2023-06-22_dataset2_laurent_loading_raw.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f1fec7f6-4c47-4c18-90ec-11e430dab517",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from pathlib import Path\n",
    "import scipy.io"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "854af98e-6f5d-4b74-8c3a-7e3e258f2aa2",
   "metadata": {},
   "outputs": [],
   "source": [
    "G_path = Path.home()/'quantic'/'grants'/'polychronies'/'RSG-spikepatterns'/'Data'/'G_Ready-Set_bin1ms_alignedReady.mat'\n",
    "H_path = Path.home()/'quantic'/'grants'/'polychronies'/'RSG-spikepatterns'/'Data'/'H_Ready-Set_bin1ms_alignedReady.mat'\n",
    "path = G_path\n",
    "# data = scipy.io.loadmat(path)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "3782c137",
   "metadata": {},
   "source": [
    "`scipy.io.loadmat` fails with this type of file\n",
    "\n",
    "## trying h5py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e5925c8e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: h5py in /opt/homebrew/lib/python3.11/site-packages (3.9.0)\n",
      "Requirement already satisfied: numpy>=1.17.3 in /opt/homebrew/lib/python3.11/site-packages (from h5py) (1.25.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install h5py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f45e7f84",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<KeysViewHDF5 ['#refs#', 'D', 'id_eye', 'id_left', 'id_neuron', 'id_short', 'id_trial', 'sp_times', 't_p', 't_s', 'wbin']>\n"
     ]
    }
   ],
   "source": [
    "import h5py\n",
    "# with h5py.File(path, 'r') as f:\n",
    "#     print(f.keys())\n",
    "f = h5py.File(path, 'r')\n",
    "print(f.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2e606d0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<HDF5 group \"/#refs#\" (850 members)>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "refs = f['#refs#']\n",
    "refs"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "64c9982d",
   "metadata": {},
   "source": [
    "The data inside each file is organized as follows:\n",
    "\n",
    "\\- D [1xS cells] is the spiking data, where S is the number of sessions. Each cell contains data from a given session in the form of a 3-D tensor [TxNxK] where T is the number of time points within a trial (sampled at 1-ms resolution), N is the number of neurons, and K is the number of trials. The entries of the tensor are 0 (no spike), or 1 (spike). Note that the data has been NaN-padded to accommodate trials of different durations. The data provided is between the Ready and the Set cues.\n",
    "\n",
    "\\- t_s [1xS cells] is the sample interval presented to the animal on every trial (duration of the Ready-Set epoch).\n",
    "\n",
    "\\- t_p [1xS cells] is the interval produced by the animal on every trial (duration of the Set-Go epoch).\n",
    "\n",
    "\\- id_eye [1xS cells] is an indicator of whether the monkey used the eye (1) or the hand (0) to respond at Go.\n",
    "\n",
    "\\- id_left [1xS cells] is an indicator of whether the target was located to the left (1) or right (0) to  fixation point.\n",
    "\n",
    "\\- id_short [1xS cells] is an indicator of whether the color cue was red (1) or blue (0) respectively corresponding to the Short and Long distribution.\n",
    "\n",
    "\\- id_trial [1xS cells] is the trial number within each session. Some trials were excluded offline due to the animal not responding or breaking fixation early.\n",
    "\n",
    "\\- id_neuron [1xS cells] is the neuron identity for each session in the form of a matrix [Nx2] where N is the number of neurons. The first column is the neuron label, the second column indicates 1 for putative single units and 0 for multi units.\n",
    "\n",
    "\\- wbin is the size of the bin (in ms) used to discretize the data\n",
    "\n",
    "\\- sp_times [1xS cells] is the spike times for each session in the form of a series of cells [Nx1] where N is the number of neurons, containing the spike times [N_times x 1]. Note here that we include ALL spikes, even those outside of trial periods. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5de02be9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((12, 1), dtype('O'))"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D = f['D']\n",
    "D.shape,  D.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "84a1e89e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<HDF5 object reference>], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "60668059",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: mat73 in /opt/homebrew/lib/python3.11/site-packages (0.60)\n",
      "Requirement already satisfied: h5py in /opt/homebrew/lib/python3.11/site-packages (from mat73) (3.9.0)\n",
      "Requirement already satisfied: numpy in /opt/homebrew/lib/python3.11/site-packages (from mat73) (1.25.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install mat73"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "2b8d69c1",
   "metadata": {},
   "source": [
    "## trying mat73"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c1dca5fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import mat73\n",
    "mat73data_dict = mat73.loadmat(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0f9413fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(1.)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt = mat73data_dict['wbin']\n",
    "dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1cbfc605",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['D', 'id_eye', 'id_left', 'id_neuron', 'id_short', 'id_trial', 'sp_times', 't_p', 't_s', 'wbin'])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat73data_dict.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d7a82965",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of sessions = 12\n"
     ]
    }
   ],
   "source": [
    "N_session = len(mat73data_dict['D'])\n",
    "print('number of sessions =', N_session)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "aa917105",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1200, 107, 1498)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i_session = 0\n",
    "N_time, N_neurons, N_trial = mat73data_dict['D'][i_session].shape\n",
    "N_time, N_neurons, N_trial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6d56b5d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x11f4b78d0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "i_trial = 0\n",
    "plt.imshow(mat73data_dict['D'][i_session][:, :, 0].T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "940e3e0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x12f9d4ed0>]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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upKQkLVq0qN1jWlpaNGbMGM2ePVtnnXXWt5owJNNqqTPDsmdA1KJnDG4RURhpbm5WdXW1fD7fV08QGyufz6fKysp2j/vd736n3r1764YbbujQ6zQ1NSkQCIQ9AACAO0UURvbt26eWlhZ5vd6w7V6vV36/v81j1q5dqyeeeEILFy7s8OuUlZUpJSUl9MjKyopkmgAQFVj0DG7RpVfTNDY2auzYsVq4cKHS0tI6fFxpaakaGhpCj7q6ui6cJQAAsCk+ksFpaWmKi4tTfX192Pb6+nqlp6cfM/7f//63duzYoZEjR4a2BYPBL184Pl5btmzR2WeffcxxHo9HHo8nkqlFFdYZASDx/od7RHRmJCEhQXl5eaqoqAhtCwaDqqioUGFh4THjBw4cqPfff181NTWhx7XXXqvLL79cNTU1fP0CAAAiOzMiSSUlJRo/frzy8/M1bNgwzZs3TwcPHlRxcbEkady4ccrMzFRZWZkSExM1ePDgsONTU1Ml6ZjtAIDI0DMCt4g4jIwaNUp79+7VzJkz5ff7NXToUK1cuTLU1FpbW6vYWBZ2BQAAHRNxGJGkyZMna/LkyW3uW7NmzXGPfeqpp07kJQEAgEtxCsOBWves0cAGAHA6wggAALCKMAIAAKwijAAAAKsIIw5kDDfKA0DPGNyDMAIAAKwijACAQ7HoGdyCMAIAAKwijDgQ64wAkHj/wz0IIwAAwCrCCAA4FD0jcAvCCAAAsIowAgAArCKMOBFNawBEAyvcgzACAACsIowAgEPRwAq3IIwAAACrCCMO1PrmeHxnDEQv3v9wC8IIAACwijACAA5FzwjcgjACAACsIowAAACrCCMO1LppzbACGgDA4QgjAADAKsIIAACwijACAACsIow4UFjPCC0jQNTi/Q+3IIwAAACrCCMA4FAsega3IIwAAACrCCMOZNr5GUB0oWcEbkEYAQAAVhFGAMCh6BmBWxBGAACAVYQRAABgFWHEgUyrrjVDBxsAwOEIIwAAwCrCCAAAsIowAgAArCKMOBCLngGQWPQM7kEYAQAAVhFGAMChWPQMbkEYAQAAVhFGHKj198R8ZwxEL97/cAvCCAAAsIowAgAORc8I3IIwAgAArCKMAAAAqwgjjsSyZwAA9yCMAAAAqwgjAADAKsIIAACwijDiQCx6BkDi/Q/3IIwAAACrCCMA4FAsega3IIwAAACrTiiMzJ8/X9nZ2UpMTFRBQYGqqqraHbtw4UJdcskl6tmzp3r27Cmfz3fc8fhmrDICQKJnBO4RcRhZunSpSkpKNGvWLG3YsEE5OTkqKirSnj172hy/Zs0ajR49Wq+//roqKyuVlZWlK6+8Urt27frWkwcAAM4XcRiZO3euJkyYoOLiYg0aNEjl5eVKSkrSokWL2hz/zDPP6JZbbtHQoUM1cOBAPf744woGg6qoqPjWkweAaEbPCNwiojDS3Nys6upq+Xy+r54gNlY+n0+VlZUdeo5Dhw7p8OHDOv3009sd09TUpEAgEPYAAADuFFEY2bdvn1paWuT1esO2e71e+f3+Dj3H9OnTlZGRERZovq6srEwpKSmhR1ZWViTTBAAADnJSr6aZM2eOlixZopdeekmJiYntjistLVVDQ0PoUVdXdxJneepj0TMgeplWb3re/3CL+EgGp6WlKS4uTvX19WHb6+vrlZ6eftxj//jHP2rOnDl69dVXdcEFFxx3rMfjkcfjiWRqAADAoSI6M5KQkKC8vLyw5tOjzaiFhYXtHvfggw/q3nvv1cqVK5Wfn3/iswUAhNDACreI6MyIJJWUlGj8+PHKz8/XsGHDNG/ePB08eFDFxcWSpHHjxikzM1NlZWWSpAceeEAzZ87U4sWLlZ2dHeot6dGjh3r06NGJpQAAACeKOIyMGjVKe/fu1cyZM+X3+zV06FCtXLky1NRaW1ur2NivTrgsWLBAzc3N+ulPfxr2PLNmzdJvf/vbbzf7KGXU+jtjvjQGogk9Y3CjiMOIJE2ePFmTJ09uc9+aNWvC/nvHjh0n8hIAACBKcG8aAHAoekbgFoQRAABgFWHEgcK+M7Y3DQAWhN0okw8AuARhBAAAWEUYAQCHomcEbkEYAQAAVhFGAACAVYQRB6KBDYhe3CgPbkQYAQAAVhFGAMChaGCFWxBGAACAVYQRBwr7zphlz4CoQs8Y3IgwAgAArCKMAIBD0TMCtyCMAAAAqwgjTsd3xkBUCbtRJu9/uARhBAAAWEUYAQCHomcEbkEYAQAAVhFGAACAVYQRBwprYLM3DQAWtF7okAZWuAVhBAAAWEUYAQCHooEVbkEYAQAAVhFGHIjvjIHoxaJncCPCCAAAsIowAgAORc8I3IIwAgAArCKMOFD4OiN8aQxEK3pG4BaEEQAAYBVhBAAcip4RuAVhBAAAWEUYAQAAVhFGHIhFj4DoxfsfbkQYAQAAVhFGAMChaGCFWxBGAACAVYQRBzLt/AzA/bhRJtyIMAIAAKwijACAQ9EzArcgjAAAAKsIIwAAwCrCiAMZY9r8GYD7segZ3IgwAgAArCKMAIBD0cAKtyCMAAAAqwgjDsSiZ0D0Cnv/8wEAlyCMAAAAqwgjAOBQ9IzALQgjAADAKsKIE9E0AkSt8HWGLE4E6ESEEQAAYBVhBAAcip4RuAVhBAAAWEUYAQAAVhFGHMi06lo1dLACUYVFz+BGJxRG5s+fr+zsbCUmJqqgoEBVVVXHHf/8889r4MCBSkxM1JAhQ7RixYoTmiwAAHCfiMPI0qVLVVJSolmzZmnDhg3KyclRUVGR9uzZ0+b4t99+W6NHj9YNN9ygjRs36rrrrtN1112nTZs2fevJA0A0o4EVbhFxGJk7d64mTJig4uJiDRo0SOXl5UpKStKiRYvaHP/II4/oqquu0rRp03Teeefp3nvv1YUXXqi//OUv33ryAADA+eIjGdzc3Kzq6mqVlpaGtsXGxsrn86mysrLNYyorK1VSUhK2raioSMuWLWv3dZqamtTU1BT670AgEMk0O+yJtdv1n/8d6pLn7kpb6xtDPy9eV6u3Pt5ncTYATqbmI8HQzzV1BzT7Hx9YnA3c5NfD+yvr9CQrrx1RGNm3b59aWlrk9XrDtnu9Xm3evLnNY/x+f5vj/X5/u69TVlam2bNnRzK1E7L8vd3aUHugy1+nK736UdtfjwFwv53/PaQn/98O29OAS4zMyXBGGDlZSktLw86mBAIBZWVldfrr/CSvrwrP7tXpz3sy7PzvISXExapPaqLtqQA4yQ42tWjbvoMakplseypwEW+yvb8nEYWRtLQ0xcXFqb6+Pmx7fX290tPT2zwmPT09ovGS5PF45PF4IpnaCRlTcGaXvwYAADi+iBpYExISlJeXp4qKitC2YDCoiooKFRYWtnlMYWFh2HhJWr16dbvjAQBAdIn4a5qSkhKNHz9e+fn5GjZsmObNm6eDBw+quLhYkjRu3DhlZmaqrKxMkjRlyhRdeumleuihhzRixAgtWbJE69ev12OPPda5lQAAAEeKOIyMGjVKe/fu1cyZM+X3+zV06FCtXLky1KRaW1ur2NivTrhcdNFFWrx4se655x7dddddGjBggJYtW6bBgwd3XhUAAMCxYow59RcUDgQCSklJUUNDg5KTadgCAMAJOvr3m3vTAAAAqwgjAADAKsIIAACwijACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsiXg7ehqOLxAYCAcszAQAAHXX07/Y3LfbuiDDS2NgoScrKyrI8EwAAEKnGxkalpKS0u98R96YJBoPavXu3TjvtNMXExHTa8wYCAWVlZamuri5q7nkTbTVTr7tRr/tFW81uq9cYo8bGRmVkZITdRPfrHHFmJDY2Vn379u2y509OTnbFP3okoq1m6nU36nW/aKvZTfUe74zIUTSwAgAAqwgjAADAqqgOIx6PR7NmzZLH47E9lZMm2mqmXnejXveLtpqjrd6jHNHACgAA3Cuqz4wAAAD7CCMAAMAqwggAALCKMAIAAKyK6jAyf/58ZWdnKzExUQUFBaqqqrI9pYiVlZXpe9/7nk477TT17t1b1113nbZs2RI25osvvtCkSZPUq1cv9ejRQz/5yU9UX18fNqa2tlYjRoxQUlKSevfurWnTpunIkSMns5QTMmfOHMXExGjq1KmhbW6sd9euXfrlL3+pXr16qXv37hoyZIjWr18f2m+M0cyZM9WnTx91795dPp9PH3/8cdhz7N+/X2PGjFFycrJSU1N1ww036LPPPjvZpXyjlpYWzZgxQ/3791f37t119tln69577w27t4WT633zzTc1cuRIZWRkKCYmRsuWLQvb31m1vffee7rkkkuUmJiorKwsPfjgg11dWruOV/Phw4c1ffp0DRkyRN/5zneUkZGhcePGaffu3WHP4aSav+nfuLWJEycqJiZG8+bNC9vupHo7hYlSS5YsMQkJCWbRokXmgw8+MBMmTDCpqammvr7e9tQiUlRUZJ588kmzadMmU1NTY6655hrTr18/89lnn4XGTJw40WRlZZmKigqzfv168/3vf99cdNFFof1HjhwxgwcPNj6fz2zcuNGsWLHCpKWlmdLSUhsldVhVVZXJzs42F1xwgZkyZUpou9vq3b9/vznzzDPNr371K7Nu3Tqzbds2s2rVKvPJJ5+ExsyZM8ekpKSYZcuWmXfffddce+21pn///ubzzz8PjbnqqqtMTk6Oeeedd8xbb71lzjnnHDN69GgbJR3XfffdZ3r16mVeeeUVs337dvP888+bHj16mEceeSQ0xsn1rlixwtx9993mxRdfNJLMSy+9FLa/M2praGgwXq/XjBkzxmzatMk8++yzpnv37uavf/3rySozzPFqPnDggPH5fGbp0qVm8+bNprKy0gwbNszk5eWFPYeTav6mf+OjXnzxRZOTk2MyMjLMww8/HLbPSfV2hqgNI8OGDTOTJk0K/XdLS4vJyMgwZWVlFmf17e3Zs8dIMm+88YYx5ss3erdu3czzzz8fGvPRRx8ZSaaystIY8+UbJzY21vj9/tCYBQsWmOTkZNPU1HRyC+igxsZGM2DAALN69Wpz6aWXhsKIG+udPn26ufjii9vdHwwGTXp6uvnDH/4Q2nbgwAHj8XjMs88+a4wx5sMPPzSSzL/+9a/QmH/+858mJibG7Nq1q+smfwJGjBhhfv3rX4dt+/GPf2zGjBljjHFXvV//Q9VZtT366KOmZ8+eYb/P06dPN+eee24XV/TNjvfH+aiqqiojyezcudMY4+ya26v3P//5j8nMzDSbNm0yZ555ZlgYcXK9Jyoqv6Zpbm5WdXW1fD5faFtsbKx8Pp8qKystzuzba2hokCSdfvrpkqTq6modPnw4rNaBAweqX79+oVorKys1ZMgQeb3e0JiioiIFAgF98MEHJ3H2HTdp0iSNGDEirC7JnfW+/PLLys/P189+9jP17t1bubm5WrhwYWj/9u3b5ff7w2pOSUlRQUFBWM2pqanKz88PjfH5fIqNjdW6detOXjEdcNFFF6miokJbt26VJL377rtau3atrr76aknuq7e1zqqtsrJS//d//6eEhITQmKKiIm3ZskX/+9//TlI1J66hoUExMTFKTU2V5L6ag8Ggxo4dq2nTpun8888/Zr/b6u2IqAwj+/btU0tLS9gfI0nyer3y+/2WZvXtBYNBTZ06VcOHD9fgwYMlSX6/XwkJCaE39VGta/X7/W3+vzi671SzZMkSbdiwQWVlZcfsc2O927Zt04IFCzRgwACtWrVKN998s2699VY9/fTTkr6a8/F+n/1+v3r37h22Pz4+XqeffvopV/Odd96pX/ziFxo4cKC6deum3NxcTZ06VWPGjJHkvnpb66zanPY73toXX3yh6dOna/To0aEbxbmt5gceeEDx8fG69dZb29zvtno7whF37UXHTJo0SZs2bdLatWttT6XL1NXVacqUKVq9erUSExNtT+ekCAaDys/P1/333y9Jys3N1aZNm1ReXq7x48dbnl3ne+655/TMM89o8eLFOv/881VTU6OpU6cqIyPDlfXiK4cPH9bPf/5zGWO0YMEC29PpEtXV1XrkkUe0YcMGxcTE2J7OKSMqz4ykpaUpLi7umCss6uvrlZ6ebmlW387kyZP1yiuv6PXXX1ffvn1D29PT09Xc3KwDBw6EjW9da3p6epv/L47uO5VUV1drz549uvDCCxUfH6/4+Hi98cYb+tOf/qT4+Hh5vV5X1StJffr00aBBg8K2nXfeeaqtrZX01ZyP9/ucnp6uPXv2hO0/cuSI9u/ff8rVPG3atNDZkSFDhmjs2LG67bbbQmfC3FZva51Vm9N+x6WvgsjOnTu1evXq0FkRyV01v/XWW9qzZ4/69esX+gzbuXOnbr/9dmVnZ0tyV70dFZVhJCEhQXl5eaqoqAhtCwaDqqioUGFhocWZRc4Yo8mTJ+ull17Sa6+9pv79+4ftz8vLU7du3cJq3bJli2pra0O1FhYW6v333w/75T/6YfD1P4K2XXHFFXr//fdVU1MTeuTn52vMmDGhn91UryQNHz78mMu1t27dqjPPPFOS1L9/f6Wnp4fVHAgEtG7durCaDxw4oOrq6tCY1157TcFgUAUFBSehio47dOiQYmPDP5ri4uIUDAYlua/e1jqrtsLCQr355ps6fPhwaMzq1at17rnnqmfPniepmo47GkQ+/vhjvfrqq+rVq1fYfjfVPHbsWL333nthn2EZGRmaNm2aVq1aJcld9XaY7Q5aW5YsWWI8Ho956qmnzIcffmhuuukmk5qaGnaFhRPcfPPNJiUlxaxZs8Z8+umnocehQ4dCYyZOnGj69etnXnvtNbN+/XpTWFhoCgsLQ/uPXup65ZVXmpqaGrNy5UpzxhlnnLKXun5d66tpjHFfvVVVVSY+Pt7cd9995uOPPzbPPPOMSUpKMn/7299CY+bMmWNSU1PN3//+d/Pee++ZH/7wh21eDpqbm2vWrVtn1q5dawYMGHBKXOr6dePHjzeZmZmhS3tffPFFk5aWZu64447QGCfX29jYaDZu3Gg2btxoJJm5c+eajRs3hq4c6YzaDhw4YLxerxk7dqzZtGmTWbJkiUlKSrJ22efxam5ubjbXXnut6du3r6mpqQn7HGt9pYiTav6mf+Ov+/rVNMY4q97OELVhxBhj/vznP5t+/fqZhIQEM2zYMPPOO+/YnlLEJLX5ePLJJ0NjPv/8c3PLLbeYnj17mqSkJPOjH/3IfPrpp2HPs2PHDnP11Veb7t27m7S0NHP77bebw4cPn+RqTszXw4gb6/3HP/5hBg8ebDwejxk4cKB57LHHwvYHg0EzY8YM4/V6jcfjMVdccYXZsmVL2Jj//ve/ZvTo0aZHjx4mOTnZFBcXm8bGxpNZRocEAgEzZcoU069fP5OYmGjOOussc/fdd4f9YXJyva+//nqb79nx48cbYzqvtnfffddcfPHFxuPxmMzMTDNnzpyTVeIxjlfz9u3b2/0ce/3110PP4aSav+nf+OvaCiNOqrczxBjTallDAACAkywqe0YAAMCpgzACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAqv8PjWC0Xlv/hvEAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(mat73data_dict['D'][i_session][200, 0, :])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "0a8fc9ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(mat73data_dict['D'][i_session][:, :, 1]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c461eb2a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 19.0\n",
      "1 3.0\n",
      "2 3.0\n",
      "3 3.0\n",
      "4 5.0\n",
      "5 2.0\n",
      "6 4.0\n",
      "7 3.0\n",
      "8 4.0\n",
      "9 3.0\n",
      "10 3.0\n",
      "11 3.0\n"
     ]
    }
   ],
   "source": [
    "for i_session in range(N_session):\n",
    "    print(i_session, np.nanmax(mat73data_dict['D'][i_session]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6d62a844",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((1200, 107, 1498), 135445891, (845, 2, 1225))"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i_session = 0\n",
    "data = mat73data_dict['D'][i_session]\n",
    "data.shape, np.nanargmax(data), np.unravel_index(np.nanargmax(data), data.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "5c4c1bb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19.0"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# time 845, neuron 2, trial 1225 has 19 spikes!\n",
    "data[845, 2, 1225]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7f580eca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 19.0 [4.37494342e-03 8.64719835e-06 8.04390544e-08 3.21756218e-08\n",
      " 2.41317163e-08 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 8.04390544e-09 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 8.04390544e-09 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 8.04390544e-09]\n",
      "1 3.0 [5.87119761e-03 1.05491290e-05]\n",
      "2 3.0 [4.53650317e-03 1.97651575e-06]\n",
      "3 3.0 [2.30410820e-03 9.60145097e-07]\n",
      "4 5.0 [5.98696053e-03 6.65220552e-06 1.95509347e-08 4.88773367e-09]\n",
      "5 2.0 [0.00150635]\n",
      "6 4.0 [6.00846089e-03 1.72957082e-05 1.13538566e-07]\n",
      "7 3.0 [1.05316617e-02 4.52644212e-05]\n",
      "8 4.0 [5.48487599e-03 2.14166002e-06 4.98060470e-08]\n",
      "9 3.0 [5.94812540e-03 5.53133105e-06]\n",
      "10 3.0 [7.39581757e-03 5.88291398e-06]\n",
      "11 3.0 [6.38379215e-03 6.60865707e-06]\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1300x6000 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(N_session, 1, figsize=(13, 5*N_session))\n",
    "for i_session, ax in enumerate(axs):\n",
    "    data = mat73data_dict['D'][i_session]\n",
    "    counts, bins, bar = ax.hist(data.ravel(), bins=int(np.nanmax(data)))\n",
    "    ax.set_yscale('log')\n",
    "    print(i_session, int(np.nanmax(data)), counts[1:]/counts[0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "c4d038c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 # of neurons 107 single units 59 multi units 48\n",
      "1 # of neurons 97 single units 44 multi units 53\n",
      "2 # of neurons 41 single units 8 multi units 33\n",
      "3 # of neurons 3 single units 0 multi units 3\n",
      "4 # of neurons 105 single units 29 multi units 76\n",
      "5 # of neurons 20 single units 1 multi units 19\n",
      "6 # of neurons 31 single units 9 multi units 22\n",
      "7 # of neurons 45 single units 10 multi units 35\n",
      "8 # of neurons 76 single units 22 multi units 54\n",
      "9 # of neurons 81 single units 29 multi units 52\n",
      "10 # of neurons 52 single units 16 multi units 36\n",
      "11 # of neurons 83 single units 33 multi units 50\n"
     ]
    }
   ],
   "source": [
    "# \\- id_neuron [1xS cells] is the neuron identity for each session in the form of a matrix [Nx2] where N is the number of neurons. The first column is the neuron label, the second column indicates 1 for putative single units and 0 for multi units.\n",
    "for i_session in range(N_session):\n",
    "    id_neuron = mat73data_dict['id_neuron'][i_session]\n",
    "    print(i_session, '# of neurons', id_neuron.shape[0], 'single units', np.sum(id_neuron[:, 1]==1), 'multi units', np.sum(id_neuron[:, 1]==0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "9dbf9f53",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1200, 107, 1498) (1200, 59, 1498)\n",
      "0 19 [4.57328896e-03 3.16858442e-06 7.40323462e-08 0.00000000e+00\n",
      " 2.96129385e-08 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 1.48064692e-08 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 1.48064692e-08]\n",
      "(1200, 97, 1907) (1200, 44, 1907)\n",
      "1 2 [0.00503295]\n",
      "(1200, 41, 1700) (1200, 8, 1700)\n",
      "2 2 [0.00887429]\n",
      "(1200, 105, 3115) (1200, 29, 3115)\n",
      "4 5 [5.27024855e-03 1.99868763e-06 0.00000000e+00 3.63397750e-08]\n",
      "(1200, 20, 2356) (1200, 1, 2356)\n",
      "5 1 []\n",
      "(1200, 31, 1769) (1200, 9, 1769)\n",
      "6 1 []\n",
      "(1200, 45, 3591) (1200, 10, 3591)\n",
      "7 2 [0.00820086]\n",
      "(1200, 76, 4061) (1200, 22, 4061)\n",
      "8 3 [6.71411968e-03 8.54019133e-07]\n",
      "(1200, 81, 3108) (1200, 29, 3108)\n",
      "9 2 [0.00628656]\n",
      "(1200, 52, 4077) (1200, 16, 4077)\n",
      "10 3 [6.20069995e-03 2.46402351e-06]\n",
      "(1200, 83, 3411) (1200, 33, 3411)\n",
      "11 2 [0.00939187]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1300x6000 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(N_session, 1, figsize=(13, 5*N_session))\n",
    "for i_session, ax in enumerate(axs):\n",
    "    data = mat73data_dict['D'][i_session]\n",
    "    id_neuron = mat73data_dict['id_neuron'][i_session]\n",
    "    if sum(id_neuron[:, 1]==1)>0:\n",
    "        data_SU = data[:, id_neuron[:, 1]==1, :]\n",
    "        print(data.shape, data_SU.shape)\n",
    "        counts, bins, bar = ax.hist(data_SU.ravel(), bins=int(np.nanmax(data_SU)))\n",
    "        ax.set_yscale('log')\n",
    "        print(i_session, int(np.nanmax(data_SU)), counts[1:]/counts[0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "aa204c8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([False, False, False])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id_neuron[:, 1]==1"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "75bc541b",
   "metadata": {},
   "source": [
    "## displaying some raster plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "fe9dd368",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1200, 83, 3411)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "014bf315",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 4.391640246799251 0.6562914299858119\n",
      "1 5.8521247891571875 1.231659537307187\n",
      "2 4.613178259113118 1.5803987622154743\n",
      "3 2.3162757398621814 1.3623696904607185\n",
      "4 5.917819795988978 1.3653212048243153\n",
      "5 1.496611322164459 0.7599168108718695\n",
      "6 6.072611639998831 1.1558447418496531\n",
      "7 10.542344320736694 1.9849740508819083\n",
      "8 5.4747380677194295 0.7260648271102701\n",
      "9 5.94070840249739 0.6165534025499333\n",
      "10 7.3426221089845285 1.2683897274950415\n",
      "11 6.322194344428245 1.215111210980463\n"
     ]
    }
   ],
   "source": [
    "for i_session in range(N_session):\n",
    "    data = mat73data_dict['D'][i_session]\n",
    "    # print(i_session, np.nanmean(data)*1000, np.nanstd(data)*1000, np.nanmean(data, axis=(0, 1)))\n",
    "    print(i_session, np.mean(np.nanmean(data, axis=(0, 1))*1000), np.std(np.nanmean(data, axis=(0, 1))*1000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "078ac161",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0;31mSignature:\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m/\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0memit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mDocstring:\u001b[0m\n",
      "Convenience method to get or set some axis properties.\n",
      "\n",
      "Call signatures::\n",
      "\n",
      "  xmin, xmax, ymin, ymax = axis()\n",
      "  xmin, xmax, ymin, ymax = axis([xmin, xmax, ymin, ymax])\n",
      "  xmin, xmax, ymin, ymax = axis(option)\n",
      "  xmin, xmax, ymin, ymax = axis(**kwargs)\n",
      "\n",
      "Parameters\n",
      "----------\n",
      "xmin, xmax, ymin, ymax : float, optional\n",
      "    The axis limits to be set.  This can also be achieved using ::\n",
      "\n",
      "        ax.set(xlim=(xmin, xmax), ylim=(ymin, ymax))\n",
      "\n",
      "option : bool or str\n",
      "    If a bool, turns axis lines and labels on or off. If a string,\n",
      "    possible values are:\n",
      "\n",
      "    ======== ==========================================================\n",
      "    Value    Description\n",
      "    ======== ==========================================================\n",
      "    'on'     Turn on axis lines and labels. Same as ``True``.\n",
      "    'off'    Turn off axis lines and labels. Same as ``False``.\n",
      "    'equal'  Set equal scaling (i.e., make circles circular) by\n",
      "             changing axis limits. This is the same as\n",
      "             ``ax.set_aspect('equal', adjustable='datalim')``.\n",
      "             Explicit data limits may not be respected in this case.\n",
      "    'scaled' Set equal scaling (i.e., make circles circular) by\n",
      "             changing dimensions of the plot box. This is the same as\n",
      "             ``ax.set_aspect('equal', adjustable='box', anchor='C')``.\n",
      "             Additionally, further autoscaling will be disabled.\n",
      "    'tight'  Set limits just large enough to show all data, then\n",
      "             disable further autoscaling.\n",
      "    'auto'   Automatic scaling (fill plot box with data).\n",
      "    'image'  'scaled' with axis limits equal to data limits.\n",
      "    'square' Square plot; similar to 'scaled', but initially forcing\n",
      "             ``xmax-xmin == ymax-ymin``.\n",
      "    ======== ==========================================================\n",
      "\n",
      "emit : bool, default: True\n",
      "    Whether observers are notified of the axis limit change.\n",
      "    This option is passed on to `~.Axes.set_xlim` and\n",
      "    `~.Axes.set_ylim`.\n",
      "\n",
      "Returns\n",
      "-------\n",
      "xmin, xmax, ymin, ymax : float\n",
      "    The axis limits.\n",
      "\n",
      "See Also\n",
      "--------\n",
      "matplotlib.axes.Axes.set_xlim\n",
      "matplotlib.axes.Axes.set_ylim\n",
      "\u001b[0;31mFile:\u001b[0m      /opt/homebrew/lib/python3.11/site-packages/matplotlib/axes/_base.py\n",
      "\u001b[0;31mType:\u001b[0m      method"
     ]
    }
   ],
   "source": [
    "ax.axis?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "d04690c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1300x6000 with 60 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "N_trial_show = 5\n",
    "fig, axs = plt.subplots(N_session, N_trial_show, figsize=(13, 5*N_session))\n",
    "for i_session, ax_ in enumerate(axs):\n",
    "    data = mat73data_dict['D'][i_session]\n",
    "    for i_trial, ax in enumerate(ax_):\n",
    "        ax.eventplot(data[:, :, i_trial])\n",
    "        ax.axis('scaled')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "8c5981d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.004488372093023256"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_ = data[:, :, i_trial]\n",
    "np.nanmean(data_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "78c52316",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "8801ec88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.,  0.,  0., nan,  0.,  0.,  0., nan,  0.,  0.,  0.,  0.,  0.,\n",
       "         0., nan,  0., nan, nan, nan, nan, nan,  0., nan,  0., nan, nan,\n",
       "        nan, nan, nan,  0.,  0., nan,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        nan,  0.,  0.,  0.,  0., nan,  0.,  0.,  0.,  0., nan, nan, nan,\n",
       "        nan,  0., nan, nan, nan,  0., nan, nan, nan, nan,  0., nan,  0.,\n",
       "         0.,  0.,  0.,  0.,  0., nan, nan, nan, nan, nan,  0., nan, nan,\n",
       "         0., nan, nan, nan, nan],\n",
       "       [ 0.,  0.,  0., nan,  0.,  0.,  0., nan,  0.,  0.,  0.,  0.,  0.,\n",
       "         0., nan,  0., nan, nan, nan, nan, nan,  0., nan,  0., nan, nan,\n",
       "        nan, nan, nan,  0.,  0., nan,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        nan,  0.,  0.,  0.,  0., nan,  0.,  0.,  0.,  0., nan, nan, nan,\n",
       "        nan,  0., nan, nan, nan,  0., nan, nan, nan, nan,  0., nan,  0.,\n",
       "         0.,  0.,  0.,  0.,  0., nan, nan, nan, nan, nan,  0., nan, nan,\n",
       "         0., nan, nan, nan, nan]])"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[:2, :, i_trial]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "a7303307",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7d29a72d0>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(data[:200, :, i_trial].T)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "d4b65e6b",
   "metadata": {},
   "source": [
    "alternative use Masked Arrays =  https://numpy.org/doc/stable/reference/maskedarray.generic.html ?\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "404df128",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "masked_array(\n",
       "  data=[[0.0, 0.0, 0.0, --, 0.0, 0.0, 0.0, --, 0.0, 0.0, 0.0, 0.0, 0.0,\n",
       "         0.0, --, 0.0, --, --, --, --, --, 0.0, --, 0.0, --, --, --, --,\n",
       "         --, 0.0, 0.0, --, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, --, 0.0,\n",
       "         0.0, 0.0, 0.0, --, 0.0, 0.0, 0.0, 0.0, --, --, --, --, 0.0, --,\n",
       "         --, --, 0.0, --, --, --, --, 0.0, --, 0.0, 0.0, 0.0, 0.0, 0.0,\n",
       "         0.0, --, --, --, --, --, 0.0, --, --, 0.0, --, --, --, --],\n",
       "        [0.0, 0.0, 0.0, --, 0.0, 0.0, 0.0, --, 0.0, 0.0, 0.0, 0.0, 0.0,\n",
       "         0.0, --, 0.0, --, --, --, --, --, 0.0, --, 0.0, --, --, --, --,\n",
       "         --, 0.0, 0.0, --, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, --, 0.0,\n",
       "         0.0, 0.0, 0.0, --, 0.0, 0.0, 0.0, 0.0, --, --, --, --, 0.0, --,\n",
       "         --, --, 0.0, --, --, --, --, 0.0, --, 0.0, 0.0, 0.0, 0.0, 0.0,\n",
       "         0.0, --, --, --, --, --, 0.0, --, --, 0.0, --, --, --, --]],\n",
       "  mask=[[False, False, False,  True, False, False, False,  True, False,\n",
       "         False, False, False, False, False,  True, False,  True,  True,\n",
       "          True,  True,  True, False,  True, False,  True,  True,  True,\n",
       "          True,  True, False, False,  True, False, False, False, False,\n",
       "         False, False, False,  True, False, False, False, False,  True,\n",
       "         False, False, False, False,  True,  True,  True,  True, False,\n",
       "          True,  True,  True, False,  True,  True,  True,  True, False,\n",
       "          True, False, False, False, False, False, False,  True,  True,\n",
       "          True,  True,  True, False,  True,  True, False,  True,  True,\n",
       "          True,  True],\n",
       "        [False, False, False,  True, False, False, False,  True, False,\n",
       "         False, False, False, False, False,  True, False,  True,  True,\n",
       "          True,  True,  True, False,  True, False,  True,  True,  True,\n",
       "          True,  True, False, False,  True, False, False, False, False,\n",
       "         False, False, False,  True, False, False, False, False,  True,\n",
       "         False, False, False, False,  True,  True,  True,  True, False,\n",
       "          True,  True,  True, False,  True,  True,  True,  True, False,\n",
       "          True, False, False, False, False, False, False,  True,  True,\n",
       "          True,  True,  True, False,  True,  True, False,  True,  True,\n",
       "          True,  True]],\n",
       "  fill_value=1e+20)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy.ma as ma\n",
    "ma.masked_invalid(data[:2, :, i_trial])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "5b3c30f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7d2aa6f90>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(ma.masked_invalid(data[:200, :, i_trial]).T)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "2f2603c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1200, 107, 1498)"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i_session = 0\n",
    "N_time, N_neurons, N_trial = mat73data_dict['D'][i_session].shape\n",
    "data = mat73data_dict['D'][i_session]\n",
    "N_time, N_neurons, N_trial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "b7b76232",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7d316fad0>"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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foZQLRYWa4hj9PGFzF/evkpQMCNMW55tQ33M1NXXYL5SW1GHRMTnuDHEM6rxjAbJ2nIbvRP3orx3ts6lqUJL0EX/ICDVOaUZqSyHEadtrRWDE95jJCaLEcfH7e0dHx4jDMsTNbR3uf9o+7IFZLxqPnlvKgirP7OkZ8WQZSpkXNawuD2g9RdfRdE9g60bd/JkQC+dErPiL2y58vqgnJoDA36OLLo9Ty8pC2/L5YcWgzpkG46vh7+Pcl6tHTEyoKSk4f1Mp1FlThl2nYU1o7dBzx/yIPOo2qokJRQlpG0bb9su3Idg2d1H3N8qgjx8X1GuMltZBiQk1PR0td4XXZi+npqfj7N3zoWVmhPT6sD9HQsDs7UXf4quhXXVF6OVc5uJnc8TzhKJAy8uzrM5IudjuRH+fPb7cKAoa7w3tsxBoYgIAmu4p/zIBHiCrjsnxZqhjXfobO0ZPTACBfTZNI/zEBCJ3PhqJkpR8oefDZUZqS8HGGc61oubK//LHpgjpXVoKvaQ4onUQUfyIm54TRBQavaQY/e5MKNUfyw7FlpSkZHTdPA9pv4vMrQHxTh8/Dn0l+VD/tFd2KFGlpqaia8kspL7FdkOUqHS3C70zxkPfXCs7lCF13V6B9Lf3SvkRCGDPCaJEEmjPCSYnSJ4Fs6EdORUT9+8SERERxRvv0vlw/PsuKXUzOUGUOBLutg6KPXpDG8T5XtlhEMUFxeGA568WyA6DSDotNwe9f27TWyKJbCb1uEd2CEREfjH9tA6pFCWmB0Gzg0DuRyUKW4J8VoXXi6wP6mCT4d6IpDFa25G27TN+FogCYByokx0CEZEfe06EQE1Jwdnv8hfKQPVXlUKdM012GJSgGtZVyg4haoy2NtkhEMlnGjA8/DWYiIgo1rDnRAjM3l7kvVg9+ooEAEj6r1qYsoOghFXw0+2yQyAiIiIiolFY3nPiscceg6IoA6apU6f6l/f29mL16tXIycnB2LFjcdttt6GpqcnqMIiIiIiIiIgoRkTkto4ZM2agoaHBP3300Uf+Zffffz/effddbNy4EVu3bsWZM2dw6623RiIMIiIiIkpAnr9acGHMISIiihkRSU7oug632+2fcnNzAQAdHR3453/+ZzzzzDO47rrrUFpaildffRXbt2/Hjh07IhFKWJq/txCKHtk7X7pvq4A+flxYZUQizlDKVOdOh3Ht1QGvP9K2N963MKi6E41n+QJornzZYQTNXDQXyvxZssMgIqI4l/3h8ZAGQ+69qRz6pIlBv067siR6T4kpnwVxzdyIVxPIdZ2ano7WVYGN7aS58tF5B8dsI6LhRSQ5ceTIERQWFmLSpElYsWIFTp48CQCora1Ff38/qqqq/OtOnToVEyZMQHX18GM4eL1eeDyeARMAtN0Z2ZOA65WdED5fROtIe2s3fKdOh1VGMHEquo7GtaN/8Q9l282PD0Hb+nHA64+07QUv7A6q7ks1r1kILSsLzavjN8GRsXE3jKbmYZfrxUXo+qb9LgDU7Z9C7N7v/9tucarp6Th3jzUDaLbfVQnd7Qp4/UA/m5GkTZ6E87dYd1y1cn/Ggv7FZVDnTpcdBgFQSmegv6rU9mVS5PgaGoddNtKxLuXfa+E7diLo+ozPjyPl/dqgXxeIzjsWQC8u+nLGrv1Qtgd+vRWqQK7rzM5O5PzLroDKM5qa4fzX0K/viCj+KUJY+4y9Dz74AF1dXZgyZQoaGhrw+OOP4/Tp09i/fz/effddrFq1Cl6vd8BrysvLce211+LJJ58csszHHnsMjz/++KD5X8PN0JUkK8NPOPr4cTAamyKehIlFamoqlPSxIyYBKD5pWVmAwRH/iaymZWYAimrbJ8vokybC98Vx2WEMpGrQiwr5+O0EY8u2aLFN5kbZIRBRlHg8HmRkZKCjowNOp3PY9SzvOXHjjTfi9ttvx+zZs7FkyRK8//77aG9vx5tvvhlymevXr0dHR4d/qq+PvxO0ouvAgtlRr/f89AIoDkdU6hIL58TU/Z9qhhNGiduSsmJt2xNeYT7gzgMg77OZiHS3C3pJsewwbEedMw1qWprsMKyRnwsU5MmOYlgd8wLv7RQtanISeqZZcy6i2BGJtqgkJUMpm2l5uUREVonIbR2XyszMxFVXXYWjR4/C7Xajr68P7e3tA9ZpamqC2z38idfhcMDpdA6YYp1e4IaonOP/W5gCimFpJ5aAJP3nbpjd3VGpSzGjv33h8DU0Ajs+saSsWNv2RGccqINx+HMAw382taws+K5jF2/LDdOZz3d96YUeLYlIiJDunbcj4/DnMA4etqSsSNwSlvavNQGvq6ano29JmeUxXM7s7UXyHwLrNm83SlIyem+K0jgMgypX0P2XFXLqtkAgbdG7dD7UlJTgCo6TYwkRxaeIJye6urrw+eefo6CgAKWlpUhKSsLmzZv9y+vq6nDy5ElUVsbXfcme5QsudF8dhtnWDv3omUtmGBC7Po1CZBLt+CRxT4qJvO2xbpjPptnVjZSDpyQEFL98jU3wHT855LKUg6dhdkUmkaqmpaH9Lvueg8xPPoPZ0yM7DNvJ3NUgtX5x/jxS958ZfcUEJnz9GLtP0j4SAhm75baRSEv7+AzMvv6A1xf9fRC1ByIYERFReCwfc+IHP/gBbrrpJhQXF+PMmTN49NFHsW/fPhw8eBB5eXm499578f777+O1116D0+nE97//fQDA9u3bA67j4j0rdh5zQk1JgdnbKzsMIiIKAI/ZRETRxTEniBJHoGNOWP6czFOnTmH58uVoaWlBXl4eFi1ahB07diAv78I9pv/4j/8IVVVx2223wev1YsmSJXjhhResDkM6XuQSUTzSx48L+wlDdsRjNhEREZFclveciIZY6DlBRBSPPMsXwPnbHbLDICKiGMeeE0SJQ9rTOii6zK/MgxYHA4QmOm3yJGhTrpQdBtGomJggIiIiokhgciLGJde3wPR6ZYdB4WptB1raZEdBIer+y4oRB8BNVGpaGjrvsP6JCpTYvF+fD73AHo/W1CZPgvnVebLDsFz/4jLoxUWywyAiogTD5ESM8x0/CWHT5ISWk422/23fEfDtxGhphXGuRXYYlupfXAZ17nTZYURF+n8chNHhkR2G7Zg9Pcj84KDsMCKmdVUltJxs2WEknDFbD8LXdFZ2GAAA89hJ6DWHZIcRtubVC6FlZaH5ewsBAI6PDsI4Hd9PurCLhnULAUUZcpk2eRLO3zL8o1jP3VMJNT09UqEREUVdTI85Mdo9K0REREREREQkD8ecICIiIiIiIqKYwOQEEREREREREUnF5AQRERERERERScXkBBERERERERFJxeQEEREREREREUnF5AQRERERERERScXkBBERERERERFJpcsOIBw3Z3wLupIkOwwi2+tctgDpr++QHUbkqRqUOVMh9h6QHQmFasFs6A1t8J2olx1J0JTSGVA7emAcPSY7lNhQPgvY+Wn81UUUQWp6OpRCF4y6o7JDCdsmc6PsEIjIZthzgigBZFWflh1CdJgGExMxTjtyCmbTWdlhhET94gxEQ7PsMGJHNJMFTEzQKPTx43D+lnLZYYzK7OyMi8QEEdFQmJwgSgCx+Cs0JSajpRVmb6/sMEJitLXB7O4Ou5yGBxYCimJBREQUKN/pM0j9932ywyAiSmgxfVsHERFRvCn46XbZIRAlHiEg+vtkR0FElNDYc4KIiIiIiIiIpIrpnhPvdPwSTqdTdhhEREREREREFAb2nCAiIiIiIiIiqWK650Q0HyVqfO1qaL0+YMcn1hWqaoBpWFeeFS4OwiaE3DhiwLnvVCL/N/thdnbKDoWIKKZE6/jZencl8t6pg9HSGtF6gnXmwYUofDqwsUUUXYfw+UKqJ5zXWlkGRVfDAwtR8Ez1yNdyqgZFVSB8PmnvMR8lSkSXY8+JAGl/3GNpYkK7sgS9Xy+1rDyr9P75fGD+TNlhxITcl6vjKjGh5WRD0WM6XxkTtLw8y57EoKalQU1NDbsczZVvQTSJQ01JgZqeLjuMUdk5zmgdP7P/X7XtEhMAAk5MAEDDmtAfb9n4vfKAjze62zVonqLraPqO/R+vSQMV/HT7qD8ydd9ahpM/LIeWmYGzd8+PUmRERCOLq+SEouvQpl8V0TrUmVMv9HgIk3H0GFLe22lBRNZKaToPrb1HdhgkQU/FFVAzOIZLpHVce4VlCUBx1UQoJUVhl9N23SRLjmuXUmdPjdvHYSrF4yGmTpQdxqhiJU4amfufQn96i+vZ0b+kXnTuf00aNE/4fMh/nk+PiUdpv6tB0U+2w2jvQO4r1bLDISICEGfJCWga+nPSIlpFf14qFDU+L7gBADs/hXH4c9lRkASO93fZ8hfGeDP2zR3oy3JYUpbYewDGgbqwy3H+doflt5j15Q19LFZ0Hb7r7ddrLBhG3VGIXZ/KDmNUsRIn2UPmv/ALqlV815dGtSei5nRCVM6JWn1ERJESV8kJ4fVC/dPeiNahfbhnyPvyFF1Hx50LIlq3HSgOBzzLg9/O3pvKoeXmDLmsdVVluGHRCLq+ucCSrv9kneT/2C07hIjTN9cO+sXWs3wBFF2H41SHpKiIRhbqOY7oUo4zHggjemOKmV4vkhrbo1YfEVGkxFVyQibh8yH7g8Oyw4g44fUi6z+D3860P9XBaG0fclneu/G537TpV6HvBvn3cWZsqoN5/rzsMEZ0/pZy6JMmyg6DIizrPw/D7O2FUXdUdihEQwr1HEd0KePQkagOLC68XviOnYhafUREkcLR7yyUKF3iQ9lOo334X0qNcy3hhGNbxsHDSD4k/xYgo61NdgijGvPOLvj4hJi4lyjHSIptbKdERERysOcEUSTxC3dgQthP2rTJEQiEiIhGwmMvERFFSkz3nHin45dwOvl0ASIiIiIiIqJYxp4TRERERERERCQVkxNEREREREREJFVM39Zxc8a3oCtJgxeo2oV/zeg9xskydotdUaBo2pCPT7W0mqRkiP6+iNZhp3oHsdv7HgRF1yPePqxk53ht0x7jQCT2ZaTen5h63xUFUFTbHasUXb/w6MZRxq9RkpIvrGeX+G26P0ciu73Krj/qonx9YOn+HSX2TeZGa+ohorgRnz0nTBtdeATLbrELEZUvcrIuNGxzgWO39z0Idv2iPxw7x2ub9hgHIrEvI/X+xNT7LoQtj1XC5wtoYF1j4Qxo066MQkQBsun+HIns9iq7/qiL8vWBpfs3hq9tiEiOoJMT27Ztw0033YTCwkIoioK33357wHIhBB555BEUFBRgzJgxqKqqwpEjRwas09raihUrVsDpdCIzMxPf/va30dXVFdaGRIM2Ywq0WBmAs3zWlxlrANqUK6FlZUkMaASqdiHeEClJyVBKZ1gY0Jf04iLo4wojUvZQlLKZUJKSwypDXDPXmmCiQHM6oU2/atB83e2CXlIsISKKBVpWFrQpNvqCaYFw27w+rhB60XgLIwpPqO+RWDgnAtF8Sd26F8aBuojWEc+UeTOgpqQMmi8q51zoBUIjsuL8PNx5c0A9Ef4cERFFStDJie7ubsyZMwfPP//8kMufeuopPPvss3jppZdQU1ODtLQ0LFmyBL29vf51VqxYgQMHDmDTpk147733sG3bNtxzzz2hb0UQvDfOH/LEGnfUCxcJWl4ezEVz/X/bkWJFbFG8KNKmXDnyhYGioOfWiojVr86dPuSXGPMr86Dl5kBEaVd0/6VF28gLWqKwaHl56FhQZOvjfMBGOR6oM6dCu+qKKAVjPVE5B7rbJTuMgFl2nI+AUc/Fl/FdVwotMyO8SsM4v3tvnA8jRRt9xQDjCGu5BSzZn0REl1GECKAf5HAvVhS89dZbuOWWWwBc6DVRWFiIBx54AD/4wQ8AAB0dHXC5XHjttdewbNkyHDp0CNOnT8euXbtQVlYGAPjDH/6Ar3/96zh16hQKC0f/ldrj8SAjIwNfw81DjzkxAr1oPHynGxKmm5nicEDLyoSvsUl2KHFDczoBTYPR1jbsOnpJMXzHTkSm/pxsiL5+mJ2dA+t0u2C0tUN4vRGp93L6pInwfXE8KnUR0fAS6TivZWUBhgHD45EdSkg0Vz5EhwfmJT/Y2Jmdj/OBnIsvpY8rhNF8LuzbFkI9v8fb9acV+5NjThAljovf3zs6OuAc4U4ES8ecOHbsGBobG1FVVeWfl5GRgYqKClRXVwMAqqurkZmZ6U9MAEBVVRVUVUVNTc2Q5Xq9Xng8ngFTqHz1p+LmxBAI4fUmxAVrNBkez6gXQ5FKTACA0dI6KDEBAL7GpqglJgDY9oKVKNHE4nH+3HcqoaanB/06o60tZhMTAGA0NcdMYgKw93E+kHPxpXynz1gynkKo5/d4u/60an8SEV3K0uREY2MjAMDlGthl0eVy+Zc1NjYiPz9/wHJd15Gdne1f53IbNmxARkaGfyoqKrIybCIiIoqi3Jerh0yyEhERUeKKiad1rF+/Hh0dHf6pvr5edkhEREREREREZBFLkxNutxsA0NQ0sHtpU1OTf5nb7UZzc/OA5T6fD62trf51LudwOOB0OgdMgehbUgZF14PdDLIx79L5Yb1eczpj6mkWo1EcDviuKw2rDH1cIdQ50yyKKHyWv0eqBu+N4bWbhLNgNrScbNlRhMx3fSkUh8OSsrQrS0IegFFz5UfsSUIRYdH73vvn5SG/NtxjvFXCed9jmZaTDSyYLTsMPyvOcdEQK3FawW7XDEQUXyz95l5SUgK3243Nmzdj7ty5AC4MflFTU4N7770XAFBZWYn29nbU1taitPTCgXzLli0wTRMVFcGNgPxOxy8DTlQQERERERERkT0FnZzo6urC0aNH/X8fO3YM+/btQ3Z2NiZMmIC1a9fixz/+MSZPnoySkhI8/PDDKCws9D/RY9q0abjhhhvw13/913jppZfQ39+PNWvWYNmyZQE9qQO48FQQAGENjElEREREREREkXXxe/uoDwoVQfrwww8FgEHTypUrhRBCmKYpHn74YeFyuYTD4RDXX3+9qKurG1BGS0uLWL58uRg7dqxwOp1i1apVorOzM+AY6uvrh4yBEydOnDhx4sSJEydOnDhx4mS/qb6+fsTv+YoQo6Uv7Mc0TdTV1WH69Omor6/nrR1kKx6PB0VFRWybZEtsn2RnbJ9kZ2yfZGdsn2RnQgh0dnaisLAQqjr8sJcxOVqkqqoYN24cAAQ1QCZRNLFtkp2xfZKdsX2SnbF9kp2xfZJdZWRkjLpOTDxKlIiIiIiIiIjiF5MTRERERERERCRVzCYnHA4HHn30UTgsepY9kVXYNsnO2D7Jztg+yc7YPsnO2D4pHsTkgJhEREREREREFD9itucEEREREREREcUHJieIiIiIiIiISComJ4iIiIiIiIhIKiYniIiIiIiIiEgqJieIiIiIiIiISKqYTE48//zzmDhxIlJSUlBRUYGdO3fKDoni3IYNGzB//nykp6cjPz8ft9xyC+rq6gas09vbi9WrVyMnJwdjx47FbbfdhqampgHrnDx5EkuXLkVqairy8/Px4IMPwufzRXNTKAE88cQTUBQFa9eu9c9j+ySZTp8+jTvvvBM5OTkYM2YMZs2ahd27d/uXCyHwyCOPoKCgAGPGjEFVVRWOHDkyoIzW1lasWLECTqcTmZmZ+Pa3v42urq5obwrFGcMw8PDDD6OkpARjxozBFVdcgR/96Ee49GF2bJ8ULdu2bcNNN92EwsJCKIqCt99+e8Byq9riJ598gq985StISUlBUVERnnrqqUhvGlFAYi458cYbb2DdunV49NFHsWfPHsyZMwdLlixBc3Oz7NAojm3duhWrV6/Gjh07sGnTJvT392Px4sXo7u72r3P//ffj3XffxcaNG7F161acOXMGt956q3+5YRhYunQp+vr6sH37dvziF7/Aa6+9hkceeUTGJlGc2rVrF15++WXMnj17wHy2T5Klra0N11xzDZKSkvDBBx/g4MGD+OlPf4qsrCz/Ok899RSeffZZvPTSS6ipqUFaWhqWLFmC3t5e/zorVqzAgQMHsGnTJrz33nvYtm0b7rnnHhmbRHHkySefxIsvvojnnnsOhw4dwpNPPomnnnoKP/vZz/zrsH1StHR3d2POnDl4/vnnh1xuRVv0eDxYvHgxiouLUVtbi6effhqPPfYYXnnllYhvH9GoRIwpLy8Xq1ev9v9tGIYoLCwUGzZskBgVJZrm5mYBQGzdulUIIUR7e7tISkoSGzdu9K9z6NAhAUBUV1cLIYR4//33haqqorGx0b/Oiy++KJxOp/B6vdHdAIpLnZ2dYvLkyWLTpk3iq1/9qrjvvvuEEGyfJNcPf/hDsWjRomGXm6Yp3G63ePrpp/3z2tvbhcPhEL/97W+FEEIcPHhQABC7du3yr/PBBx8IRVHE6dOnIxc8xb2lS5eKu+++e8C8W2+9VaxYsUIIwfZJ8gAQb731lv9vq9riCy+8ILKysgac23/4wx+KKVOmRHiLiEYXUz0n+vr6UFtbi6qqKv88VVVRVVWF6upqiZFRouno6AAAZGdnAwBqa2vR398/oG1OnToVEyZM8LfN6upqzJo1Cy6Xy7/OkiVL4PF4cODAgShGT/Fq9erVWLp06YB2CLB9klz/9m//hrKyMtx+++3Iz8/HvHnz8POf/9y//NixY2hsbBzQPjMyMlBRUTGgfWZmZqKsrMy/TlVVFVRVRU1NTfQ2huLOwoULsXnzZhw+fBgA8PHHH+Ojjz7CjTfeCIDtk+zDqrZYXV2NP/uzP0NycrJ/nSVLlqCurg5tbW1R2hqioemyAwjGuXPnYBjGgItnAHC5XPjss88kRUWJxjRNrF27Ftdccw1mzpwJAGhsbERycjIyMzMHrOtyudDY2OhfZ6i2e3EZUThef/117NmzB7t27Rq0jO2TZPriiy/w4osvYt26dfi7v/s77Nq1C3/zN3+D5ORkrFy50t++hmp/l7bP/Pz8Act1XUd2djbbJ4XloYcegsfjwdSpU6FpGgzDwE9+8hOsWLECANg+yTasaouNjY0oKSkZVMbFZZfeckcUbTGVnCCyg9WrV2P//v346KOPZIdCBACor6/Hfffdh02bNiElJUV2OEQDmKaJsrIy/MM//AMAYN68edi/fz9eeuklrFy5UnJ0lOjefPNN/PrXv8ZvfvMbzJgxA/v27cPatWtRWFjI9klEFGUxdVtHbm4uNE0bNMJ8U1MT3G63pKgokaxZswbvvfcePvzwQ4wfP94/3+12o6+vD+3t7QPWv7Rtut3uIdvuxWVEoaqtrUVzczOuvvpq6LoOXdexdetWPPvss9B1HS6Xi+2TpCkoKMD06dMHzJs2bRpOnjwJ4Mv2NdK53e12Dxr42ufzobW1le2TwvLggw/ioYcewrJlyzBr1izcdddduP/++7FhwwYAbJ9kH1a1RZ7vyc5iKjmRnJyM0tJSbN682T/PNE1s3rwZlZWVEiOjeCeEwJo1a/DWW29hy5Ytg7rDlZaWIikpaUDbrKurw8mTJ/1ts7KyEp9++umAk8amTZvgdDoHXbgTBeP666/Hp59+in379vmnsrIyrFixwv9/tk+S5Zprrhn06OXDhw+juLgYAFBSUgK32z2gfXo8HtTU1Axon+3t7aitrfWvs2XLFpimiYqKiihsBcWrnp4eqOrAy2FN02CaJgC2T7IPq9piZWUltm3bhv7+fv86mzZtwpQpU3hLB8kne0TOYL3++uvC4XCI1157TRw8eFDcc889IjMzc8AI80RWu/fee0VGRob44x//KBoaGvxTT0+Pf53vfve7YsKECWLLli1i9+7dorKyUlRWVvqX+3w+MXPmTLF48WKxb98+8Yc//EHk5eWJ9evXy9gkinOXPq1DCLZPkmfnzp1C13Xxk5/8RBw5ckT8+te/FqmpqeJXv/qVf50nnnhCZGZminfeeUd88skn4uabbxYlJSXi/Pnz/nVuuOEGMW/ePFFTUyM++ugjMXnyZLF8+XIZm0RxZOXKlWLcuHHivffeE8eOHRO///3vRW5urvjbv/1b/zpsnxQtnZ2dYu/evWLv3r0CgHjmmWfE3r17xYkTJ4QQ1rTF9vZ24XK5xF133SX2798vXn/9dZGamipefvnlqG8v0eViLjkhhBA/+9nPxIQJE0RycrIoLy8XO3bskB0SxTkAQ06vvvqqf53z58+L733veyIrK0ukpqaKb3zjG6KhoWFAOcePHxc33nijGDNmjMjNzRUPPPCA6O/vj/LWUCK4PDnB9kkyvfvuu2LmzJnC4XCIqVOnildeeWXActM0xcMPPyxcLpdwOBzi+uuvF3V1dQPWaWlpEcuXLxdjx44VTqdTrFq1SnR2dkZzMygOeTwecd9994kJEyaIlJQUMWnSJPH3f//3Ax6zyPZJ0fLhhx8Oeb25cuVKIYR1bfHjjz8WixYtEg6HQ4wbN0488cQT0dpEohEpQgghp88GEREREREREVGMjTlBRERERERERPGHyQkiIiIiIiIikorJCSIiIiIiIiKSiskJIiIiIiIiIpKKyQkiIiIiIiIikorJCSIiIiIiIiKSiskJIiIiIiIiIpKKyQkiIiIiIiIikorJCSIiIiIiIiKSiskJIiIiIiIiIpKKyQkiIiIiIiIikur/A+0X3A5RAzKrAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1300x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(13, 5))\n",
    "ax.imshow(ma.masked_invalid(data[:, :, i_trial]).T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "efc0e9b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan])"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(data[:, :, i_trial], axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "538d37ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7d3186510>"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1300x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(13, 5))\n",
    "ax.imshow(np.isnan(data[:, :, i_trial]).T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "1c06e1b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "107"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "N_neurons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "50dd3732",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 10,  10,  10, ..., 107, 107, 107])"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KAABwDoECALCGJSiwhUABAADOIVAAAPaxCAU+ESgAAGsM+4xhCYECAACcQ6AAAKzjDg/8IlAAAIBzCBQAgDWsQIEtBAoAAHAOgQIAsI5PM4ZfBAoAwBp2GcMWAgUAADiHQAEAWMcdHvhFoAAAAOcQKAAAi1iEAjsIFAAA4BwCBQBgHUtQ4BeBAgCwhm3GsIVAAQAAziFQAADW8ZNk4ReBAgAAnEOgAACsYQkKbCFQAACAcwgUAIB1rECBXwQKAMAathnDFgIFAAA4h0ABAFjHLmP4RaAAAADnECgAAGsMG41hCYECAACcQ6AAAJKARSjwh0ABAFjDNmPYQqAAAADnECgAAOvYZgy/CBQAAOAcAgUAYA1rUGALgQIAAJxDoAAArGMJCvwiUAAA1vCTZGELgQIAAJxDoAAArGObMfwiUAAAgHMIFACANWwzhi1JD5RZs2YpEAiovLzce+7QoUMqKytTbm6uOnXqpFGjRqm+vj7ZQwEAAG1EUgNl06ZNeuKJJ3ThhRcmPD9x4kS98sorWrZsmdauXas9e/bouuuuS+ZQAACtKMBGY/iUtEA5cOCASktL9dRTT6lLly7e842NjXr66af16KOP6oorrlD//v21aNEivfXWW9qwYUOyhgMAANqQpAVKWVmZhg8frmg0mvB8TU2NmpubE57v1auXCgsLVVVVlazhAACANiQ9GRddunSp3n77bW3atOlbx2KxmDIyMpSTk5PwfDgcViwWO+H1mpqa1NTU5P06Ho9bHS8AwC62GcMv6++g1NXVacKECVq8eLEyMzOtXLOiokKhUMh7FBQUWLkuAABwk/VAqamp0d69e3XxxRcrPT1d6enpWrt2rebOnav09HSFw2EdPnxYDQ0NCV9XX1+vSCRywmtOmzZNjY2N3qOurs72sAEAFrDNGLZYv8UzdOhQvfvuuwnP3XrrrerVq5emTJmigoICtW/fXpWVlRo1apQkqba2Vrt371ZxcfEJrxkMBhUMBm0PFQAAOMp6oHTu3Fl9+vRJeK5jx47Kzc31nh87dqwmTZqkrl27Kjs7W3fffbeKi4t12WWX2R4OACAFWIICv5KySPZ/89hjjyktLU2jRo1SU1OTSkpK9Pjjj6diKAAAi/g0Y9jSKoHy5ptvJvw6MzNT8+fP1/z581vjtwcAAG0Mn8UDALAuwD5j+ESgAAAA5xAoAABr2GYMWwgUAADgHAIFAAA4h0ABAFjDHR7YQqAAAADnECgAAOvYZQy/CBQAAOAcAgUAYI1hnzEsIVAAAIBzCBQAgHWsQYFfBAoAwBpu8MAWAgUAADiHQAEAWBcQ93jgD4ECAACcQ6AAAKxhlzFsIVAAAIBzCBQAgHVsM4ZfBAoAwCLu8cAOAgUAADiHQAEAWMcdHvhFoAAAAOcQKAAAa9hmDFsIFAAA4BwCBQBgXYB9xvCJQAEAWMMdHthCoAAAAOcQKAAA67jBA78IFAAA4BwCBQBgDduMYQuBAgAAnEOgAADsYxEKfCJQAADWGO7xwBICBQAAOIdAAQBYxx0e+EWgAAAA5xAoAABrWIECWwgUAADgHAIFAGAdn2YMvwgUAIA17DKGLQQKAABwDoECALCOGzzwi0ABAADOIVAAANYYNhrDEgIFAAA4h0ABAFjHLmP4RaAAAOzhDg8sIVAAAIBzCBQAgHUBNhrDJwIFAAA4h0ABAFjDEhTYQqAAAADnECgAAOvYZgy/CBQAgDV8mjFsIVAAAIBzCBQAAOAcAgUAADiHQAEAWMOnGcMW64FSUVGhSy65RJ07d1ZeXp5Gjhyp2trahHMOHTqksrIy5ebmqlOnTho1apTq6+ttDwUAALRR1gNl7dq1Kisr04YNG7R69Wo1Nzfryiuv1MGDB71zJk6cqFdeeUXLli3T2rVrtWfPHl133XW2hwIASJEA+4zhU7rtC65atSrh188884zy8vJUU1Ojyy+/XI2NjXr66ae1ZMkSXXHFFZKkRYsWqXfv3tqwYYMuu+wy20MCALQSthnDlqSvQWlsbJQkde3aVZJUU1Oj5uZmRaNR75xevXqpsLBQVVVVJ7xGU1OT4vF4wgMAAJy5khooLS0tKi8v1+DBg9WnTx9JUiwWU0ZGhnJychLODYfDisViJ7xORUWFQqGQ9ygoKEjmsAEAPnGDB34lNVDKysq0fft2LV261Nd1pk2bpsbGRu9RV1dnaYQAAMBF1tegHDN+/HitXLlS69atU48ePbznI5GIDh8+rIaGhoR3Uerr6xWJRE54rWAwqGAwmKyhAgAsYQkKbLH+DooxRuPHj9fy5cu1Zs0aFRUVJRzv37+/2rdvr8rKSu+52tpa7d69W8XFxbaHAwAA2iDr76CUlZVpyZIleumll9S5c2dvXUkoFFJWVpZCoZDGjh2rSZMmqWvXrsrOztbdd9+t4uJidvAAwBmCXcbwy3qgLFiwQJL0s5/9LOH5RYsW6ZZbbpEkPfbYY0pLS9OoUaPU1NSkkpISPf7447aHAgBoZYZ9xrDEeqCcyh/OzMxMzZ8/X/Pnz7f92wMAgDMAn8UDALCOWzzwi0ABAADOIVAAANawAgW2ECgAAMA5BAoAwLoAP+wePhEoAAB7uMcDSwgUAADgHAIFAGAd24zhF4ECALDGcI8HlhAoAADAOQQKAABwDoECALCOJSjwi0ABAFjDhxnDFgIFAAA4h0ABANjHPmP4RKAAAKzhFg9sIVAAAIBzCBQAAOAcAgUAYB0rUOAXgQIAsIYlKLCFQAEAAM4hUAAA1rHLGH4RKAAAawz7jGEJgQIAAJxDoAAArOMOD/wiUAAAgHPSUz0Al9R8sk8r3/ks1cMAgDZr97+/SPUQcIYgUI5TGzugRf/zz1QPAwDavE6Z7VM9BLRxBMpxLsjPVtnPz031MACgTWsXCOjaH5+V6mGgjSNQjnNRQY4uKshJ9TAAAPjeY5EsAABwDoECAACcQ6AAAADnECgAAMA5BAoAAHAOgQIAAJxDoAAAAOcQKAAAwDkECgAAcA6BAgAAnEOgAAAA5xAoAADAOQQKAABwTpv8NGNjjCQpHo+neCQAAOBUHfu+fez7+Mm0yUDZv3+/JKmgoCDFIwEAAKdr//79CoVCJz0nYE4lYxzT0tKiPXv2qHPnzgoEAlavHY/HVVBQoLq6OmVnZ1u99pmGuTp1zNWpY65OHXN1epivU5esuTLGaP/+/crPz1da2slXmbTJd1DS0tLUo0ePpP4e2dnZ/AE+RczVqWOuTh1zdeqYq9PDfJ26ZMzV//bOyTEskgUAAM4hUAAAgHMIlG8IBoP67W9/q2AwmOqhOI+5OnXM1aljrk4dc3V6mK9T58JctclFsgAA4MzGOygAAMA5BAoAAHAOgQIAAJxDoAAAAOcQKMeZP3++zjnnHGVmZmrgwIHauHFjqofU6ioqKnTJJZeoc+fOysvL08iRI1VbW5twzqFDh1RWVqbc3Fx16tRJo0aNUn19fcI5u3fv1vDhw9WhQwfl5eXp3nvv1ZEjR1rzpbS6WbNmKRAIqLy83HuOufrap59+qptuukm5ubnKyspS3759tXnzZu+4MUYzZsxQ9+7dlZWVpWg0qp07dyZcY9++fSotLVV2drZycnI0duxYHThwoLVfSlIdPXpU06dPV1FRkbKysnTuuefqgQceSPjsku/zXK1bt07XXHON8vPzFQgEtGLFioTjtubmnXfe0U9+8hNlZmaqoKBAs2fPTvZLs+5kc9Xc3KwpU6aob9++6tixo/Lz8/XLX/5Se/bsSbhGSufKwBhjzNKlS01GRob5y1/+Yt577z1z++23m5ycHFNfX5/qobWqkpISs2jRIrN9+3azdetWc/XVV5vCwkJz4MAB75w77rjDFBQUmMrKSrN582Zz2WWXmUGDBnnHjxw5Yvr06WOi0ajZsmWLefXVV023bt3MtGnTUvGSWsXGjRvNOeecYy688EIzYcIE73nm6iv79u0zZ599trnllltMdXW1+fjjj83rr79uPvroI++cWbNmmVAoZFasWGG2bdtmrr32WlNUVGS+/PJL75yrrrrKXHTRRWbDhg3mH//4h/nRj35kbrzxxlS8pKSZOXOmyc3NNStXrjS7du0yy5YtM506dTJ/+tOfvHO+z3P16quvmvvuu8+8+OKLRpJZvnx5wnEbc9PY2GjC4bApLS0127dvN88//7zJysoyTzzxRGu9TCtONlcNDQ0mGo2av/3tb+bDDz80VVVV5tJLLzX9+/dPuEYq54pA+Y9LL73UlJWVeb8+evSoyc/PNxUVFSkcVert3bvXSDJr1641xnz1h7p9+/Zm2bJl3jkffPCBkWSqqqqMMV/9pUhLSzOxWMw7Z8GCBSY7O9s0NTW17gtoBfv37zc9e/Y0q1evNj/96U+9QGGuvjZlyhQzZMiQ/3q8paXFRCIR84c//MF7rqGhwQSDQfP8888bY4x5//33jSSzadMm75zXXnvNBAIB8+mnnyZv8K1s+PDh5rbbbkt47rrrrjOlpaXGGObqeN/8pmtrbh5//HHTpUuXhL+DU6ZMMeedd16SX1HynCjmvmnjxo1Gkvnkk0+MMamfK27xSDp8+LBqamoUjUa959LS0hSNRlVVVZXCkaVeY2OjJKlr166SpJqaGjU3NyfMVa9evVRYWOjNVVVVlfr27atwOOydU1JSong8rvfee68VR986ysrKNHz48IQ5kZir47388ssaMGCArr/+euXl5alfv3566qmnvOO7du1SLBZLmKtQKKSBAwcmzFVOTo4GDBjgnRONRpWWlqbq6urWezFJNmjQIFVWVmrHjh2SpG3btmn9+vUaNmyYJObqZGzNTVVVlS6//HJlZGR455SUlKi2tlaff/55K72a1tfY2KhAIKCcnBxJqZ+rNvlhgbb961//0tGjRxO+SUhSOBzWhx9+mKJRpV5LS4vKy8s1ePBg9enTR5IUi8WUkZHh/QE+JhwOKxaLeeecaC6PHTuTLF26VG+//bY2bdr0rWPM1dc+/vhjLViwQJMmTdJvfvMbbdq0Sffcc48yMjI0ZswY77WeaC6On6u8vLyE4+np6eratesZNVdTp05VPB5Xr1691K5dOx09elQzZ85UaWmpJDFXJ2FrbmKxmIqKir51jWPHunTpkpTxp9KhQ4c0ZcoU3Xjjjd6HA6Z6rggU/FdlZWXavn271q9fn+qhOKmurk4TJkzQ6tWrlZmZmerhOK2lpUUDBgzQQw89JEnq16+ftm/froULF2rMmDEpHp1bXnjhBS1evFhLlizRBRdcoK1bt6q8vFz5+fnMFZKiublZN9xwg4wxWrBgQaqH4+EWj6Ru3bqpXbt239pdUV9fr0gkkqJRpdb48eO1cuVKvfHGG+rRo4f3fCQS0eHDh9XQ0JBw/vFzFYlETjiXx46dKWpqarR3715dfPHFSk9PV3p6utauXau5c+cqPT1d4XCYufqP7t276/zzz094rnfv3tq9e7ekr1/ryf4ORiIR7d27N+H4kSNHtG/fvjNqru69915NnTpVo0ePVt++fXXzzTdr4sSJqqiokMRcnYytufm+/L2Uvo6TTz75RKtXr/bePZFSP1cEiqSMjAz1799flZWV3nMtLS2qrKxUcXFxCkfW+owxGj9+vJYvX641a9Z86627/v37q3379glzVVtbq927d3tzVVxcrHfffTfhD/axP/jf/CbVlg0dOlTvvvuutm7d6j0GDBig0tJS77+Zq68MHjz4W9vVd+zYobPPPluSVFRUpEgkkjBX8Xhc1dXVCXPV0NCgmpoa75w1a9aopaVFAwcObIVX0Tq++OILpaUl/tPcrl07tbS0SGKuTsbW3BQXF2vdunVqbm72zlm9erXOO++8M+r2zrE42blzp/7+978rNzc34XjK58r3MtszxNKlS00wGDTPPPOMef/99824ceNMTk5Owu6K74M777zThEIh8+abb5rPPvvMe3zxxRfeOXfccYcpLCw0a9asMZs3bzbFxcWmuLjYO35s6+yVV15ptm7dalatWmV+8IMfnHFbZ0/k+F08xjBXx2zcuNGkp6ebmTNnmp07d5rFixebDh06mL/+9a/eObNmzTI5OTnmpZdeMu+8844ZMWLECbeH9uvXz1RXV5v169ebnj17nhFbZ483ZswYc9ZZZ3nbjF988UXTrVs3M3nyZO+c7/Nc7d+/32zZssVs2bLFSDKPPvqo2bJli7fzxMbcNDQ0mHA4bG6++Wazfft2s3TpUtOhQ4c2t834ZHN1+PBhc+2115oePXqYrVu3Jvx7f/yOnFTOFYFynHnz5pnCwkKTkZFhLr30UrNhw4ZUD6nVSTrhY9GiRd45X375pbnrrrtMly5dTIcOHcwvfvEL89lnnyVc55///KcZNmyYycrKMt26dTO//vWvTXNzcyu/mtb3zUBhrr72yiuvmD59+phgMGh69eplnnzyyYTjLS0tZvr06SYcDptgMGiGDh1qamtrE87597//bW688UbTqVMnk52dbW699Vazf//+1nwZSRePx82ECRNMYWGhyczMND/84Q/Nfffdl/BN4/s8V2+88cYJ/40aM2aMMcbe3Gzbts0MGTLEBINBc9ZZZ5lZs2a11ku05mRztWvXrv/67/0bb7zhXSOVcxUw5rgfTwgAAOAA1qAAAADnECgAAMA5BAoAAHAOgQIAAJxDoAAAAOcQKAAAwDkECgAAcA6BAgAAnEOgAAAA5xAoAADAOQQKAABwDoECAACc8/8BK6Cr6FqWZAAAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.isnan(data[:, :, i_trial]).sum(axis=1))\n",
    "np.isnan(data[:, :, i_trial]).sum(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "275b8d87",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7d3233e50>]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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6lS677DLHnQUAnFrYtRdeiDmMLF68WBMnTlRxcbEGDhyo8vJyJScna8WKFa2e09zcrPHjx2vevHk677zzXHUYAACcXmIKI01NTaqurlYgEPj8A+LjFQgEVFlZ2ep5v/nNb9SrVy/ddNNNbbpOY2OjQqFQ1AsAcOqitBduxBRGDhw4oObmZvn9/qjjfr9fwWCwxXM2btyoBx98UMuXL2/zdcrKypSamhp5ZWdnx9JNAEBHYZYGHmjXapqGhgbdeOONWr58udLT09t8Xmlpqerr6yOv3bt3t2MvAQCATV1iaZyenq6EhATV1dVFHa+rq1NGRsYJ7f/zn//ogw8+0OjRoyPHwuHwZxfu0kXbt2/X+eeff8J5Pp9PPp8vlq4BACyKY54GLsT0ZCQxMVG5ubmqqKiIHAuHw6qoqFBBQcEJ7fv376+33npLNTU1kdf111+vK6+8UjU1NUy/AACA2J6MSFJJSYmKioqUl5en4cOHa8mSJTp8+LCKi4slSRMmTFBWVpbKysqUlJSkQYMGRZ2flpYmSSccBwB0PiwZgRdiDiNjx47V/v37NWfOHAWDQQ0dOlTr1q2LLGqtra1VfDxf7AoAANom5jAiSVOmTNGUKVNafG/Dhg0nPffhhx92ckkAwCmMFSNwg0cYAADHDNv2wgOEEQAAYBVhBADgHvM0cIEwAgAArCKMAAAcY8kIvEAYAQAAVhFGAACuxbFoBC4QRgAAjjFLAy8QRgAAgFWEEQCAa2zaCzcIIwAAwCrCCADAMUp74QXCCAAAsIowAgBwjSUjcIMwAgBwzFDcCw8QRgAAgFWEEQCAa5T2wg3CCAAAsIowAgBwjNJeeIEwAgAArCKMAABcY9deuEEYAQAAVhFGAACAVYQRAIBrlPbCDcIIAACwijACAHDMUNsLDxBGAACAVYQRAIBrLBmBG4QRAIBjTNLAC4QRAABgFWEEAOAetb1wgTACAACsIowAAByjshdeIIwAAACrCCMAANdYMQI3CCMAAMcMxb3wAGEEAABYRRgBALhGZS/cIIwAAACrCCMAAMco7YUXCCMAAMAqwggAwLU4invhAmEEAOAYszTwAmEEAABYRRgBALhGaS/cIIwAAACrCCMAAMco7YUXCCMAAMAqwggAwDWWjMANwggAwAXmaeAeYQQAAFhFGAEAuEZpL9wgjAAAAKsIIwAAxyjthRcIIwAAwCrCCADAtTgWjcAFR2Fk6dKlysnJUVJSkvLz81VVVdVq2+XLl+uyyy5Tjx491KNHDwUCgZO2BwB0HkzTwAsxh5FVq1appKREc+fO1ebNmzVkyBAVFhZq3759LbbfsGGDxo0bpxdffFGVlZXKzs7W1VdfrT179rjuPAAA6PxiDiOLFy/WxIkTVVxcrIEDB6q8vFzJyclasWJFi+0feeQR3XbbbRo6dKj69++vBx54QOFwWBUVFa47DwAAOr+YwkhTU5Oqq6sVCAQ+/4D4eAUCAVVWVrbpM44cOaKjR4/q7LPPbrVNY2OjQqFQ1AsAAJyeYgojBw4cUHNzs/x+f9Rxv9+vYDDYps+YMWOGMjMzowLNl5WVlSk1NTXyys7OjqWbAIAOYvg6eHigQ6tpFi5cqJUrV+rpp59WUlJSq+1KS0tVX18fee3evbsDewkAADpSl1gap6enKyEhQXV1dVHH6+rqlJGRcdJz//CHP2jhwoV6/vnndfHFF5+0rc/nk8/ni6VrAACLqOyFGzE9GUlMTFRubm7U4tPji1ELCgpaPe+ee+7R3XffrXXr1ikvL895bwEApxRKe+GFmJ6MSFJJSYmKioqUl5en4cOHa8mSJTp8+LCKi4slSRMmTFBWVpbKysokSb/73e80Z84cPfroo8rJyYmsLenWrZu6devm4a0AAIDOKOYwMnbsWO3fv19z5sxRMBjU0KFDtW7dusii1traWsXHf/7AZdmyZWpqatIPf/jDqM+ZO3eufv3rX7vrPQDglBAn5mngXMxhRJKmTJmiKVOmtPjehg0bon7+4IMPnFwCAACcIdibBgDgGEtG4AXCCAAAsIowAgBwjdJeuEEYAQA4RmkvvEAYAQAAVhFGAACuMUsDNwgjAADAKsIIAMAxdu2FFwgjAADAKsIIAMA1SnvhBmEEAOAcszTwAGEEAABYRRgBALjGrr1wgzACAACsIowAABxjyQi8QBgBAABWEUYAAK5R2gs3CCMAAMcM2/bCA4QRAABgFWEEAABYRRgBAABWEUYAAI6xYgReIIwAAACrCCMAANfiqO2FC4QRAIBjVPbCC4QRAABgFWEEAOAakzRwgzACAACsIowAABxjyQi8QBgBAABWEUYAAK5R2Qs3CCMAAMfYtRdeIIwAAACrCCMAANeYpYEbhBEAAGAVYQQA4BgrRuAFwggAALCKMAIAcI1de+EGYQQA4BzzNPAAYQQAAFhFGAEAuMYsDdwgjAAAHDPM08ADhBEAAGAVYQQAAFhFGAEAuMaSEbhBGAEAOMamvfACYQQAAFhFGAEAuEdtL1wgjAAAHGOaBl4gjAAAAKsIIwAAwCrCCADANVaMwA3CCADAMb4OHl4gjAAAAKsIIwAA16jshRuEEQCAY5T2wguOwsjSpUuVk5OjpKQk5efnq6qq6qTtn3jiCfXv319JSUkaPHiw1q5d66izAADg9BNzGFm1apVKSko0d+5cbd68WUOGDFFhYaH27dvXYvtXXnlF48aN00033aQtW7ZozJgxGjNmjLZu3eq68wCAU0Mc9TRwIeYwsnjxYk2cOFHFxcUaOHCgysvLlZycrBUrVrTY/t5779U111yj22+/XQMGDNDdd9+tSy65RH/5y19cdx4AAHR+XWJp3NTUpOrqapWWlkaOxcfHKxAIqLKyssVzKisrVVJSEnWssLBQq1evbvU6jY2NamxsjPwcCoVi6WabPbhxl/7v/460y2cDwJlgW7DBdhdwGogpjBw4cEDNzc3y+/1Rx/1+v7Zt29biOcFgsMX2wWCw1euUlZVp3rx5sXTNkTVv7tXm2kPtfh0AON11S4rpzwkQ5ZT87SktLY16mhIKhZSdne35dX6Q20cF5/f0/HMB4EzS82s+XT3Q/9UNgVbEFEbS09OVkJCgurq6qON1dXXKyMho8ZyMjIyY2kuSz+eTz+eLpWuOjM8/t92vAQAATi6mBayJiYnKzc1VRUVF5Fg4HFZFRYUKCgpaPKegoCCqvSStX7++1fYAAODMEvM0TUlJiYqKipSXl6fhw4dryZIlOnz4sIqLiyVJEyZMUFZWlsrKyiRJU6dO1eWXX65FixZp1KhRWrlypTZt2qT777/f2zsBAACdUsxhZOzYsdq/f7/mzJmjYDCooUOHat26dZFFqrW1tYqP//yBy4gRI/Too4/qrrvu0p133qkLL7xQq1ev1qBBg7y7CwAA0GnFGXPqf5lvKBRSamqq6uvrlZKSYrs7AACgDdr695u9aQAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVMX8dvA3HvyQ2FApZ7gkAAGir43+3v+rL3jtFGGloaJAkZWdnW+4JAACIVUNDg1JTU1t9v1PsTRMOh7V37151795dcXFxnn1uKBRSdna2du/ezZ43X4Gxig3j1XaMVdsxVm3HWMWmvcbLGKOGhgZlZmZGbaL7ZZ3iyUh8fLz69OnTbp+fkpLCL2sbMVaxYbzajrFqO8aq7Rir2LTHeJ3sichxLGAFAABWEUYAAIBVZ3QY8fl8mjt3rnw+n+2unPIYq9gwXm3HWLUdY9V2jFVsbI9Xp1jACgAATl9n9JMRAABgH2EEAABYRRgBAABWEUYAAIBVZ3QYWbp0qXJycpSUlKT8/HxVVVXZ7lKHKisr0ze/+U11795dvXr10pgxY7R9+/aoNp9++qkmT56snj17qlu3bvrBD36gurq6qDa1tbUaNWqUkpOT1atXL91+++06duxYR95Kh1u4cKHi4uI0bdq0yDHGKtqePXv005/+VD179lTXrl01ePBgbdq0KfK+MUZz5sxR79691bVrVwUCAb333ntRn3Hw4EGNHz9eKSkpSktL00033aSPP/64o2+lXTU3N2v27Nnq16+funbtqvPPP19333131F4eZ+pYvfzyyxo9erQyMzMVFxen1atXR73v1bi8+eabuuyyy5SUlKTs7Gzdc8897X1r7eJk43X06FHNmDFDgwcP1te+9jVlZmZqwoQJ2rt3b9RnWBsvc4ZauXKlSUxMNCtWrDBvv/22mThxoklLSzN1dXW2u9ZhCgsLzUMPPWS2bt1qampqzHXXXWf69u1rPv7440ibSZMmmezsbFNRUWE2bdpkvvWtb5kRI0ZE3j927JgZNGiQCQQCZsuWLWbt2rUmPT3dlJaW2rilDlFVVWVycnLMxRdfbKZOnRo5zlh97uDBg+bcc881P/vZz8xrr71mdu7caZ577jnz/vvvR9osXLjQpKammtWrV5s33njDXH/99aZfv37mk08+ibS55pprzJAhQ8yrr75q/v3vf5sLLrjAjBs3zsYttZv58+ebnj17mmeffdbs2rXLPPHEE6Zbt27m3nvvjbQ5U8dq7dq1ZtasWeapp54ykszTTz8d9b4X41JfX2/8fr8ZP3682bp1q3nsscdM165dzV//+teOuk3PnGy8Dh06ZAKBgFm1apXZtm2bqaysNMOHDze5ublRn2FrvM7YMDJ8+HAzefLkyM/Nzc0mMzPTlJWVWeyVXfv27TOSzEsvvWSM+eyX96yzzjJPPPFEpM27775rJJnKykpjzGe//PHx8SYYDEbaLFu2zKSkpJjGxsaOvYEO0NDQYC688EKzfv16c/nll0fCCGMVbcaMGebSSy9t9f1wOGwyMjLM73//+8ixQ4cOGZ/PZx577DFjjDHvvPOOkWRef/31SJt//etfJi4uzuzZs6f9Ot/BRo0aZX7+859HHfv+979vxo8fb4xhrI778h9Xr8blvvvuMz169Ij6f3DGjBnmoosuauc7al8thbcvq6qqMpLMhx9+aIyxO15n5DRNU1OTqqurFQgEIsfi4+MVCARUWVlpsWd21dfXS5LOPvtsSVJ1dbWOHj0aNU79+/dX3759I+NUWVmpwYMHy+/3R9oUFhYqFArp7bff7sDed4zJkydr1KhRUWMiMVZf9swzzygvL08/+tGP1KtXLw0bNkzLly+PvL9r1y4Fg8Go8UpNTVV+fn7UeKWlpSkvLy/SJhAIKD4+Xq+99lrH3Uw7GzFihCoqKrRjxw5J0htvvKGNGzfq2muvlcRYtcarcamsrNS3v/1tJSYmRtoUFhZq+/bt+t///tdBd2NHfX294uLilJaWJsnueHWKjfK8duDAATU3N0f9UZAkv9+vbdu2WeqVXeFwWNOmTdPIkSM1aNAgSVIwGFRiYmLkF/U4v9+vYDAYadPSOB5/73SycuVKbd68Wa+//voJ7zFW0Xbu3Klly5appKREd955p15//XX94he/UGJiooqKiiL329J4fHG8evXqFfV+ly5ddPbZZ59W4zVz5kyFQiH1799fCQkJam5u1vz58zV+/HhJYqxa4dW4BINB9evX74TPOP5ejx492qX/tn366aeaMWOGxo0bF9kYz+Z4nZFhBCeaPHmytm7dqo0bN9ruyilp9+7dmjp1qtavX6+kpCTb3TnlhcNh5eXlacGCBZKkYcOGaevWrSovL1dRUZHl3p1aHn/8cT3yyCN69NFH9Y1vfEM1NTWaNm2aMjMzGSu0i6NHj+rHP/6xjDFatmyZ7e5IOkOradLT05WQkHBCpUNdXZ0yMjIs9cqeKVOm6Nlnn9WLL76oPn36RI5nZGSoqalJhw4dimr/xXHKyMhocRyPv3e6qK6u1r59+3TJJZeoS5cu6tKli1566SX96U9/UpcuXeT3+xmrL+jdu7cGDhwYdWzAgAGqra2V9Pn9nuz/wYyMDO3bty/q/WPHjungwYOn1Xjdfvvtmjlzpn7yk59o8ODBuvHGGzV9+nSVlZVJYqxa49W4nEn/X0qfB5EPP/xQ69evjzwVkeyO1xkZRhITE5Wbm6uKiorIsXA4rIqKChUUFFjsWccyxmjKlCl6+umn9cILL5zw6C03N1dnnXVW1Dht375dtbW1kXEqKCjQW2+9FfULfPwX/Mt/jDqzq666Sm+99ZZqamoir7y8PI0fPz7y34zV50aOHHlCmfiOHTt07rnnSpL69eunjIyMqPEKhUJ67bXXosbr0KFDqq6ujrR54YUXFA6HlZ+f3wF30TGOHDmi+Pjof4oTEhIUDoclMVat8WpcCgoK9PLLL+vo0aORNuvXr9dFF1102k3RHA8i7733np5//nn17Nkz6n2r4+Vq+WsntnLlSuPz+czDDz9s3nnnHXPLLbeYtLS0qEqH092tt95qUlNTzYYNG8xHH30UeR05ciTSZtKkSaZv377mhRdeMJs2bTIFBQWmoKAg8v7xctWrr77a1NTUmHXr1plzzjnntCxX/bIvVtMYw1h9UVVVlenSpYuZP3++ee+998wjjzxikpOTzd///vdIm4ULF5q0tDTzj3/8w7z55pvmu9/9botlmcOGDTOvvfaa2bhxo7nwwgs7fbnqlxUVFZmsrKxIae9TTz1l0tPTzR133BFpc6aOVUNDg9myZYvZsmWLkWQWL15stmzZEqn+8GJcDh06ZPx+v7nxxhvN1q1bzcqVK01ycnKnLO092Xg1NTWZ66+/3vTp08fU1NRE/Zv/xcoYW+N1xoYRY4z585//bPr27WsSExPN8OHDzauvvmq7Sx1KUouvhx56KNLmk08+Mbfddpvp0aOHSU5ONt/73vfMRx99FPU5H3zwgbn22mtN165dTXp6uvnlL39pjh492sF30/G+HEYYq2j//Oc/zaBBg4zP5zP9+/c3999/f9T74XDYzJ492/j9fuPz+cxVV11ltm/fHtXmv//9rxk3bpzp1q2bSUlJMcXFxaahoaEjb6PdhUIhM3XqVNO3b1+TlJRkzjvvPDNr1qyoPxBn6li9+OKLLf4bVVRUZIzxblzeeOMNc+mllxqfz2eysrLMwoULO+oWPXWy8dq1a1er/+a/+OKLkc+wNV5xxnzha/4AAAA62Bm5ZgQAAJw6CCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAKsIIAACwijACAACs+n/Jc9gryi9RgwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# trim time\n",
    "plt.plot(np.isnan(data[:, :, i_trial]).sum(axis=1)<N_neurons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "2a0d65bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(900, 107)"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_trimT = data[np.isnan(data[:, :, i_trial]).sum(axis=1)<N_neurons, :, i_trial]\n",
    "data_trimT.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "025e2420",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(900, 97)"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_trim = data_trimT[:, np.isnan(data_trimT).sum(axis=0)==0]\n",
    "data_trim.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "58fdd143",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7d3781790>"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1300x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(13, 8))\n",
    "ax.imshow((data_trim>0)[:300, :].T, cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6855dc76",
   "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": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}