dPCA_Allen.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "dPCA_Allen.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ooSZA8gjY7WY"
      },
      "source": [
        "The following is an application of the following dimensionality reduction algorithm to the Allen Institute 2-P dataset:\n",
        "\n",
        "D Kobak+, W Brendel+, C Constantinidis, CE Feierstein, A Kepecs, ZF Mainen, X-L Qi, R Romo, N Uchida, CK Machens\n",
        "Demixed principal component analysis of neural population data\n",
        "eLife 2016, https://elifesciences.org/content/5/e10989\n",
        "(arXiv link: http://arxiv.org/abs/1410.6031)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1Xm2F5-0aIN2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "72f6de8e-d11c-410a-ae94-64341ef5311b"
      },
      "source": [
        "!python -m pip install --upgrade pip\n",
        "!pip install mindscope_utilities\n"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
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            "  Building wheel for argschema (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for argschema: filename=argschema-2.0.2-py2.py3-none-any.whl size=17795 sha256=f50345de1d481c8721ea5a87c89cdf5fcfedac743061799ae84d4844c09f0fe1\n",
            "  Stored in directory: /root/.cache/pip/wheels/ee/97/a8/4dbf0458be0af473d083a6354c0c126490e82447237bb0b907\n",
            "Successfully built mindscope-utilities glymur argschema\n",
            "Installing collected packages: ruamel.yaml.clib, numpy, urllib3, ruamel.yaml, pandas, jmespath, h5py, multidict, hdmf, botocore, yarl, s3transfer, pynwb, marshmallow, distro, async-timeout, xarray, tables, simplejson, simpleitk, scikit-build, requests-toolbelt, pynrrd, pyflakes, pycodestyle, psycopg2-binary, nest-asyncio, ndx-events, mccabe, glymur, boto3, argschema, aiohttp, flake8, allensdk, mindscope-utilities\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/ruamel.yaml.clib\n",
            "  sysconfig: /usr/include/python3.7m/ruamel.yaml.clib\u001b[0m\n",
            "  Attempting uninstall: numpy\n",
            "    Found existing installation: numpy 1.19.5\n",
            "    Uninstalling numpy-1.19.5:\n",
            "      Successfully uninstalled numpy-1.19.5\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/numpy\n",
            "  sysconfig: /usr/include/python3.7m/numpy\u001b[0m\n",
            "  Attempting uninstall: urllib3\n",
            "    Found existing installation: urllib3 1.24.3\n",
            "    Uninstalling urllib3-1.24.3:\n",
            "      Successfully uninstalled urllib3-1.24.3\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/urllib3\n",
            "  sysconfig: /usr/include/python3.7m/urllib3\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/ruamel.yaml\n",
            "  sysconfig: /usr/include/python3.7m/ruamel.yaml\u001b[0m\n",
            "  Attempting uninstall: pandas\n",
            "    Found existing installation: pandas 1.1.5\n",
            "    Uninstalling pandas-1.1.5:\n",
            "      Successfully uninstalled pandas-1.1.5\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/pandas\n",
            "  sysconfig: /usr/include/python3.7m/pandas\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/jmespath\n",
            "  sysconfig: /usr/include/python3.7m/jmespath\u001b[0m\n",
            "  Attempting uninstall: h5py\n",
            "    Found existing installation: h5py 3.1.0\n",
            "    Uninstalling h5py-3.1.0:\n",
            "      Successfully uninstalled h5py-3.1.0\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/h5py\n",
            "  sysconfig: /usr/include/python3.7m/h5py\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/multidict\n",
            "  sysconfig: /usr/include/python3.7m/multidict\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/hdmf\n",
            "  sysconfig: /usr/include/python3.7m/hdmf\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/botocore\n",
            "  sysconfig: /usr/include/python3.7m/botocore\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/yarl\n",
            "  sysconfig: /usr/include/python3.7m/yarl\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/s3transfer\n",
            "  sysconfig: /usr/include/python3.7m/s3transfer\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/pynwb\n",
            "  sysconfig: /usr/include/python3.7m/pynwb\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/marshmallow\n",
            "  sysconfig: /usr/include/python3.7m/marshmallow\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/distro\n",
            "  sysconfig: /usr/include/python3.7m/distro\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/async-timeout\n",
            "  sysconfig: /usr/include/python3.7m/async-timeout\u001b[0m\n",
            "  Attempting uninstall: xarray\n",
            "    Found existing installation: xarray 0.18.2\n",
            "    Uninstalling xarray-0.18.2:\n",
            "      Successfully uninstalled xarray-0.18.2\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/xarray\n",
            "  sysconfig: /usr/include/python3.7m/xarray\u001b[0m\n",
            "  Attempting uninstall: tables\n",
            "    Found existing installation: tables 3.4.4\n",
            "    Uninstalling tables-3.4.4:\n",
            "      Successfully uninstalled tables-3.4.4\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/tables\n",
            "  sysconfig: /usr/include/python3.7m/tables\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/simplejson\n",
            "  sysconfig: /usr/include/python3.7m/simplejson\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/simpleitk\n",
            "  sysconfig: /usr/include/python3.7m/simpleitk\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/scikit-build\n",
            "  sysconfig: /usr/include/python3.7m/scikit-build\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/requests-toolbelt\n",
            "  sysconfig: /usr/include/python3.7m/requests-toolbelt\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/pynrrd\n",
            "  sysconfig: /usr/include/python3.7m/pynrrd\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/pyflakes\n",
            "  sysconfig: /usr/include/python3.7m/pyflakes\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/pycodestyle\n",
            "  sysconfig: /usr/include/python3.7m/pycodestyle\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/psycopg2-binary\n",
            "  sysconfig: /usr/include/python3.7m/psycopg2-binary\u001b[0m\n",
            "  Attempting uninstall: nest-asyncio\n",
            "    Found existing installation: nest-asyncio 1.5.1\n",
            "    Uninstalling nest-asyncio-1.5.1:\n",
            "      Successfully uninstalled nest-asyncio-1.5.1\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/nest-asyncio\n",
            "  sysconfig: /usr/include/python3.7m/nest-asyncio\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/ndx-events\n",
            "  sysconfig: /usr/include/python3.7m/ndx-events\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/mccabe\n",
            "  sysconfig: /usr/include/python3.7m/mccabe\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/glymur\n",
            "  sysconfig: /usr/include/python3.7m/glymur\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/boto3\n",
            "  sysconfig: /usr/include/python3.7m/boto3\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/argschema\n",
            "  sysconfig: /usr/include/python3.7m/argschema\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/aiohttp\n",
            "  sysconfig: /usr/include/python3.7m/aiohttp\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/flake8\n",
            "  sysconfig: /usr/include/python3.7m/flake8\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/allensdk\n",
            "  sysconfig: /usr/include/python3.7m/allensdk\u001b[0m\n",
            "\u001b[33m  WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/10151>\n",
            "  distutils: /usr/local/include/python3.7/mindscope-utilities\n",
            "  sysconfig: /usr/include/python3.7m/mindscope-utilities\u001b[0m\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "tensorflow 2.5.0 requires h5py~=3.1.0, but you have h5py 2.10.0 which is incompatible.\n",
            "tensorflow 2.5.0 requires numpy~=1.19.2, but you have numpy 1.18.5 which is incompatible.\n",
            "nbclient 0.5.3 requires jupyter-client>=6.1.5, but you have jupyter-client 5.3.5 which is incompatible.\n",
            "google-colab 1.0.0 requires pandas~=1.1.0; python_version >= \"3.0\", but you have pandas 0.25.3 which is incompatible.\n",
            "fbprophet 0.7.1 requires pandas>=1.0.4, but you have pandas 0.25.3 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\n",
            "arviz 0.11.2 requires xarray>=0.16.1, but you have xarray 0.15.1 which is incompatible.\n",
            "albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
            "Successfully installed aiohttp-3.7.4 allensdk-2.11.2 argschema-2.0.2 async-timeout-3.0.1 boto3-1.17.21 botocore-1.20.112 distro-1.5.0 flake8-3.9.2 glymur-0.8.19 h5py-2.10.0 hdmf-2.4.0 jmespath-0.10.0 marshmallow-3.0.0rc6 mccabe-0.6.1 mindscope-utilities-0.1.7 multidict-5.1.0 ndx-events-0.2.0 nest-asyncio-1.2.0 numpy-1.18.5 pandas-0.25.3 psycopg2-binary-2.9.1 pycodestyle-2.7.0 pyflakes-2.3.1 pynrrd-0.4.2 pynwb-1.4.0 requests-toolbelt-0.9.1 ruamel.yaml-0.17.10 ruamel.yaml.clib-0.2.6 s3transfer-0.3.7 scikit-build-0.11.1 simpleitk-2.1.0 simplejson-3.17.3 tables-3.6.1 urllib3-1.25.11 xarray-0.15.1 yarl-1.6.3\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "numpy",
                  "pandas"
                ]
              }
            }
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y9IVdfYxP764"
      },
      "source": [
        "pip install dpca"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cgFHDxOcaJut"
      },
      "source": [
        "import os\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from tqdm import tqdm\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "from dPCA import dPCA\n",
        "\n",
        "import mindscope_utilities\n",
        "import mindscope_utilities.visual_behavior_ophys as ophys\n",
        "\n",
        "from allensdk.brain_observatory.behavior.behavior_project_cache import VisualBehaviorOphysProjectCache\n",
        "\n",
        "pd.set_option('display.max_columns', 500)"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pvamvtoUbWTR",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ab87e497-de37-456e-fbb5-e5db58d43d4f"
      },
      "source": [
        "data_storage_directory = \"/temp\" # Note: this path must exist on your local drive\n",
        "cache = VisualBehaviorOphysProjectCache.from_s3_cache(cache_dir=data_storage_directory)"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ophys_session_table.csv: 100%|██████████| 165k/165k [00:00<00:00, 1.73MMB/s]\n",
            "behavior_session_table.csv: 100%|██████████| 885k/885k [00:00<00:00, 5.51MMB/s] \n",
            "ophys_experiment_table.csv: 100%|██████████| 336k/336k [00:00<00:00, 2.16MMB/s] \n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pOCbdeNbd7w8"
      },
      "source": [
        "session_table = cache.get_ophys_session_table()\n",
        "experiment_table = cache.get_ophys_experiment_table()"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q3IyXgjTaJmG",
        "outputId": "30decbdc-ec69-4832-8891-015b2159d0d4"
      },
      "source": [
        "experiment_id = experiment_table.query('session_type == \"OPHYS_1_images_A\"').query('project_code== \"VisualBehavior\"').sample(random_state=100).index[0]\n",
        "print('getting experiment data for experiment_id {}'.format(experiment_id))\n",
        "exp = cache.get_behavior_ophys_experiment(experiment_id)\n"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\rbehavior_ophys_experiment_873972085.nwb:   0%|          | 0.00/728M [00:00<?, ?MB/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "getting experiment data for experiment_id 873972085\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "behavior_ophys_experiment_873972085.nwb: 100%|██████████| 728M/728M [00:40<00:00, 18.0MMB/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q1CXALDZUpdA"
      },
      "source": [
        "#exp = experiments[ophys_experiment_ids[0]]\n",
        "\n",
        "hit_change_time = exp.trials[(exp.trials.aborted==False)&(exp.trials.hit==True)].change_time\n",
        "miss_change_time = exp.trials[(exp.trials.aborted==False)&(exp.trials.miss==True)].change_time\n",
        "cor_rej_change_time = exp.trials[(exp.trials.aborted==False)&(exp.trials.correct_reject==True)].change_time\n",
        "false_ala_hit_change_time = exp.trials[(exp.trials.aborted==False)&(exp.trials.false_alarm==True)].change_time"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lEuH7WAtWnxy",
        "outputId": "4840ba44-9bbf-416d-ddb5-e770e99c8c55"
      },
      "source": [
        "print(len(hit_change_time))\n",
        "print(len(miss_change_time))\n",
        "print(len(cor_rej_change_time))\n",
        "print(len(false_ala_hit_change_time))"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "150\n",
            "39\n",
            "18\n",
            "8\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tlCMrr1Fbf6I",
        "outputId": "19754dc8-06dc-4c75-c7e3-69b246876560"
      },
      "source": [
        "neural_data = []\n",
        "for ophys_experiment_id in tqdm([experiment_id]): #tqdm is a package that shows progress bars for items that are iterated over\n",
        "    \n",
        "    this_experiment_neural_data = ophys.build_tidy_cell_df(exp)\n",
        "    \n",
        "    # add some columns with metadata for the experiment\n",
        "    metadata_keys = [\n",
        "        'ophys_experiment_id',\n",
        "        'ophys_session_id',\n",
        "        'targeted_structure',\n",
        "        'imaging_depth',\n",
        "        'equipment_name',\n",
        "        'cre_line',\n",
        "        'mouse_id',\n",
        "        'sex',\n",
        "    ]\n",
        "    for metadata_key in metadata_keys:\n",
        "        this_experiment_neural_data[metadata_key] = exp.metadata[metadata_key]\n",
        "        \n",
        "    # append the data for this experiment to a list\n",
        "    neural_data.append(this_experiment_neural_data)\n",
        "    \n",
        "# concatate the list of dataframes into a single dataframe\n",
        "neural_data = pd.concat(neural_data)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 1/1 [00:15<00:00, 15.04s/it]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1AbRKekeb8zn",
        "outputId": "b0d4b5a9-7ada-4ea1-b5ed-23f339db2668"
      },
      "source": [
        "cell_ids = neural_data['cell_specimen_id'].unique()\n",
        "print('there are {} unique cells'.format(len(cell_ids)))\n",
        "print('cell ids are: {}'.format(cell_ids))"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "there are 85 unique cells\n",
            "cell ids are: [1086566314, 1086509375, 1086510902, 1086528930, 1086529593, ..., 1086571256, 1086534861, 1086532683, 1086533229, 1086512002]\n",
            "Length: 85\n",
            "Categories (85, int64): [1086566314, 1086509375, 1086510902, 1086528930, ..., 1086534861, 1086532683,\n",
            "                         1086533229, 1086512002]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "5Gix-iDLU_Ig",
        "outputId": "84bf0be8-a275-4233-d02e-c2c68938188d"
      },
      "source": [
        "cell_id = cell_ids[11]\n",
        "etr = mindscope_utilities.event_triggered_response(\n",
        "    data = neural_data.query('cell_specimen_id == @cell_id'),\n",
        "    t = 'timestamps',\n",
        "    y = 'dff',\n",
        "    event_times = hit_change_time,\n",
        "    t_before=3,\n",
        "    t_after=3,\n",
        "    output_sampling_rate = 50,\n",
        ")\n",
        "etr"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>dff</th>\n",
              "      <th>event_number</th>\n",
              "      <th>event_time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-3.00</td>\n",
              "      <td>-0.032935</td>\n",
              "      <td>0</td>\n",
              "      <td>426.585248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-2.98</td>\n",
              "      <td>-0.017502</td>\n",
              "      <td>0</td>\n",
              "      <td>426.585248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-2.96</td>\n",
              "      <td>0.005773</td>\n",
              "      <td>0</td>\n",
              "      <td>426.585248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-2.94</td>\n",
              "      <td>0.029626</td>\n",
              "      <td>0</td>\n",
              "      <td>426.585248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-2.92</td>\n",
              "      <td>0.029960</td>\n",
              "      <td>0</td>\n",
              "      <td>426.585248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45145</th>\n",
              "      <td>2.92</td>\n",
              "      <td>0.010071</td>\n",
              "      <td>149</td>\n",
              "      <td>3723.291648</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45146</th>\n",
              "      <td>2.94</td>\n",
              "      <td>-0.000067</td>\n",
              "      <td>149</td>\n",
              "      <td>3723.291648</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45147</th>\n",
              "      <td>2.96</td>\n",
              "      <td>-0.034162</td>\n",
              "      <td>149</td>\n",
              "      <td>3723.291648</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45148</th>\n",
              "      <td>2.98</td>\n",
              "      <td>-0.047786</td>\n",
              "      <td>149</td>\n",
              "      <td>3723.291648</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45149</th>\n",
              "      <td>3.00</td>\n",
              "      <td>-0.047786</td>\n",
              "      <td>149</td>\n",
              "      <td>3723.291648</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>45150 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       time       dff  event_number   event_time\n",
              "0     -3.00 -0.032935             0   426.585248\n",
              "1     -2.98 -0.017502             0   426.585248\n",
              "2     -2.96  0.005773             0   426.585248\n",
              "3     -2.94  0.029626             0   426.585248\n",
              "4     -2.92  0.029960             0   426.585248\n",
              "...     ...       ...           ...          ...\n",
              "45145  2.92  0.010071           149  3723.291648\n",
              "45146  2.94 -0.000067           149  3723.291648\n",
              "45147  2.96 -0.034162           149  3723.291648\n",
              "45148  2.98 -0.047786           149  3723.291648\n",
              "45149  3.00 -0.047786           149  3723.291648\n",
              "\n",
              "[45150 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "25Q8vBriVbBV",
        "outputId": "6539851c-022f-405b-8099-93fdec0ed543"
      },
      "source": [
        "sns.lineplot(\n",
        "    data=etr,\n",
        "    x='time',\n",
        "    y='dff',\n",
        "    n_boot=500\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe1bddd0890>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gegKvUsEVfHS"
      },
      "source": [
        "def make_event_triggered_plot_modified(df, x, y, events_times, ax, t_before=3, t_after=3):\n",
        "    etr = mindscope_utilities.event_triggered_response(\n",
        "        data = df,\n",
        "        t = 'timestamps',\n",
        "        y = y,\n",
        "        event_times = events_times,\n",
        "        t_before=t_before,\n",
        "        t_after=t_before,\n",
        "        output_sampling_rate = 50,\n",
        "    )\n",
        "    sns.lineplot(\n",
        "        data=etr,\n",
        "        x=x,\n",
        "        y=y,\n",
        "        n_boot=500,\n",
        "        ax=ax\n",
        "    )"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "aZl7mxjqV7WD",
        "outputId": "dbcce29d-e7ae-4b03-8d21-16669aae7808"
      },
      "source": [
        "np.random.seed(2)\n",
        "fig, ax = plt.subplots()\n",
        "for cell_id in tqdm(np.random.choice(cell_ids, size=10, replace=False)):\n",
        "    \n",
        "    make_event_triggered_plot_modified(\n",
        "        df = neural_data.query('cell_specimen_id == @cell_id'), \n",
        "        x = 'time', \n",
        "        y = 'dff', \n",
        "        events_times = hit_change_time, \n",
        "        ax=ax\n",
        "    )"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 10/10 [00:43<00:00,  4.39s/it]\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "XDaI0u1dWCSY",
        "outputId": "8a3305fb-df56-417f-aecf-a0cc873940c7"
      },
      "source": [
        "np.random.seed(2)\n",
        "fig, ax = plt.subplots()\n",
        "for cell_id in tqdm(np.random.choice(cell_ids, size=10, replace=False)):\n",
        "    \n",
        "    make_event_triggered_plot_modified(\n",
        "        df = neural_data.query('cell_specimen_id == @cell_id'), \n",
        "        x = 'time', \n",
        "        y = 'dff', \n",
        "        events_times = cor_rej_change_time, \n",
        "        ax=ax\n",
        "    )"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 10/10 [00:38<00:00,  3.84s/it]\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "E4tRZjtMc9pR",
        "outputId": "092d1374-085b-4113-ac15-8849d5b39c51"
      },
      "source": [
        "etr"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>dff</th>\n",
              "      <th>event_number</th>\n",
              "      <th>event_time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-3.00</td>\n",
              "      <td>-0.032935</td>\n",
              "      <td>0</td>\n",
              "      <td>426.585248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-2.98</td>\n",
              "      <td>-0.017502</td>\n",
              "      <td>0</td>\n",
              "      <td>426.585248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-2.96</td>\n",
              "      <td>0.005773</td>\n",
              "      <td>0</td>\n",
              "      <td>426.585248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-2.94</td>\n",
              "      <td>0.029626</td>\n",
              "      <td>0</td>\n",
              "      <td>426.585248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-2.92</td>\n",
              "      <td>0.029960</td>\n",
              "      <td>0</td>\n",
              "      <td>426.585248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45145</th>\n",
              "      <td>2.92</td>\n",
              "      <td>0.010071</td>\n",
              "      <td>149</td>\n",
              "      <td>3723.291648</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45146</th>\n",
              "      <td>2.94</td>\n",
              "      <td>-0.000067</td>\n",
              "      <td>149</td>\n",
              "      <td>3723.291648</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45147</th>\n",
              "      <td>2.96</td>\n",
              "      <td>-0.034162</td>\n",
              "      <td>149</td>\n",
              "      <td>3723.291648</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45148</th>\n",
              "      <td>2.98</td>\n",
              "      <td>-0.047786</td>\n",
              "      <td>149</td>\n",
              "      <td>3723.291648</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45149</th>\n",
              "      <td>3.00</td>\n",
              "      <td>-0.047786</td>\n",
              "      <td>149</td>\n",
              "      <td>3723.291648</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>45150 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       time       dff  event_number   event_time\n",
              "0     -3.00 -0.032935             0   426.585248\n",
              "1     -2.98 -0.017502             0   426.585248\n",
              "2     -2.96  0.005773             0   426.585248\n",
              "3     -2.94  0.029626             0   426.585248\n",
              "4     -2.92  0.029960             0   426.585248\n",
              "...     ...       ...           ...          ...\n",
              "45145  2.92  0.010071           149  3723.291648\n",
              "45146  2.94 -0.000067           149  3723.291648\n",
              "45147  2.96 -0.034162           149  3723.291648\n",
              "45148  2.98 -0.047786           149  3723.291648\n",
              "45149  3.00 -0.047786           149  3723.291648\n",
              "\n",
              "[45150 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2Z7UYP4NeFOh",
        "outputId": "8510be98-8b83-4b2f-a791-9f6e90fd2df7"
      },
      "source": [
        "example_row = etr.groupby(['time'])['dff'].mean().reset_index()['dff']\n",
        "len_row = example_row.shape[0]\n",
        "len_row"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "301"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DQCpvDFkeShr",
        "outputId": "0bc378cc-936b-4b63-eef9-1716bf010e89"
      },
      "source": [
        "#X[n,t,s,d] \n",
        "tensor = np.zeros((cell_ids.shape[0],len_row,2,2))\n",
        "i = 0\n",
        "for cell_id in tqdm(cell_ids):\n",
        "  etr11 = mindscope_utilities.event_triggered_response(\n",
        "    data = neural_data.query('cell_specimen_id == @cell_id'),\n",
        "    t = 'timestamps',\n",
        "    y = 'dff',\n",
        "    event_times = hit_change_time,\n",
        "    t_before=3,\n",
        "    t_after=3,\n",
        "    output_sampling_rate = 50,\n",
        "  ).groupby(['time'])['dff'].mean().reset_index()['dff']\n",
        "  etr10 = mindscope_utilities.event_triggered_response(\n",
        "    data = neural_data.query('cell_specimen_id == @cell_id'),\n",
        "    t = 'timestamps',\n",
        "    y = 'dff',\n",
        "    event_times = miss_change_time,\n",
        "    t_before=3,\n",
        "    t_after=3,\n",
        "    output_sampling_rate = 50,\n",
        "  ).groupby(['time'])['dff'].mean().reset_index()['dff']\n",
        "  etr00 = mindscope_utilities.event_triggered_response(\n",
        "    data = neural_data.query('cell_specimen_id == @cell_id'),\n",
        "    t = 'timestamps',\n",
        "    y = 'dff',\n",
        "    event_times = cor_rej_change_time,\n",
        "    t_before=3,\n",
        "    t_after=3,\n",
        "    output_sampling_rate = 50,\n",
        "  ).groupby(['time'])['dff'].mean().reset_index()['dff']\n",
        "  etr01 = mindscope_utilities.event_triggered_response(\n",
        "    data = neural_data.query('cell_specimen_id == @cell_id'),\n",
        "    t = 'timestamps',\n",
        "    y = 'dff',\n",
        "    event_times = false_ala_hit_change_time,\n",
        "    t_before=3,\n",
        "    t_after=3,\n",
        "    output_sampling_rate = 50,\n",
        "  ).groupby(['time'])['dff'].mean().reset_index()['dff']\n",
        "  #print(etr10)\n",
        "  #print(etr01)\n",
        "  #print(etr00)\n",
        "  #print(etr11)\n",
        "  tensor[i,:,0,0] = etr11\n",
        "  tensor[i,:,0,1] = etr10\n",
        "  tensor[i,:,1,0] = etr01\n",
        "  tensor[i,:,1,1] = etr00\n",
        "  i+=1\n",
        "\n",
        "\n",
        "  \n",
        "    "
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 85/85 [01:11<00:00,  1.18it/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I92qd9DNjONY"
      },
      "source": [
        "tensor = (tensor-np.mean(tensor,axis=1,keepdims=True))"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PPdzojQzmyTy"
      },
      "source": [
        "dpca = dPCA.dPCA(labels='tsd',regularizer=None)\n",
        "dpca.protect = ['t']\n",
        "#dpca.n_trials = 4"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yPWkK3Ezh7zm"
      },
      "source": [
        "Z = dpca.fit_transform(tensor)"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "id": "ydVJT_kGl6xK",
        "outputId": "f45494a9-f155-47d1-85af-dd245e30e88b"
      },
      "source": [
        "time = np.arange(301)\n",
        "\n",
        "plt.figure(figsize=(16,7))\n",
        "plt.subplot(131)\n",
        "S=2\n",
        "\n",
        "plt.plot(time,Z['t'][0,:,0,0], label='s=0')\n",
        "plt.plot(time,Z['t'][0,:,1,0], label='s = 1')\n",
        "\n",
        "plt.title('1st time component')\n",
        "    \n",
        "plt.subplot(132)\n",
        "\n",
        "\n",
        "plt.plot(time,Z['s'][0,:,0,0], label='0')\n",
        "plt.plot(time,Z['s'][0,:,1,0], label='1')\n",
        "\n",
        "plt.title('1st stimulus component')\n",
        "    \n",
        "plt.subplot(133)\n",
        "\n",
        "\n",
        "plt.plot(time,Z['td'][0,:,0,0], label='s=0')\n",
        "plt.plot(time,Z['td'][0,:,1,0], label='s=1')\n",
        "\n",
        "    \n",
        "plt.title('1st decision component')\n",
        "plt.legend(loc=\"upper left\")\n",
        "plt.show()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x504 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}