9xc0JmfPOwlv/uQOV1/nD+6QWmKWuqnjG3fEv1++uIJt5v4+FIASREASREASREASREASRV97y73fZW21tsP2371FKDAXXpOgrbsyXdKmlJRJwvqU/SilKDAXWp+vCpX9I02/1qbQK5q/pIQL2qbNrykaT7JX0oabekzyLihXy9zj3vRvexTySar8rDpzMlXStpvqRZkgZtX5+v17nn3eDMge4nBXqkysOn5ZLei4i9EXFQ0jpJU/OzDvi/UiWKDyVdbHu6bau1591wmbGA+lR5TjGk1o6omyS91V7r0UJzAbWpuufdvZLuLTQL0Ai8ow0kRAEkRAEkPT3zbv/Wvklz9tWJ2vbk4iLrLLhxU5F1Spmq99excKQAEqIAEqIAEqIAEqIAEqIAEqIAEqIAEqIAEqIAEqIAEqIAEqIAEqIAEqIAEqIAEqIAEqIAkp6ejvr5vOnadl/10zabdsqm1MyZShj94UXF1hp8ZqjYWicTRwogIQogIQogIQogmTAK24/b3mN7S8dlM22/aHtb+88zT+6YQO8cz5Hit5KuTJfdJWljRCyQtLH9PTAlTBhFRPxR0r508bWSnmx//aSkH5QdC6hPt88pvhoRuyWp/edXyo0E1OukP9Hu3Ajy8IHRk31zQGXdRvFX2+dIUvvPPUe7YudGkH2nD3Z5c0DvdBvFekk3tr++UdLvy4wD1O94XpJ9WtKfJZ1ne8T2TyX9RtIVtrdJuqL9PTAlTPiBwIi47ig/WlZ4FqAReEcbSIgCSIgCSIgCSBwRPbuxGZ4ZF3lqPj8vdYbaZDk7bbIbio3aH/s83s84UgAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQAJUQBJT8+8s71X0gcTXO3Lkv7Wg3GOF/NMrGkzHc88X4uIs8f7QU+jOB62X4+IJXXPcQTzTKxpM1Wdh4dPQEIUQNLEKB6te4CEeSbWtJkqzdO45xRA3Zp4pABqRRRA0pgobF9p+13b223Xvtuq7bm2X7Y9bHur7ZV1zyRJtvtsv2n72QbMcobttbbfaf89XVLzPLe376sttp+2fWo36zQiCtt9kh6WdJWkhZKus72w3ql0SNIdEfENSRdL+kUDZpKklZKG6x6i7SFJz0fE1yVdoBrnsj1b0q2SlkTE+ZL6JK3oZq1GRCHpQknbI2JHRIxJWqPWtsS1iYjdEbGp/fUBte7w2XXOZHuOpKslrapzjvYsMyRdJukxSYqIsYj4tNahWpsQTbPdL2m6pF3dLNKUKGZL2tnx/Yhq/h+wk+15khZJqvu3Hz8o6U5JX9Q8hySdK2mvpCfaD+dW2a5tp8+I+EjS/ZI+lLRb0mcR8UI3azUlivF++3MjXiu2fZqkZyTdFhH7a5zjGkl7IuKNumZI+iUtlvRIRCySNCqptueCts9U69HFfEmzJA3avr6btZoSxYikuR3fz1GXh76SbJ+iVhCrI2JdzeNcKun7tt9X6+Hl5bafqnGeEUkjEXHk6LlWrUjqslzSexGxNyIOSlonaWk3CzUlitckLbA93/aAWk+Q1tc5kG2r9Xh5OCIeqHMWSYqIuyNiTkTMU+vv56WI6OpfwkLzfCxpp+3z2hctk/R2XfOo9bDpYtvT2/fdMnX5xH/C3VF7ISIO2b5Z0ga1XjV4PCK21jzWpZJukPSW7c3ty34ZEc/VN1Lj3CJpdfsfsh2SbqprkIgYsr1W0ia1Xjl8U11+3IOPeQBJUx4+AY1BFEBCFEBCFEBCFEBCFEBCFEDyL77/vVudcwURAAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(res_reshaped[:, :, 0], cmap='viridis')"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## Persistence for different dimensions"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"persistence.persistence(res, 1)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# persistence.persistence(res, 2)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# persistence.persistence(res, 3)"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## PCA"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"res_df = pd.DataFrame(res[:limit], columns=['x' + str(i) for i in range(20)])"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"from sklearn.decomposition import PCA\n",
"import seaborn as sns"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.heatmap(res_df.corr())"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Seems like we need about 5 components"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>PC1</th>\n",
" <th>PC2</th>\n",
" <th>PC3</th>\n",
" <th>PC4</th>\n",
" <th>PC5</th>\n",
" <th>PC6</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>-1.612520</td>\n",
" <td>-0.547999</td>\n",
" <td>-0.110458</td>\n",
" <td>-0.530344</td>\n",
" <td>0.888399</td>\n",
" <td>-0.105346</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>-1.007680</td>\n",
" <td>-0.069920</td>\n",
" <td>-0.222961</td>\n",
" <td>0.443805</td>\n",
" <td>-0.416626</td>\n",
" <td>-0.541131</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>-0.228229</td>\n",
" <td>0.523023</td>\n",
" <td>0.226259</td>\n",
" <td>-0.233582</td>\n",
" <td>-0.340139</td>\n",
" <td>-0.273262</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-0.178205</td>\n",
" <td>0.297823</td>\n",
" <td>0.294549</td>\n",
" <td>-0.225669</td>\n",
" <td>-0.151865</td>\n",
" <td>0.018889</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.113908</td>\n",
" <td>-0.155210</td>\n",
" <td>0.616534</td>\n",
" <td>0.036769</td>\n",
" <td>0.003957</td>\n",
" <td>-0.032182</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" PC1 PC2 PC3 PC4 PC5 PC6\n",
"0 -1.612520 -0.547999 -0.110458 -0.530344 0.888399 -0.105346\n",
"1 -1.007680 -0.069920 -0.222961 0.443805 -0.416626 -0.541131\n",
"2 -0.228229 0.523023 0.226259 -0.233582 -0.340139 -0.273262\n",
"3 -0.178205 0.297823 0.294549 -0.225669 -0.151865 0.018889\n",
"4 0.113908 -0.155210 0.616534 0.036769 0.003957 -0.032182"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"N_COMP = 6\n",
"pca = PCA(n_components=N_COMP)\n",
"pca.fit(res_df)\n",
"data_pca = pca.transform(res_df)\n",
"data_pca = pd.DataFrame(data_pca, columns=[f'PC{i+1}' for i in range(N_COMP)])\n",
"data_pca.head()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": "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",
"text/latex": [
"$\\displaystyle \\left( 432, \\ 6\\right)$"
],
"text/plain": [
"(432, 6)"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_pca.shape"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## UMAP decoding"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# reducer = umap.UMAP()\n",
"# embedding = reducer.fit_transform(data_pca.to_numpy())"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# %matplotlib notebook\n",
"# plt.scatter(\n",
"# embedding[:, 0],\n",
"# embedding[:, 1])\n",
"# plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# embedding.shape"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## Cohomological decoding"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Decoding... done\n"
]
}
],
"source": [
"param_1 = decoding.cohomological_parameterization(res_df, coeff=12).to_numpy()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7f51aaf69b40>"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"plt.title(\"Parameter 1 of CP vs. phase\")\n",
"plt.scatter(phi_deg, param_1)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7f51aafa6bc0>"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.title(\"Parameter 1 of CP vs. orientation\")\n",
"plt.scatter(theta_deg, param_1)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"data_without_features = decoding.remove_feature(data_pca.to_numpy(), pd.DataFrame(param_1))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"pycharm": {
"is_executing": true,
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Decoding... "
]
}
],
"source": [
"param_2 = decoding.cohomological_parameterization(\n",
" pd.DataFrame(data_without_features[:limit])).to_numpy()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"pycharm": {
"is_executing": true,
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"plt.scatter([phi_deg[i] * 180 / np.pi for i in phi_reorder], [param_2[i] for i in phi_reorder])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"pycharm": {
"is_executing": true,
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"plt.scatter([theta_deg[i] for i in theta_reorder], [param_2[i] for i in theta_reorder])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"pycharm": {
"is_executing": true,
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"phi_reorder[:10]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"pycharm": {
"is_executing": true,
"name": "#%%\n"
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"pycharm": {
"is_executing": true,
"name": "#%%\n"
}
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.10.5 64-bit",
"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": "3.10.5"
},
"vscode": {
"interpreter": {
"hash": "e7370f93d1d0cde622a1f8e1c04877d8463912d04d973331ad4851f04de6915a"
}
}
},
"nbformat": 4,
"nbformat_minor": 0
}