diff --git a/src/pages/dashboard.py b/src/pages/dashboard.py index 7de5141ede48d7c6e9eeea5a062320934a25033f..79dcc3941c71afd4d39dc7527decc407e3b2c874 100644 --- a/src/pages/dashboard.py +++ b/src/pages/dashboard.py @@ -116,7 +116,7 @@ first_day_of_week = [0, 1] min_date_allowed = "2017-02-20" max_date_allowed = "2018-08-09" initial_visible_month = "2017-02-01" -forecast_length_label = ["forecast length:", "Vorhersagedauer:"] +forecast_length_label = ["forecast length", "Vorhersagedauer"] region_label = ["region:", "Region:"] forecast_length_options = [["4 days", "3 days", "2 days", "1 day"], ["4 Tage", "3 Tage", "2 Tage", "1 Tag"]] @@ -131,6 +131,11 @@ emis_scen_label = ["emission scenario:", "Emissionsszenario:"] help_metrics_label = ["Help on metrics", "Hilfe zu Ausgabemetriken"] help_emissions_label = ["Help on emission scenarios", "Hilfe zu Emissions-Szenarien"] map_select_label = ["Select on map", "auf Karte auswählen"] +time_step_label = ["Time step", "Zeitschritt"] +start_date_label = ["Start date", "Startdatum"] +location_label = ["Location", "Ort"] +day_label = ["day", "Tag"] +day_plural_label = ["s", "e"] save_label = ["Save Results", "Ergebnisse sichern"] download_label = ["Download Data", "Daten herunterladen"] downscaling_label = ["Postprocessing with ML-Downscaling", "Postprocessing mit ML-Downscaling"] @@ -264,7 +269,7 @@ def generate_ml_fcast_body(language_id=0): def generate_ml_fcast_output_body(language_id): return [ - dbc.Row(dbc.Label("Start date: 17 June 2017, ozone, Nordrhein Westfalen")), + dbc.Row(dbc.Label(f"{start_date_label[language_id]}: 17 June 2017, ozone, Nordrhein Westfalen")), dbc.Row([ dbc.Col(dbc.Label("station:"), width=3), dbc.Col( @@ -327,7 +332,7 @@ def generate_eurad_im_body(language_id=0): dbc.Col(dcc.DatePickerSingle(date=dt.date.today(), display_format=date_format[language_id], first_day_of_week=first_day_of_week[language_id])), - dbc.Col(dbc.Label(forecast_length_label[language_id])), + dbc.Col(dbc.Label(f"{forecast_length_label[language_id]}:")), dbc.Col(dcc.Dropdown(value=forecast_length_options[language_id][0], options=forecast_length_options[language_id])) ], class_name="row mt-3"), dbc.Row([ @@ -370,23 +375,23 @@ def generate_eurad_im_output_body(language_id, context): # TODO: Zeit in Stunden seit Start start_date = pd.to_datetime(timestep_list[0]).strftime("%d %B %Y") - fc_lenght = (len(timestep_list)-1) // 24 - fc_lenght_str = "{} day{}".format(fc_lenght, "s" if fc_lenght > 1 else "") + fc_length = (len(timestep_list)-1) // 24 + fc_length_str = "{} {}{}".format(fc_length, day_label[language_id], day_plural_label[language_id] if fc_length > 1 else "") variables_list = info.get_available_variables(infile) stations_list = info.get_available_stations() stations_list = sorted(stations_list) return [ - dbc.Row([dbc.Label("Start date: {}, forecast length: {}".format(start_date, fc_lenght_str))]), + dbc.Row([dbc.Label(f"{start_date_label[language_id]}: {start_date}, {forecast_length_label[language_id]}: {fc_length_str}")]), dbc.Row([ - dbc.Col(dbc.Label("Time step:"), width=3), + dbc.Col(dbc.Label(f"{time_step_label[language_id]}"), width=3), dbc.Col(dcc.Dropdown(value=timestep_strings[0], options=timestep_strings, id='time-step-dropdown-{}'.format(context)), width=3) ], class_name="row mt-3"), dbc.Row([ dbc.Col(dbc.Label("Variable:"), width=3), dbc.Col(dcc.Dropdown(value=variables_list[0], options=variables_list, id='variable-dropdown-{}'.format(context)), width=3), - dbc.Col(dbc.Label("Location:"), width=3), + dbc.Col(dbc.Label(f"{location_label[language_id]}:"), width=3), dbc.Col(dcc.Dropdown(value=stations_list[0], options=stations_list, id='station-dropdown-{}'.format(context)), width=3) ], class_name="row mt-3"), dbc.Row([ @@ -399,7 +404,7 @@ def generate_eurad_im_output_body(language_id, context): dbc.Row([ dbc.Col(html.Br(), width=12), dbc.Col([ - dbc.Checkbox(label=f"{show_downscaling_label[language_id]}", value=1) + dbc.Checkbox(label=f"{show_downscaling_label[language_id]}", value=0) ], style={"display": "flex"}), ], class_name="row mt-3f"), ] @@ -465,7 +470,7 @@ def generate_eurad_scen_body(language_id): dbc.Col(dcc.DatePickerSingle(date=dt.date.today(), display_format=date_format[language_id], first_day_of_week=first_day_of_week[language_id])), - dbc.Col(dbc.Label(f"{forecast_length_label[language_id]}")), + dbc.Col(dbc.Label(f"{forecast_length_label[language_id]}:")), dbc.Col(dcc.Dropdown(value=forecast_length_options[language_id][0], options=forecast_length_options[language_id])) ], class_name="row mt-3"), dbc.Row([