From f231b8971199130deb14336ad45dc916ad95ef05 Mon Sep 17 00:00:00 2001
From: Elmo Chavez <50608494+sobieddch90@users.noreply.github.com>
Date: Thu, 13 Jul 2023 01:02:28 +0200
Subject: [PATCH] Storing EEG Datasets in Google Drive
---
EEG Dataset Exploration.ipynb | 5435 ++-------------------------------
1 file changed, 246 insertions(+), 5189 deletions(-)
diff --git a/EEG Dataset Exploration.ipynb b/EEG Dataset Exploration.ipynb
index 1aab3bb..91990cb 100644
--- a/EEG Dataset Exploration.ipynb
+++ b/EEG Dataset Exploration.ipynb
@@ -3,11 +3,11 @@
{
"cell_type": "markdown",
"metadata": {
- "colab_type": "text",
- "id": "view-in-github"
+ "id": "view-in-github",
+ "colab_type": "text"
},
"source": [
- "\n"
+ ""
]
},
{
@@ -97,5124 +97,183 @@
"- Pip: `pip install mne`\n",
"- Conda: `conda install -c conda-forge mne-base`\n",
"\n",
- "_Suggestion_: Create a new conda environment to install MNE\n",
- "\n",
- "**HMMLEARN**\\\n",
- "Is a set of algorithms for unsupervised learning and inference of Hidden Markov Models. For supervised learning learning of HMMs and similar models see seqlearn.\\\n",
- "https://hmmlearn.readthedocs.io/en/latest/index.html\n",
- "\n",
- "- Pip: `!pip install hmmlearn`\n",
- "- Conda: `conda install -c conda-forge hmmlearn`\n"
+ "_Suggestion_: Create a new conda environment to install MNE\n"
]
},
{
"cell_type": "code",
- "execution_count": 21,
- "metadata": {
- "id": "-BNnrwS7kMhA"
- },
- "outputs": [],
"source": [
- "import numpy as np\n",
- "import pandas as pd\n",
- "import matplotlib.pyplot as plt\n",
- "%matplotlib inline\n",
- "\n",
- "import openneuro as on\n",
- "import mne\n",
- "import os\n",
- "\n",
- "#from hmmlearn import hmm"
- ]
- },
- {
- "cell_type": "markdown",
+ "%%capture\n",
+ "!pip install openneuro-py\n",
+ "!pip install mne"
+ ],
"metadata": {
- "id": "zvw_ohHZhQEh"
+ "id": "g_sw4-jbRQ5b"
},
- "source": [
- "# Download Dataset\n",
- "\n",
- "Downloading the dataset directly from the website using openneuro package.\n",
- "\n",
- "**PD**: _running the download command may take several minutes to load and download all the datasets._\n"
- ]
+ "execution_count": 1,
+ "outputs": []
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 2,
"metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 257,
- "referenced_widgets": [
- "3d9501b78b4d4fe083ebbcf6763e56ea",
- "d2cad9f4d3bf45eeabbc125ad21f559d",
- "4c6a6c417b7e4b078e3069335809796e",
- "e49979f8b9364d58a544c39ce6dfaba2",
- "9e58b979ae6647c4a174bc469f179901",
- "a193d9437e81410190fb33cd60d2668a",
- "9649c2a38c194a9cb697d2681c29132e",
- "563df12e5ca848be95cd35fdbe05ba87",
- "7269fa0498b04970ba57753795ab5b44",
- "89fb9ba4cef148c69e79d84faa768cb1",
- "a59223247b2a4c4e9f14df230cd947b7"
- ]
- },
- "id": "58FZHqG0UCIh",
- "outputId": "d5300211-de37-4dd1-8596-c7fa6057c57d"
+ "id": "-BNnrwS7kMhA"
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\n",
- "👋 Hello! This is openneuro-py 2023.1.0. Great to see you! 🤗\n",
- "\n",
- " 👉 Please report problems 🤯 and bugs 🪲 at\n",
- " https://github.com/hoechenberger/openneuro-py/issues\n",
- "\n",
- "🌍 Preparing to download ds004504 …\n"
- ]
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "de1733cff7f54f8ea45ea3cd8116fd80",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "📁 Traversing directories for ds004504 : 0 entities [00:00, ? entities/s]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "📥 Retrieving up to 357 files (5 concurrent downloads). \n",
- "✅ Finished downloading ds004504.\n",
- " \n",
- "🧠 Please enjoy your brains.\n",
- " \n"
- ]
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "588e0494df064c2a89678e453c54999e",
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- },
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- ]
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- ]
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- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "a12ccda647284229ae5d88a8e6a9f072",
- "version_major": 2,
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- ]
- },
- "metadata": {},
- "output_type": "display_data"
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import pandas as pd\n",
+ "import matplotlib.pyplot as plt\n",
+ "%matplotlib inline\n",
+ "\n",
+ "import openneuro as on\n",
+ "import mne\n",
+ "import os\n",
+ "\n",
+ "#from hmmlearn import hmm"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "zvw_ohHZhQEh"
+ },
+ "source": [
+ "# Download Dataset\n",
+ "\n",
+ "Downloading the dataset directly from the website using openneuro package.\n",
+ "\n",
+ "**PD**: _running the download command may take several minutes to load and download all the datasets._\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 263,
+ "referenced_widgets": [
+ "701ef7ba353a4eb789c9d2f3a92fd0d2",
+ "a4a50615df5d48c0aea547d744499281",
+ "1493a05b34c246f1911c6b5e4e032413",
+ "ee038715dd604e75b12f650cf9856d54",
+ "aee7fddbfb9b42a688e5b389eac6be51",
+ "569c76f29c1e44fc8d7dc066d8ff79ca",
+ "50d6d520131a4ee188fdc92e87cd4624",
+ "7f498786b4e04a97a67cc97f2e9fc2bb",
+ "4c9b27d238d743d987f408bc1d73c1e6",
+ "6a995cb9232a4ee8a8de53cfd18e2a9f",
+ "38ebc5a4023b4642891e94568a92e5f7"
+ ]
},
+ "id": "58FZHqG0UCIh",
+ "outputId": "66bba051-98fa-4d90-c76f-c2ea3e9ef801"
+ },
+ "outputs": [
{
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "2b1715115c7e441a84a1817b58402297",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
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- ]
- },
- "metadata": {},
- "output_type": "display_data"
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\n",
+ "👋 Hello! This is openneuro-py 2023.1.0. Great to see you! 🤗\n",
+ "\n",
+ " 👉 Please report problems 🤯 and bugs 🪲 at\n",
+ " https://github.com/hoechenberger/openneuro-py/issues\n",
+ "\n",
+ "🌍 Preparing to download ds004504 …\n"
+ ]
},
{
+ "output_type": "display_data",
"data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "4046edec7ba8455aa84b0f8e104c5757",
- "version_major": 2,
- "version_minor": 0
- },
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- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
+ "📁 Traversing directories for ds004504 : 0 entities [00:00, ? entities/s]"
+ ],
"application/vnd.jupyter.widget-view+json": {
- "model_id": "acdcdc2bd9964a339f9557e98af4f453",
"version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
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- ]
+ "version_minor": 0,
+ "model_id": "701ef7ba353a4eb789c9d2f3a92fd0d2"
+ }
},
- "metadata": {},
- "output_type": "display_data"
+ "metadata": {}
},
{
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "a94b56ebbdd049f491b425f18682a9a5",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Skipping sub-088_task-eyesclosed_eeg.set: already downloaded.: 100%|##########| 30.3M/30.3M [00:00, ?B/s]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "📥 Retrieving up to 357 files (5 concurrent downloads). \n",
+ "✅ Finished downloading ds004504.\n",
+ " \n",
+ "🧠 Please enjoy your brains.\n",
+ " \n"
+ ]
}
],
"source": [
"# Run this code when use colab\n",
- "# !mkdir /content/dataset \n",
- "# output_dir = \"/content/dataset\"\n",
- "\n",
- "# Set direction to store the dataset\n",
- "output_dir = os.getcwd()+'/dataset'\n",
+ "!mkdir /content/dataset\n",
"\n",
+ "output_dir = \"/content/dataset\"\n",
"dataset_id = \"ds004504\"\n",
"\n",
"on.download(dataset=dataset_id, target_dir=output_dir)"
]
},
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Storing Dataset in Google Drive"
+ ],
+ "metadata": {
+ "id": "BI3ByryXSEpB"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from google.colab import drive\n",
+ "import shutil\n",
+ "\n",
+ "drive.mount('/content/drive')\n",
+ "\n",
+ "source_folder = '/content/dataset'\n",
+ "destination_folder = '/content/drive/MyDrive/EEG_Dataset/ds004504'\n",
+ "\n",
+ "shutil.copytree(source_folder, destination_folder)"
+ ],
+ "metadata": {
+ "id": "QI0zhVQgSJ5O",
+ "outputId": "b292603d-08d2-47d7-a634-c784d72bfabc",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 73
+ }
+ },
+ "execution_count": 7,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
+ ]
+ },
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "'/content/drive/MyDrive/EEG_Dataset/ds004504'"
+ ],
+ "application/vnd.google.colaboratory.intrinsic+json": {
+ "type": "string"
+ }
+ },
+ "metadata": {},
+ "execution_count": 7
+ }
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {
@@ -5247,7 +306,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -5368,7 +427,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
@@ -5439,7 +498,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -5489,7 +548,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -5530,7 +589,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -5571,7 +630,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -5618,7 +677,7 @@
},
{
"cell_type": "code",
- "execution_count": 24,
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