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| a | b/notebooks/Deep_EEG_Muse.ipynb | ||
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| 1 | { |
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| 2 | "nbformat": 4, |
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| 3 | "nbformat_minor": 0, |
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| 4 | "metadata": { |
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| 5 | "colab": { |
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| 6 | "name": "Deep_EEG_Muse.ipynb", |
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| 7 | "provenance": [], |
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| 8 | "collapsed_sections": [], |
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| 9 | "toc_visible": true, |
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| 10 | "include_colab_link": true |
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| 11 | }, |
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| 12 | "kernelspec": { |
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| 13 | "name": "python3", |
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| 14 | "display_name": "Python 3" |
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| 15 | }, |
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| 16 | "accelerator": "GPU" |
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| 17 | }, |
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| 18 | "cells": [ |
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| 19 | { |
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| 20 | "cell_type": "markdown", |
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| 21 | "metadata": { |
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| 22 | "id": "view-in-github", |
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| 23 | "colab_type": "text" |
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| 24 | }, |
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| 25 | "source": [ |
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| 26 | "<a href=\"https://colab.research.google.com/github/kylemath/DeepEEG/blob/master/notebooks/Deep_EEG_Muse.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" |
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| 27 | ] |
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| 28 | }, |
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| 29 | { |
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| 30 | "cell_type": "markdown", |
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| 31 | "metadata": { |
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| 32 | "id": "cH7KRd8ZZPMd", |
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| 33 | "colab_type": "text" |
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| 34 | }, |
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| 35 | "source": [ |
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| 36 | "## DeepEEG\n" |
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| 37 | ] |
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| 38 | }, |
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| 39 | { |
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| 40 | "cell_type": "code", |
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| 41 | "metadata": { |
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| 42 | "id": "KjZu4dFMFHJV", |
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| 43 | "colab_type": "code", |
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| 44 | "colab": { |
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| 45 | "base_uri": "https://localhost:8080/", |
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| 46 | "height": 734 |
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| 47 | }, |
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| 48 | "outputId": "c6c06cec-2bcb-49b4-ddae-32e16b5da89d" |
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| 49 | }, |
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| 50 | "source": [ |
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| 51 | "!git clone https://github.com/kylemath/DeepEEG\n", |
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| 52 | "!chmod +x ./DeepEEG/install.sh\n", |
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| 53 | "%cd DeepEEG\n", |
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| 54 | "!./install.sh\n", |
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| 55 | "from utils import *\n", |
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| 56 | "%matplotlib inline" |
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| 57 | ], |
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| 58 | "execution_count": 3, |
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| 59 | "outputs": [ |
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| 60 | { |
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| 61 | "output_type": "stream", |
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| 62 | "text": [ |
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| 63 | "Cloning into 'DeepEEG'...\n", |
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| 64 | "remote: Enumerating objects: 13, done.\u001b[K\n", |
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| 65 | "remote: Counting objects: 100% (13/13), done.\u001b[K\n", |
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| 66 | "remote: Compressing objects: 100% (12/12), done.\u001b[K\n", |
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| 67 | "remote: Total 947 (delta 2), reused 5 (delta 1), pack-reused 934\u001b[K\n", |
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| 68 | "Receiving objects: 100% (947/947), 19.62 MiB | 8.43 MiB/s, done.\n", |
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| 69 | "Resolving deltas: 100% (489/489), done.\n", |
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| 70 | "/content/DeepEEG/DeepEEG\n", |
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| 71 | "Requirement already up-to-date: pip in /usr/local/lib/python3.6/dist-packages (20.2.2)\n", |
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| 72 | "Requirement already satisfied: absl-py==0.7.0 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 1)) (0.7.0)\n", |
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| 73 | "Requirement already satisfied: astor==0.7.1 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 2)) (0.7.1)\n", |
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| 74 | "Requirement already satisfied: cycler==0.10.0 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 3)) (0.10.0)\n", |
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| 75 | "Requirement already satisfied: gast==0.2.2 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 4)) (0.2.2)\n", |
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| 76 | "Requirement already satisfied: grpcio==1.18.0 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 5)) (1.18.0)\n", |
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| 77 | "Requirement already satisfied: h5py==2.9.0 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 6)) (2.9.0)\n", |
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| 78 | "Requirement already satisfied: Keras==2.2.4 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 7)) (2.2.4)\n", |
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| 79 | "Requirement already satisfied: Keras-Applications==1.0.7 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 8)) (1.0.7)\n", |
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| 80 | "Requirement already satisfied: Keras-Preprocessing==1.0.9 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 9)) (1.0.9)\n", |
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| 81 | "Requirement already satisfied: kiwisolver==1.0.1 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 10)) (1.0.1)\n", |
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| 82 | "Requirement already satisfied: Markdown==3.0.1 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 11)) (3.0.1)\n", |
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| 83 | "Requirement already satisfied: matplotlib==3.0.2 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 12)) (3.0.2)\n", |
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| 84 | "Requirement already satisfied: mne==0.17.0 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 13)) (0.17.0)\n", |
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| 85 | "Requirement already satisfied: numpy==1.16.1 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 14)) (1.16.1)\n", |
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| 86 | "Requirement already satisfied: pandas==0.24.1 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 15)) (0.24.1)\n", |
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| 87 | "Requirement already satisfied: protobuf==3.6.1 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 16)) (3.6.1)\n", |
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| 88 | "Requirement already satisfied: pyparsing==2.3.1 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 17)) (2.3.1)\n", |
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| 89 | "Requirement already satisfied: python-dateutil==2.8.0 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 18)) (2.8.0)\n", |
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| 90 | "Requirement already satisfied: pytz==2018.9 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 19)) (2018.9)\n", |
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| 91 | "Requirement already satisfied: PyYAML==4.2b1 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 20)) (4.2b1)\n", |
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| 92 | "Requirement already satisfied: scikit-learn==0.20.2 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 21)) (0.20.2)\n", |
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| 93 | "Requirement already satisfied: scipy==1.2.0 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 22)) (1.2.0)\n", |
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| 94 | "Requirement already satisfied: six==1.12.0 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 23)) (1.12.0)\n", |
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| 95 | "Requirement already satisfied: sklearn==0.0 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 24)) (0.0)\n", |
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| 96 | "Requirement already satisfied: tensorboard==1.12.2 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 25)) (1.12.2)\n", |
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| 97 | "Requirement already satisfied: tensorflow==1.13.0rc1 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 26)) (1.13.0rc1)\n", |
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| 98 | "Requirement already satisfied: termcolor==1.1.0 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 27)) (1.1.0)\n", |
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| 99 | "Requirement already satisfied: Werkzeug==0.14.1 in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 28)) (0.14.1)\n", |
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| 100 | "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from kiwisolver==1.0.1->-r requirements.txt (line 10)) (49.6.0)\n", |
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| 101 | "Requirement already satisfied: wheel>=0.26; python_version >= \"3\" in /usr/local/lib/python3.6/dist-packages (from tensorboard==1.12.2->-r requirements.txt (line 25)) (0.35.1)\n", |
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| 102 | "Requirement already satisfied: tensorflow-estimator<1.14.0rc0,>=1.13.0rc0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.13.0rc1->-r requirements.txt (line 26)) (1.13.0)\n", |
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| 103 | "Requirement already satisfied: mock>=2.0.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-estimator<1.14.0rc0,>=1.13.0rc0->tensorflow==1.13.0rc1->-r requirements.txt (line 26)) (4.0.2)\n" |
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| 104 | ], |
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| 105 | "name": "stdout" |
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| 106 | } |
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| 107 | ] |
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| 108 | }, |
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| 109 | { |
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| 110 | "cell_type": "markdown", |
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| 111 | "metadata": { |
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| 112 | "id": "FhkDPfIq1ewa", |
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| 113 | "colab_type": "text" |
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| 114 | }, |
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| 115 | "source": [ |
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| 116 | "#Load Data, Concatenate\n" |
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| 117 | ] |
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| 118 | }, |
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| 119 | { |
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| 120 | "cell_type": "code", |
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| 121 | "metadata": { |
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| 122 | "id": "jhU8hlcg1e6T", |
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| 123 | "colab_type": "code", |
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| 124 | "colab": { |
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| 125 | "base_uri": "https://localhost:8080/", |
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| 126 | "height": 1000 |
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| 127 | }, |
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| 128 | "outputId": "f5548962-7f6e-4dbb-83f4-618cf9c36f49" |
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| 129 | }, |
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| 130 | "source": [ |
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| 131 | "!git clone https://github.com/kylemath/eeg-notebooks_v0.1/\n", |
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| 132 | "data_dir = 'visual/cueing'\n", |
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| 133 | "\n", |
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| 134 | "subs = [101, 102, 103, 104, 105, 106, 108, 109, 110, 111, 112,\n", |
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| 135 | " 202, 203, 204, 205, 207, 208, 209, 210, 211,\n", |
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| 136 | " 301, 302, 303, 304, 305, 306, 307, 308, 309,\n", |
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| 137 | " 1101, 1102, 1103, 1104, 1105, 1106, 1108, 1109, 1110,\n", |
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| 138 | " 1202, 1203, 1205, 1206, 1209, 1210, 1211, 1215,\n", |
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| 139 | " 1301, 1302, 1313, \n", |
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| 140 | " 1401, 1402, 1403, 1404, 1405, 1408, 1410, 1411, 1412, 1413, 1413, 1414, 1415, 1416]\n", |
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| 141 | "\n", |
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| 142 | "nsesh = 2\n", |
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| 143 | "event_id = {'LeftCue':1, 'RightCue':2}\n", |
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| 144 | "\n", |
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| 145 | "raw = LoadMuseData(subs,nsesh,data_dir)\n", |
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| 146 | "\n", |
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| 147 | "#subs = [ 1]\n", |
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| 148 | "#nsesh = 1\n", |
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| 149 | "#data_dir = 'visual/P300'\n", |
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| 150 | "#event_names = ['Standard','Target']\n", |
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| 151 | "\n", |
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| 152 | "#subs = [ 4]\n", |
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| 153 | "#nsesh = 1\n", |
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| 154 | "#data_dir = 'visual/SSVEP'\n", |
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| 155 | "#event_names = ['f30Hz','f20Hz']" |
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| 156 | ], |
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| 157 | "execution_count": 4, |
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| 158 | "outputs": [ |
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| 159 | { |
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| 160 | "output_type": "stream", |
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| 161 | "text": [ |
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| 162 | "Cloning into 'eeg-notebooks_v0.1'...\n", |
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| 163 | "remote: Enumerating objects: 2451, done.\u001b[K\n", |
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| 164 | "remote: Total 2451 (delta 0), reused 0 (delta 0), pack-reused 2451\u001b[K\n", |
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| 165 | "Receiving objects: 100% (2451/2451), 166.74 MiB | 12.34 MiB/s, done.\n", |
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| 166 | "Resolving deltas: 100% (1096/1096), done.\n", |
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| 167 | "Checking out files: 100% (632/632), done.\n", |
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| 168 | "Loading Data\n", |
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| 355 | " Session number 1/2\n", |
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| 356 | "No files for subject with filename []\n", |
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| 365 | " Session number 1/2\n", |
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| 369 | "Subject number 41/63\n", |
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| 370 | " Session number 1/2\n", |
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| 375 | " Session number 1/2\n", |
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| 379 | "Subject number 43/63\n", |
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| 380 | " Session number 1/2\n", |
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| 381 | "No files for subject with filename []\n", |
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| 384 | "Subject number 44/63\n", |
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| 385 | " Session number 1/2\n", |
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| 386 | "No files for subject with filename []\n", |
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| 390 | " Session number 1/2\n", |
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| 405 | " Session number 1/2\n", |
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| 410 | " Session number 1/2\n", |
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| 419 | "Subject number 51/63\n", |
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| 420 | " Session number 1/2\n", |
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| 424 | "Subject number 52/63\n", |
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| 425 | " Session number 1/2\n", |
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| 429 | "Subject number 53/63\n", |
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| 430 | " Session number 1/2\n", |
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| 432 | " Session number 2/2\n", |
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| 434 | "Subject number 54/63\n", |
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| 435 | " Session number 1/2\n", |
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| 436 | "No files for subject with filename []\n", |
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| 437 | " Session number 2/2\n", |
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| 438 | "No files for subject with filename []\n", |
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| 439 | "Subject number 55/63\n", |
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| 440 | " Session number 1/2\n", |
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| 441 | "No files for subject with filename []\n", |
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| 443 | "No files for subject with filename []\n", |
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| 444 | "Subject number 56/63\n", |
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| 445 | " Session number 1/2\n", |
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| 446 | "No files for subject with filename []\n", |
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| 447 | " Session number 2/2\n", |
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| 448 | "No files for subject with filename []\n", |
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| 449 | "Subject number 57/63\n", |
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| 450 | " Session number 1/2\n", |
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| 451 | "No files for subject with filename []\n", |
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| 452 | " Session number 2/2\n", |
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| 453 | "No files for subject with filename []\n", |
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| 454 | "Subject number 58/63\n", |
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| 455 | " Session number 1/2\n", |
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| 456 | "No files for subject with filename []\n", |
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| 457 | " Session number 2/2\n", |
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| 458 | "No files for subject with filename []\n", |
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| 459 | "Subject number 59/63\n", |
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| 460 | " Session number 1/2\n", |
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| 461 | "No files for subject with filename []\n", |
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| 462 | " Session number 2/2\n", |
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| 463 | "No files for subject with filename []\n", |
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| 464 | "Subject number 60/63\n", |
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| 465 | " Session number 1/2\n", |
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| 466 | "No files for subject with filename []\n", |
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| 467 | " Session number 2/2\n", |
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| 468 | "No files for subject with filename []\n", |
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| 469 | "Subject number 61/63\n", |
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| 470 | " Session number 1/2\n", |
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| 471 | "No files for subject with filename []\n", |
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| 472 | " Session number 2/2\n", |
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| 473 | "No files for subject with filename []\n", |
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| 474 | "Subject number 62/63\n", |
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| 475 | " Session number 1/2\n", |
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| 476 | "No files for subject with filename []\n", |
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| 477 | " Session number 2/2\n", |
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| 478 | "No files for subject with filename []\n", |
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| 479 | "Subject number 63/63\n", |
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| 480 | " Session number 1/2\n", |
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| 481 | "No files for subject with filename []\n", |
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| 482 | " Session number 2/2\n", |
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| 483 | "No files for subject with filename []\n" |
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| 484 | ], |
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| 485 | "name": "stdout" |
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| 486 | }, |
||
| 487 | { |
||
| 488 | "output_type": "error", |
||
| 489 | "ename": "TypeError", |
||
| 490 | "evalue": "ignored", |
||
| 491 | "traceback": [ |
||
| 492 | "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", |
||
| 493 | "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", |
||
| 494 | "\u001b[0;32m<ipython-input-4-6099eec806a7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0mevent_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m'LeftCue'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'RightCue'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m \u001b[0mraw\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLoadMuseData\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mnsesh\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdata_dir\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[0;31m#subs = [ 1]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", |
||
| 495 | "\u001b[0;32m/content/DeepEEG/utils.py\u001b[0m in \u001b[0;36mLoadMuseData\u001b[0;34m(subs, nsesh, data_dir, load_verbose, sfreq)\u001b[0m\n\u001b[1;32m 106\u001b[0m raw.append(muse_load_data(data_dir, sfreq=sfreq ,subject_nb=sub,\n\u001b[1;32m 107\u001b[0m session_nb=isesh+1,verbose=load_verbose))\n\u001b[0;32m--> 108\u001b[0;31m \u001b[0mraw\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconcatenate_raws\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mraw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 109\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mraw\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 110\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", |
||
| 496 | "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/mne/io/base.py\u001b[0m in \u001b[0;36mconcatenate_raws\u001b[0;34m(raws, preload, events_list, verbose)\u001b[0m\n", |
||
| 497 | "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/mne/utils.py\u001b[0m in \u001b[0;36mverbose\u001b[0;34m(function, *args, **kwargs)\u001b[0m\n\u001b[1;32m 950\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0muse_log_level\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mverbose_level\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 951\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mfunction\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\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;32m--> 952\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunction\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\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[0m\u001b[1;32m 953\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 954\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", |
||
| 498 | "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/mne/io/base.py\u001b[0m in \u001b[0;36mconcatenate_raws\u001b[0;34m(raws, preload, events_list, verbose)\u001b[0m\n\u001b[1;32m 2635\u001b[0m \u001b[0mfirst\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlast\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfirst_samp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlast_samp\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mr\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mraws\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2636\u001b[0m \u001b[0mevents\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconcatenate_events\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mevents_list\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfirst\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlast\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2637\u001b[0;31m \u001b[0mraws\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mraws\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpreload\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2638\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2639\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mevents_list\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", |
||
| 499 | "\u001b[0;31mTypeError\u001b[0m: append() takes exactly one argument (2 given)" |
||
| 500 | ] |
||
| 501 | } |
||
| 502 | ] |
||
| 503 | }, |
||
| 504 | { |
||
| 505 | "cell_type": "markdown", |
||
| 506 | "metadata": { |
||
| 507 | "id": "oEd72sIHuiFc", |
||
| 508 | "colab_type": "text" |
||
| 509 | }, |
||
| 510 | "source": [ |
||
| 511 | "#Run Preprocessing\n", |
||
| 512 | "\n", |
||
| 513 | "**Input: mne.raw, event_id**\n", |
||
| 514 | "\n", |
||
| 515 | "**Output: mne.epochs**\n", |
||
| 516 | "```python\n", |
||
| 517 | "plot_psd=False\n", |
||
| 518 | "filter_data=True\n", |
||
| 519 | "eeg_filter_highpass=1\n", |
||
| 520 | "plot_events=False\n", |
||
| 521 | "epoch_time=(-.2,1)\n", |
||
| 522 | "baseline=(-.2,0)\n", |
||
| 523 | "rej_thresh_uV=200\n", |
||
| 524 | "rereference=False\n", |
||
| 525 | "emcp_raw=False\n", |
||
| 526 | "emcp_epochs=False\n", |
||
| 527 | "epoch_decim=1\n", |
||
| 528 | "plot_electrodes=False\n", |
||
| 529 | "plot_erp=False\n", |
||
| 530 | "```" |
||
| 531 | ] |
||
| 532 | }, |
||
| 533 | { |
||
| 534 | "cell_type": "code", |
||
| 535 | "metadata": { |
||
| 536 | "id": "3HiHs8CluhjP", |
||
| 537 | "colab_type": "code", |
||
| 538 | "colab": { |
||
| 539 | "base_uri": "https://localhost:8080/", |
||
| 540 | "height": 85 |
||
| 541 | }, |
||
| 542 | "outputId": "70c40caf-689c-4f7e-868d-7b94affceeb7" |
||
| 543 | }, |
||
| 544 | "source": [ |
||
| 545 | "epochs = PreProcess(raw,event_id)\n" |
||
| 546 | ], |
||
| 547 | "execution_count": null, |
||
| 548 | "outputs": [ |
||
| 549 | { |
||
| 550 | "output_type": "stream", |
||
| 551 | "text": [ |
||
| 552 | "Filtering Data Between 1 and 30 Hz.\n", |
||
| 553 | "4583 events found\n", |
||
| 554 | "Event IDs: [ 1 2 11 12 21 22]\n", |
||
| 555 | "Remaining Trials: 1408\n" |
||
| 556 | ], |
||
| 557 | "name": "stdout" |
||
| 558 | } |
||
| 559 | ] |
||
| 560 | }, |
||
| 561 | { |
||
| 562 | "cell_type": "markdown", |
||
| 563 | "metadata": { |
||
| 564 | "id": "pwqD_voiDypa", |
||
| 565 | "colab_type": "text" |
||
| 566 | }, |
||
| 567 | "source": [ |
||
| 568 | "#Run FeatureEngineer\n", |
||
| 569 | "**Input: mne.epochs**\n", |
||
| 570 | "\n", |
||
| 571 | "**Output: deepeeg.feats**\n", |
||
| 572 | "```python\n", |
||
| 573 | "model_type='NN'\n", |
||
| 574 | "frequency_domain=False\n", |
||
| 575 | "normalization=True\n", |
||
| 576 | "electrode_median=False\n", |
||
| 577 | "wavelet_decim=1\n", |
||
| 578 | "flims=(3,30)\n", |
||
| 579 | "f_bins=20\n", |
||
| 580 | "wave_cycles=3\n", |
||
| 581 | "spect_baseline=[-1,-.5]\n", |
||
| 582 | "electrodes_out=[11,12,13,14,15]\n", |
||
| 583 | "test_split = 0.2\n", |
||
| 584 | "val_split = 0.2\n", |
||
| 585 | "random_seed=1017\n", |
||
| 586 | "watermark = False\n", |
||
| 587 | "```" |
||
| 588 | ] |
||
| 589 | }, |
||
| 590 | { |
||
| 591 | "cell_type": "code", |
||
| 592 | "metadata": { |
||
| 593 | "id": "i_jYlTW1A6sb", |
||
| 594 | "colab_type": "code", |
||
| 595 | "colab": { |
||
| 596 | "base_uri": "https://localhost:8080/", |
||
| 597 | "height": 221 |
||
| 598 | }, |
||
| 599 | "outputId": "4a93d84c-7ea9-45a9-d312-f801fb29fcb1" |
||
| 600 | }, |
||
| 601 | "source": [ |
||
| 602 | "feats = FeatureEngineer(epochs,model_type='NN')" |
||
| 603 | ], |
||
| 604 | "execution_count": null, |
||
| 605 | "outputs": [ |
||
| 606 | { |
||
| 607 | "output_type": "stream", |
||
| 608 | "text": [ |
||
| 609 | "Constructing Time Domain Features\n", |
||
| 610 | "Normalizing X\n", |
||
| 611 | "Combined X Shape: (1408, 256, 4)\n", |
||
| 612 | "Combined Y Shape: (1408,)\n", |
||
| 613 | "Y Example (should be 1s & 0s): [1 1 0 0 0 0 0 1 0 0]\n", |
||
| 614 | "X Range: -12.106191:9.781672\n", |
||
| 615 | "Input Shape: (256, 4)\n", |
||
| 616 | "x_train shape: (844, 256, 4)\n", |
||
| 617 | "844 train samples\n", |
||
| 618 | "282 test samples\n", |
||
| 619 | "282 validation samples\n", |
||
| 620 | "Class Weights: [0.97011494 1.03178484]\n" |
||
| 621 | ], |
||
| 622 | "name": "stdout" |
||
| 623 | } |
||
| 624 | ] |
||
| 625 | }, |
||
| 626 | { |
||
| 627 | "cell_type": "markdown", |
||
| 628 | "metadata": { |
||
| 629 | "id": "9ChMvr-jKp8P", |
||
| 630 | "colab_type": "text" |
||
| 631 | }, |
||
| 632 | "source": [ |
||
| 633 | "# Run CreateModel\n", |
||
| 634 | "\n", |
||
| 635 | "**Input: deepeeg.feats**\n", |
||
| 636 | "\n", |
||
| 637 | "**Output: deepeeg.model, deepeeg.encoder**\n", |
||
| 638 | "\n", |
||
| 639 | "```python\n", |
||
| 640 | "units=[16,8,4,8,16]\n", |
||
| 641 | "dropout=.25\n", |
||
| 642 | "batch_norm=True\n", |
||
| 643 | "filt_size=3\n", |
||
| 644 | "pool_size=2\n", |
||
| 645 | "```" |
||
| 646 | ] |
||
| 647 | }, |
||
| 648 | { |
||
| 649 | "cell_type": "code", |
||
| 650 | "metadata": { |
||
| 651 | "id": "HFf3rBbJKqHR", |
||
| 652 | "colab_type": "code", |
||
| 653 | "colab": {} |
||
| 654 | }, |
||
| 655 | "source": [ |
||
| 656 | "model, _ = CreateModel(feats)" |
||
| 657 | ], |
||
| 658 | "execution_count": null, |
||
| 659 | "outputs": [] |
||
| 660 | }, |
||
| 661 | { |
||
| 662 | "cell_type": "markdown", |
||
| 663 | "metadata": { |
||
| 664 | "id": "-EKBjSapfE4O", |
||
| 665 | "colab_type": "text" |
||
| 666 | }, |
||
| 667 | "source": [ |
||
| 668 | "# TrainTestVal\n", |
||
| 669 | "\n", |
||
| 670 | "**Input: deepEEG.model, deepEEG.feats**\n", |
||
| 671 | "\n", |
||
| 672 | "```python\n", |
||
| 673 | "batch_size=2\n", |
||
| 674 | "train_epochs=20\n", |
||
| 675 | "show_plots=True\n", |
||
| 676 | "```" |
||
| 677 | ] |
||
| 678 | }, |
||
| 679 | { |
||
| 680 | "cell_type": "code", |
||
| 681 | "metadata": { |
||
| 682 | "id": "u6ize7eJfB3J", |
||
| 683 | "colab_type": "code", |
||
| 684 | "colab": {} |
||
| 685 | }, |
||
| 686 | "source": [ |
||
| 687 | "TrainTestVal(model, feats)" |
||
| 688 | ], |
||
| 689 | "execution_count": null, |
||
| 690 | "outputs": [] |
||
| 691 | } |
||
| 692 | ] |
||
| 693 | } |