{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "19:14:03 [I] klustakwik KlustaKwik2 version 0.2.6\n" ] } ], "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", "\n", "from tqdm import tqdm_notebook as tqdm\n", "from tqdm._tqdm_notebook import tqdm_notebook\n", "tqdm_notebook.pandas()\n", "\n", "from spike_statistics.core import permutation_resampling\n", "\n", "from spikewaveform.core import calculate_waveform_features_from_template, cluster_waveform_features\n", "\n", "from septum_mec.analysis.plotting import violinplot" ] }, { "cell_type": "code", "execution_count": 3, "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\"\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": 4, "metadata": {}, "outputs": [], "source": [ "data_loader = dp.Data()\n", "actions = data_loader.actions\n", "project = data_loader.project" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "identification_action = actions['identify-neurons']\n", "sessions = pd.read_csv(identification_action.data_path('sessions'))\n", "units = pd.read_csv(identification_action.data_path('units'))\n", "session_units = pd.merge(sessions, units, on='action')" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "lfp_action = actions['stimulus-spike-lfp-response']\n", "lfp_results = pd.read_csv(lfp_action.data_path('results'))" ] }, { "cell_type": "code", "execution_count": 7, "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": 8, "metadata": {}, "outputs": [], "source": [ "statistics_action = actions['calculate-statistics']\n", "shuffling = actions['shuffling']\n", "\n", "statistics_results = pd.read_csv(statistics_action.data_path('results'))\n", "statistics_results = session_units.merge(statistics_results, how='left')\n", "quantiles_95 = pd.read_csv(shuffling.data_path('quantiles_95'))\n", "action_columns = ['action', 'channel_group', 'unit_name']\n", "data = pd.merge(statistics_results, quantiles_95, on=action_columns, suffixes=(\"\", \"_threshold\"))" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "data['unit_day'] = data.apply(lambda x: str(x.unit_idnum) + '_' + x.action.split('-')[1], axis=1)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "data = data.merge(lfp_results, how='left')" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "waveform_action = actions['waveform-analysis']\n", "waveform_results = pd.read_csv(waveform_action.data_path('results')).drop('template', axis=1)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "data = data.merge(waveform_results, how='left')" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "colors = ['#1b9e77','#d95f02','#7570b3','#e7298a']\n", "labels = ['Baseline I', '11 Hz', 'Baseline II', '30 Hz']\n", "queries = ['baseline and Hz11', 'frequency==11', 'baseline and Hz30', 'frequency==30']" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "data.bs = data.bs.astype(bool)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of gridcells 225\n" ] } ], "source": [ "grid_query = 'gridness > gridness_threshold and information_rate > information_rate_threshold'\n", "sessions_above_threshold = data.query(grid_query)\n", "print(\"Number of gridcells\", len(sessions_above_threshold))\n", "# print(\"Number of animals\", len(sessions_above_threshold.groupby(['entity'])))" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "gridcell_sessions = data[data.unit_day.isin(sessions_above_threshold.unit_day.values)]" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
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1186 | \n", "1833-260619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.244049 | \n", "0.571337 | \n", "3.425185 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1189 | \n", "1833-260619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.222604 | \n", "0.576271 | \n", "6.484767 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1191 | \n", "1833-260619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.189559 | \n", "0.248665 | \n", "3.564358 | \n", "False | \n", "NaN | \n", "0.0 | \n", "
1193 | \n", "1833-260619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.257469 | \n", "0.636957 | \n", "26.839270 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1194 | \n", "1833-260619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.252255 | \n", "0.587372 | \n", "4.589373 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1197 | \n", "1833-260619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.261129 | \n", "0.592306 | \n", "7.407060 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1199 | \n", "1833-260619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.277189 | \n", "0.615988 | \n", "9.221822 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1202 | \n", "1833-260619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.287132 | \n", "0.616235 | \n", "7.835622 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1204 | \n", "1833-260619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.300175 | \n", "0.610068 | \n", "9.358786 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1208 | \n", "1833-200619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.293775 | \n", "0.657679 | \n", "7.071948 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1214 | \n", "1833-200619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.252895 | \n", "0.600200 | \n", "15.695836 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1215 | \n", "1833-200619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.271023 | \n", "0.699617 | \n", "11.768979 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1217 | \n", "1833-200619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.343906 | \n", "0.698383 | \n", "4.442023 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1218 | \n", "1833-200619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.304748 | \n", "0.641151 | \n", "3.102590 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1219 | \n", "1833-200619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.277708 | \n", "0.585645 | \n", "6.900656 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1220 | \n", "1833-200619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.294291 | \n", "0.639177 | \n", "22.458685 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1221 | \n", "1833-200619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.258204 | \n", "0.608094 | \n", "3.767155 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1223 | \n", "1833-200619-3 | \n", "True | \n", "1833 | \n", "NaN | \n", "False | \n", "True | \n", "3 | \n", "NaN | \n", "False | \n", "baseline ii | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.276894 | \n", "0.623636 | \n", "12.778706 | \n", "True | \n", "NaN | \n", "1.0 | \n", "
1255 | \n", "1833-010719-2 | \n", "False | \n", "1833 | \n", "11.0 | \n", "True | \n", "False | \n", "2 | \n", "ms | \n", "True | \n", "stim i | \n", "... | \n", "11.016969 | \n", "11.215476 | \n", "0.198507 | \n", "0.058616 | \n", "0.277537 | \n", "0.570597 | \n", "5.734302 | \n", "True | \n", "1.0 | \n", "NaN | \n", "
1257 | \n", "1833-010719-2 | \n", "False | \n", "1833 | \n", "11.0 | \n", "True | \n", "False | \n", "2 | \n", "ms | \n", "True | \n", "stim i | \n", "... | \n", "11.023725 | \n", "11.224735 | \n", "0.201010 | \n", "0.038708 | \n", "0.248774 | \n", "0.604394 | \n", "2.814742 | \n", "True | \n", "1.0 | \n", "NaN | \n", "
1263 | \n", "1833-010719-2 | \n", "False | \n", "1833 | \n", "11.0 | \n", "True | \n", "False | \n", "2 | \n", "ms | \n", "True | \n", "stim i | \n", "... | \n", "10.994052 | \n", "11.225703 | \n", "0.231651 | \n", "0.045162 | \n", "0.280033 | \n", "0.560729 | \n", "4.760330 | \n", "True | \n", "1.0 | \n", "NaN | \n", "
1264 | \n", "1833-010719-2 | \n", "False | \n", "1833 | \n", "11.0 | \n", "True | \n", "False | \n", "2 | \n", "ms | \n", "True | \n", "stim i | \n", "... | \n", "11.000518 | \n", "11.216176 | \n", "0.215657 | \n", "0.037637 | \n", "0.281934 | \n", "0.627089 | \n", "15.890929 | \n", "True | \n", "1.0 | \n", "NaN | \n", "
1268 | \n", "1833-010719-2 | \n", "False | \n", "1833 | \n", "11.0 | \n", "True | \n", "False | \n", "2 | \n", "ms | \n", "True | \n", "stim i | \n", "... | \n", "11.034662 | \n", "11.197408 | \n", "0.162746 | \n", "0.021146 | \n", "0.266512 | \n", "0.594033 | \n", "2.704037 | \n", "True | \n", "1.0 | \n", "NaN | \n", "
1275 | \n", "1833-010719-2 | \n", "False | \n", "1833 | \n", "11.0 | \n", "True | \n", "False | \n", "2 | \n", "ms | \n", "True | \n", "stim i | \n", "... | \n", "11.016058 | \n", "11.203307 | \n", "0.187249 | \n", "0.050767 | \n", "0.257098 | \n", "0.545188 | \n", "5.292658 | \n", "True | \n", "1.0 | \n", "NaN | \n", "
271 rows × 67 columns
\n", "\n", " | action | \n", "baseline | \n", "entity | \n", "frequency | \n", "i | \n", "ii | \n", "session | \n", "stim_location | \n", "stimulated | \n", "tag | \n", "... | \n", "stim_half_f2 | \n", "stim_half_width | \n", "stim_energy | \n", "half_width | \n", "peak_to_trough | \n", "average_firing_rate | \n", "bs | \n", "bs_stim | \n", "bs_ctrl | \n", "gridcell | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
33 | \n", "1833-260619-1 | \n", "True | \n", "1833 | \n", "NaN | \n", "True | \n", "False | \n", "1 | \n", "NaN | \n", "False | \n", "baseline i | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.272875 | \n", "0.602667 | \n", "5.945508 | \n", "True | \n", "NaN | \n", "1.0 | \n", "True | \n", "
34 | \n", "1833-260619-1 | \n", "True | \n", "1833 | \n", "NaN | \n", "True | \n", "False | \n", "1 | \n", "NaN | \n", "False | \n", "baseline i | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.226452 | \n", "0.274814 | \n", "2.860048 | \n", "False | \n", "NaN | \n", "0.0 | \n", "True | \n", "
35 | \n", "1833-260619-1 | \n", "True | \n", "1833 | \n", "NaN | \n", "True | \n", "False | \n", "1 | \n", "NaN | \n", "False | \n", "baseline i | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.247266 | \n", "0.570104 | \n", "3.365674 | \n", "True | \n", "NaN | \n", "1.0 | \n", "True | \n", "
39 | \n", "1833-260619-1 | \n", "True | \n", "1833 | \n", "NaN | \n", "True | \n", "False | \n", "1 | \n", "NaN | \n", "False | \n", "baseline i | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.284542 | \n", "0.644111 | \n", "17.471520 | \n", "True | \n", "NaN | \n", "1.0 | \n", "True | \n", "
40 | \n", "1833-260619-1 | \n", "True | \n", "1833 | \n", "NaN | \n", "True | \n", "False | \n", "1 | \n", "NaN | \n", "False | \n", "baseline i | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.259920 | \n", "0.581698 | \n", "5.891739 | \n", "True | \n", "NaN | \n", "1.0 | \n", "True | \n", "
5 rows × 68 columns
\n", "