{ "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": [ "/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:25: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0\n", "Please use `tqdm.notebook.*` instead of `tqdm._tqdm_notebook.*`\n" ] } ], "source": [ "import os\n", "import pathlib\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from matplotlib import colors\n", "import seaborn as sns\n", "import re\n", "import shutil\n", "import pandas as pd\n", "import scipy.stats\n", "\n", "import exdir\n", "import expipe\n", "from distutils.dir_util import copy_tree\n", "import septum_mec\n", "import spatial_maps as sp\n", "import head_direction.head as head\n", "import septum_mec.analysis.data_processing as dp\n", "import septum_mec.analysis.registration\n", "from septum_mec.analysis.plotting import violinplot, despine\n", "from spatial_maps.fields import find_peaks, calculate_field_centers, separate_fields_by_laplace\n", "from spike_statistics.core import permutation_resampling\n", "\n", "from tqdm import tqdm_notebook as tqdm\n", "from tqdm._tqdm_notebook import tqdm_notebook\n", "tqdm_notebook.pandas()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "project_path = dp.project_path()\n", "project = expipe.get_project(project_path)\n", "actions = project.actions\n", "\n", "output_path = pathlib.Path(\"output\") / \"longitudinal-comparisons-gridcells\"\n", "(output_path / \"statistics\").mkdir(exist_ok=True, parents=True)\n", "(output_path / \"figures\").mkdir(exist_ok=True, parents=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Load cell statistics and shuffling quantiles" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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