septum-mec/actions/stimulus-spike-lfp-response.../data/20_stimulus-spike-lfp-respo...

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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import expipe\n",
"import pathlib\n",
"import numpy as np\n",
"import spatial_maps.stats as stats\n",
"import septum_mec\n",
"import septum_mec.analysis.data_processing as dp\n",
"import septum_mec.analysis.registration\n",
"import head_direction.head as head\n",
"import spatial_maps as sp\n",
"import speed_cells.speed as spd\n",
"import re\n",
"import joblib\n",
"import multiprocessing\n",
"import shutil\n",
"import psutil\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib\n",
"import seaborn as sns\n",
"from distutils.dir_util import copy_tree\n",
"from neo import SpikeTrain\n",
"import scipy\n",
"from functools import reduce\n",
"from tqdm.notebook import tqdm_notebook as tqdm\n",
"tqdm.pandas()\n",
"\n",
"from spikewaveform.core import calculate_waveform_features_from_template, cluster_waveform_features\n",
"\n",
"from septum_mec.analysis.plotting import violinplot, despine\n",
"\n",
"from septum_mec.analysis.statistics import load_data_frames, make_paired_tables, make_statistics_table"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## chose where to sample LFP"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"#################################################\n",
"\n",
"# lfp_location = ''\n",
"lfp_location = '-other-tetrode'\n",
"# lfp_location = '-other-drive'\n",
"\n",
"##################################################"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"plt.rc('axes', titlesize=12)\n",
"plt.rcParams.update({\n",
" 'font.size': 12, \n",
" 'figure.figsize': (6, 4), \n",
" 'figure.dpi': 150\n",
"})\n",
"\n",
"output_path = pathlib.Path(\"output\") / (\"stimulus-spike-lfp-response\" + lfp_location)\n",
"(output_path / \"statistics\").mkdir(exist_ok=True, parents=True)\n",
"(output_path / \"figures\").mkdir(exist_ok=True, parents=True)\n",
"output_path.mkdir(exist_ok=True)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"project_path = dp.project_path()\n",
"project = expipe.get_project(project_path)\n",
"actions = project.actions"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of sessions above threshold 194\n",
"Number of animals 4\n",
"Number of individual gridcells 139\n",
"Number of gridcell recordings 230\n"
]
}
],
"source": [
"data, labels, colors, queries = load_data_frames()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"lfp_action = actions['stimulus-spike-lfp-response' + lfp_location]\n",
"lfp_results = pd.read_csv(lfp_action.data_path('results'))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# lfp_results has old unit id's but correct on (action, unit_name, channel_group)\n",
"lfp_results = lfp_results.drop('unit_id', axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"data = data.merge(lfp_results, how='left')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"data['stim_strength'] = data.stim_p_max / data.theta_peak"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"keys = [\n",
" 'theta_energy',\n",
" 'theta_peak',\n",
" 'theta_freq',\n",
" 'theta_half_width',\n",
" 'theta_vec_len',\n",
" 'theta_ang',\n",
" 'stim_energy',\n",
" 'stim_half_width',\n",
" 'stim_p_max',\n",
" 'stim_strength',\n",
" 'stim_vec_len',\n",
" 'stim_ang'\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"results, labels = make_paired_tables(data, keys)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
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],
"text/plain": [
" entity unit_idnum channel_group date Baseline I 11 Hz \\\n",
"51 1833 8 0 20719 0.251582 NaN \n",
"85 1833 13 0 20719 NaN 0.057134 \n",
"86 1833 14 0 20719 NaN 0.049972 \n",
"58 1833 23 0 200619 0.247097 NaN \n",
"127 1833 26 0 200619 NaN NaN \n",
".. ... ... ... ... ... ... \n",
"139 1849 835 4 150319 NaN NaN \n",
"43 1849 851 5 60319 0.665441 NaN \n",
"65 1849 932 7 280219 0.034074 NaN \n",
"74 1849 937 7 280219 NaN 0.126604 \n",
"105 1849 939 7 280219 NaN NaN \n",
"\n",
" Baseline II 30 Hz \n",
"51 NaN NaN \n",
"85 0.194778 0.042542 \n",
"86 0.129583 NaN \n",
"58 NaN NaN \n",
"127 0.179928 0.034969 \n",
".. ... ... \n",
"139 NaN 0.023559 \n",
"43 NaN NaN \n",
"65 NaN NaN \n",
"74 NaN NaN \n",
"105 0.246451 NaN \n",
"\n",
"[137 rows x 8 columns]"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"results['gridcell']['theta_peak']"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAgkAAAFGCAYAAADghAzcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAgAElEQVR4nOydd5hU1dnAf7N9F5bem4DAK4iIBRsqWKIGBVvsRNGoMRGjJppijFETxR5jiUb9FFssITawKyoKggiIAvKCSO8ddpdtM/P9ce7M3B1mZ3dnZ3bKnt/zzDO3nHPvOzN37n3P247H7/djsVgsFovFEk5WsgWwWCwWi8WSmlglwWKxWCwWS0SskmCxWCwWiyUiVkmwWCwWi8USEaskWCwWi8ViiYhVEiwWi8VisUTEKgkWi8VisVgiYpUEi8VisVgsEbFKgsVisVgslohYJcFisVgsFktErJJgsVgsFoslIlZJsFgsFovFEhGrJFgsFovFYomIVRIsFovFYrFEJCfZAjQnRGSIqn4bYftE4BJntauqbmhSwcKoTU5LchGR3sByZ/XfqnpVEsVptoiI31l8X1VPifOxbwX+6qweqaozYzjGp8AIoEJVC8L2NUp2ERkJfOKs/klV74rQJg/oq6qLG3r8eBH2PfZR1RXJkiXdsZaEJkBEWovIP4G5yZYlGiLSRUReAN5MtiwWiyX9EJETgW+B85MtiyU+WEtC0/AAcFmyhagHLwLHAyuTLYjFYkkvRKQn8GGy5bDEF6skNA3ZyRagnqSLnBZL0lBVT7JliIaqjkzgsT8Favv89v6RgVh3g8VisVgslohYJcFisVgsFktErLshgYRF2Aa2BaKLP6vNLOhEsd8InAJ0B3YBi4CJwLOq6o/Uz+mbC4wDzgGGAO2AHcB8YBLwjKpWhvWZSCi7AmAfl5zPquq4sPadgSuAEwBxzlENbAVmAy8D/4smZyyIyHznM+0EOqtqRZS2/4eJA/EBvVR1bdj+gcB45zP0wJhQV2Mitx9W1UV1yJINnApc6sjUHdgDLAReBZ5Q1fIYPmajcXzD1wAnA72BPGA98DnwuKp+WUu/WzHX605VbSMiXYDfAqOBXkAV8D3wCvBYtO8/imzjgGec1baY3+c64CygL+Z3+AF4Dfinqu6q5TiFmGvwTMz3X4y5Ln4EPgD+parrGypfPT9DxAyBsMj/gzD/2auB8zD/k3xgBTAFuF9VN9bjXB2BGzC/QW+gHFgCvIT5DSoj9PmUWrIbwtp5MPeKK4HBmN9iCeY+8Yiqlkbo4/6MwewG13cS4K8iErj3Hee4KdzHaYe5Rk8F+gFFwCZgJuYe9W5tcjv9c4BzgcuB/YA2wDJMXNU/ovW1NAxrSUg9zsbciH+NuWnmAx0xf/pngLedP8heiEg/jDLwBPAToDOQ6/Q/EXgcmC8iEqtwInIJJg3vb8BIoKsjYwvMg+Rs4L/Am86DNJ4867y3Bn4aRcZ8Rw6AjyMoCH8BvsN8x4KRvchZvgr4TkRudW6ikY7fBZiKyQI5g9Dv1AYYDvwTmCsivWL4jI1CRH6BudHfiHl4tgIKgD7AxcAMEfm3o0xGO87RGIXnRsxNuAjzvR+BuQl/5dzoGyUu5ne4DTgQ86BvCQwFbgcWOApzuGw9MZlC/8Rcg+0w13kH4DDgZmCZiJzRSPkaQyfga0zQ8uGYa6MQGIj5TheLyCF1HONoQIHfO/0KMYrV4cCDwHQRaRWjfDkYZfZpzG/aEnOtHArcBXzvKNJxR0RGYR7otwLDMJ8pH+iJGdy8IyJvikhxLf3bAZ9hFILjMPegQoyiMwH4CmifCNmbI1ZJSCyPY0YUk13bDnJel9fS5xHMaOpRjCXhOODPQECr/ylmdFcD58H1OeZmUun0PxVz0zwd84D1Ym74n4hIV1f3WxyZ5jjr611y3uI6x/EYa0YhsA1zI/8p5iZztnPOwMhmdJTPGCsvYiwWABdEaXca5oEG8Jx7hzNavh0TZPUtRik4CnNDvhZz88rCjKhrWIGc/gWYkdSxzqZpwFjMd3AW8L6zfSDwVl0P43jijNKfwigFy4HfAcdgPt8VwDdO0ysximRtFAJvYR4aj2Guw6Mwlpd1TpshwB2NFPkNjGL5EjAG8x1eilFywDw0HovQbyLmOvYC92MsJsMw1/ujmGukEHgh7DpvSp4FDgDewzz4DsekBc529rcBnqtNEXW412n3POb/dCzmGt3i7A880GPheOBnwBqMteNIzH1iirO/J/ChiLSO3H0vDsJ8/wH+Tege8nVgo4icgLm22mAsB7dg7nFHAD8HPnWajgFeDx9oiEgW8C7megTz/zvX6T8W8/0OwQwALHHAuhsSiFMUaYOIbHNt+yZKF4AK4HhVneHa9qmITAUCZuJLgHvC+j0OdMG4Jk5U1dlh+98SkUmYP2hXzGjwfEemVcAqESlx2lbWIuftzns1cLKqfh22/zUReY+QUnQO5mYRF1R1o4i8j7kZjRaRlqpaEqHphc57CcZsDYCIHAz8xVl9HrhMVatd/aY7boopmBHqLSLyapjr4WbMAwqMW+I3Yed+3eW+ORDzHT/fsE/acESkG+YBCfAxcHqYufhLR67nMArWOBF5RVXfi3C4PIwSdVrY/i9F5B1gAcaycKGI/EZVq2IUuwtwhao+5do2S0TewJjquwIni0iXQIExEdkH84AD+Kuqhisq74jIIsx30QJzLdwfo3yNoQtwh6re7Nr2lYi8jhnpHggMwijxs6Ic51xVneRa/1xEJmOsPIXAWBEZr6q+BsrnwXzHI1R1i2v7WyJyL8bF0R1zvd9Y18FU9RsR2eHatCH8HuK4iF7AXFvfASeo6mZXk1kYxe5ujPXkBIxy+7irzS8w3xmY/9UlLrfmLBF5BWMhObMumS31w1oSUo9HwhQEAJzKa4FiTPu5XQ4iMgCjeYO5MYUrCIFjTCFksj/HebDUCxEpwpgEtwGTIygI7nMEbhbd63v8BhCwDBRiRj7hcrYmNKKZpKplrt2/w1zzW4GrwhQEAJwH62WAH3MjvcZ17CxC1pFlzvEicQPGfw9mlNsUXI15cFcDF0fyJzuf91cY3z2YUWltvBZJgVDV5YRy4Vth3BixMjtMQQicYwfmRg/mNxji2t3Ftby0luM+jbGo/IXoD+BEsh5jTq+BE0Mw0bXpwCjH+F+YghA4xnLMaBqMi2afGGUcF6YgBPgToe/2MqeCYjwYS+j3uzxMQXDzZ0xcCux9jf7Sed8O/Do87sm5xi8jdI1bGolVElKPd6LsC/xxswiZ0wFGEcpdrquYSeD4WZjRcr1Q1TJVHaaq7TFmymgEykrn1/f4DeAtQkpIJJfD2a7zBl0Njlk3EMcwPUx5qIFzE/7eWT3BtWsYJs4D4KXaRtDOjfdgoIOqjq39o8SVgGK0SFXX1dZIVXcC053VY6O4Qz6Icq5lruWIfuN6Ess5fiDkcnpARM4I/wyqWq6qV6jq31X1i0bI1ximRlJCHer7/dXnXgAmJqOhzIsymKgG/uM69qExHD8SgWt0p6p+VVsj5/yBa2O/wGDGCZg+2Nk+uRYrYkDJfD0+IlusuyH1WBNlnzta3v3bHeRantuAuMS+9W3oJmDaFJEWmJHkvhgT/IEY335Pp2nclVBVLXdMir8EThKRdqq6zdXkIud9FSH/JpjI8LbO8pgI0di14R4pD3AtRy2xraoL6nn8RuNYlQ5wVoc04LMVYZSeSNfciij93DfnxtxDGnwOVd0qIk9iLCLdMQ+D3SLyCfAR8IGqaiNkihcrouyr7/cXy72gvtRlYZnnWj4A2Mu6GQOB+1TrBlyjYO5T6zCBroHBUF1u268wmRuWRmKVhNRjdz3buQOeOsR4rrZ1N6mJiPTAmNnHULuS4SOxVqpnMUpCLsaq8YQjWzdC1pEXwkyRsX5HOSJSrKq7CVkRwLgsUoW2xP59tyXywyjiKM3B/b02pvpgrOe4FhO7Mx5zDyvGXI9jAERkGSZN88EoJu1EE4/vL5Z7QX3ZVMd+txuisVksARp7n2rI/6/O9FJL/bBKQuoRS20
"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 555x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"xlabel = {\n",
" 'theta_energy': 'Theta coherence energy',\n",
" 'theta_peak': 'Theta peak coherence',\n",
" 'theta_freq': '(Hz)',\n",
" 'theta_half_width': '(Hz)',\n",
" 'theta_vec_len': 'a.u.',\n",
" 'theta_ang': 'rad'\n",
"}\n",
"for cell_type in ['gridcell', 'ns_inhibited', 'ns_not_inhibited']:\n",
" for key in xlabel:\n",
" fig = plt.figure(figsize=(3.7,2.2))\n",
" plt.suptitle(key + ' ' + cell_type)\n",
" legend_lines = []\n",
" for color, label in zip(colors, labels):\n",
" legend_lines.append(matplotlib.lines.Line2D([0], [0], color=color, label=label))\n",
" sns.kdeplot(data=results[cell_type][key].loc[:,labels], cumulative=True, legend=False, palette=colors, common_norm=False)\n",
" plt.xlabel(xlabel[key])\n",
" plt.legend(\n",
" handles=legend_lines,\n",
" bbox_to_anchor=(1.04,1), borderaxespad=0, frameon=False)\n",
" plt.tight_layout()\n",
" plt.grid(False)\n",
" despine()\n",
" figname = f'spike-lfp-coherence-histogram-{key}-{cell_type}'.replace(' ', '-')\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.png', \n",
" bbox_inches='tight', transparent=True)\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.svg', \n",
" bbox_inches='tight', transparent=True)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAc8AAAFGCAYAAAAMxxQ7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAgAElEQVR4nOzdd5hbxdXA4Z+k7cXrbuOCKxxww4CDIRgwvdqmh14dSgIJSShpX4AUCIEkJECAUEMxARLTbIqxabaxgdBtw9gGbMC9by+S7vfHXJVdS1pJK2097/PsI83VvaPRrlZHd+7MGY/jOCillFIqed62boBSSinV0WjwVEoppVKkwVMppZRKkQZPpZRSKkUaPJVSSqkUafBUSimlUqTBUymllEqRBk+llFIqRRo8lVJKqRRp8FRKKaVSpMFTKaWUSpEGT6WUUipFGjyVUkqpFGnwVEoppVKU09YNUNknIuOMMZ/E2P4wcL5b3MUYs75VG6ZUC4jIKmAIYIwxe6Rx/GTgdbd4oTHm4Uy1raXivTYRGQp85RbvNcZc1uqNU4AGz05NRMqA3wI/RP/WSimVMfqB2rn9BbiorRuhlFKdjQbPzs2X6EFjzAXABa3SEqUyzBgztK3boLouHTCklFJKpUiDp1JKKZUi7bbtAEREgB8AhwPDsF96NgPvAzOBGcYYf9T+NwDXN6nDce++aYyZ7G57mDijbaNG+/3ZGHO1iBwPXAHsC5QAXwP/Bf5kjNnhHjMe+BlwKNDHbeNrwO+MMctb/ItIQEQGA1cCRwNDgTxgHTAfuMcYsyjOcTdgf1c7jDHdRaQ/8FNgCrAr0AB8BjwJ3G2MqUvQBg9wOnAWMAHoDVS4xz/ntqMyzrGhv89PgNnAncAk9/lXAj83xsyN2n8ocLX7encFqoCP3Od4SkTuAS4FVoe6N0XkauBWt4qLjDEPJXgt+wHvuMUrjTF3xts3zvF9sL/HqcBwoB5YBjwM3AdcC9wMYIzxpPO7SGa0rYgcBPwI+74dAKwHXgg9d5Kv5TDgYuzfNPSeMNi/6R2h93+cY/cHLgEOcZ+/AVgFzAH+boz5Otl2qPZFg2c7JyJnAQ9hg0G0Qe7PNOAnInKMMWZDltoQ+iButBn4JTBFRA4AzgT+AeRG7TMAOAeYJiIHGWM+zlL7LsZ+wBY0eWiY+3OeiPwTuMIY05CgnknYD8SeTR7a3/25UEQONcZsjXFsX+wXmQObPNQL+8E/Cft3OjVeIHcNBhZiv3yE7IMNGqHnOgb7xaUoap887JeWQ0XkJGwwbeoxbNDIAc7Gvq/iOde9rQdmJNhvJyKyL/BSk9dQQOT3eAawIImqmv1dJGiDF/g7dqR5tCHYL4FnA39spo5S7O/olCYPFWAD6QTgchE5rul7W0Ry3Oe/PMaxY92fK0TkR8aYfzb3elT7o9227ZiIjAQexH4wfoX9R5wEHIANSqEP4fHYwBVyD7A39ht2yN7uz/QUm3E+NnAa4PvY4HAu9tsz2A+B/wD3Ahuw3/IPAI4DXnH3KQX+luLzJkVELgDux34ofYU98z0I+K7b3o/cXS8BEn1IFQLPA92Au4Fj3DquANa6+4wD/hCjDcXY+YIHAg42SJ0E7AccC9wB1GK/TMwRkdEJ2nEV9oz1T+7rOA24yRizyn2u/d12FmED25+xQfMg7Bl0BTY4ndu0Yrdn4WW3eKiIDIjVABHJdesAmBXry0I87hnx69iAFwQewJ4dfxd7JroBmIw982xOwt9FM/5EJHCuAi7Dvi9PAJ4CepDg7NPtRXieSOD8BPu/cwC2VyL0hWIAMFtEejSp4n4igXMB9v9of+xr/yX2DDgfuFdEzkd1OHrm2b6djf0HCwCHGmNWRz22WESeAt7AfjCdJCK9jTGb3Q/J9SIS/tAzxnxEenpjPzgOMsaUu9veFpEPgSVu+RjsB9REY8zG0IEi8gqwGPgOcLCIdDfGbE+zHTtxP/zvcovzgGnGmOgzrkVu1/Qj2DPjC0TkSWPMy+wsDzs6+YQmjy8SkRexr7UIOMs9W4g+g/0DMArwAycZY2Y1qftlEXkEeBPb5f0A9oM0Fi82QPwqatt/3NfrxZ5h52ID55HGmLei9lvgvifeovHZWrSHsQHEi/2d/DnGPsdg/+4A/4pTTzx/xX5ZAjjbGPPvqMcWicgTbvt2S6KuuL+LRERkT+DHbnEJcLAxZlvULrNF5B1iv/aQi7GBDuAZ4HtN/uazRGQ5cAMwEPsl63fu859I5HLIzcaYXzap+00RuR/7vzsKuEtEZhljtjT32lT7oWee7Vt/97aSyNlPmPvPfD22e+gnZO/v+euowBl67qXYa3khN0YHTnefIJGzXw8wIsPt+iE2oPmB85oEzlAb/NgzgNB1qR833SfKzFiB1RjzFfCqW+yG7QoGQES6Y89wAe6LEThDdfwPezYEMFFEJiZox91xtk/CXrsDey36raY7GGM+x57hxfMCEPqQPjvOPqGz1k3Y7tekiMiuwIlu8YkmgTPUvvWkNvc43u8ikYuJnBhc1iRwhtrxF2wQj+cS97Ycm30oVnf/H4DQe/6oqO3XuLdLgV8RgzFmE3YcA0AxqfcIqTamwbN9+9y9LQOedr9RN2KMmWuM+bEx5m9Ng1eGBImkMGtqTdT9eXH2iW5TSUZaFHG8e7vMGLPTl4sQd0DHQrd4sNstGcucBM/1RdT90qj7k4lce3yVxF6Mun94nH3WGGO+jfPYlKj7ia5XPgnEPMM3xkRfw9y76XvKzUoVep7HE10jTrd9xpgF2MFDzUn0u0jkOPd2tTFmYYL9Hoy10R00NsEtPh9vQJD7xexgoL8x5iD32B7Yrl2AecYYJ9axrgXYbnaI/35Q7ZR227Zvj2C/xQ7EDgyaJiJfYj+k5wJzM9kNGsfmeCNEgeiRp+uS2McTZ5+UuQMyxrrFcVEjNJtTBPQDYn0or0pwXPTvIPr/Zu+o+zPtwOikDI+z/ZsEx4x3b3cYY1bE28kY0+B2qx8aZ5eHsCOTwV47jz47Oo3IwKtUu2zHR93/XzP7voPtskwk0e8iJrdre3e32NwAtXfjbN+NyHv1g0QVGGNMk03jo479kYj8qJk2hMR7P6h2Ss882zG3u+kI7HXDkOHYATxPA5tFZJ6InO0OcMiGiuZ3CX8Lb009SP/923RwR0i8LwlgBwKFRP+uezfdsYVtKI+zHWzQh0i3ayJxeyGMMR9ir2ODvYYb/XpCXbafpHGdPNS+QKyu0mTbFyXR7yKeXkQyazX3e4o3Or1f1P1Ur0Nm+v2g2ik982zn3GtYB7jXyE7BdkmFRmv6gMPcnwtFZIoxpibDTWjtoJis6Pfuy8AvUji22akOabbjRGB1vB2biDc3MNEZdGi6UjJfGpo7E38IO7hnKHaU8AIRGYId1Qqpn3U2ap+IeJrpskympyDZ3oR4xzT3hTJel3RLPhejj/09dkpRMgIteE7VBjR4dhDGmHewXV3XutdkDsOOmjwRO83icOyk+d+1WSNbV/T0CV8LRhNnsh2bstyOzdj5tb2TCE7NnQE9jh3AlItN7LDAvfVgvzA9nmb7cOvoFVVOp33p2oINirnEH3Ec0nQ+b0j037RXis8ffWxNG74vVZZp8GzHRKQQ+2HZ4I5uBcIjFmcAM0Rkb+z1JS82mHaJ4GmMqRORlcBIYF8RyUnUdSwil2HP1FcBr2Swm3lJ1P39gbcTtGF37DXFVcC7ia5bxvER9iyxBHtdLmbWJve63/hYj4UYYzaJyGzsl6+p2Pm509yHX04z4cZHREbw7kPiAVj7JngsbcYYR0SWAXth3xeJvmTE+x1FD2baK9Hzicgt2B6hL7FfPpq+HxIdm4ftMfkWO+gtUfIM1c7oNc92yv3H2gJ8SILh+u71q9BgnaYZdoLZaV27EUrC0JPIpP6duMkm7sLOkbwjw9dn5xHp2p6eYCQvwK+xXXmPERmRmYropBfxppmAHYWczJndw+7tEBE5KqpN6XTZAkRP04nbPhEZS+OBVpkW6irtT2REdiznxdrojvANDQSa6ibB2Il7rXgqdgrWHsa
"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 495x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"xlabel = {\n",
" 'stim_energy': 'Coherence energy',\n",
" 'stim_half_width': '(Hz)',\n",
" 'stim_p_max': 'Peak coherence',\n",
" 'stim_strength': 'Ratio',\n",
" 'stim_vec_len': 'a.u.',\n",
" 'stim_ang': 'rad'\n",
"}\n",
"# key = 'theta_energy'\n",
"# key = 'theta_peak'\n",
"for cell_type in ['gridcell', 'ns_inhibited', 'ns_not_inhibited']:\n",
" for key in xlabel:\n",
" fig = plt.figure(figsize=(3.3,2.2))\n",
" plt.suptitle(key + ' ' + cell_type)\n",
" legend_lines = []\n",
" for color, label in zip(colors[1::2], labels[1::2]):\n",
" legend_lines.append(matplotlib.lines.Line2D([0], [0], color=color, label=label))\n",
" sns.kdeplot(data=results[cell_type][key].loc[:,labels[1::2]], cumulative=True, legend=False, palette=colors[1::2], common_norm=False)\n",
" plt.xlabel(xlabel[key])\n",
" plt.legend(\n",
" handles=legend_lines,\n",
" bbox_to_anchor=(1.04,1), borderaxespad=0, frameon=False)\n",
" plt.tight_layout()\n",
" plt.grid(False)\n",
" despine()\n",
" figname = f'spike-lfp-coherence-histogram-{key}-{cell_type}'.replace(' ', '-')\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.png', \n",
" bbox_inches='tight', transparent=True)\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.svg', \n",
" bbox_inches='tight', transparent=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## polar plot"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"from septum_mec.analysis.statistics import VonMisesKDE"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAe4AAAFGCAYAAACsWHzVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAgAElEQVR4nOydeXhU1dnAf3dmsofsCavs8IIggiiIVgFXqgKKFXfEtWqlrm1dsKVYq7TWpVj0s264K24oLsUWte4LFRGQgwJBwhYIWUhC9vv9ce4kM5OZZJJMVs7veea5M/eec+65M3fue8573sWybRuDwWAwGAydA1d7d8BgMBgMBkP4GMFtMBgMBkMnwghug8FgMBg6EUZwGwwGg8HQiTCC22AwGAyGToQR3AaDwWAwdCKM4DYYDAaDoRNhBLfBYDAYDJ0II7gNBoPBYOhEGMFtMBgMBkMnwghug8FgMBg6EUZwGwwGg8HQiTCC22AwGAyGToQR3AaDwWAwdCI87d0BQ9siIqOUUquD7H8SuMj52FMptbNNO2ZoESLizc/7L6XUlHbtTAdHRGYDTzgfz1VKvdCMNj4AJgJblFL9I9a5FtLQtZn/eNfBCO4DBBFJBuYDv8L87gaDwdBpMQ/wA4d7gUvauxMGg8FgaBlGcB84uBs6qJSaDcxuk54YDO2IUupJ4Ml27obB0GyMcZrBYDAYDJ0II7gNBoPBYOhEGFV5J0NEBLgaOB4YgB587QFWAq8CzymlqnzKzwP+ENCG1wL5Q6XUJGffk4SwOBWRbKAf8Del1E0icipwDTAWSAR+Al4B/qKUKnTqjAZuBCYDmU4fVwB3KKU2tPiL8L+epcA0oAY4SCm1vYGyt6ON9AAmKKU+Dzh+EDAHOBnoD0QDO4CPgIeVUp+F0Z/jgEuBw4G+QCWggKXAQu931NaISBr62k4FBgPxQC7wOfCEUuqdEPVmU2epnIr+nq8DZgADAQv4EX3/PaCUKmphP6cCvwTGAcnALuA9YIFSaoOIlAExwB+VUvN86s1D3+uFTj9vRN+nPZ3rfF8pNSscq3IRSXH6cBYwyLnGb4FFSqkXw7yOTPR/6kz095Ti9OMz4CGl1PsN1I0HrgJOB4YBSUAe8DXwHPCSUqomnH4Yuh5GcHciROQ89AMnOuBQH+c1HbheRKYopXa1Uh8eRj/Q/HYDtwJTRWQCcC6wCIjyKdMLuACYLiLHKKW+jWC3FqMFtwuYCdzfQNnzne2GIEL7UuBBIDagzgDnNUtEHgGuUUpVBjYsIt3Qv8+ZAYdi0UL8cOAqETklwtffKCJyCvAsWnj4cpDzOktE3gAuUErta6gp4CX0gMSX0c7rchE5VimV3Yw+uoCHgcuD9PES4DwRuSDM5u4CfufzuQ9QHWY/RgNvowW+L8cCx4rIaTSirXS+72fQAwhf+qAHA2eJyIPAr5VSdkDdI4DXgN4BdXsCU53XHBH5hVJqRzjXZOhaGFV5J0FEBgOPo4X2ZvRo/GfABLRA9M4ER6OFppeHgTHAmz77xjivy5rYjYvQQluhH65HAxcC2c7xQ4CXgf9Dz5J+7fTvFOBfTpluwANNPG9jLAP2Ou/PDVVIRMaiBQ/A0wHHZgOPooXsZvRs7RjgKPS1rnKKXgE8EqRtC3iDOqG9Gv39TkA/aJ9z9vcC3hKRwAd6qyEixzt98874fo/WhByJ/v0+cIpOA14TkYYMGV9HC+3nnfJHAhcDXi3KQcBDzezqA9QJ7Y3o7/pI5zyvoH+b56k/cA2kG1por0ULyWOBeeH0S0R6Ax+ihaSNNmKbgr4PrkVrXy5A3/uh2jgOfU+mAhXoweAU9P91DrDNKXoNcFNA3RHA+2ihvQ9YAJwEjEcPSl93ih4FLBeRhMauydD1MDPuzsP5aPVgNTBZKbXF59jnIvIS+gF8FHCGiGQopfY4Ku+dIuIVbCilVtE8MtAC6RgfdeinIvINsMb5PAUtyMcrpXK9FUXkX2iV7BHoWUuKUqqgmf3wQylVISLPo33Ux4nIIKXUxiBFz3O2Nj6CW0R6Af9wPv4HmK6UKvGp95mzlPAUemAwW0ReVEq961PmUmCS8/414OyAWfkyEdmAFiC90Q/tO5p6rU1FROLQMz838B1wvFJqt0+RL4BnRGQB8Fv0Eszl6AFfMHoAlyulHvVtQ0ReB9ahBd7JItKjKQE+RGQMegkI4EvghICZ/5siciNwTxjNudDq8sk+1/pRmF35C1otDXBFwHV+JiIvOm0NCVZZRGKAf6JV62XOdXziU+QTEXkV+Ao9iJsrIg8ppYqd488ACUAOMCngPv4SWCIiV6Pv15HA7cDNYV6boYtgZtydhx7Othiot4brCIk/AH8Hrqf1ftu5gWuYSqm1wPc+u/7oK7SdMjXUzfot9LphJHnK5/05gQcdNax3/4cBA59fodd7q4BZAUIbAMdu4Cq0QAA9+/LlCmdbBFwcTJUO3Ime8YKeRbUFF1B371wWILR9uQ29Tg31r82XrwKEGQDOIOwl56MFjGpiP+eg71kbuCiYul4p9Tf0wCocXm7gWoPirGvPdD7+O8R17qL+UpEvx6PXs0HbfHwSWMCxwVjgfExED7YRkRPRGjOAG0MMPlFKLaJOS3KViEQFK2fouhjB3XlY72yT0aPu4YEFlFL/Vkpdq5R6IFBwRogatBovGNt83od6uPr2KTEiPXJQSn1J3XcUTF0+CT3DAX8hD9pYC2BdQ4ZtjlGZ90F8rPeBKSI90OvXAG+EMj5zhP+xQA+l1DGhryaieK+t0PmOguL0bbnzcZijhQjG8hD7Qau3vXQLt4POoMrbz8+UUusbKP5/YTb7eeNF6nESdVrI50IVcozKNoc4PNXnfeB95svj6BlzvFLK+52e6nP8vYa7ytvONgmtxTIcQBhVeefhKeA3aDXrdLSR1yb0H/zf6BlCRFTPDbDHR6UXSLnP+1AGM75lrMh0yY/FaKOkESJyiFLqO59jXqO0UvQ6PAAi4kGvzQOM8rG4b4x4oDtapTmEuuv5X0OVlFIqzPYjxRhnm9yEawM9aww2iMluoI7vvdGUZ0tPIMt5/3UjZb8Is82tTTi/l2E+7xtbTvoKbbAYyFBnWxRqxgzg/I/WBuwe4/N+r3YgCYuBwKfhFjZ0fsyMu5OglMoHTsB/JjEQrbZbAuwRkf+IyPmOoVRr0JC1cS2+7mhtzDNorQD4zLqddccZzsfXA9SwqTT/f+A1MOvusy+vmW21FhnNrBfKeC7UwA20mttLU+5B3+9vTyNlw9UkNcclrSm/YyivDW8bzbkPIv1bGbooZsbdiXBUiBNEZDzaevkUYIRz2A0c57wuFpGpSqn9Ee5CewnksFBK5YjICvQA5xy0ixpoFaTXDWpxQDXf/8C7wC1NOKV3Tbgj/4+8fVtNnZ9+OIRSBbcGvlbijQ2iwtUaNEW7EKxOYwOPYDYM0LJ7wVt3D3BiE+pta7yIoSvRkR84hhAopb5Aqwx/66yvHgechg7WEIc2kLmJNrBa7oAsRgvuASIy3vmuvNbk29HLCr7s9XnvbqbFvW8b6c2o35rsRRunxbXAm6C18Z1lZzZStrmz0nDwXeLJBLaEKgikhdjvvReacx946yYCq02AFUMojODuJDhuPQJUOlbcADguN88BzzkuNV+jZy2ncWAK7lfRfuzd0G5xa6kz+nk28GGolCoXkR/RkcTGioinIVW/iFyJ1m5ko3NfV6HdoLwc2lDnHLerM4FNwMw2sEtYgxbcg70ugg307Ry0qjcbbTNRz7q+ldiEVm0nAYc1UnZsK/bDd835CBpebx8dYv86tO9+koj0DxWIxvHjV+jBweNKqYfQv9WRaH/10TRgLyEiU9Datmy0l0RjSwyGLoRZ4+4EiEg0es3sGxoIIqGU+oa6WUNg9K8DYvSulPI1PpuOHsB4v4tQVr7e4DBpBHEl8+IEwfkHOqDGQq+AV0rloB/CANNCBcVwbA+moV3hhrWB0Ia6a7OAK0MVcvK1P4KOOvcszVM1NwtnMOW1kj5SRBpyFWyKur+p/AvwDlYuDmUrIiKHEFpw+2p
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"for paradigm in ['stim', 'theta']:\n",
" key = paradigm + '_vec_len'\n",
" for cell_type in ['gridcell', 'ns_inhibited', 'ns_not_inhibited']:\n",
" fig = plt.figure(figsize=(3.2,2.2))\n",
" plt.suptitle(key + ' ' + cell_type)\n",
" legend_lines = []\n",
" for color, query, label in zip(colors, queries, labels):\n",
" data_query = data.query(query + ' and ' + cell_type)\n",
" values = data_query[key].values\n",
" angles = data_query[paradigm + '_ang'].values\n",
" kde = VonMisesKDE(angles, weights=values, kappa=5)\n",
" bins = np.linspace(-np.pi, np.pi, 100)\n",
" plt.polar(bins, kde.evaluate(bins), color=color, lw=2)\n",
" plt.polar(angles, values, color=color, lw=1, ls='none', marker='.', markersize=2)\n",
"# values.hist(\n",
"# bins=bins[key], density=density, cumulative=cumulative, lw=lw, \n",
"# histtype=histtype, color=color)\n",
" legend_lines.append(matplotlib.lines.Line2D([0], [0], color=color, lw=2, label=label))\n",
" plt.legend(\n",
" handles=legend_lines,\n",
" bbox_to_anchor=(1.04,1), borderaxespad=0, frameon=False)\n",
" plt.tight_layout()\n",
"# plt.grid(False)\n",
" figname = f'spike-lfp-polar-plot-{paradigm}-{cell_type}'.replace(' ', '-')\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.png', \n",
" bbox_inches='tight', transparent=True)\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.svg', \n",
" bbox_inches='tight', transparent=True)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"stats = {}\n",
"for cell_type, result in results.items():\n",
" stats[cell_type], _ = make_statistics_table(result, labels)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"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>Theta energy</th>\n",
" <th>Theta peak</th>\n",
" <th>Theta freq</th>\n",
" <th>Theta half width</th>\n",
" <th>Theta vec len</th>\n",
" <th>Theta ang</th>\n",
" <th>Stim energy</th>\n",
" <th>Stim half width</th>\n",
" <th>Stim p max</th>\n",
" <th>Stim strength</th>\n",
" <th>Stim vec len</th>\n",
" <th>Stim ang</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Baseline I</th>\n",
" <td>2.5e-01 ± 3.3e-02 (63)</td>\n",
" <td>2.2e-01 ± 2.5e-02 (63)</td>\n",
" <td>7.6e+00 ± 9.6e-02 (63)</td>\n",
" <td>7.2e-01 ± 3.4e-02 (63)</td>\n",
" <td>2.1e-01 ± 1.2e-02 (63)</td>\n",
" <td>3.9e+00 ± 1.3e-01 (63)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11 Hz</th>\n",
" <td>1.1e-01 ± 1.6e-02 (56)</td>\n",
" <td>8.0e-02 ± 7.9e-03 (56)</td>\n",
" <td>7.7e+00 ± 1.2e-01 (56)</td>\n",
" <td>4.6e-01 ± 7.6e-02 (56)</td>\n",
" <td>4.8e-02 ± 7.3e-03 (56)</td>\n",
" <td>3.5e+00 ± 2.7e-01 (56)</td>\n",
" <td>9.7e-02 ± 1.0e-02 (58)</td>\n",
" <td>3.0e-01 ± 5.1e-02 (58)</td>\n",
" <td>4.5e-01 ± 3.5e-02 (58)</td>\n",
" <td>8.2e+00 ± 9.1e-01 (58)</td>\n",
" <td>2.3e-01 ± 1.5e-02 (58)</td>\n",
" <td>3.1e+00 ± 2.6e-01 (58)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Baseline II</th>\n",
" <td>2.7e-01 ± 3.2e-02 (46)</td>\n",
" <td>2.0e-01 ± 2.1e-02 (46)</td>\n",
" <td>8.2e+00 ± 7.7e-02 (46)</td>\n",
" <td>7.8e-01 ± 5.9e-02 (46)</td>\n",
" <td>2.0e-01 ± 1.2e-02 (46)</td>\n",
" <td>3.6e+00 ± 1.3e-01 (46)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30 Hz</th>\n",
" <td>3.7e-02 ± 1.5e-03 (35)</td>\n",
" <td>3.5e-02 ± 2.1e-03 (35)</td>\n",
" <td>8.8e+00 ± 1.6e-01 (35)</td>\n",
" <td>2.7e-01 ± 2.9e-02 (35)</td>\n",
" <td>1.7e-02 ± 2.3e-03 (35)</td>\n",
" <td>3.3e+00 ± 3.8e-01 (35)</td>\n",
" <td>1.0e-01 ± 1.0e-02 (33)</td>\n",
" <td>2.6e-01 ± 5.1e-03 (33)</td>\n",
" <td>4.3e-01 ± 3.7e-02 (33)</td>\n",
" <td>1.3e+01 ± 1.1e+00 (33)</td>\n",
" <td>2.7e-01 ± 1.5e-02 (33)</td>\n",
" <td>3.0e+00 ± 2.5e-01 (33)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>LMM Baseline I - 11 Hz</th>\n",
" <td>NaN</td>\n",
" <td>1.5e-13, 1.4e-01</td>\n",
" <td>9.3e-01, -2.9e-02</td>\n",
" <td>1.5e-03, 2.8e-01</td>\n",
" <td>NaN</td>\n",
" <td>6.2e-01, 2.9e-01</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>LMM Baseline I - Baseline II</th>\n",
" <td>9.8e-01, -1.1e-03</td>\n",
" <td>3.7e-01, -2.8e-02</td>\n",
" <td>3.7e-02, 3.2e-01</td>\n",
" <td>9.7e-01, -5.1e-03</td>\n",
" <td>NaN</td>\n",
" <td>7.5e-01, -1.2e-01</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>LMM Baseline I - 30 Hz</th>\n",
" <td>1.1e-35, 1.9e-01</td>\n",
" <td>2.7e-09, 1.7e-01</td>\n",
" <td>1.4e-02, -9.9e-01</td>\n",
" <td>1.3e-09, 4.5e-01</td>\n",
" <td>2.6e-12, 1.8e-01</td>\n",
" <td>1.3e-01, 7.9e-01</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>LMM 11 Hz - Baseline II</th>\n",
" <td>3.3e-02, 1.7e-01</td>\n",
" <td>1.1e-01, 1.2e-01</td>\n",
" <td>1.7e-01, 4.6e-01</td>\n",
" <td>7.4e-03, 3.3e-01</td>\n",
" <td>1.6e-03, 1.3e-01</td>\n",
" <td>7.9e-01, -1.7e-01</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>LMM 11 Hz - 30 Hz</th>\n",
" <td>1.4e-02, -6.8e-02</td>\n",
" <td>NaN</td>\n",
" <td>1.5e-04, 8.8e-01</td>\n",
" <td>2.1e-03, -1.8e-01</td>\n",
" <td>7.2e-02, -3.8e-02</td>\n",
" <td>7.6e-01, -2.3e-01</td>\n",
" <td>9.9e-01, 5.8e-04</td>\n",
" <td>5.9e-01, -5.3e-02</td>\n",
" <td>9.7e-01, 3.0e-03</td>\n",
" <td>1.4e-01, 5.0e+00</td>\n",
" <td>3.5e-01, 4.6e-02</td>\n",
" <td>4.9e-01, -4.2e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>LMM Baseline II - 30 Hz</th>\n",
" <td>1.5e-02, 2.1e-01</td>\n",
" <td>3.6e-02, 1.5e-01</td>\n",
" <td>1.4e-01, -4.8e-01</td>\n",
" <td>1.1e-02, 4.7e-01</td>\n",
" <td>1.2e-13, 1.7e-01</td>\n",
" <td>4.1e-01, 6.0e-01</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Theta energy Theta peak \\\n",
"Baseline I 2.5e-01 ± 3.3e-02 (63) 2.2e-01 ± 2.5e-02 (63) \n",
"11 Hz 1.1e-01 ± 1.6e-02 (56) 8.0e-02 ± 7.9e-03 (56) \n",
"Baseline II 2.7e-01 ± 3.2e-02 (46) 2.0e-01 ± 2.1e-02 (46) \n",
"30 Hz 3.7e-02 ± 1.5e-03 (35) 3.5e-02 ± 2.1e-03 (35) \n",
"LMM Baseline I - 11 Hz NaN 1.5e-13, 1.4e-01 \n",
"LMM Baseline I - Baseline II 9.8e-01, -1.1e-03 3.7e-01, -2.8e-02 \n",
"LMM Baseline I - 30 Hz 1.1e-35, 1.9e-01 2.7e-09, 1.7e-01 \n",
"LMM 11 Hz - Baseline II 3.3e-02, 1.7e-01 1.1e-01, 1.2e-01 \n",
"LMM 11 Hz - 30 Hz 1.4e-02, -6.8e-02 NaN \n",
"LMM Baseline II - 30 Hz 1.5e-02, 2.1e-01 3.6e-02, 1.5e-01 \n",
"\n",
" Theta freq Theta half width \\\n",
"Baseline I 7.6e+00 ± 9.6e-02 (63) 7.2e-01 ± 3.4e-02 (63) \n",
"11 Hz 7.7e+00 ± 1.2e-01 (56) 4.6e-01 ± 7.6e-02 (56) \n",
"Baseline II 8.2e+00 ± 7.7e-02 (46) 7.8e-01 ± 5.9e-02 (46) \n",
"30 Hz 8.8e+00 ± 1.6e-01 (35) 2.7e-01 ± 2.9e-02 (35) \n",
"LMM Baseline I - 11 Hz 9.3e-01, -2.9e-02 1.5e-03, 2.8e-01 \n",
"LMM Baseline I - Baseline II 3.7e-02, 3.2e-01 9.7e-01, -5.1e-03 \n",
"LMM Baseline I - 30 Hz 1.4e-02, -9.9e-01 1.3e-09, 4.5e-01 \n",
"LMM 11 Hz - Baseline II 1.7e-01, 4.6e-01 7.4e-03, 3.3e-01 \n",
"LMM 11 Hz - 30 Hz 1.5e-04, 8.8e-01 2.1e-03, -1.8e-01 \n",
"LMM Baseline II - 30 Hz 1.4e-01, -4.8e-01 1.1e-02, 4.7e-01 \n",
"\n",
" Theta vec len Theta ang \\\n",
"Baseline I 2.1e-01 ± 1.2e-02 (63) 3.9e+00 ± 1.3e-01 (63) \n",
"11 Hz 4.8e-02 ± 7.3e-03 (56) 3.5e+00 ± 2.7e-01 (56) \n",
"Baseline II 2.0e-01 ± 1.2e-02 (46) 3.6e+00 ± 1.3e-01 (46) \n",
"30 Hz 1.7e-02 ± 2.3e-03 (35) 3.3e+00 ± 3.8e-01 (35) \n",
"LMM Baseline I - 11 Hz NaN 6.2e-01, 2.9e-01 \n",
"LMM Baseline I - Baseline II NaN 7.5e-01, -1.2e-01 \n",
"LMM Baseline I - 30 Hz 2.6e-12, 1.8e-01 1.3e-01, 7.9e-01 \n",
"LMM 11 Hz - Baseline II 1.6e-03, 1.3e-01 7.9e-01, -1.7e-01 \n",
"LMM 11 Hz - 30 Hz 7.2e-02, -3.8e-02 7.6e-01, -2.3e-01 \n",
"LMM Baseline II - 30 Hz 1.2e-13, 1.7e-01 4.1e-01, 6.0e-01 \n",
"\n",
" Stim energy Stim half width \\\n",
"Baseline I NaN NaN \n",
"11 Hz 9.7e-02 ± 1.0e-02 (58) 3.0e-01 ± 5.1e-02 (58) \n",
"Baseline II NaN NaN \n",
"30 Hz 1.0e-01 ± 1.0e-02 (33) 2.6e-01 ± 5.1e-03 (33) \n",
"LMM Baseline I - 11 Hz NaN NaN \n",
"LMM Baseline I - Baseline II NaN NaN \n",
"LMM Baseline I - 30 Hz NaN NaN \n",
"LMM 11 Hz - Baseline II NaN NaN \n",
"LMM 11 Hz - 30 Hz 9.9e-01, 5.8e-04 5.9e-01, -5.3e-02 \n",
"LMM Baseline II - 30 Hz NaN NaN \n",
"\n",
" Stim p max Stim strength \\\n",
"Baseline I NaN NaN \n",
"11 Hz 4.5e-01 ± 3.5e-02 (58) 8.2e+00 ± 9.1e-01 (58) \n",
"Baseline II NaN NaN \n",
"30 Hz 4.3e-01 ± 3.7e-02 (33) 1.3e+01 ± 1.1e+00 (33) \n",
"LMM Baseline I - 11 Hz NaN NaN \n",
"LMM Baseline I - Baseline II NaN NaN \n",
"LMM Baseline I - 30 Hz NaN NaN \n",
"LMM 11 Hz - Baseline II NaN NaN \n",
"LMM 11 Hz - 30 Hz 9.7e-01, 3.0e-03 1.4e-01, 5.0e+00 \n",
"LMM Baseline II - 30 Hz NaN NaN \n",
"\n",
" Stim vec len Stim ang \n",
"Baseline I NaN NaN \n",
"11 Hz 2.3e-01 ± 1.5e-02 (58) 3.1e+00 ± 2.6e-01 (58) \n",
"Baseline II NaN NaN \n",
"30 Hz 2.7e-01 ± 1.5e-02 (33) 3.0e+00 ± 2.5e-01 (33) \n",
"LMM Baseline I - 11 Hz NaN NaN \n",
"LMM Baseline I - Baseline II NaN NaN \n",
"LMM Baseline I - 30 Hz NaN NaN \n",
"LMM 11 Hz - Baseline II NaN NaN \n",
"LMM 11 Hz - 30 Hz 3.5e-01, 4.6e-02 4.9e-01, -4.2e-01 \n",
"LMM Baseline II - 30 Hz NaN NaN "
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"stats['gridcell']"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"for cell_type, stat in stats.items():\n",
" stat.to_latex(output_path / \"statistics\" / f\"statistics_{cell_type}.tex\")\n",
" stat.to_csv(output_path / \"statistics\" / f\"statistics_{cell_type}.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"for cell_type, cell_results in results.items():\n",
" for key, result in cell_results.items():\n",
" result.to_latex(output_path / \"statistics\" / f\"values_{cell_type}_{key}.tex\")\n",
" result.to_csv(output_path / \"statistics\" / f\"values_{cell_type}_{key}.csv\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# psd plots"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"from septum_mec.analysis.plotting import plot_bootstrap_timeseries"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"coher = pd.read_feather(output_path / 'data' / 'coherence.feather')\n",
"freqs = pd.read_feather(output_path / 'data' / 'freqs.feather')"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"freq = freqs.T.iloc[0].values\n",
"\n",
"mask = (freq < 100)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for cell_type in ['gridcell', 'ns_inhibited', 'ns_not_inhibited']:\n",
" fig, axs = plt.subplots(1, 2, sharex=True, sharey=True, figsize=(5,2))\n",
" axs = axs.repeat(2)\n",
" for i, (ax, query) in enumerate(zip(axs.ravel(), queries)):\n",
" selection = [\n",
" f'{r.action}_{r.channel_group}_{r.unit_name}' \n",
" for i, r in data.query(query + ' and ' + cell_type).iterrows()]\n",
" values = coher.loc[mask, selection].dropna(axis=1).to_numpy()\n",
" values = 10 * np.log10(values)\n",
" plot_bootstrap_timeseries(freq[mask], values, ax=ax, lw=1, label=labels[i], color=colors[i])\n",
" # ax.set_title(titles[i])\n",
" ax.set_xlabel('Frequency Hz')\n",
" ax.legend(frameon=False)\n",
" ax.set_ylim(-30, 0)\n",
" axs[0].set_ylabel('Coherence')\n",
" despine()\n",
" figname = f'spike-lfp-coherence-{cell_type}'.replace(' ', '-')\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.png', \n",
" bbox_inches='tight', transparent=True)\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.svg', \n",
" bbox_inches='tight', transparent=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# NSni vs NSi analysis"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"nsi_vs_nsni = {}\n",
"for key in keys:\n",
" df = pd.DataFrame()\n",
" dfs = [results[k][key].loc[:, ['entity', 'unit_idnum', 'Baseline I']].rename({'Baseline I': k}, axis=1) for k in ['ns_inhibited', 'ns_not_inhibited']]\n",
" df = pd.merge(*dfs, on=['entity', 'unit_idnum'], how='outer')\n",
" nsi_vs_nsni[key] = df"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"nsi_vs_nsni.keys()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"nsi_vs_nsni['theta_energy']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from septum_mec.analysis.statistics import LMM"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"LMM(nsi_vs_nsni['theta_energy'], 'ns_inhibited', 'ns_not_inhibited', 'theta_energy')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"stat, stat_vals = make_statistics_table(nsi_vs_nsni, ['ns_inhibited', 'ns_not_inhibited'], wilcoxon_test=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"stat"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"stat.to_latex(output_path / \"statistics\" / f\"statistics_nsi_vs_nsni.tex\")\n",
"stat.to_csv(output_path / \"statistics\" / f\"statistics_nsi_vs_nsni.csv\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Store results in Expipe action"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"action = project.require_action(\"stimulus-spike-lfp-response\" + lfp_location)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"copy_tree(output_path, str(action.data_path()))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"septum_mec.analysis.registration.store_notebook(action, \"20_stimulus-spike-lfp-response.ipynb\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 4
}