117 lines
2.9 KiB
Plaintext
117 lines
2.9 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import os\n",
|
|
"import pandas as pd\n",
|
|
"import wget\n",
|
|
"import ssl\n",
|
|
"ssl._create_default_https_context = ssl._create_unverified_context"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"SERVER = \"https://www.perceptualui.org/files/schweigert19_muc/\""
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"if (False):\n",
|
|
" sorted(data_files)\n",
|
|
" data_files = [\"DataStudyCollection/%s\" % file for file in os.listdir(\"DataStudyCollection\") if file.endswith(\".csv\") and \"userData\" or \"studyData\" in file]\n",
|
|
" with open('DataStudyCollection/files.txt', 'w') as filehandle:\n",
|
|
" for listitem in data_files:\n",
|
|
" filehandle.write('%s\\n' % listitem)\n",
|
|
"\n",
|
|
"\n",
|
|
" sorted(data_files)\n",
|
|
" data_files = [\"DataStudyEvaluation/%s\" % file for file in os.listdir(\"DataStudyEvaluation\") if file.endswith(\".csv\") and \"userData\" or \"studyData\" in file]\n",
|
|
" with open('DataStudyEvaluation/files.txt', 'w') as filehandle:\n",
|
|
" for listitem in data_files:\n",
|
|
" filehandle.write('%s\\n' % listitem)\n",
|
|
" \n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"df = pd.read_csv('DataStudyCollection/files.txt', header=None)\n",
|
|
"df.columns = [\"File\"]\n",
|
|
"df.File = df.File.apply(lambda x: SERVER + x)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"scrolled": true
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"for i, e in df.iterrows():\n",
|
|
" print(e.File)\n",
|
|
" wget.download(e.File, out=\"DataStudyCollection/\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"df = pd.read_csv('DataStudyEvaluation/files.txt', header=None)\n",
|
|
"df.columns = [\"File\"]\n",
|
|
"df.File = df.File.apply(lambda x: SERVER + x)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"for i, e in df.iterrows():\n",
|
|
" print(e.File)\n",
|
|
" wget.download(e.File, out=\"DataStudyEvaluation/\")"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.7.3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|