diff --git a/bstim-covid19-dash.ipynb b/bstim-covid19-dash.ipynb
index a84ced66141ba9c66a1b9c1c62205bb516642b00..5efdea48c8d5b16c796908f3dd26e7c36839f2fe 100644
--- a/bstim-covid19-dash.ipynb
+++ b/bstim-covid19-dash.ipynb
@@ -35,7 +35,7 @@
},
{
"cell_type": "code",
- "execution_count": 64,
+ "execution_count": 168,
"metadata": {},
"outputs": [],
"source": [
@@ -47,6 +47,7 @@
"import dash_player\n",
"from flask_caching import Cache\n",
"\n",
+ "import os\n",
"import pandas as pd"
]
},
@@ -62,7 +63,7 @@
},
{
"cell_type": "code",
- "execution_count": 66,
+ "execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
@@ -87,7 +88,7 @@
},
{
"cell_type": "code",
- "execution_count": 72,
+ "execution_count": 349,
"metadata": {},
"outputs": [],
"source": [
@@ -125,25 +126,29 @@
},
{
"cell_type": "code",
- "execution_count": 73,
+ "execution_count": 350,
"metadata": {},
"outputs": [],
"source": [
"from datetime import datetime as dt, timedelta\n",
"\n",
- "#asset_url=app.get_asset_url('assets') # = $JUPYTERHUB_SERVICE_PREFIX/assets/\n",
+ "asset_url=app.get_asset_url('assets') # = $JUPYTERHUB_SERVICE_PREFIX/assets/\n",
"# example: \"https://jupyter-jsc.fz-juelich.de/user/<user>@fz-juelich.de/<machine>/proxy/8050/assets/\"\n",
- "asset_url=\"https://jupyter-jsc.fz-juelich.de/user/j.goebbert@fz-juelich.de/jureca_login/proxy/8050/assets/\"\n",
+ "#asset_url=\"https://jupyter-jsc.fz-juelich.de/user/j.goebbert@fz-juelich.de/jureca_login/proxy/8050/assets/\"\n",
"\n",
"metadata = pd.read_csv(\"assets/metadata.csv\")\n",
"#for index, row in metadata.iterrows():\n",
"# print(row['countyId'])\n",
"\n",
+ "deltadays = 25\n",
+ "\n",
"min_date=dt(2020, 1, 29).date()\n",
- "max_date=dt(2020, 6, 16).date() # dt.today().date()\n",
+ "max_date=dt(2020, 10, 1).date() # dt.today().date()\n",
+ "\n",
"init_date=dt(2020, 6, 16).date() # dt.today().date()\n",
+ "init_assets_dir = (init_date -timedelta(days=deltadays)).strftime('%Y_%m_%d') + \"/\"\n",
+ "\n",
"init_countyid=11001\n",
- "deltadays = 25\n",
"\n",
"def get_assets_dir(date):\n",
" date = dt.strptime(date.split(' ')[0], '%Y-%m-%d')\n",
@@ -160,7 +165,7 @@
},
{
"cell_type": "code",
- "execution_count": 74,
+ "execution_count": 351,
"metadata": {},
"outputs": [],
"source": [
@@ -194,32 +199,39 @@
},
{
"cell_type": "code",
- "execution_count": 75,
+ "execution_count": 352,
"metadata": {},
"outputs": [],
"source": [
"## load dynamic data\n",
"# => dataframe 'inf'\n",
"import plotly.graph_objects as go\n",
+ "from numpy import nan\n",
"\n",
"def create_map(mapcsv_path):\n",
"\n",
- " # read number of infections from csv file\n",
- " mapcsv = pd.read_csv(mapcsv_path)\n",
- " #print(mapcsv.loc[mapcsv['countyID'] == 3159]) # test with Freiburg\n",
- "\n",
- " # create (correctly sorted) dataframe from no.infections\n",
" infArr=[]\n",
- " # loop over all counties and read no.infections from mapcsv\n",
- " for feat in counties_geojson['features']: # same loop as for df (important)\n",
- " cca_str = feat['properties'].get('RS')\n",
- " if cca_str is not None:\n",
- " # read value for this county from mapcsv\n",
- " cca_valuedf = mapcsv.loc[mapcsv['countyID']==int(cca_str), 'newInf100k']\n",
- " cca_value = next(iter(cca_valuedf), 0.0)\n",
- " infArr.append(cca_value)\n",
- " else:\n",
- " infArr.append(0.0)\n",
+ " try:\n",
+ " # read number of infections from csv file \n",
+ " mapcsv = pd.read_csv(mapcsv_path)\n",
+ " #print(mapcsv.loc[mapcsv['countyID'] == 3159]) # test with Freiburg\n",
+ "\n",
+ " # create (correctly sorted) dataframe from no.infections\n",
+ " # loop over all counties and read no.infections from mapcsv\n",
+ " for feat in counties_geojson['features']: # same loop as for df (important)\n",
+ " cca_str = feat['properties'].get('RS')\n",
+ " if cca_str is not None:\n",
+ " # read value for this county from mapcsv\n",
+ " cca_valuedf = mapcsv.loc[mapcsv['countyID']==int(cca_str), 'newInf100k']\n",
+ " cca_value = next(iter(cca_valuedf), 0.0)\n",
+ " infArr.append(cca_value)\n",
+ " else:\n",
+ " infArr.append(0.0)\n",
+ " except: #IOError as e:\n",
+ " print(\"File not found: \" + mapcsv_path)\n",
+ " for feat in counties_geojson['features']:\n",
+ " infArr.append(nan)\n",
+ "\n",
" counties_infdf = pd.DataFrame(data={'infections': infArr})\n",
"\n",
" # test\n",
@@ -233,7 +245,7 @@
" z=counties_infdf.infections,\n",
" text=counties_metadf.names,\n",
" colorscale=\"Jet\",\n",
- " colorbar=dict(thickness=20, ticklen=3, title=\"Neuinfektionen pro 100.000 Einwohner\", titleside=\"right\"),\n",
+ " colorbar=dict(thickness=20, ticklen=3, title=\"Neuinfektionen pro 100.000 Einwohner und Tag\", titleside=\"right\"),\n",
" zmin=0, zmax=10,\n",
" marker_opacity=0.5, marker_line_width=0,\n",
" hovertemplate=\n",
@@ -263,7 +275,7 @@
" margin={\"r\":0,\"t\":0,\"l\":0,\"b\":0})\n",
" return mapfig\n",
"\n",
- "#mapfig = create_map(\"assets/figures/2020_06_12/map.csv\")\n",
+ "init_mapfig = create_map(\"assets/figures/\" + init_assets_dir + \"map.csv\")\n",
"#mapfig.show(config={\"displayModeBar\": False, \"showTips\": False, \"modeBarButtonsToRemove\": ['toImage']}) # \"staticPlot\": True})"
]
},
@@ -276,7 +288,7 @@
},
{
"cell_type": "code",
- "execution_count": 76,
+ "execution_count": 353,
"metadata": {},
"outputs": [],
"source": [
@@ -356,7 +368,7 @@
},
{
"cell_type": "code",
- "execution_count": 77,
+ "execution_count": 354,
"metadata": {},
"outputs": [],
"source": [
@@ -457,7 +469,7 @@
},
{
"cell_type": "code",
- "execution_count": 78,
+ "execution_count": 355,
"metadata": {},
"outputs": [],
"source": [
@@ -768,7 +780,7 @@
},
{
"cell_type": "code",
- "execution_count": 79,
+ "execution_count": 356,
"metadata": {},
"outputs": [],
"source": [
@@ -814,7 +826,7 @@
},
{
"cell_type": "code",
- "execution_count": 80,
+ "execution_count": 357,
"metadata": {},
"outputs": [],
"source": [
@@ -961,7 +973,7 @@
},
{
"cell_type": "code",
- "execution_count": 81,
+ "execution_count": 358,
"metadata": {},
"outputs": [],
"source": [
@@ -981,7 +993,7 @@
" dcc.Loading(\n",
" id = \"left_date_tab1_loading_graph\", \n",
" children=[html.Div(children=[\n",
- " dcc.Graph(id='left_date_tab1_graph', figure={}),\n",
+ " dcc.Graph(id='left_date_tab1_graph', figure=init_mapfig),\n",
" ])],\n",
" type=\"circle\", # 'graph', 'cube', 'circle', 'dot', 'default'\n",
" color=\"#343A40\",\n",
@@ -1138,10 +1150,6 @@
" type=\"circle\", # 'graph', 'cube', 'circle', 'dot', 'default'\n",
" color=\"#343A40\",\n",
" ), \n",
- " html.Div(\n",
- " id=\"left_date_tab3_txt\",\n",
- " children=[\"left_date_tab3_txt\"],\n",
- " ),\n",
" dbc.Tooltip(\n",
" \"Die Infektionszahlen (Nowcast) pro Tag pro Landkreis und gewähltem Zeitfenster. \"\n",
" \"Der angezeigte Wert entspricht dem Nowcast, also der Schätzung der Anzahl der tatsächlich Neuinfizierten. \"\n",
@@ -1151,6 +1159,10 @@
" style={\"width\": \"200%\"},\n",
" placement=\"left\",\n",
" ),\n",
+ " #html.Div(\n",
+ " # id=\"left_date_tab3_txt\",\n",
+ " # children=[\"left_date_tab3_txt\"],\n",
+ " #),\n",
" ]),\n",
" ]),\n",
" ])\n",
@@ -1169,7 +1181,7 @@
},
{
"cell_type": "code",
- "execution_count": 82,
+ "execution_count": 359,
"metadata": {},
"outputs": [],
"source": [
@@ -1212,7 +1224,9 @@
"def update_left_date_picker(date):\n",
" if date is not None:\n",
" return get_assets_dir(date)\n",
- " \n",
+ " else:\n",
+ " return init_assets_dir\n",
+ "\n",
"# Interactive Map\n",
"@app.callback(\n",
" Output(component_id='left_date_tab1_graph', component_property='figure'),\n",
@@ -1221,8 +1235,10 @@
"def update_left_date_tab1_map(date):\n",
" if date is not None:\n",
" assets_dir = get_assets_dir(date)\n",
- " mapfig = create_map(\"assets/figures/\" + assets_dir + \"/map.csv\") \n",
- " return mapfig\n",
+ " mapfig = create_map(\"assets/figures/\" + assets_dir + \"/map.csv\")\n",
+ " else:\n",
+ " mapfig = create_map(\"assets/placeholders/map_empty.csv\")\n",
+ " return mapfig\n",
"\n",
"# Interaction Kernel\n",
"@app.callback(\n",
@@ -1233,8 +1249,11 @@
"def update_left_date_tab2_img(date):\n",
" if date is not None:\n",
" assets_dir = get_assets_dir(date)\n",
- " imgUrl = asset_url + \"figures/\" + assets_dir + \"/interaction_kernel.png\"\n",
- " return imgUrl, imgUrl\n",
+ " imgUrl = \"figures/\" + assets_dir + \"interaction_kernel.png\"\n",
+ " if imgUrl and not os.path.isfile(\"assets/\" + imgUrl): \n",
+ " imgUrl = \"placeholders/plot_not_found.png\"\n",
+ " imgUrl = asset_url + imgUrl\n",
+ " return imgUrl, imgUrl\n",
"\n",
"# Static Kernel\n",
"@app.callback(\n",
@@ -1244,13 +1263,16 @@
"def update_left_date_tab3_img(date):\n",
" if date is not None:\n",
" assets_dir = get_assets_dir(date)\n",
- " imgUrl = asset_url + \"figures/\" + assets_dir + \"/map.png\"\n",
- " return imgUrl"
+ " imgUrl = \"figures/\" + assets_dir + \"map.png\"\n",
+ " if imgUrl and not os.path.isfile(\"assets/\" + imgUrl): \n",
+ " imgUrl = \"placeholders/plot_not_found.png\"\n",
+ " imgUrl = asset_url + imgUrl\n",
+ " return imgUrl"
]
},
{
"cell_type": "code",
- "execution_count": 83,
+ "execution_count": 360,
"metadata": {},
"outputs": [],
"source": [
@@ -1270,7 +1292,7 @@
" dcc.Loading(\n",
" id = \"right_date_tab1_loading_graph\", \n",
" children=[html.Div(children=[\n",
- " dcc.Graph(id='right_date_tab1_graph', figure={}),\n",
+ " dcc.Graph(id='right_date_tab1_graph', figure=init_mapfig),\n",
" ])],\n",
" type=\"circle\", # 'graph', 'cube', 'circle', 'dot', 'default'\n",
" color=\"#343A40\",\n",
@@ -1436,10 +1458,10 @@
" style={\"width\": \"200%\"},\n",
" placement=\"right\",\n",
" ),\n",
- " html.Div(\n",
- " id=\"right_date_tab3_txt\",\n",
- " children=[\"right_date_tab3_txt\"],\n",
- " ),\n",
+ " #html.Div(\n",
+ " # id=\"right_date_tab3_txt\",\n",
+ " # children=[\"right_date_tab3_txt\"],\n",
+ " #),\n",
" ]),\n",
" ]),\n",
" ])\n",
@@ -1458,7 +1480,7 @@
},
{
"cell_type": "code",
- "execution_count": 84,
+ "execution_count": 361,
"metadata": {},
"outputs": [],
"source": [
@@ -1501,7 +1523,7 @@
},
{
"cell_type": "code",
- "execution_count": 85,
+ "execution_count": 362,
"metadata": {},
"outputs": [],
"source": [
@@ -1544,6 +1566,8 @@
"def update_right_date_picker(date):\n",
" if date is not None:\n",
" return get_assets_dir(date)\n",
+ " else:\n",
+ " return init_assets_dir\n",
"\n",
"# Interactive Map\n",
"@app.callback(\n",
@@ -1554,7 +1578,9 @@
" if date is not None:\n",
" assets_dir = get_assets_dir(date)\n",
" mapfig = create_map(\"assets/figures/\" + assets_dir + \"/map.csv\") \n",
- " return mapfig\n",
+ " else:\n",
+ " mapfig = create_map(\"assets/placeholders/map_empty.csv\")\n",
+ " return mapfig\n",
" \n",
"# Interaction Kernel\n",
"@app.callback(\n",
@@ -1565,9 +1591,12 @@
"def update_right_date_tab2_img(date):\n",
" if date is not None:\n",
" assets_dir = get_assets_dir(date)\n",
- " imgUrl = asset_url + \"figures/\" + assets_dir + \"/interaction_kernel.png\"\n",
- " return imgUrl, imgUrl\n",
- " \n",
+ " imgUrl = \"figures/\" + assets_dir + \"interaction_kernel.png\"\n",
+ " if imgUrl and not os.path.isfile(\"assets/\" + imgUrl): \n",
+ " imgUrl = \"placeholders/plot_not_found.png\"\n",
+ " imgUrl = asset_url + imgUrl\n",
+ " return imgUrl, imgUrl\n",
+ "\n",
"# Static Kernel\n",
"@app.callback(\n",
" Output(component_id='right_date_tab3_img', component_property='src'),\n",
@@ -1576,13 +1605,16 @@
"def update_right_date_tab3_img(date):\n",
" if date is not None:\n",
" assets_dir = get_assets_dir(date)\n",
- " imgUrl = asset_url + \"figures/\" + assets_dir + \"/map.png\"\n",
- " return imgUrl"
+ " imgUrl = \"figures/\" + assets_dir + \"map.png\"\n",
+ " if imgUrl and not os.path.isfile(\"assets/\" + imgUrl): \n",
+ " imgUrl = \"placeholders/plot_not_found.png\"\n",
+ " imgUrl = asset_url + imgUrl\n",
+ " return imgUrl"
]
},
{
"cell_type": "code",
- "execution_count": 86,
+ "execution_count": 363,
"metadata": {},
"outputs": [],
"source": [
@@ -1636,8 +1668,10 @@
" color=\"#343A40\",\n",
" ), \n",
" html.Div(\n",
- " id=\"left_pos_tab1_txt\",\n",
- " children=[\"left_pos_tab1_txt\"],\n",
+ " dcc.Markdown(\n",
+ " id=\"left_pos_tab1_txt\",\n",
+ " children=[\"\"],\n",
+ " )\n",
" ),\n",
" dbc.Tooltip(\n",
" \"Analyse und Vorhersage der Infektionszahlen für den ausgewählten Landkreis. \"\n",
@@ -1713,8 +1747,10 @@
" color=\"#343A40\",\n",
" ), \n",
" html.Div(\n",
- " id=\"left_pos_tab2_txt\",\n",
- " children=[\"left_pos_tab2_txt\"],\n",
+ " dcc.Markdown(\n",
+ " id=\"left_pos_tab2_txt\",\n",
+ " children=[\"\"],\n",
+ " )\n",
" ),\n",
" dbc.Tooltip(\n",
" \"Analyse und Vorhersage der Infektionszahlen für den ausgewählten Landkreis. \"\n",
@@ -1744,7 +1780,7 @@
},
{
"cell_type": "code",
- "execution_count": 87,
+ "execution_count": 364,
"metadata": {},
"outputs": [],
"source": [
@@ -1801,8 +1837,11 @@
"@cache.memoize(timeout=cache_timeout)\n",
"def update_left_pos_tab1_img(value, assets_dir):\n",
" if value is not None:\n",
- " imgUrl = asset_url + \"figures/\" + assets_dir + \"curve_trend_{0:05d}.png\".format(value)\n",
- " return imgUrl, imgUrl\n",
+ " imgUrl = \"figures/\" + assets_dir + \"curve_trend_{0:05d}.png\".format(value)\n",
+ " if imgUrl and not os.path.isfile(\"assets/\" + imgUrl): \n",
+ " imgUrl = \"placeholders/plot_not_found.png\"\n",
+ " imgUrl = asset_url + imgUrl\n",
+ " return imgUrl, imgUrl\n",
"\n",
"# ungeglättet\n",
"@app.callback(\n",
@@ -1813,8 +1852,11 @@
"@cache.memoize(timeout=cache_timeout)\n",
"def update_left_pos_tab2_img(value, assets_dir):\n",
" if value is not None:\n",
- " imgUrl = asset_url + \"figures/\" + assets_dir + \"curve_{0:05d}.png\".format(value)\n",
- " return imgUrl, imgUrl\n",
+ " imgUrl = \"figures/\" + assets_dir + \"curve_{0:05d}.png\".format(value)\n",
+ " if imgUrl and not os.path.isfile(\"assets/\" + imgUrl): \n",
+ " imgUrl = \"placeholders/plot_not_found.png\"\n",
+ " imgUrl = asset_url + imgUrl\n",
+ " return imgUrl, imgUrl\n",
"\n",
"# print meta-information\n",
"@app.callback(\n",
@@ -1825,14 +1867,28 @@
"@cache.memoize(timeout=cache_timeout)\n",
"def update_left_pos_txt(value, assets_dir):\n",
" if value is not None:\n",
- " mdat = pd.read_csv(\"./assets/figures/\" + assets_dir + \"/metadata.csv\")\n",
- " msg = mdat.loc[mdat['countyID'] == value]['probText'].to_string(index=False)\n",
- " return msg, msg"
+ " try:\n",
+ " mdat = pd.read_csv(\"./assets/figures/\" + assets_dir + \"/metadata.csv\")\n",
+ " msg = mdat.loc[mdat['countyID'] == value]['probText'].to_string(index=False)\n",
+ " try:\n",
+ " val = float(msg)\n",
+ " if val<0.0:\n",
+ " msg = 'Die Infektioneszahlen werden mit einer Wahrscheinlichkeit von **{:.1f}%** fallen.'.format(val)\n",
+ " else:\n",
+ " msg = 'Die Neuinfektionen werden mit einer Wahrscheinlichkeit von **{:.1f}%** steigen.'.format(val)\n",
+ " except:\n",
+ " print(\"Exception in update_right_pos_txt\")\n",
+ " pass\n",
+ " except:\n",
+ " msg = \" \"\n",
+ " else:\n",
+ " msg = \" \"\n",
+ " return msg, msg"
]
},
{
"cell_type": "code",
- "execution_count": 88,
+ "execution_count": 365,
"metadata": {},
"outputs": [],
"source": [
@@ -1886,8 +1942,10 @@
" color=\"#343A40\",\n",
" ), \n",
" html.Div(\n",
- " id=\"right_pos_tab1_txt\",\n",
- " children=[\"right_pos_tab1_txt\"],\n",
+ " dcc.Markdown(\n",
+ " id=\"right_pos_tab1_txt\",\n",
+ " children=[\"\"],\n",
+ " )\n",
" ),\n",
" dbc.Tooltip(\n",
" \"Analyse und Vorhersage der Infektionszahlen für den ausgewählten Landkreis. \"\n",
@@ -1963,8 +2021,10 @@
" color=\"#343A40\",\n",
" ), \n",
" html.Div(\n",
- " id=\"right_pos_tab2_txt\",\n",
- " children=[\"right_pos_tab2_txt\"],\n",
+ " dcc.Markdown(\n",
+ " id=\"right_pos_tab2_txt\",\n",
+ " children=[\"\"],\n",
+ " )\n",
" ),\n",
" dbc.Tooltip(\n",
" \"Analyse und Vorhersage der Infektionszahlen für den ausgewählten Landkreis. \"\n",
@@ -1994,7 +2054,7 @@
},
{
"cell_type": "code",
- "execution_count": 89,
+ "execution_count": 366,
"metadata": {},
"outputs": [],
"source": [
@@ -2051,8 +2111,11 @@
"@cache.memoize(timeout=cache_timeout)\n",
"def update_right_pos_tab1_img(value, assets_dir):\n",
" if value is not None:\n",
- " imgUrl = asset_url + \"figures/\" + assets_dir + \"curve_trend_{0:05d}.png\".format(value)\n",
- " return imgUrl, imgUrl\n",
+ " imgUrl = \"figures/\" + assets_dir + \"curve_trend_{0:05d}.png\".format(value)\n",
+ " if imgUrl and not os.path.isfile(\"assets/\" + imgUrl): \n",
+ " imgUrl = \"placeholders/plot_not_found.png\"\n",
+ " imgUrl = asset_url + imgUrl\n",
+ " return imgUrl, imgUrl\n",
" \n",
"# ungeglättet\n",
"@app.callback(\n",
@@ -2063,8 +2126,11 @@
"@cache.memoize(timeout=cache_timeout)\n",
"def update_right_pos_tab2_img(value, assets_dir):\n",
" if value is not None:\n",
- " imgUrl = asset_url + \"figures/\" + assets_dir + \"curve_{0:05d}.png\".format(value)\n",
- " return imgUrl, imgUrl\n",
+ " imgUrl = \"figures/\" + assets_dir + \"curve_{0:05d}.png\".format(value)\n",
+ " if imgUrl and not os.path.isfile(\"assets/\" + imgUrl): \n",
+ " imgUrl = \"placeholders/plot_not_found.png\"\n",
+ " imgUrl = asset_url + imgUrl\n",
+ " return imgUrl, imgUrl\n",
"\n",
"# print meta-information\n",
"@app.callback(\n",
@@ -2075,9 +2141,23 @@
"@cache.memoize(timeout=cache_timeout)\n",
"def update_right_pos_txt(value, assets_dir):\n",
" if value is not None:\n",
- " mdat = pd.read_csv(\"./assets/figures/\" + assets_dir + \"/metadata.csv\")\n",
- " msg = mdat.loc[mdat['countyID'] == value]['probText'].to_string(index=False)\n",
- " return msg, msg"
+ " try:\n",
+ " mdat = pd.read_csv(\"./assets/figures/\" + assets_dir + \"/metadata.csv\")\n",
+ " msg = mdat.loc[mdat['countyID'] == value]['probText'].to_string(index=False)\n",
+ " try:\n",
+ " val = float(msg)\n",
+ " if val<0.0:\n",
+ " msg = 'Die Infektioneszahlen werden mit einer Wahrscheinlichkeit von **{:.1f}% fallen**.'.format(val)\n",
+ " else:\n",
+ " msg = 'Die Neuinfektionen werden mit einer Wahrscheinlichkeit von **{:.1f}% steigen**.'.format(val)\n",
+ " except:\n",
+ " print(\"Exception in update_right_pos_txt\")\n",
+ " pass\n",
+ " except:\n",
+ " msg = \" \"\n",
+ " else:\n",
+ " msg = \" \"\n",
+ " return msg, msg"
]
},
{
@@ -2092,7 +2172,7 @@
},
{
"cell_type": "code",
- "execution_count": 90,
+ "execution_count": 367,
"metadata": {},
"outputs": [],
"source": [
@@ -2264,7 +2344,7 @@
" # --- Ortsangabe (left) ---\n",
" dbc.Card(\n",
" style={\n",
- " 'margin': '0% 0% 0% 0%', # top, right, bottom, left\n",
+ " 'margin': '0% 0% 0% 0%', # top, right, bottom, leftleft\n",
" 'padding': '0',\n",
" }, \n",
" children=[\n",
@@ -2278,8 +2358,8 @@
" id=\"left_pos-card-tabs\",\n",
" active_tab=\"tab-0\", \n",
" children=[\n",
- " dbc.Tab(left_pos_tab1, label=\"geglättet\", style={'padding': '0', 'height': '300px'}),\n",
- " dbc.Tab(left_pos_tab2, label=\"ungeglättet\", style={'padding': '0', 'height': '300px'}),\n",
+ " dbc.Tab(left_pos_tab1, label=\"geglättet\", style={'padding': '0', 'height': '320px'}),\n",
+ " dbc.Tab(left_pos_tab2, label=\"ungeglättet\", style={'padding': '0', 'height': '320px'}),\n",
" ]),\n",
"\n",
" html.P(\n",
@@ -2341,8 +2421,8 @@
" id=\"right_pos-card-tabs\",\n",
" active_tab=\"tab-0\", \n",
" children=[\n",
- " dbc.Tab(right_pos_tab1, label=\"geglättet\", style={'padding': '0', 'height': '300px'}),\n",
- " dbc.Tab(right_pos_tab2, label=\"ungeglättet\", style={'padding': '0', 'height': '300px'}),\n",
+ " dbc.Tab(right_pos_tab1, label=\"geglättet\", style={'padding': '0', 'height': '320px'}),\n",
+ " dbc.Tab(right_pos_tab2, label=\"ungeglättet\", style={'padding': '0', 'height': '320px'}),\n",
" ]),\n",
"\n",
" html.P(\n",
@@ -2369,11 +2449,11 @@
},
{
"cell_type": "code",
- "execution_count": 91,
+ "execution_count": 368,
"metadata": {},
"outputs": [],
"source": [
- "app.run_server(mode=\"jupyterlab\") #,port=8052,debug=True)\n",
+ "app.run_server(mode=\"external\") #,port=8052,debug=True)\n",
"# mode=\"jupyterlab\" -> will open the app in a tab in JupyterLab\n",
"# mode=\"inline\" -> will open the app below this cell\n",
"# mode=\"external\" -> will displays a URL that you can click on to open the app in a browser tab"