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spike lfp analysis
2019-10-17 17:44:01 +00:00
{
"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": [
statistics
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"11:00:42 [I] klustakwik KlustaKwik2 version 0.2.6\n"
spike lfp analysis
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]
}
],
"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",
analysis update
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"from tqdm.notebook import tqdm_notebook as tqdm\n",
"tqdm.pandas()\n",
"\n",
spike lfp analysis
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"\n",
"from spike_statistics.core import permutation_resampling\n",
"\n",
"from spikewaveform.core import calculate_waveform_features_from_template, cluster_waveform_features\n",
"\n",
new selection of grid cells color changes and histogram overview of change
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"from septum_mec.analysis.plotting import violinplot, despine"
spike lfp analysis
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]
},
{
"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": [],
new selection of grid cells color changes and histogram overview of change
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"source": [
"stim_action = actions['stimulus-response']\n",
"stim_results = pd.read_csv(stim_action.data_path('results'))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# lfp_results has old unit id's but correct on (action, unit_name, channel_group)\n",
"stim_results = stim_results.drop('unit_id', axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
spike lfp analysis
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"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",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 11,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"data['unit_day'] = data.apply(lambda x: str(x.unit_idnum) + '_' + x.action.split('-')[1], axis=1)"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 12,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"data = data.merge(lfp_results, how='left')"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"data = data.merge(stim_results, how='left')"
]
},
{
"cell_type": "code",
"execution_count": 14,
spike lfp analysis
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"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",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 15,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"data = data.merge(waveform_results, how='left')"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 16,
spike lfp analysis
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"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",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 17,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"data.bs = data.bs.astype(bool)"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
analysis update
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"data.loc[data.eval('t_i_peak == t_i_peak and not bs'), 'ns_inhibited'] = True\n",
new selection of grid cells color changes and histogram overview of change
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"data.ns_inhibited.fillna(False, inplace=True)\n",
"\n",
analysis update
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"data.loc[data.eval('t_i_peak != t_i_peak and not bs'), 'ns_not_inhibited'] = True\n",
new selection of grid cells color changes and histogram overview of change
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"data.ns_not_inhibited.fillna(False, inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"# make baseline for inhibited vs not inhibited\n",
"data.loc[data.unit_id.isin(data.query('ns_inhibited').unit_id.values), 'ns_inhibited'] = True\n",
"data.loc[data.unit_id.isin(data.query('ns_not_inhibited').unit_id.values), 'ns_not_inhibited'] = True"
]
},
{
"cell_type": "code",
"execution_count": 20,
spike lfp analysis
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
analysis update
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"Number of sessions above threshold 194\n",
"Number of animals 4\n"
spike lfp analysis
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]
}
],
"source": [
new selection of grid cells color changes and histogram overview of change
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"query = (\n",
" 'gridness > gridness_threshold and '\n",
" 'information_rate > information_rate_threshold and '\n",
" 'gridness > .2 and '\n",
" 'average_rate < 25'\n",
")\n",
"sessions_above_threshold = data.query(query)\n",
"print(\"Number of sessions above threshold\", len(sessions_above_threshold))\n",
"print(\"Number of animals\", len(sessions_above_threshold.groupby(['entity'])))"
spike lfp analysis
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]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 21,
spike lfp analysis
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"metadata": {},
analysis update
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of gridcells 139\n",
"Number of gridcell recordings 231\n",
"Number of animals 4\n"
]
}
],
spike lfp analysis
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"source": [
analysis update
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"gridcell_sessions = data[data.unit_day.isin(sessions_above_threshold.unit_day.values)]\n",
"print(\"Number of gridcells\", gridcell_sessions.unit_idnum.nunique())\n",
"print(\"Number of gridcell recordings\", len(gridcell_sessions))\n",
"print(\"Number of animals\", len(gridcell_sessions.groupby(['entity'])))"
spike lfp analysis
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]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 22,
spike lfp analysis
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"metadata": {},
"outputs": [
{
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"<table border=\"1\" class=\"dataframe\">\n",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>action</th>\n",
" <th>baseline</th>\n",
" <th>entity</th>\n",
" <th>frequency</th>\n",
" <th>i</th>\n",
" <th>ii</th>\n",
" <th>session</th>\n",
" <th>stim_location</th>\n",
" <th>stimulated</th>\n",
" <th>tag</th>\n",
" <th>...</th>\n",
new selection of grid cells color changes and histogram overview of change
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" <th>t_i_peak</th>\n",
" <th>p_i_peak</th>\n",
spike lfp analysis
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" <th>half_width</th>\n",
" <th>peak_to_trough</th>\n",
" <th>average_firing_rate</th>\n",
" <th>bs</th>\n",
" <th>bs_stim</th>\n",
" <th>bs_ctrl</th>\n",
new selection of grid cells color changes and histogram overview of change
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" <th>ns_inhibited</th>\n",
" <th>ns_not_inhibited</th>\n",
spike lfp analysis
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" </tr>\n",
" </thead>\n",
" <tbody>\n",
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analysis update
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" <th>14</th>\n",
spike lfp analysis
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" <td>stim ii</td>\n",
" <td>...</td>\n",
analysis update
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" <td>0.0087</td>\n",
" <td>0.000055</td>\n",
" <td>0.259757</td>\n",
" <td>0.362390</td>\n",
" <td>0.180529</td>\n",
new selection of grid cells color changes and histogram overview of change
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analysis update
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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" <td>0.0008</td>\n",
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1839-120619-4</td>\n",
" <td>False</td>\n",
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new selection of grid cells color changes and histogram overview of change
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" <td>NaN</td>\n",
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spike lfp analysis
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" <td>0.279806</td>\n",
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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" <td>0.0005</td>\n",
" <td>0.002365</td>\n",
spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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analysis update
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spike lfp analysis
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analysis update
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" <th>1263</th>\n",
" <td>1833-010719-2</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" <td>1833</td>\n",
analysis update
2019-12-13 10:43:57 +00:00
" <td>11.0</td>\n",
spike lfp analysis
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" <td>True</td>\n",
" <td>False</td>\n",
analysis update
2019-12-13 10:43:57 +00:00
" <td>2</td>\n",
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" <td>True</td>\n",
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spike lfp analysis
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" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
analysis update
2019-12-13 10:43:57 +00:00
" <td>0.280033</td>\n",
" <td>0.560729</td>\n",
" <td>4.760330</td>\n",
spike lfp analysis
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" <td>True</td>\n",
" <td>1.0</td>\n",
analysis update
2019-12-13 10:43:57 +00:00
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
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spike lfp analysis
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" <tr>\n",
analysis update
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" <th>1264</th>\n",
" <td>1833-010719-2</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>1833</td>\n",
analysis update
2019-12-13 10:43:57 +00:00
" <td>11.0</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>True</td>\n",
" <td>False</td>\n",
analysis update
2019-12-13 10:43:57 +00:00
" <td>2</td>\n",
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" <td>True</td>\n",
" <td>stim i</td>\n",
spike lfp analysis
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" <td>...</td>\n",
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analysis update
2019-12-13 10:43:57 +00:00
" <td>0.281934</td>\n",
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" <td>15.890929</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>True</td>\n",
" <td>1.0</td>\n",
analysis update
2019-12-13 10:43:57 +00:00
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
analysis update
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" <th>1268</th>\n",
" <td>1833-010719-2</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" <td>1833</td>\n",
analysis update
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" <td>11.0</td>\n",
spike lfp analysis
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" <td>True</td>\n",
" <td>False</td>\n",
analysis update
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" <td>2</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
spike lfp analysis
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" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
analysis update
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" <td>0.266512</td>\n",
" <td>0.594033</td>\n",
" <td>2.704037</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>True</td>\n",
" <td>1.0</td>\n",
analysis update
2019-12-13 10:43:57 +00:00
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
analysis update
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" <th>1271</th>\n",
" <td>1833-010719-2</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" <td>1833</td>\n",
analysis update
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" <td>11.0</td>\n",
spike lfp analysis
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" <td>True</td>\n",
" <td>False</td>\n",
analysis update
2019-12-13 10:43:57 +00:00
" <td>2</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
spike lfp analysis
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" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
analysis update
2019-12-13 10:43:57 +00:00
" <td>0.223261</td>\n",
" <td>0.592553</td>\n",
" <td>9.658453</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>1275</th>\n",
" <td>1833-010719-2</td>\n",
" <td>False</td>\n",
" <td>1833</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
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" <td>0.257098</td>\n",
" <td>0.545188</td>\n",
" <td>5.292658</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" </tbody>\n",
"</table>\n",
analysis update
2019-12-13 10:43:57 +00:00
"<p>231 rows × 73 columns</p>\n",
spike lfp analysis
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"</div>"
],
"text/plain": [
" action baseline entity frequency i ii session \\\n",
analysis update
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"14 1839-120619-4 False 1839 30.0 False True 4 \n",
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"21 1839-120619-4 False 1839 30.0 False True 4 \n",
"29 1839-120619-4 False 1839 30.0 False True 4 \n",
"30 1839-120619-4 False 1839 30.0 False True 4 \n",
"31 1839-120619-4 False 1839 30.0 False True 4 \n",
"... ... ... ... ... ... ... ... \n",
"1263 1833-010719-2 False 1833 11.0 True False 2 \n",
"1264 1833-010719-2 False 1833 11.0 True False 2 \n",
"1268 1833-010719-2 False 1833 11.0 True False 2 \n",
analysis update
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"1271 1833-010719-2 False 1833 11.0 True False 2 \n",
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"1275 1833-010719-2 False 1833 11.0 True False 2 \n",
"\n",
analysis update
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" stim_location stimulated tag ... t_i_peak p_i_peak half_width \\\n",
"14 ms True stim ii ... 0.0087 0.000055 0.259757 \n",
"21 ms True stim ii ... 0.0008 0.000880 0.242524 \n",
"29 ms True stim ii ... NaN NaN 0.279806 \n",
"30 ms True stim ii ... 0.0005 0.002365 0.265158 \n",
"31 ms True stim ii ... NaN NaN 0.246920 \n",
"... ... ... ... ... ... ... ... \n",
"1263 ms True stim i ... NaN NaN 0.280033 \n",
"1264 ms True stim i ... NaN NaN 0.281934 \n",
"1268 ms True stim i ... NaN NaN 0.266512 \n",
"1271 ms True stim i ... NaN NaN 0.223261 \n",
"1275 ms True stim i ... NaN NaN 0.257098 \n",
spike lfp analysis
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"\n",
analysis update
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" peak_to_trough average_firing_rate bs bs_stim bs_ctrl \\\n",
"14 0.362390 0.180529 False 0.0 NaN \n",
"21 0.534827 2.265039 True 1.0 NaN \n",
"29 0.598967 10.924422 True 1.0 NaN \n",
"30 0.581451 3.984881 True 1.0 NaN \n",
"31 0.570844 3.497452 True 1.0 NaN \n",
"... ... ... ... ... ... \n",
"1263 0.560729 4.760330 True 1.0 NaN \n",
"1264 0.627089 15.890929 True 1.0 NaN \n",
"1268 0.594033 2.704037 True 1.0 NaN \n",
"1271 0.592553 9.658453 True 1.0 NaN \n",
"1275 0.545188 5.292658 True 1.0 NaN \n",
spike lfp analysis
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"\n",
new selection of grid cells color changes and histogram overview of change
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" ns_inhibited ns_not_inhibited \n",
analysis update
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"14 True False \n",
new selection of grid cells color changes and histogram overview of change
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"21 False False \n",
"29 False False \n",
"30 False False \n",
"31 False False \n",
"... ... ... \n",
"1263 False False \n",
"1264 False False \n",
"1268 False False \n",
analysis update
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"1271 False False \n",
new selection of grid cells color changes and histogram overview of change
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"1275 False False \n",
spike lfp analysis
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"\n",
analysis update
2019-12-13 10:43:57 +00:00
"[231 rows x 73 columns]"
spike lfp analysis
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]
},
new selection of grid cells color changes and histogram overview of change
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"execution_count": 22,
spike lfp analysis
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gridcell_sessions"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 23,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
new selection of grid cells color changes and histogram overview of change
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"data.loc[:,'gridcell'] = np.nan\n",
"data['gridcell'] = data.isin(gridcell_sessions)\n",
"\n",
"data.loc[data.eval('not gridcell and bs'), 'bs_not_gridcell'] = True\n",
"data.bs_not_gridcell.fillna(False, inplace=True)"
spike lfp analysis
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]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 24,
spike lfp analysis
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"metadata": {},
"outputs": [
{
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new selection of grid cells color changes and histogram overview of change
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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],
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" action baseline entity frequency i ii session \\\n",
"33 1833-260619-1 True 1833 NaN True False 1 \n",
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"\n",
new selection of grid cells color changes and histogram overview of change
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" stim_location stimulated tag ... half_width peak_to_trough \\\n",
"33 NaN False baseline i ... 0.272875 0.602667 \n",
"34 NaN False baseline i ... 0.226452 0.274814 \n",
"35 NaN False baseline i ... 0.247266 0.570104 \n",
"39 NaN False baseline i ... 0.284542 0.644111 \n",
"40 NaN False baseline i ... 0.259920 0.581698 \n",
spike lfp analysis
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"\n",
new selection of grid cells color changes and histogram overview of change
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" average_firing_rate bs bs_stim bs_ctrl ns_inhibited \\\n",
"33 5.945508 True NaN 1.0 False \n",
"34 2.860048 False NaN 0.0 False \n",
"35 3.365674 True NaN 1.0 False \n",
"39 17.471520 True NaN 1.0 False \n",
"40 5.891739 True NaN 1.0 False \n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
"\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" ns_not_inhibited gridcell bs_not_gridcell \n",
"33 False True False \n",
"34 True True False \n",
"35 False True False \n",
"39 False True False \n",
"40 False True False \n",
spike lfp analysis
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"\n",
new selection of grid cells color changes and histogram overview of change
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"[5 rows x 75 columns]"
spike lfp analysis
2019-10-17 17:44:01 +00:00
]
},
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 24,
spike lfp analysis
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.query('baseline and Hz11 and gridcell').head()"
]
},
{
"cell_type": "code",
statistics
2019-12-13 10:47:07 +00:00
"execution_count": 33,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAewAAAFGCAYAAACorazoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAgAElEQVR4nO3dd5xdVbn/8c9kJm0mJKRQE3rgIVRRaRJM4NI0AiLlJ0gJJYBSvIgi94IICCLiDUi5cEEhCBeQ3hERKQJXRHrzoUgvUhJKMukzvz/W2jN7Tk6dOXXyfb9e89pnn733OutMe85ae61nNXV2diIiIiL1bUCtKyAiIiKFKWCLiIg0AAVsERGRBqCALSIi0gAUsEVERBqAAraIiEgDUMAWERFpAArYIiIiDUABW0REpAEoYIuIiDQABWwREZEGoIAtIiLSABSwRUREGoACtoiISANoqXUFlkZmtpG7P5Pl+RnAAXF3JXd/v6oVy5CrnvXAzKYCl8Xdvd39mhrVI1mf9m533ynL8WHAT4HdgLHAXOA9YIq7v16tepbCzE4m1BlgS3f/ay/KeB1YDXjA3SfnOCfX38H9wCRgvrsPKfW1601f34+ZrQ68FndPcfeTy1a5Psr33gr9bUjpFLCryMxGAKcCR1DH33szWxH4FbAVsEaNq9OwzGwA8Edgy9TTQ4A24J2aVKoO6PdLpHfqNmj0U9OBg2pdiSL8L7At8EatK9LgdqA7WD8DnAS8D7S6+8Ka1ar29Psl0gsK2NXVXOsKFKlR6lnv1k89/qG731OzmpQgdrmeXMGXWKp+v3LdEhAplQadiVROW+rxaznPEhEpggK2SOWk/74W1awWItIvqEu8CjJG3SbPJSMo842iXR34EbATYYTxZ8ALwAzgcnfvzHZdvHYgMBXYE9gIGAV8AjwNXA9c5u4LMq6ZQfcodYDVUvW83N2nZpy/AjAN+DfA4mssAj4GHgOuAW7IV89yiaOx/x3YHRgPdBBatdcD57r7Z3muHQ4cTLjnvCHhfTQBM4EngRuBK4q975waIZ32mpklj9fo6whxM3sDWBV41t03ynHOg8DWcXdTd/97lnOmARfH3fXc/cViRonHgWNHA1OANYH5hJ/52e7+xxz1mUEJv1+p6zYEjiXc916B7p/Lxe5+c7ZrimVmywBHAXsQfoc7gZeBq4FfE0b3Xx1P7/FzS/2cfw2cAZxH+FttAl4HznD3q4oZJW5mGwPHEMY8rEr4G7oH+AXhe1vMe9mU8Pe4Fd2/f68CfwDOcff38lw7ATiS8Lc8Lr6Ht4D7gPPc/YVi6iCVpRZ2/dodeBH4HuEf4mBgOcIf/mXAHWaW9QOXmY0nBOaLge0J/+QGxuu3Ay4CnrZUBCmVmR1ACIg/AyYDK8U6thH+4ewOXAfcYmaVvme5LvB8rMsXgGHAcGDj+NwTZrZqtgvNbEfCP9fpdH8wGkoYzb0yISD9FvhL/OdeL+6I2w3iB6cezKwN2CL11OQc5Xw9bl9x9xeLeWEz2x54CfgPwofBYcBowvfvbjM7vZhyinytownB+QBgFWAQsCLwNeAmM7s4z+WFyl4jln06sAnQSvj9/QJwJvB3wt9OIcOBBwkfjpchfD82oMiZAGZ2PN3vcR3C795Ywgfup4BdClw/0MzOA/5GCNjrxffRRvj5HAe8aGbb5bj+J8CzhP81Fq9rjY8PB541s5PNrKmY9yOVo4BdHRcR/iHclnpuk/h1SI5rzid8yr2A8I9wG+AEYE48/jXgB5kXxZbPX4AJwIJ4/RRgM2BX4HJgMSHI3WdmK6UuPynW6fG4/16qnielXmNbQit/KKG1c2qszxaEQH1BfG2AnfO8x3L5KeFDwm3x9beKr5ncN16L8DPoIX5guRUYSZgffQ7wDcL72JXQapodT98c+M8i6/N1wvfsf1LPTaH7e/lukeXkc3vcNhE+hGWaRPiQlpiceYKZDSK0qCB8Hwoys00IHxaWARYSvmfbAhOBE4FPCd+nVbJcXtTvV8pgQut1DvBzwvvcgRBMk96OaWa2VzF1z3gfIwhBdq341A2E39UtgcMILdMNgF8WUVwSaH9L+L7vQmiVPlBEPY4k/J41AR8BPwS+Qnif/0P4gHJ2gWIuIbSOIfzOH034G9iJ8Le4CBhB+ICzZsbrn0z4+20mzGQ4PL7+ROD7hO/DAMLfWI9eQqk+dYlXQUyA8r6ZzUw991SBy+YD27r7I6nn7jezPwP/F/cPYMl/KBcRWiCfAdu5+2MZx281s+sJ/6BXIvwz+Has05vAm2aWBKkFOep5atwuAnbM0tV6o5n9ge4PKHvSM3hVwrHuPj21/4iZ3Ui4hbAisJOZLe/uH6TO+QnhHyLAPlm6V281s2sJXb0thPfxH4UqknQfmlk68c0LZU6U8megndAS2p4wVSotCeILCYF7opk1u/vi1DlbEwIvFBmwCR8kBxJuOezs7nenjj0cf7ceAsZkXljC71faR8DW7v6P1HP3mNlTdHdVHwBcW2T9EycTun4Bjnf3M1PH/mpmVwN303MOfS4DgKvcPf3B9LZcJyfMbDngtLj7LvAVd09PdbvHzO4h9FTlKmM7um8z/B/h7/Hz1Cl3m9ljhA/Ywwgf+g+O136R8DcAcAVwkLunx1o8bGa/JXw4nAycZGbXqnu8dtTCrl/nZwRrAOL9xCfi7rrpbnEzW4fu7rPTswTrpIzbCS1tgD3NbOViK2VmrYSWz0zgtmz3RVOv8UncHVts+b3094xgndRhFnBV3G2i5zQrCLcIPgCeyHUvNAaU5+Nupd9H0dx9HnBv3M3Wwk6e+13cjiC0ZNOS7vCZhCCbl5ltQGh9AVyaEayTejmhC7ZcTskI1onfE4I5hJZw0cxsCHBo3H0kI1gDEIPePhQ/WPDCUuoQ/T/CzwXguIxgndTjBkIwzSV5Hx3A/hnBOinjckKXO8D2qa7tYwkx4GPg8IxgnVw7h5A7opPwN3RUoTcllaOAXb/uzHPs5bgdQPcfPIR/wMkfY6E5v0n5A8h9f3MJ7t7u7pu6+2jCQJ18khbm4GLL76W78hx7OfV4VPqAu+/o7isAmxYov1rvo1RJt/hYM1svedLMlqc7iJ1D922UbTKu/1rc3pnR8s7l66nHV+U8Kww2nFtEecXI+ncQBzK+GndHZTsnj38j9ExAaHlmFXtEsg6gy7CIcL+7VMn3cz6hSz6XS7M9GT+sJyk/H3H3V/KUsTvhNsVq7t4Zg3by83/Y3dtzXejurxHG00D3LRSpAXWJ16+38xybl3qc/hmmW1BPlDCmbM3CpyzJ3Tuga4DTGoT7gesSBntNpPs+ZqU/GPbme9Ul9T6GAKsTvh9GGLCzFbB2PLXeBt3ckXq8PaH7H0Lrugl4392fM7NHCfeZJwNnQdcMhAnx/GK7w9dNPc7Zle3uc83sWcK4ib4q5mdb6v+xL6QeFwq0j9Lzg0o2H8Uej1Il308vcP3f6W7hpq1E9y2NJ8gjBt201QljNwB2SY3WL0SpZGtIAbt+LdG1lUP6j3iJ+4ZFGln4lJ7MbByhS20Xcgf8DqrTi9Ob7xUAZjaKMB0smdaTrb7Veh8lcfd3zOxJwge17QkDtKC7O/y+1HZbet7HToLQAsK0n2IkI6Y74u2GfP5VZJn5LMicephDqR+k0iO/P8p5VvBBgeMQxov0RlKPj/Od5O5z4n3/zFkK6feRt4wsevu/osXMlsnW9S6Vp4Bdv3ozdzn989yM7pG0hXxYyouY2U6E+c3pTF6fE7rNnicM0voTcBNL3jeuhF7N8zazLxG6XJdPPT0X+Aehtfp3QrA7nTDKux7dTgjYk8xsYJwrnnRb3pexHQ58kfDzSQL2/SX88+36PptZU4H59eXIlV6p+fuDUo8LfRArpg69rWdyXTEfOLJ9P/vy/zt97aWEOeTFytl9LpWlgN2/zEw9fsfdyzF9qIc4bewaQrBeSJiScjWhW68z49xh5X79cond3zfQHazPI/zjejbzfm49vw9CwP4JYQTwFmb2HmGKG3QH6r8RpqcNAybH7urkfnax3eEQpmFBCHK
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAewAAAFGCAYAAACorazoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAgAElEQVR4nO3dd5xcZdn/8c+WtE0hZUMNBEjgIqAgj4AgYIIiRdqDGHzoCU2QoggoCj+KEooo8FAeI6AEQYmAlNCbgIKCSBOIXqEGCCWkQrJpuzu/P+4z7MnstJ2d2ZnZ+b5fr32dnTn3OXPN7Oxcc9/nLnWJRAIRERGpbPXlDkBERERyU8IWERGpAkrYIiIiVUAJW0REpAooYYuIiFQBJWwREZEqoIQtIiJSBZSwRUREqoAStoiISBVQwhYREakCStgiIiJVQAlbRESkCihhi4iIVAElbBERkSrQWO4AJD0z29Ld/5Xm/mnAEdHNddz9wx4NLEWmOCuJmW0CnAtMAJqBhcBMd/9qGcOSNMzscWA8sMLd+xf53BOAx6KbP3b3iwo4x7nAOdHNHdz96di+x+lm7GaWXO/4QXffI0OZsv7PpbyOk919WrliqTVK2BXGzNYAfgqcQAX/fcxsbeAXwI7ARmUOJyMzWw94Ghgeu3st4N/liUikMGY2FrgSGED48ik1pmITQg27FDiy3EHk4ffAV4HZ5Q4kh5PoSNa3Ab8ClgMtZYtIpDAPAhsDT5Q7ECkPJezK01DuAPJULXFuEW1XAUe4uxJ1BXP3CeWOIRt3P5dweaVU56/Lsrta/uekRNTpTHq7gdF2rpK1iFQzJWzp7ZLv8dayRiEi0k1qEq8QKb1Pk/cle4w+kamp0Mw2BE4H9gDWAz4BZgLTgBvcPZHuuOjYPsAkYCKwJeFa7yLgJcL13uvdfWXKMdPo6KUOMDoW5w3uPiml/FrAMcDXAIseoxWYDzwLTAf+lC3Oropek7dS7o7HOdvdN4zKJu87BbgXuArYidCE/jpwhrs/Ejt3l1+zNPF9jdCp8IvAmsAc4C7gQsJrszAq2qUeuCnPe39gRhTr4YRLA4Ojx3oQ+KW7v5HlXN8EDgW2i2JsAd4HHgeudfcX8o2rK7L1tI7/rdz98ijGo4H/AoYBHxF6L1+eT3zR3/J44CBgHOHz8B3C63Z5uhEY2XqJpyn7FcL/5g6Elp53gPuAy9z9nQzHdOolHntNksbHyp0XNdOnPq9JdO89ujNwMuE9ui7wIXA34T0qZaIadnU7gNDb+buEzij9gJGEf+7rgXvNLO2XsqjH6UvANcDXCT2n+0TH7wpMBV4yMys0ODM7gpBAfkbo1bpOFONAYIMo/luBu8ys3Nfn1geeAnYDmoA1CIng9WSB7r5mZtZoZtcAjxAS6gZAf2AM8APgRcKXmmJoih7nN4T3QzPhtd+YkKReNbNvpImxj5ndAfwpinG96DmuQUhqxwPPm1k5P7gbzOz3hBj3JPwd+hL+hocD/zSzY3KcYx3gn8D/AtsTnt9AwnP8EeHvuHWhAZrZKYQvN3sDIwh/502B7wP/MbOJhZ47x+N29z1ab2ZXAX8BvkUYAdIPGA2cCLxC+BInZaCEXTmmAlsTvsUmbR39HJ3hmKuAOuBqQg17F+BMYGm0f09CIlhNNCTrr4QPp5XR8XsR/hH3A24A2oDNgMfMbJ3Y4WdHMT0X3f4gFufZscf4KqGWPwBYQBiqtifhw/GA6DGT3/L3yfIcC/F+LKZ0cXZKVIQP0mbg58DOhNrJBe7+dvR8uvOaJf2C0NoAoXf9cYTa1zeBhwjJ8dbCnnInvyS8H54GDgO+BPw38HC0vx8wzcwGpRx3RlQO4M4otm0JLSQ/IbSMAJxhZvsUKdauOg04mPBl9VjCe2pP4I/R/nrgSjPbIMs5TibUPv8KHAJ8mdCi8FK0f03gJjPL1gksk36E0R7LgQuArxBGVFxJaEEZANxsZl/K83xHE963H0S3n6PjvTw1WahI79GfE1p/AN6m4z26N3ALoSVDtewyUZN4hYia3z40swWx+17McdgK4Kvu/rfYfY+b2Z+Bv0e3jyD8E8ZNBdYmNJ/v6u7PpuyfYWa3EZoG1wEuA/4niukd4B0zWxKVXZkhzp9G21Zgd3f/Z8r+283sATq+oEwEfp312eYpau57ESCPOJPqCQn6zNh9t8V+L/g1i+LYklBDgXDJYmd3XxA7/g4zuxz4Xh5PMR9rAzcCk9y9PRbHDOAewpeWkYQP9D/GjksOKXzE3fdPOeefzexeQsJoJCTLu+l5awOPAnu7+/LY/Q+Y2UJCkulHaOq+OMt5rgC+H7sc83czu5VwqWZLYHNgm+h2Vy0Fdkl5nzxmZg8TLn80EL5wb5vrRO7+OoCZJb/gLsnwXu7ue3QcHe+/V4CvuPvC2PH3mtkzhC+DUgaqYVe3q1KSNQDRdbXno5ubxZvFzWxTYN/o5pQ0/9TJc9xD+EYOMNHM1s03KDNrInxgLgDuTpOs44+xKLq5Xr7nL6FfpbuzSK/ZZDqG5RyfkqyTTgNe7XLU6S0nJKP2+J1Rcro2dtdWKcetHW1fS3fSaIat8wk1x98XJ9SCnJySrJPiX/pSn1vc+8DpqX0noi9718Xu+lyB8Z2b7n3i7nfT8R7Zxsy2KfD8qynSe/QoOipxx6Uk6+TxlxKay6UMlLCr231Z9iU/cOsJ1+eSvkFoRoeO5tFc56+nCzMruXuLu2/r7iMI18GySXbs6Zfv+Utkjru/l2FfMV6zvaPtu+6e9gPP3VtZPZl2x3MZvhQAxDubDU7Z959oe5SZnRLNvLcadz/P3c909+nFCLQAc9x9ZoZ92Z5b3KNZOl7Fv6wMz1Amm3ZC34FMboj9vlsB50+nGO/R5KWi2e7+VJbjf9vl6KQo1CRe3TIlGAg1rKT43znekeb5LvQp2zjfgnHJGp6ZDSR0YBlDuIa2FaE39vpR0XJ/eXw3y75uvWZRh7rk65frMkenFpMCvZ1l35LY76mfARcSmsj7Eq7D/tzM/k7owPYw8A93bytSjIV6O8u+bM8trpD/nXzNSlc7jYn3YP98AedPp7vv0XpCpzjouI6fyT+6FpoUixJ2dfs0z3LxjjPNBT7WsK4eYGajgFMJTXWZEn475U/WEK77ZdLd16yZjuc4L8cx7xf4WKmWZNkXbwZerVOVu98SdUT7BSH+RkInvJ2B84AFZnYnYdjTy0WKtasyPjd3T8SSVbYOY4X87+Rrbrad7r7YzFoJr20hNfh0uvseHUHHJZv5GcomfVTgY0k3KWFXt0LGLsf/5tsRxhvn4+OuPIiZ7UHotDUwdvenhJ69rxI68jwC3EHH9KHllO217O5rFr+OnCsBZB0f2xPc/bdmNp3wRWs/wvCgEdHu4YSOaUeY2Ununva6fxUo2rj/blpRpPN09z2a8UtcGvmeW4pMCbv2xK9rznH3YtXoPhMNL5lOSNarCM2sNwOe2sknzbCiStTd12whYThNA2G4UDZdbskohWga1+nA9Gho01aExH0AYYhYA3CFmT3g7qmT1NS6rLVmMxtOx2dvrtpsvrr7Hp1P+F9NjtnOplitAtJFSti155XY79sDt2cqGI0TnUC4ZvhUlk5ZqQ6lo6Pb+e7+03SFzKwfYWKHStet18zdW83sX4TrjF80s/rU3tsxXyhOyIWJZqbbDHjR3RfDZz3LX4x+LjGzSwkzwzUSxv9Xay27VMaaWT93z1R7jk888nyGMl3V3fdowsxmEr6YfdHM6rLMPljW92gtq4Rrh7K6TB/kxfJg7Pfjc5S9BLiIUNNKvQadLc6xsd+fy1gq1NaS009W8pfHYrxm90TbtejoMZ7O4V2OrkjM7FBCr/3HCX+bTOKjE/pnLFW7+tMxxCqd5CRBCVZ/b+WS7X+uGO/RP0XbtQnj8zMp23u01ilhV57PvpWXork4GhOdHFa0q5n9JF05MzuV0NEIQs3qrxniTBdjvGPVnhnOvx1h5qekcg/ryqhIr9mv6FiD+2ozG53m+CPJ/kFZag/TcQ39LDMbkaHcwbHfC5lUpBZckW6mtWi
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAewAAAFGCAYAAACorazoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAgAElEQVR4nOzdeZyd4/n48c9kJplkJpJMEoQEQbjErq2tVEIVtfWXKl/VqFhr+2pRSqnqorWV1lK+KFG11JIQexXRolTVHq7YEmopsiCZbDNzfn9c98k8c+bsc/ZzvV+veZ3lWc59zpzzXM9zL9fdEIvFcM4551xl61fuAjjnnHMuMw/YzjnnXBXwgO2cc85VAQ/YzjnnXBXwgO2cc85VAQ/YzjnnXBXwgO2cc85VAQ/YzjnnXBXwgO2cc85VAQ/YzjnnXBXwgO2cc85VAQ/YzjnnXBXwgO2cc85VAQ/YzjnnXBWoyYAtIpuneH6qiMTC36hSlytJeZKW0zlXfMX8/UWOMw8UYd9nR/a/XZ77mBm2X5pkWZ/KLiITI/s4LcU6A0Rko3z2XygJn+PYcpYlWzUVsEVkqIj8Dvh3ucuSjoiMEpE/AXeVuyzO1ZtqOU7UKhHZFXgROLDcZak2TeUuQIFdBBxW7kJk4UZgF2BuuQviXB2qluNEzRGRtYCHyl2OalVrAbux3AXIUrWU07laVPTfn6o2FPs1+kJVJxZx3zOBVO/fj319UFNV4s4551yt8oDtnHPOVYGaqBIXkbOBnyY8Fwt3H0tV/RN6Bp4C7AGMBj4DZgFTgetVNZZsu7Btf2AKsD+wOTAcWAi8ANwOXKeqyxO2mQocEnlqnUg5r1fVKQnrrw4cCXwVkPAaHcA84BngFuCOdOUsBBEZDxwfyjEGq+56F3gUuFRVZ6XYbir2fl9Q1S1FZAPgB8Du2OfdjnU++SP2/rvSlCHnzztsNxZ4OzycBHyAtWF+AViC/b+PVdUXI9tsDpyI9TNYI7zO08AlqvpQ6D27O5HvlohcBhwXdrGLqj6a5r0cAPw5PNxHVe9JtW7CdnOAdYDfqeoPRGQX4Fhge2AkMB94HPh9htf/EvA9YAKwFtAFfAz8A/tOzSjGdyryO/1UVYeFkRonAfsAawMrgFexz+YKVV2WZl/NwHeBbwFbAm3Y/+kV4E7gKlVdkuL1o89lPE7kI7LfB1V1j8jzE7HfDcBW2PfvOOB/sN94MzAHuAf4jar+N4vXWhX4IfY5jgWWArOBm7HPMdnvYib2/1+mqgPT7LsB+90dBWyKfVdmY7+5y1R1cZJtou/xdFU9Nzyf+J36qYjE/x87h6r06H6GA/8L7AWMA1qAj4CnsN/7/anKHbZvAg4AjgA2AoYBb2J9iC5Ot22lqucr7P2wg8OxwHrYD2VV7Et8HXBv+If3IiLjsEBxFfA1YHWgf9h+V+BK4AURkXwLJyKHYIHmF8BELHA0A63YwW0/4DbgLhEpWruQiPwEeAn7nCS8fku4fzTwUhgekbbNTkT2A54P+1kfGIgF3YnAtcCD4SCcbNtCfd5bYQeSL4fXbwO2AN6KvNahWO/hKdjnHH+dvYG/iMgFKfY9NXL/OxnKcXC4/S+Q79CZ84CHse/BmsAAYBQWwB4RkV+k2O5U4J/YQWwD7HNowU4EDsSC3V9EpDWfcuVQ/h2x4HoKdjBtAYYC22EH03+GA3aybTen+/uwG7Aa3f+nicBvAQ0nJpVsNeBf2AnktlhAGQSMxz6X10Tkixn2sSOgwKlhu0HY93pb7HN4QkSG5Fm+JuBW7Pe5HTAYGAJ8CTgXeDWczBeciOyJBdezga2x99SMnWDuD9wnIneJyCopth8OPIYF552x4+cg7KTj19hvYEQxyl5MtRKwr8QOxndHntsq/B2RYpvLsCvFy7Er7J2BM4D4GePXsbP/HsJVwd+xH8fysP1ewDbAN4DrgU7sIPSoiKwR2fysUKZnw+MPIuU8K/Iau2ABYBB21fTzUJ7tsAP05eG1wc6qU73HPglXJD/HOoq8iAXoL2MHie9jP6h+2FXLT5PvBbDAd2O4fz52pb4jcBpWqwEWeH+QpAx9+bwTnYn9z08HdsCu0M5W1UXhtfbDDk6NoVw/Bb6CXWn/Jrz+D7HvSg+q+i/g5fDwW2lOPlbFvm8AN6pqR5rypvI/2AH6Xawm4MvY5/d7IH4Vc2biGF0R2Qk70DZgAe9Quv+fR2BXe4R9/TyPcmVrEDADO/hfgX0eX8Zqcd4P62wOnJO4Yail+St2wgh2Jbo/FqAmYQEG7MA+U0Q2jWyez3GimK4HNsNO2uLv4UCs9gwsgP8xw8nwBWG9G7BjwU7Yb/OTsDweXPOxC3YC+B+sFmB77DcXrxFaC3hIRIZmub+tsN9u3P/R/fn/K/6kiHwV+34Mw66oz8J+c9thJ7szw6r7AtMTL1hEpB9wP/adAvgbdqW9HTAZ+3w3xy4eqkpNVImr6ofAhyIyP/Lc8xk2W4ZVXT4ZeW6miDyCVQ2CVeeen7DdldiVzGfArqr6TMLyGSJyO/aFWwO7WjgwlOkd4B0RWRTWXZ6inPGDZQewewgGUdNCtWz8wLM/9uUvGBH5AvCT8PAG4LCE4PKEiPwB+/FOBM4SkVtTVI+3YSdCOya83ydE5DHgSSyITAHOS9g27887iX7ACap6dXi88n8frih/Gx7OD2V9NbLtoyJyJzYkJVUV4lTgQuxKcW/gjiTrHEj37+76FPvJZBR2dfoVVV0Qef5hEZlL92d4CFZ9GHco9jnPAyao6qeRZU+IyG1Y7cL6wOEicqqqduZZxnQGYCdFe6tqtIbhHyJyH3bi0wIcJCInqOqKyDq/x66kAU5W1YsS9n1n2MdUrDboRhHZUlVjeR4nimkUcI6qnhl57p8iMh27AtwC2Bg7OX06zX4OUNXbI4//LiJ3Y9+RQcBkETk+XZNTCg3YSdwEVf0k8vyMUNP0Q6xp60ysRiAtVX1eRBZGnvow8fMXkUHAn7Dvx0vAV1X148gqTwN/CjVMp2In/0dix4m4w7HPDOzYdUikiedpEfkzdmI3KVOZK02tXGHn47KEYA2Aqj5Fd0KFjaLV4iKyIXZWB/ZDSwwe8X3cQ/fBeH8RWTPbQolIC1b1Mx+4O0mwjr5G/Ms/Otv95+Bk7PsxDzg62ZVgaL86DLuqa8Dam1L5fbKDY/i84+3HG0WvTIvweS8hdZDcD2ufB2t3ezVxBVV9nCRXfRF/wk6yIHW1eLw6/Plou3keTk0I1nFX032VvUXCsnh2v48SgjUAqvoZdvC9CKttStm2WQDTEoJ1vAxv0z1OdwiwbnyZiGyJXf0D3JskWMf3cT3dTRSb012jUWk+wKp8ewhtzlMjTyX+H6PuSAjW8X28jV1lAqyCNXnkY0pCsI47HXg93D9MRAbkuf9Ek+n+nh6REKyjzgDeCPe/n7Dse+F2AdY/pUfbeTiWHQb0+g1UunoO2PelWRb/IvbDrpbi9qR7fGGmwf/x/ffDrkCzoqrtqrq1qo7AqqPS+TDcJq1+zVeogvt6ePiEqranWjccGOLB7atpdvuXNMvejNwfHLlf6M/738k64AT7hNsVdFffJ3NVqgWhg1D8ILmniAyLLg9t7FuHh1PTvEYmHcAjKcqwADtQgR2oo14Lt+NF5GoR6XUQV9VbVPVkVb08WYeiAsr2+xB9D7tH7meqUfp95P7XU65VXo+kaRJJ9RkkyuY4BtZfJFfPpTlJ7gBuiuy7UP0F4lXmn6rqP1OtFF4//h3aKH6SHjrqfiE8f3e8uSvJ9guB6YUpcunURJV4nv6TZlk0v270M9oqcv/fOfQpWy/bFaPiVVihunZdrKpyI+yMe0esDQkKf+I1FqvGBtg3Se/OVNZNs2xOmmXRH1UxP+9302yzZbh9NV2gUtWPRORtUr/X67Dg34w1VVwdWRa/ul5B98EuH/9V1V45oCMWYQfRxN/35Vh14SpYm+0RIvIKdjL0V2BmkYN01Jw0y1J9H6Lt0dGq/mSew/ocDMDaiSvRnDTLUn0GifI5jmUrXTU82GcctxmRJqY+iP/mh+Z
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"\n",
"density = True\n",
"cumulative = True\n",
"histtype = 'step'\n",
"lw = 2\n",
"bins = {\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" 'theta_energy': np.arange(0, 2.1, .03),\n",
" 'theta_peak': np.arange(0, 1, .03),\n",
" 'theta_freq': np.arange(4, 12, .1),\n",
" 'theta_half_width': np.arange(0, 5, .1)\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
"}\n",
"xlabel = {\n",
" 'theta_energy': 'Theta coherence energy',\n",
" 'theta_peak': 'Theta peak coherence',\n",
" 'theta_freq': '(Hz)',\n",
" 'theta_half_width': '(Hz)',\n",
"}\n",
statistics
2019-12-13 10:47:07 +00:00
"results = {}\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"for cell_type in ['gridcell', 'ns_inhibited', 'ns_not_inhibited']:\n",
statistics
2019-12-13 10:47:07 +00:00
" results[cell_type] = {}\n",
spike lfp analysis
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" for key in bins:\n",
statistics
2019-12-13 10:47:07 +00:00
" results[cell_type][key] = pd.DataFrame()\n",
spike lfp analysis
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" fig = plt.figure(figsize=(3.5,2.2))\n",
" plt.suptitle(key + ' ' + cell_type)\n",
" legend_lines = []\n",
" for color, query, label in zip(colors, queries, labels):\n",
statistics
2019-12-13 10:47:07 +00:00
" values = data.query(query + ' and ' + cell_type)[key]\n",
" results[cell_type][key] = pd.concat([\n",
" results[cell_type][key], \n",
" values.rename(label).reset_index(drop=True)], axis=1)\n",
" values.hist(\n",
spike lfp analysis
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" 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=lw, label=label))\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",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" plt.xlim(-0.05, bins[key].max() - bins[key].max()*0.02)\n",
" despine()\n",
spike lfp analysis
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" 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",
analysis update
2019-12-13 10:43:57 +00:00
"execution_count": 26,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [],
"source": [
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"data['stim_strength'] = data.stim_p_max / data.theta_peak"
spike lfp analysis
2019-10-17 17:44:01 +00:00
]
},
{
"cell_type": "code",
statistics
2019-12-13 10:47:07 +00:00
"execution_count": 34,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAcEAAAFGCAYAAAASDiSIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAgAElEQVR4nO3deZxcRbn/8U/PDCHJZBsSMJCEsAQeCCKgKCIguS4sV/ZFZZOAoKgYf15AVOAaUMPqFUQELgoIEpYgIouiELggSNgMsj9hC2gQIQsJIWSZ5fdHVc90enqbnu7pnjnf9+uV1+lzTp3q6p5OP111akl1dHQgIiKSRA21LoCIiEitKAiKiEhiKQiKiEhiKQiKiEhiKQiKiEhiKQiKiEhiKQiKiEhiKQiKiEhiKQiKiEhiKQiKiEhiKQiKiEhiKQiKiEhiKQiKiEhiKQiKiEhiNdW6AFKcmX3I3Z/Kcfxq4Oi4u6G7v9mnBasT+d6fpDKzQcBm7v5C1vFNgFfj7uXufkJfl62SKvF6zGw68IO4u6m7z69I4Xqp0Gszs6nAVXH3MHe/oW9LN7CoJljHzGykmV0E/K3WZalHZjbJzP4I/KzWZakXZvYZ4Cngi7Uui0h/oJpgffsf4NhaF6KO/QnYDLi/1gWpB2Y2Abi71uUQ6U8UBOtbY6GT7j4VmNonJalPBd+fBErU+xGbLlO1Lof0b2oOFRGRxFIQFBGRxFJzaB8wMwO+Dnwa2JTw42Mh8ARwCzDT3Vsz0k+nq8da+lhHfHi/u0+Jx64mT+9QM5sPTAR+4u4nm9nngBOBjwDDgNeB3wLnufvSeM32wEnAfwDrxzLeC/zQ3ef1+o3Iw8w+Tbj3+QlgI2A18CbwIPBrd/+/rPT/B+yecWj3jPfnTHefHtPNJ7wHFwFnAxcDexGa0OYDZ7v7zIx8U8DngcOBHYExwLvA88DvgcvcfXme15B+/m+7+4VmdhBwHPBhoAX4N3AfcKG7zy3yfuwLfBX4GDAyXns3cK67zzOzlcC6Wa+1IyubH5hZ+jP0H9nvYcbrPYrQpL4dMBRYANwVy/lSoXIWY2YfAr4NfArYEHgHeAT4mbvfbWZ3AXuS8ZmO100hvFcAOxA+Ez8Gtib8PZ6K5R5Ekd6hZtZE+JseB2wFjAJeBq4Dflri61gXOCQ+59bAWGAZ8HfgN8A17t6e59qyP1PSN1QTrDIzO5zwn3YasA3hi2YwMB7YH/g18JiZfaCKZbgMuIMQANYHhgAGfB/4i5k1m9lxwKPAkcA4whfMRnH/cTPbrkpl+zlwD+FLYpP4vMOASYQv5/vM7Nr4ZVauEcADwKHA8Jj/Bwlf+OlybAD8BbgB2I/w2gcBo4FdgfMBN7OdizxXo5ldR/iBsTfwgZjPBOBLhPfy+FwXmlmDmf0vcBvwOcLfKn3tscDfzezgnr74PIYTAuuvCT961iN8LjcHvgHMNbM9y83czI4h9GqeCmwMrEN4PfsAfzaz80vM6j+B24HtCYF/DOFz8q8SyrAeodPUdYTXuCHhs/9Bwo+iRwl/30J5bAk8Tgh2e8bXMiiW49OEoQoPmNmoHNdW6jMlVaQgWEVmNgm4kq5frF8jfPh3JgSXh2PS7YFfZFx6GeEX8O0Zx3aI/47rYTGOJtQqHDge2IXwi3Z+PL8tcDNwOaHGMS2W7z8JvS8hfGFe1MPnLcrMjiJ84UL4sjoM2IlQy5tGqK1CeK++lnHpcYT3Iv1F+ARd789lOZ7qaGBL4Fcx7/2Ai939/liOZkLNYxegg/CFdyChJrY3oQa5kvAl9mcz26bAyzqZENCfB74CfDzmcWM83wBcbGYb57j2IsLfCEJtJX39foSgOhi4nvB5yrYDIXCmXU7Xe/J4jvSHE77EnyK8n7sQaizpGtgw4BozG17gteYUA/WVhI46ywitGrsRaoQ/IdT0TyYEpmJ+CCwltGLsApxAaJnIrvlml6EB+COhdQHCj6DPE97PI4HHgA8RWmjy5bE+oTXig/HQbYQa4ccJn9VH4/FdCIE289pKfqakitQcWl1HEH69thGapF7LODfHzG4C/o/wH/VAMxvj7gtjs+abZrY4ndjdnyyzDGMIX3S7ufuyeOyvZjYXeCbu70UIiju5+1vpC83sT8Ac4KPAJ81slLu/U2Y5ckkP/3gO2MPdV2ece8DMfhfL3kIICBcDpJvpzCydfnmR96eB0OSc+QMi8wfGj4HJQCtwoLvfkXX9XWZ2DSFQDyME04/nea6xwGxgH3dfmZXHEsKX+LqEL9Fz0yfNbAe6vpAfBT7j7u9mltfMTgIuyPWk7v6kmWX+bd4s4TNzC2Gwdef7bmY3A3cSvqg3IHw2ZhXJp1P88r8w7i4GdnX35zOS3GdmtxJqoYNLyLIB+IK7p4d+/LXEonyZEHAArgWOzgicj5jZjcBNhMCUz08JtVeAk939JxnnHonv1R+BzwD/aWa7uftf4vlKfqakilQTrK6xcbsceCP7pLuvIfxK/hnh3km1/h6nZwTA9HM/S6itpJ2ZGQBjmna6gkWK0FRWSen357WsAJh+/n8C/w2cR6g99aY7/KW5DsZmrHTt64ocX1bpsjweywGwk5ntVOC5pmUFwLTLMx5nNy9/k/D37yB8Yb+bdZ74JTy7wPP2xCrgK9nvewwUme/VB+mZgwlN/QDfywqA6ed4kBAkSvFyRgDsia/G7RLg69k1x3gP/lhCLbMbMxtJqDkCPJAVADPzOCnj0J7x2mp8pqRKFASrKz1t1UhglpltnZ3A3e9x92+5+0XZQahC2ulq4sq2IONxvi/XzDINq0iJuqTfn73M7MfxHspa3P3n7n6qu/9vsSawAlrJ3SQIMIVwnxaKDzT/Q8bjT+dJs8Ddn8tz7uWMx53NjLHpLt2U+XD2dGdZLi9wricedfdFec69mPF4vR7mu2/criGriTDL/5aY35wePj/x/vqH4+7t+TqexFaN3+XJZi/CfUyAa/I9V5yubwdgpLufHg9PobKfKakiNYdW1zXAKYSOJvsD+5vZK4T/GPcA91S4eTGXhQV6n63KeJyvo0FmmkoPTL6A0FGiidBJ57tm9jfCe3M38GCuGmIZFuapmUH4Aku7JXTkLclmeY7PL3BN5t8h8//ehoSmR8gfrNMeKXK+VP8scC7zverpd8T2cfu8u7+XL5G7v2VmrxJ6Sxfyjx4+P4ROX+nParEm4UfJPeHElhmPC05bmKPZudKfKaki1QSryN2XEO4XZP6a3YzQVDMLWGhms83siF429RXSrVktl8whGn3F3R8i3JNJfyE3ELqRf5dQM11kZjeY2a69fKplBc6NKTPPljzH83Z3z6rJZv69M3sGLyzyvJVqLSjpc0HPf/ikX0ux1wGlvZZCf7tiZQDIV9tN+3cF8shW6c+UVJFqglUWm7Z2ju39BxN6XaZ7gjUSesx9CjjGzPZ19/crXIQ+D2494e53xA44ewEHEO6rjIunhwFfAL5gZme7+/fLfJpCzaiZ/wcOAF7LlzBLzntJZcrs7Vnsh2m5TcLVyidb+rWU8gO7lDKUU858PzZyWZPneG++G+vhMyUlUhDsI+7+CKEp6ztmNpYQ+PYh/CcZQrgfcDKhS3iixA5Ct8d/mNlWhBr0AYT3KQV8z8z+EDtVVNLijMdv96IXbm9k1prWz5sqKLeW0VcWEn7EFHsdUL3Xktm0X6wc+e55Zn4uRtM1XKcU9fCZkhIpCFaRmaUHpa+JvTEBiEMgZgIzY9f4xwm/nPchQUEwDmbeCnjV3Tu/uGLt+QXg52Y2ja4xivsSxm1V0jMZjz9OgS74ceD0oYT7fo+6+4v50vbQK4RmvxF0dejI5yMVes5qeZIQBLc0s+Z89wVjD8pq3QN7gTAsqZEwvKeQ7fMcz+zctB2Qd5YfM/sLoSnzwThrTT18pqREuidYJRYWNl1E+M+Ts3s+QJxCKx0AssdN5ZyKaSCI9/kWAQ+x9kD4bJm956rx/symq8n4ODNbp0Da04EfEQY+V2yWjzgUJf06P25mhYaiHF3gXD18XtJDataha4hBLkdRpe+f2Os1vbz
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
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new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
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new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "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
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
analysis update
2019-12-13 10:43:57 +00:00
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAcEAAAFGCAYAAAASDiSIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAgAElEQVR4nO3debxd873/8dfJJCJIJJQmESR8IqqmlrqGpret4daYVrXG1KXo4P560WpphbYo7b0ULdWaqwi5qqiWUGqIqVHzJ6YEqTEDIiLDOb8/vt+ds+zsea89nLPez8fjPNbZew37u9dee3/Wd+7o6upCREQki/q0OgEiIiKtoiAoIiKZpSAoIiKZpSAoIiKZpSAoIiKZpSAoIiKZpSAoIiKZpSAoIiKZpSAoIiKZpSAoIiKZpSAoIiKZpSAoIiKZpSAoIiKZpSAoIiKZ1a/VCaiGmX3c3R8r8PylwKHx4Xru/lpTE9Ymip2frDKzAcBG7v5M3vMbAC/Ghxe6+1HNTptUr1HXd6OvhzR+n8xsFjAacHcfl3h+A+pMu5lNAi6JD7/q7lcX2GYwsI67v1Dt8dOSPI/u3pHWcXtETtDM1jSzc4B/tDot7cjMxprZn4Fftjot7cLMPgc8Bnyl1WmR+pjZumZ2JfDHVqcli8xsf+AZYOdWp6URekpO8H+Aw1qdiDb2F2Aj4K5WJ6QdmNko4LZWp0NS83vg34HZrU5I1pjZTsBKOcPepKcEwb6lVrr7JGBSU1LSnkqenwzS+ehdGvp5uvssILXitUZw9w0aeOxLgUuLrO7136UeURwqIiLSCAqCIiKSWR1dXV1NezEzM+AbwGeBDQlB+C3gEWAqcJW7L0tsPxk4ucjh7nL3CXG7SynS+irRquoX7n6cmX0B+BawDTAYeAm4HjjT3d+O+2wJHAt8Blg7pvEO4MfuPrOOU1CSmX2WUPf5b8BHgSXAa8A9wGXu/re87f8GfLrI4U5x98lxu1mEc3AOcDpwLrAboQhoFnC6u1+VOG4H8GXgAOATwHDgXeBpQuOEC9x9YZH3kLugvuPuZ5vZROBwYGtgKPA6cCdwtrvPKHM+9gSOBLYF1oz73gb8zN1nmtliYJW891rqgv6Mu/8tv0UdcDRwMKFIfQtgEDAHuDWm87lS6SyR/lTORbXXRVoS36t/uvuWZrYx8P+AXYERwCJC46PLYzo6SxxrDcJ73xv4GLA6MBeYAUwBrkh+9/Nev5DLYjVI3Uq1sMxrOTkU6CScg4mEevgO4DnC79c57v5OgeNfSuL3CRgIHE/4Do4A3gGeIhRJXubuK13DlbYOJfy2fTu+3ibAYuAJ4A/Ab919aYFjJ9/jV9396rzjFrJhLEZOHmdUfO1dgQ2AAcCrwN8Jvxn3lzgeZrYq4Tt4MLAx4Tw9A/wO+A1wMT25daiZHUD4whwDbEb4oRkIjCR8MS4DHjKzjzQwDRcANxEuvrWBVQEDfgD83cxWM7PDgQeBgwgX6ADCD89BwMNmtkWD0nYecDsh8GwQX3cwMJZwYdxpZleYWT31uGsAdwP7EX6EBhN+kOYk0rEO4aK9GtiL8N4HAMOAHYGzADez7cu8Vl8z+z3hBmN34CPxOKOAQwjn8ohCO5pZHzP7DXAj8AXCZ5Xb9zDgn2b2xWrffBGrEwLrZYSbnrUI1+UY4JvADDPbtc7XqOdcNOO6KCue70cJN7FjCOdoLWAC4cfpL2a2SpF9P0P4MfsFoYXhWkB/YF3C+biYcJ7HNPI9pMCAx4FTCDdLue/QlsCpwBMxeJTyRcLN5DcIQXQVwvX9aUIgurmOz3Iw8DdCQ8ItCL9vQ4GdgF8Bj5jZejUeuyQz+09gJiG4f5zwWzOQkNk5BLjPzC40s/5F9h9NaP3/K2B7wo33YMJN+K+Bv8bjpa4pQdDMxhIu9AGEu4ujCT+o2xOCS+4OYUvCSci5ANgK+FPiua3i3+FVJuNQQq7CgSOAHQh3HLPi+s2B6wh3U68TgvX2wH8QWl9CuOjPqfJ1yzKzgwk/uBBaeH4V2I7wxTiGkFuFcK6OTux6OOFcvBofP0L3+bmgwEvl7g5/F4+9F3Cuu98V07EaIWeyA9AFXAnsS8iJ7U7IQS4mBMa/mtlmJd7WcYQf7qeBrwOfise4Jq7vA5xrZusX2PccwmcE8Hxi/70IgWQg4c52QIF9tyIEzpwL6T4nDxfY/gBCycRjhPO5AyEXfGdcPxi43MxWL/Fey6npXNRxXaRtfUILTYAzCedrR+AEQi4G4HOEHNKHxJulmwk5oNw1tRfhfXyF8OMG4Wbs73k/0j8ifG6PxMev0v1Z/iiF91WtGwjn4g+E9/Ap4GuEH38INzW/LnOM8wi5x/MJN+OfAU4E3ovrdwf+u8b0HUC4fp+K6foU4Vq+N67fnMqD7L8I5zl5c3Yy3ef/X7knY07yt4Tv5YuEUrSdCCUXRxBuniBc+7/Jf6H4u3MXkMvh/pHu83s44fx+lnDznrpmtQ49kHDHs5xQJJVs6jzdzK4l3MH8G7CvmQ1397diseZrZjYvt7G7P0pthhN+6HZKFFncZ2YzCMUFEC7KWcB27v5Gbkcz+wswHfgksLOZDXH3BTWmo5Bc94+ngF3cfUli3d1m9n8x7UMJF9K5ALliOjPLbb+wzPnpQyhyTt5AJG8wfgqMB5YB+7r7TXn732pmlxMu2MGEYPqpIq+1LjAN2MPdF+cdYz5wFOGa+Crws9xKM9uKcJcMIUf+OXd/N5leMzsW+HmhF3X3R80s+dm8VsE1M5VQDLTivJvZdYQf792BdQjXxpQyxymmpnNBjddFAwwl/EjvmHcu7zWzu4D7CD/sk/jwZ9mXcPO7KqEYcX93vy6x/4PANWb2I0Luaj3CTcteAO7+EvCSmeWK3pfU8f1Pw7rAEe7+28RzD5jZDYTPaD1gVzNbt0SH+A+Af3f3+xLP/c3M7qA7M3Ao4WajWh2E7+bu7v5+In3XEwL3lwkB7EhCEC4qXmuPmtmQxNMv5Z9/M/to4ljTgL3d/b3EJvfH4uDLCdf3JDO7xt1vTWzzA0JRL8BP3f2kxLoHzOxqQmlNudKnmjSrOHTduFxI4g4iJ5ZTn0zo7P2dBqbrpPwye3d/knCHnnNKMgDGbTrpDhYdhOKgNOXOz+y8H7rc679CuPM9k5BjqKc8vOCdarzYc3d9FxUIgLm0PEz3F3Q7M9uuxGsdk/ejn3Nh4v/84uVvEz7/LuDQvACYS8MvCF+4NHwAfD3/vMd6meS5+lidr1PLuWjmdVHOrwoFIHefTgjEAOPyikT3pPvu/td5ATB5jFMJN8EAe5rZ+HSSnLqH8gIgAPGG+Nr4sINQHFjMeXkBMHeM6XQPBjKuxiLRD4ADEwEwd+xOwnf77fhUmqUG3yRUbS0DDskLgLnXXxZfM/f6/5VbZ2Z96P7dcQq0AYnHPIRwI5W6ZgXB3LBVawJTzGzT/A3c/XZ3/y93Pyc/CKWkk+4irnxzEv8X+3FNpmlwKinqljs/u5nZT2O93Ie4+3nu/j13/02hivMKLaNwkSCEup1B8f9yHc1vSfz/2SLbzHH3p4qsez7x/4pixviFyBVl3u95w53lubDEumo86O5zi6x7NvH/WnW8RtXnImrWdVGJv5ZYl3wPye9Gsi613OeVrAbZrdJENVml56BU0fktJdblrrc+hN/Kat3i7nMKrYg3/zfEh5vFHFwact/Xp9x9pQxO4vXfprtYdudE3eAnCHWiANe4+/Ii+z9HaM+QumYVh15OqDAdQWgEs7eZvUD4sb0duD3l4sVC3irWopFwB5XzagXbpH3H/XNgD8Ln8QPgBDP7B+Hc3AbcUygnUIO3iuRGIBST5EwNDXkrslGR52eV2Cf5OSSvwfUIRY9QPFjnPFBmfaVeKbEuea7q+a7MKrGu2LmA5l0XlZhVYl2x9/CxxPonKG164v/NK09WU80qsa7U55jUyOut3HdiBt2tVDenQKlcNWJuNfdZfbxMy+ykQYTGYa/QXVIA3XWHxTxIuFlPVVNygu4+n1BxnrzQNyKUTU8B3jKzaWZ2YAOLdFYqVis
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"\n",
"density = True\n",
"cumulative = True\n",
"histtype = 'step'\n",
"lw = 2\n",
"bins = {\n",
" 'stim_energy': np.arange(0, .4, .01),\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" 'stim_half_width': np.arange(0, 1.5, .01),\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" 'stim_p_max': np.arange(0, 1, .01),\n",
" 'stim_strength': np.arange(0, 50, 1)\n",
"}\n",
"xlabel = {\n",
" 'stim_energy': 'Coherence energy',\n",
" 'stim_half_width': '(Hz)',\n",
" 'stim_p_max': 'Peak coherence',\n",
" 'stim_strength': 'Ratio',\n",
"}\n",
"# key = 'theta_energy'\n",
"# key = 'theta_peak'\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"for cell_type in ['gridcell', 'ns_inhibited', 'ns_not_inhibited']:\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" for key in bins:\n",
statistics
2019-12-13 10:47:07 +00:00
" results[cell_type][key] = pd.DataFrame()\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" 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[1::2], queries[1::2], labels[1::2]):\n",
statistics
2019-12-13 10:47:07 +00:00
" values = data.query(query + ' and ' + cell_type)[key]\n",
" results[cell_type][key] = pd.concat([\n",
" results[cell_type][key], \n",
" values.rename(label).reset_index(drop=True)], axis=1)\n",
" values.hist(\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" 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=lw, label=label))\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",
" plt.xlim(-0.05, bins[key].max() - bins[key].max()*0.02)\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" despine()\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" 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)"
]
},
statistics
2019-12-13 10:47:07 +00:00
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# stats"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"def summarize(data):\n",
" return \"{:.2f} ± {:.2f} ({})\".format(data.mean(), data.sem(), sum(~np.isnan(data)))\n",
"\n",
"\n",
"def MWU(df, keys):\n",
" '''\n",
" Mann Whitney U\n",
" '''\n",
" Uvalue, pvalue = scipy.stats.mannwhitneyu(\n",
" df[keys[0]].dropna(), \n",
" df[keys[1]].dropna(),\n",
" alternative='two-sided')\n",
"\n",
" return \"{:.2f}, {:.3f}\".format(Uvalue, pvalue)\n",
"\n",
"\n",
"def PRS(df, keys):\n",
" '''\n",
" Permutation ReSampling\n",
" '''\n",
" pvalue, observed_diff, diffs = permutation_resampling(\n",
" df[keys[0]].dropna(), \n",
" df[keys[1]].dropna(), statistic=np.median)\n",
"\n",
" return \"{:.2f}, {:.3f}\".format(observed_diff, pvalue)\n",
"\n",
"\n",
"def rename(name):\n",
" return name.replace(\"_field\", \"-field\").replace(\"_\", \" \").capitalize()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"stats = {}\n",
"for cell_type in results:\n",
" stat = pd.DataFrame()\n",
"\n",
" for key, df in results[cell_type].items():\n",
" Key = rename(key)\n",
" stat[Key] = df.agg(summarize)\n",
" stat[Key] = df.agg(summarize)\n",
"\n",
" for i, c1 in enumerate(df.columns):\n",
" for c2 in df.columns[i+1:]:\n",
" stat.loc[f'MWU {c1} {c2}', Key] = MWU(df, [c1, c2])\n",
" stat.loc[f'PRS {c1} {c2}', Key] = PRS(df, [c1, c2])\n",
"\n",
" stats[cell_type] = stat"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"stats['gridcell']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for cell_type, stat in stats.items():\n",
" stat.to_latex(output_path / f\"statistics_{cell_type}\" / \"statistics.tex\")\n",
" stat.to_latex(output_path / f\"statistics_{cell_type}\" / \"statistics.csv\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# psd plots"
]
},
spike lfp analysis
2019-10-17 17:44:01 +00:00
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 28,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [],
"source": [
"from septum_mec.analysis.plotting import plot_bootstrap_timeseries"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 29,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"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",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 30,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [],
"source": [
"freq = freqs.T.iloc[0].values\n",
"\n",
"mask = (freq < 100)"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 31,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [
{
"data": {
statistics
2019-12-13 10:47:07 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 750x300 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
statistics
2019-12-13 10:47:07 +00:00
"image/png": "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
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"text/plain": [
"<Figure size 750x300 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
statistics
2019-12-13 10:47:07 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 750x300 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
new selection of grid cells color changes and histogram overview of change
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"for cell_type in ['gridcell', 'ns_inhibited', 'ns_not_inhibited']:\n",
spike lfp analysis
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" 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",
new selection of grid cells color changes and histogram overview of change
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" ax.set_ylim(-30, 0)\n",
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" axs[0].set_ylabel('Coherence')\n",
new selection of grid cells color changes and histogram overview of change
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" despine()\n",
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" 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": [
"# Store results in Expipe action"
]
},
{
"cell_type": "code",
analysis update
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"execution_count": 32,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"action = project.require_action(\"stimulus-spike-lfp-response\")"
]
},
{
"cell_type": "code",
analysis update
2019-12-13 10:43:57 +00:00
"execution_count": 33,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/data/freqs.feather',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/data/coherence.feather',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_not_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-not-bs.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-gridcell.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-gridcell.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_not_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-not-bs.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-not-bs.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-gridcell.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_inhibited.svg',\n",
spike lfp analysis
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" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-not-bs.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-not-bs.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_inhibited.png',\n",
spike lfp analysis
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" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-not-bs.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_not_inhibited.png',\n",
spike lfp analysis
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" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-gridcell.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-not-bs.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-not-bs.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-gridcell.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_not_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-not-bs.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-not-bs.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_inhibited.png',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-gridcell.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_inhibited.png',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-gridcell.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_not_inhibited.png',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-not-bs.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-gridcell.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-gridcell.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-gridcell.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-gridcell.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_not_inhibited.png',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-gridcell.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-not-bs.svg']"
]
},
analysis update
2019-12-13 10:43:57 +00:00
"execution_count": 33,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"copy_tree(output_path, str(action.data_path()))"
]
},
{
"cell_type": "code",
analysis update
2019-12-13 10:43:57 +00:00
"execution_count": 34,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"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": 2
}