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980 lines
243 KiB
980 lines
243 KiB
{ |
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"cells": [ |
|
{ |
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"cell_type": "markdown", |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
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"name": "#%% md\n" |
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} |
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}, |
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"source": [ |
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"# Decoding population activity" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
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"name": "#%% md\n" |
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} |
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}, |
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"source": [ |
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"**Imports**" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 1, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
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"name": "#%%\n" |
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} |
|
}, |
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"outputs": [], |
|
"source": [ |
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"%matplotlib inline\n", |
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"from sym_model import Population, sigmoid\n", |
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"\n", |
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"import sys\n", |
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"import seaborn as sns\n", |
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"import umap\n", |
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"import numpy as np\n", |
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"import pandas as pd\n", |
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"from matplotlib import pyplot as plt\n", |
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"sys.path.insert(0, './model')\n", |
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"\n", |
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"from model import decoding\n", |
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"from model import persistence\n", |
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"from utils import get_orientation_phase_grid" |
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] |
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}, |
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{ |
|
"cell_type": "markdown", |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
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"name": "#%% md\n" |
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} |
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}, |
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"source": [ |
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"## Getting the data\n", |
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"\n", |
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"**Sampling the activity using the model**" |
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] |
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}, |
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{ |
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"cell_type": "code", |
|
"execution_count": 2, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [], |
|
"source": [ |
|
"limit = 500\n", |
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"# n_theta, n_phi = 18, 24\n", |
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"n_theta, n_phi = 36, 72\n", |
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"# n_theta, n_phi = 9, 12\n", |
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"step_phi, step_theta = 360 // n_phi, 180 // n_theta\n", |
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"N = 40 # number of cells" |
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] |
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}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 3, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [ |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"[0. 0.] [3.05432619 6.19591884] (2592, 2)\n" |
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] |
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} |
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], |
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"source": [ |
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"grid = get_orientation_phase_grid(step_phi, step_theta)\n", |
|
"grid = grid.reshape((-1, 2))\n", |
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"print(grid[0], grid[-1], grid.shape)" |
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] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 4, |
|
"metadata": {}, |
|
"outputs": [], |
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"source": [ |
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"population = Population.random(N)" |
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] |
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}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 5, |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"phi_deg, theta_deg = grid[:, 1] * 180 / np.pi, grid[:, 0] * 180 / np.pi" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 6, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [], |
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"source": [ |
|
"# res = population.sample_responses(limit, custom_grid=grid, use_sigmoid=False)\n", |
|
"# res, phi_deg, theta_deg = res[:, :, 0], res[:, 0, 1], res[:, 0, 2]" |
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] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 7, |
|
"metadata": {}, |
|
"outputs": [], |
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"source": [ |
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"res = np.abs(population.response_func(grid[:, 1], grid[:, 0]).swapaxes(0, 1)) * 10" |
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] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 8, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
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"name": "#%%\n" |
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} |
|
}, |
|
"outputs": [], |
|
"source": [ |
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"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])" |
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] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 9, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"image/png": "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", |
|
"text/latex": [ |
|
"$\\displaystyle \\left( 2592, \\ 40\\right)$" |
|
], |
|
"text/plain": [ |
|
"(2592, 40)" |
|
] |
|
}, |
|
"execution_count": 9, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
} |
|
], |
|
"source": [ |
|
"res.shape" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 10, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [], |
|
"source": [ |
|
"res_reshaped = res.reshape((n_phi, n_theta, -1))" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 11, |
|
"metadata": {}, |
|
"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": 11, |
|
"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": [ |
|
"sns.distplot(res.ravel())" |
|
] |
|
}, |
|
{ |
|
"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('Marginal 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('Marginal 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": 15, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"data": { |
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"image/png": 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", |
|
"text/plain": [ |
|
"<Figure size 432x288 with 9 Axes>" |
|
] |
|
}, |
|
"metadata": { |
|
"needs_background": "light" |
|
}, |
|
"output_type": "display_data" |
|
} |
|
], |
|
"source": [ |
|
"fig, ax = plt.subplots(3, 3)\n", |
|
"ax = ax.flatten()\n", |
|
"# set title\n", |
|
"fig.suptitle('Joint Tunings')\n", |
|
"for i in range(9):\n", |
|
" ax[i].imshow(res_reshaped[:, :, i], cmap='viridis', extent=[0, 180, 0, 360])" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 16, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<matplotlib.image.AxesImage at 0x7fefe9397f40>" |
|
] |
|
}, |
|
"execution_count": 16, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
}, |
|
{ |
|
"data": { |
|
"image/png": 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kI7kFwLcB3GdmlzZ6e9bDMIMzC2Cve7wHwKkhrn8oSFbRCc2DZnb1oPDYnYIyzOAcA3AryTdmJ4Xdjc6pGWODJNG5k+AJM/uc+9LYnYIy7KPj7wXweQBlAA+Y2X8MbeVDQPJdAH4G4CkA7Wz6M+i8z3kIwF8gu9OOmZ3fkI1cI/rkWEL0ybGEKDgSouBIiIIjIQqOhCg4EqLgSIiCIyF/Am3T3AxM9WMMAAAAAElFTkSuQmCC", |
|
"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": [ |
|
"## PCA" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 20, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [], |
|
"source": [ |
|
"res_df = pd.DataFrame(res, columns=['x' + str(i) for i in range(N)])" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 21, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [], |
|
"source": [ |
|
"from sklearn.decomposition import PCA\n", |
|
"import seaborn as sns" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 22, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<AxesSubplot:>" |
|
] |
|
}, |
|
"execution_count": 22, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
}, |
|
{ |
|
"data": { |
|
"image/png": 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", |
|
"text/plain": [ |
|
"<Figure size 432x288 with 2 Axes>" |
|
] |
|
}, |
|
"metadata": { |
|
"needs_background": "light" |
|
}, |
|
"output_type": "display_data" |
|
} |
|
], |
|
"source": [ |
|
"sns.heatmap(res_df.corr())" |
|
] |
|
}, |
|
{ |
|
"cell_type": "markdown", |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%% md\n" |
|
} |
|
}, |
|
"source": [ |
|
"Let's take 6 components" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 52, |
|
"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", |
|
" <th>PC7</th>\n", |
|
" </tr>\n", |
|
" </thead>\n", |
|
" <tbody>\n", |
|
" <tr>\n", |
|
" <th>0</th>\n", |
|
" <td>1.152136</td>\n", |
|
" <td>6.882893</td>\n", |
|
" <td>-1.545938</td>\n", |
|
" <td>-0.027471</td>\n", |
|
" <td>-1.348491</td>\n", |
|
" <td>-0.067572</td>\n", |
|
" <td>3.253269</td>\n", |
|
" </tr>\n", |
|
" <tr>\n", |
|
" <th>1</th>\n", |
|
" <td>1.081195</td>\n", |
|
" <td>6.691970</td>\n", |
|
" <td>-1.446044</td>\n", |
|
" <td>-0.080450</td>\n", |
|
" <td>-1.327843</td>\n", |
|
" <td>-0.204249</td>\n", |
|
" <td>3.526015</td>\n", |
|
" </tr>\n", |
|
" <tr>\n", |
|
" <th>2</th>\n", |
|
" <td>0.996579</td>\n", |
|
" <td>6.447147</td>\n", |
|
" <td>-1.338009</td>\n", |
|
" <td>-0.133996</td>\n", |
|
" <td>-1.298363</td>\n", |
|
" <td>-0.338896</td>\n", |
|
" <td>3.770720</td>\n", |
|
" </tr>\n", |
|
" <tr>\n", |
|
" <th>3</th>\n", |
|
" <td>0.937118</td>\n", |
|
" <td>6.268197</td>\n", |
|
" <td>-1.259541</td>\n", |
|
" <td>-0.170523</td>\n", |
|
" <td>-1.273480</td>\n", |
|
" <td>-0.424933</td>\n", |
|
" <td>3.869237</td>\n", |
|
" </tr>\n", |
|
" <tr>\n", |
|
" <th>4</th>\n", |
|
" <td>0.938863</td>\n", |
|
" <td>6.362412</td>\n", |
|
" <td>-1.261052</td>\n", |
|
" <td>-0.188472</td>\n", |
|
" <td>-1.318064</td>\n", |
|
" <td>-0.425958</td>\n", |
|
" <td>3.715137</td>\n", |
|
" </tr>\n", |
|
" </tbody>\n", |
|
"</table>\n", |
|
"</div>" |
|
], |
|
"text/plain": [ |
|
" PC1 PC2 PC3 PC4 PC5 PC6 PC7\n", |
|
"0 1.152136 6.882893 -1.545938 -0.027471 -1.348491 -0.067572 3.253269\n", |
|
"1 1.081195 6.691970 -1.446044 -0.080450 -1.327843 -0.204249 3.526015\n", |
|
"2 0.996579 6.447147 -1.338009 -0.133996 -1.298363 -0.338896 3.770720\n", |
|
"3 0.937118 6.268197 -1.259541 -0.170523 -1.273480 -0.424933 3.869237\n", |
|
"4 0.938863 6.362412 -1.261052 -0.188472 -1.318064 -0.425958 3.715137" |
|
] |
|
}, |
|
"execution_count": 52, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
} |
|
], |
|
"source": [ |
|
"N_COMP = 7\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": 53, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"image/png": "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", |
|
"text/latex": [ |
|
"$\\displaystyle \\left( 2592, \\ 7\\right)$" |
|
], |
|
"text/plain": [ |
|
"(2592, 7)" |
|
] |
|
}, |
|
"execution_count": 53, |
|
"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": 25, |
|
"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": 26, |
|
"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": 27, |
|
"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": 37, |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"step = 5" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 54, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"image/png": 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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(data_pca[::step]).to_numpy()" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 55, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<matplotlib.collections.PathCollection at 0x7fefdadbe350>" |
|
] |
|
}, |
|
"execution_count": 55, |
|
"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[::step], param_1)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "markdown", |
|
"metadata": {}, |
|
"source": [ |
|
"#### Orientation is decoded:" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 56, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<matplotlib.collections.PathCollection at 0x7fefd8911d20>" |
|
] |
|
}, |
|
"execution_count": 56, |
|
"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[::step], param_1)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 57, |
|
"metadata": { |
|
"collapsed": false, |
|
"pycharm": { |
|
"name": "#%%\n" |
|
} |
|
}, |
|
"outputs": [], |
|
"source": [ |
|
"data_without_features = decoding.remove_feature(data_pca[::step].to_numpy(), pd.DataFrame(param_1))" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 58, |
|
"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... done\n" |
|
] |
|
} |
|
], |
|
"source": [ |
|
"param_2 = decoding.cohomological_parameterization(\n", |
|
" pd.DataFrame(data_without_features)).to_numpy()" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 59, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<matplotlib.collections.PathCollection at 0x7fefd8815360>" |
|
] |
|
}, |
|
"execution_count": 59, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
}, |
|
{ |
|
"data": { |
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"image/png": 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", |
|
"text/plain": [ |
|
"<Figure size 640x480 with 1 Axes>" |
|
] |
|
}, |
|
"metadata": {}, |
|
"output_type": "display_data" |
|
} |
|
], |
|
"source": [ |
|
"plt.title(\"Parameter 2 of CP vs. orientation\")\n", |
|
"plt.scatter(theta_deg[::step], param_2)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 60, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<matplotlib.collections.PathCollection at 0x7fefd887ce50>" |
|
] |
|
}, |
|
"execution_count": 60, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
}, |
|
{ |
|
"data": { |
|
"image/png": 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", |
|
"text/plain": [ |
|
"<Figure size 640x480 with 1 Axes>" |
|
] |
|
}, |
|
"metadata": {}, |
|
"output_type": "display_data" |
|
} |
|
], |
|
"source": [ |
|
"plt.title(\"Parameter 2 of CP vs. phase\")\n", |
|
"plt.scatter(phi_deg[::step], param_2)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"metadata": {}, |
|
"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 |
|
}
|
|
|