diff --git a/prepare_userdb.py b/prepare_userdb.py
index b373e2df65027dbaecd76050039e8eae8d90b95f..af72c2e3a8da4a4a900c29d7105c356a5fa65d34 100644
--- a/prepare_userdb.py
+++ b/prepare_userdb.py
@@ -1,6 +1,6 @@
import sqlite3
-conn = sqlite3.connect('src/destine_de370c_users.db')
+conn = sqlite3.connect('src/static/data/destine_de370c_users.db')
print("Opened database successfully")
# First, create the controlled vocabulary
@@ -56,6 +56,23 @@ conn.execute("INSERT INTO convoc_status (id,job_status) \
conn.execute("INSERT INTO convoc_status (id,job_status) \
VALUES (3, 'aborted')")
+conn.commit()
+
+# There is the need for controlled_vocabulary for regions of interest
+# 0: finished
+# 1: active
+conn.execute('''CREATE TABLE convoc_region
+ (id INT PRIMARY KEY NOT NULL,
+ region_name TEXT NOT NULL);''')
+
+conn.execute("INSERT INTO convoc_region (id,region_name) \
+ VALUES (0, 'North Rhine-Westphalia')")
+conn.execute("INSERT INTO convoc_region (id,region_name) \
+ VALUES (1, 'Berlin-Brandenburg')")
+
+conn.commit()
+
+
# Second, create the dashboard tables
conn.execute('''CREATE TABLE users
(id INT PRIMARY KEY NOT NULL,
@@ -64,61 +81,66 @@ conn.execute('''CREATE TABLE users
FOREIGN KEY(language) REFERENCES convoc_language(id));''')
conn.execute("INSERT INTO users (id,name,language) \
- VALUES (1, 'Sabine English', 0)")
+ VALUES (1, 'User English', 0)")
conn.execute("INSERT INTO users (id,name,language) \
- VALUES (2, 'Sabine Deutsch', 1)")
+ VALUES (2, 'Benutzer Deutsch', 1)")
conn.commit()
conn.execute('''CREATE TABLE jobs
- (id CHAR(50) NOT NULL,
- user_id INT NOT NULL,
- status INT NOT NULL,
- application INT NOT NULL,
- FOREIGN KEY(user_id) REFERENCES user(id),
- FOREIGN KEY(status) REFERENCES convoc_status(id),
- FOREIGN KEY(application) REFERENCES convoc_application(id));''')
-
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('832tgjhingj1', 1, 1, 0)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('jjkl7t3li97m', 1, 0, 1)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('7zhtglaza8ah', 1, 1, 2)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('ji54Fdr0z99m', 1, 0, 0)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('7zknt6702rx5', 1, 3, 0)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('klj836kahg2l', 1, 0, 2)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('a89uj20gxybb', 1, 2, 2)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('832tgjhingj1', 2, 1, 0)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('jjkl7t3li97m', 2, 0, 1)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('7zhtglaza8ah', 2, 1, 2)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('ji54Fdr0z99m', 2, 0, 0)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('7zknt6702rx5', 2, 3, 0)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('klj836kahg2l', 2, 0, 2)")
-conn.execute("INSERT INTO jobs (id,user_id,application,status) \
- VALUES ('a89uj20gxybb', 2, 2, 2)")
+ (id CHAR(50) NOT NULL,
+ user_id INT NOT NULL,
+ status INT NOT NULL,
+ application INT NOT NULL,
+ start_date datetime NOT NULL,
+ forecast_length INT NOT NULL,
+ region INT NOT NULL,
+ creation_date datetime NOT NULL,
+ FOREIGN KEY(user_id) REFERENCES user(id),
+ FOREIGN KEY(status) REFERENCES convoc_status(id),
+ FOREIGN KEY(application) REFERENCES convoc_application(id),
+ FOREIGN KEY(region) REFERENCES convoc_region(id));''')
+
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('832tgjhingj1', 1, 0, 1, '2018-07-18 00:00', 4, 1, '2024-01-12 16:03')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('jjkl7t3li97m', 1, 1, 0, '2017-01-25 00:00', 3, 0, '2024-01-09 10:14')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('7zhtglaza8ah', 1, 2, 1, '2018-07-18 00:00', 4, 1, '2024-01-15 08:01')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('ji54Fdr0z99m', 1, 0, 0, '2018-07-18 00:00', 1, 0, '2023-12-18 13:57')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('7zknt6702rx5', 1, 0, 3, '2017-01-25 00:00', 3, 0, '2023-12-12 11:27')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('klj836kahg2l', 1, 2, 0, '2018-07-18 00:00', 1, 0, '2023-12-21 17:59')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('a89uj20gxybb', 1, 2, 2, '2017-01-25 00:00', 4, 0, '2024-01-02 14:35')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('832tgjhingj1', 2, 0, 1, '2018-07-18 00:00', 4, 1, '2024-01-12 16:03')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('jjkl7t3li97m', 2, 1, 0, '2017-01-25 00:00', 3, 0, '2024-01-09 10:14')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('7zhtglaza8ah', 2, 2, 1, '2018-07-18 00:00', 4, 1, '2024-01-15 08:01')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('ji54Fdr0z99m', 2, 0, 0, '2018-07-18 00:00', 1, 0, '2023-12-18 13:57')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('7zknt6702rx5', 2, 0, 3, '2017-01-25 00:00', 3, 0, '2023-12-12 11:27')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('klj836kahg2l', 2, 2, 0, '2018-07-18 00:00', 1, 0, '2023-12-21 17:59')")
+conn.execute("INSERT INTO jobs (id,user_id,application,status,start_date,forecast_length, region, creation_date) \
+ VALUES ('a89uj20gxybb', 2, 2, 2, '2017-01-25 00:00', 4, 0, '2024-01-02 14:35')")
conn.commit()
conn.execute('''CREATE TABLE results
- (id INT NOT NULL,
- user_id INT NOT NULL,
- job_id CHAR(50) NOT NULL,
- application INT NOT NULL,
- used_options CHAR(50) NOT NULL,
- FOREIGN KEY(user_id) REFERENCES user(id),
- FOREIGN KEY(job_id) REFERENCES jobs(id),
+ (id INT NOT NULL,
+ user_id INT NOT NULL,
+ job_id CHAR(50) NOT NULL,
+ application INT NOT NULL,
+ used_options CHAR(50) NOT NULL,
+ FOREIGN KEY(user_id) REFERENCES user(id),
+ FOREIGN KEY(job_id) REFERENCES jobs(id),
FOREIGN KEY(application) REFERENCES convoc_application(id));''')
conn.execute("INSERT INTO results (user_id,id,job_id,application,used_options) \
@@ -142,4 +164,4 @@ conn.commit()
print("Example tables successfully created")
-conn.close()
\ No newline at end of file
+conn.close()
diff --git a/src/eurad_plot.py b/src/eurad_plot.py
index bdc582bcc6cc7e807df27c11c745c876b30454a4..1ec179339ac420ed2f1b7011374c4f135418c98b 100644
--- a/src/eurad_plot.py
+++ b/src/eurad_plot.py
@@ -11,8 +11,8 @@ def get_euradim_plot(jobnr, timestep, species, station):
DATA_PATH = APP_HOME.joinpath("static", "data")
ASSETS_PATH = APP_HOME.joinpath("assets", "generated_plots")
- # This needs to come from outside!
- infile = str(DATA_PATH.joinpath('ctmout_wrf_cut_199_h09.nc'))
+ # Output file is linked to jobnr
+ infile = str(DATA_PATH.joinpath(f'{jobnr}.nc'))
if station:
station = station.split(',')[0] # extract station code
@@ -36,8 +36,8 @@ def get_timeseries_plot(jobnr, station, species, timestep):
DATA_PATH = APP_HOME.joinpath("static", "data")
ASSETS_PATH = APP_HOME.joinpath("assets", "generated_plots")
- # This needs to come from outside!
- infile = str(DATA_PATH.joinpath('ctmout_wrf_cut_199_h09.nc'))
+ # Output file is linked to jobnr
+ infile = str(DATA_PATH.joinpath(f'{jobnr}.nc'))
if station:
station = station.split(',')[0] # extract station code
diff --git a/src/pages/dashboard.py b/src/pages/dashboard.py
index 79dcc3941c71afd4d39dc7527decc407e3b2c874..b6c578bbe9c49fc35b435a6c49389c7d6d2c91e6 100644
--- a/src/pages/dashboard.py
+++ b/src/pages/dashboard.py
@@ -12,11 +12,13 @@ import eurad.info as info
import numpy as np
from eurad_plot import get_euradim_plot, get_timeseries_plot
import os
+import zipfile
# the following should be done with static files!
APP_HOME = Path.cwd()
IMAGE_PATH = APP_HOME.joinpath("static", "images")
DATA_PATH = APP_HOME.joinpath("static", "data")
+ASSETS_PATH = APP_HOME.joinpath("assets", "generated_plots")
dash.register_page(__name__, title="DestinE Air Quality Use Case", path="/")
@@ -43,10 +45,10 @@ description = [["The DestinE Air Quality Use Case demonstrates interactive trigg
"Die Dokumentation des Anwendungsfalls finden Sie ",
html.A("hier", href="https://www.fz-juelich.de/de/iek/iek-8/projekte/"
+ "destination-earth-use-case-fuer-luftqualitaet-de370c")]]
-jobs_columns = [["Jobnr", "Status", "Application"],
- ["Jobnr", "Status", "Anwendung"]]
-results_columns = [["Result_ID", "Jobnr", "Application", "Used Options"],
- ["Resultats_ID", "Jobnr", "Anwendung", "Verwendete Optionen"]]
+jobs_columns = [["Application", "Status", "Start date", "Forecast Length", "Region", "Creation Date", "Jobnr"],
+ ["Anwendung", "Status", "Startdatum", "Vorhersagedauer", "Region", "Erstellungsdatum", "Jobnr"]]
+results_columns = [["Result_ID", "Jobnr", "Application", "Used Options"],
+ ["Resultats_ID", "Jobnr", "Anwendung", "Verwendete Optionen"]]
eurad_scenarios = ["avoid all anthropogenic emissions",
"home office",
"industry",
@@ -57,13 +59,15 @@ status_text = [["finished", "active", "waiting", "aborted"],
["beendet", "aktiv", "in der Warteschlange", "abgebrochen"]]
application_text = [["Field forecasting with EURAD-IM", "Point forecasting with MLAir", "EURAD-IM emission scenarios"],
["Gebietsvorhersage mit EURAD-IM", "Stationsvorhersage mit MLAir", "EURAD-IM Emissionsszenarien"]]
+region_text = [["North Rhine-Westphalia", "Berlin-Brandenburg"],
+ ["Nordrhein-Westfalen", "Berlin-Brandenburg"]]
description_text = [["This application produces high-resolution, i.e. 1 km or less, on-demand results over a "
+ "user-selected area for a forecast period of up to 4 days. Here, users can select the forecast "
+ "start date (default today) and the forecast length (shorter runs require less time and "
+ "resources), and the regional domain of the simulation. There are two EURAD-IM model "
+ "configurations applied in the background of this application: i) the default 9 km resolution "
+ "model covering all of Europe, and ii) region-specific 1 km configurations, initially limited "
- + "to Northrhine-Westphalia and Brandenburg. Users can select whether they wish to perform a "
+ + "to North Rhine-Westphalia and Brandenburg. Users can select whether they wish to perform a "
+ "dedicated 1 km EURAD-IM simulation, or whether the 1 km results shall be obtained with ML "
+ "downscaling from the results of a 9 km simulation. For more information about EURAD-IM and ML "
+ "downscaling, please refer to the description tab.",
@@ -109,9 +113,11 @@ description_text = [["This application produces high-resolution, i.e. 1 km or le
+ "Informationen über EURAD-IM Emissionen finden sich im Beschreibungs-Tab."]]
user_label = ["user:", "Benutzer:"]
run_label = ["run", "Starten"]
+run2_label = ["Run", "Lauf"]
close_label = ["close", "Schließen"]
date_label = ["date:", "Datum:"]
date_format = ["M/D/Y", "D.M.Y"]
+date_format2 = ['%Y-%m-%d %H:%M', '%d.%m.%Y %H:%M']
first_day_of_week = [0, 1]
min_date_allowed = "2017-02-20"
max_date_allowed = "2018-08-09"
@@ -138,6 +144,7 @@ day_label = ["day", "Tag"]
day_plural_label = ["s", "e"]
save_label = ["Save Results", "Ergebnisse sichern"]
download_label = ["Download Data", "Daten herunterladen"]
+im_download_label = ["Download Plots", "Plots herunterladen"]
downscaling_label = ["Postprocessing with ML-Downscaling", "Postprocessing mit ML-Downscaling"]
show_downscaling_label = ["Show results with ML downscaling", "Ergebnisse mit ML-Downscaling anzeigen"]
out_option_label = ["output option", "Ausgabe-Option"]
@@ -292,7 +299,7 @@ def generate_ml_fcast_output_modal(jobnr=None, lisopen=False, language_id=0):
return html.Div([
dbc.Modal(
[
- dbc.ModalTitle(f"Run {jobnr}", style={"fontSize": 15}),
+ dbc.ModalTitle(f"{run2_label[language_id]} {jobnr}", style={"fontSize": 15}),
dbc.ModalHeader(dbc.ModalTitle(application_text[language_id][1])),
dbc.ModalBody(generate_ml_fcast_output_body(language_id)),
dbc.ModalFooter([dbc.Button(f"{close_label[language_id]}", id="ml_fcast_output_close",
@@ -309,7 +316,7 @@ def generate_ml_fcast_output_modal(jobnr=None, lisopen=False, language_id=0):
def generate_ml_fcast_result_modal(jobnr=None, lisopen=False, language_id=0):
return dbc.Modal(
[
- dbc.ModalTitle(f"Run {jobnr}", style={"fontSize": 15}),
+ dbc.ModalTitle(f"{run2_label[language_id]} {jobnr}", style={"fontSize": 15}),
dbc.ModalHeader(dbc.ModalTitle(application_text[language_id][1])),
dbc.ModalBody(generate_ml_fcast_output_body(language_id)),
dbc.ModalFooter(dbc.Button(f"{close_label[language_id]}", id="ml_fcast_result_close",
@@ -344,37 +351,52 @@ def generate_eurad_im_body(language_id=0):
@callback(
[Output('image-container-output', 'children'),
- Output('image-container-timeseries-output', 'children')],
+ Output('image-container-timeseries-output', 'children'),
+ Output("plot-info", "data")],
[Input('time-step-dropdown-output', 'value'),
Input('variable-dropdown-output', 'value'),
- Input('station-dropdown-output', 'value')]
+ Input('station-dropdown-output', 'value')],
+ [State("user-info", "data"),
+ State("job-info", "data")]
)
-def update_image(selected_time_step, selected_variable, selected_station):
+def update_image(selected_time_step, selected_variable, selected_station, users_dict, jobs_dict):
+ plotinfo_dict = {}
if selected_time_step and selected_variable:
+
+ jobnr = json.loads(jobs_dict)["jobnr"]
+ try:
+ language_id = json.loads(users_dict)["language_id"]
+ except:
+ language_id = 0
- image_path = get_euradim_plot("dummyjob", selected_time_step, selected_variable, selected_station)
- timeseries_image_path = get_timeseries_plot("dummyjob", selected_station, selected_variable, selected_time_step)
+ image_path = get_euradim_plot(jobnr, selected_time_step, selected_variable, selected_station)
+ timeseries_image_path = get_timeseries_plot(jobnr, selected_station, selected_variable, selected_time_step)
first_image = html.Img(src=image_path, className='image-fit-container')
second_image = html.Img(src=timeseries_image_path, className='image-fit-container')
+
+ plotinfo_dict["time_step"] = selected_time_step
+ plotinfo_dict["variable"] = selected_variable
+ plotinfo_dict["station"] = selected_station.split(',')[0]
+ plotinfo_json = json.dumps(plotinfo_dict)
- return first_image, second_image
+ return first_image, second_image, plotinfo_json
- return None, None
+ plotinfo_json = json.dumps(plotinfo_dict)
+ return None, None, plotinfo_json
def generate_eurad_im_output_body(language_id, context):
-
# This needs to come from outside!
- infile = str(DATA_PATH.joinpath('ctmout_wrf_cut_199_h09.nc'))
+ infile = str(DATA_PATH.joinpath('ctmout_wrf_cutcropped_199_h09.nc'))
timestep_list = info.get_available_time_stamps(infile)
timestep_strings = [np.datetime_as_string(ts, unit="m") for ts in timestep_list]
# TODO: Zeit in Stunden seit Start
- start_date = pd.to_datetime(timestep_list[0]).strftime("%d %B %Y")
+ start_date = pd.to_datetime(timestep_list[0]).strftime(date_format2[language_id])
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 "")
@@ -385,21 +407,27 @@ def generate_eurad_im_output_body(language_id, context):
return [
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(f"{time_step_label[language_id]}"), 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(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)
+ dbc.Col(dbc.Label(f"{location_label[language_id]}:"), width=1),
+ dbc.Col(dcc.Dropdown(value=stations_list[0], options=stations_list, id='station-dropdown-{}'.format(context)), width=5)
], class_name="row mt-3"),
dbc.Row([
dbc.Col(html.Div(id='image-container-{}'.format(context)), width=6),
dbc.Col([html.Div(id='image-container-timeseries-{}'.format(context)),
dbc.Col(dbc.Button(f"{save_label[language_id]}", class_name="fzj_style_btn"), width=6),
dbc.Col(html.Br()),
- dbc.Button(f"{download_label[language_id]}", class_name="fzj_style_btn")], width=6),
+ html.Div([dbc.Button(f"{download_label[language_id]}", id="eurad_im_output_download",
+ class_name="fzj_style_btn"),
+ dcc.Download(id="eurad_im_download_result")]),
+ dbc.Col(html.Br()),
+ html.Div([dbc.Button(f"{im_download_label[language_id]}", id="eurad_im_plots_download",
+ class_name="fzj_style_btn"),
+ dcc.Download(id="eurad_im_download_plots")])], width=6),
], class_name="row mt-3"),
dbc.Row([
dbc.Col(html.Br(), width=12),
@@ -414,7 +442,7 @@ def generate_eurad_im_output_modal(jobnr=None, lisopen=False, language_id=0):
return html.Div([
dbc.Modal(
[
- dbc.ModalTitle(f"Run {jobnr}", style={"fontSize": 15}, id="eurad_im_output_modal_title"),
+ dbc.ModalTitle(f"{run2_label[language_id]} {jobnr}", style={"fontSize": 15}, id="eurad_im_output_modal_title"),
dbc.ModalHeader(dbc.ModalTitle(application_text[language_id][0])),
dbc.ModalBody(generate_eurad_im_output_body(language_id, "output")),
dbc.ModalFooter([dbc.Button(f"{close_label[language_id]}", id="eurad_im_output_close",
@@ -431,7 +459,7 @@ def generate_eurad_im_output_modal(jobnr=None, lisopen=False, language_id=0):
def generate_eurad_im_result_modal(jobnr=None, lisopen=False, language_id=0):
return dbc.Modal(
[
- dbc.ModalTitle(f"Run {jobnr}", style={"fontSize": 15}),
+ dbc.ModalTitle(f"{run2_label[language_id]} {jobnr}", style={"fontSize": 15}),
dbc.ModalHeader(dbc.ModalTitle(application_text[language_id][0])),
dbc.ModalBody(generate_eurad_im_output_body(language_id, "result")),
dbc.ModalFooter(dbc.Button(f"{close_label[language_id]}", id="eurad_im_result_close",
@@ -503,7 +531,7 @@ def generate_eurad_scen_output_modal(container_id="eurad_scen_output_modal_conta
return html.Div([
dbc.Modal(
[
- dbc.ModalTitle(f"Run {jobnr}", style={"fontSize": 15}),
+ dbc.ModalTitle(f"{run2_label[language_id]} {jobnr}", style={"fontSize": 15}),
dbc.ModalHeader(dbc.ModalTitle(application_text[language_id][2])),
dbc.ModalBody(generate_eurad_scen_output_body(language_id)),
dbc.ModalFooter([dbc.Button(f"{close_label[language_id]}", id="eurad_scen_output_close",
@@ -521,7 +549,7 @@ def generate_eurad_scen_result_modal(container_id="eurad_scen_result_modal_conta
return html.Div([
dbc.Modal(
[
- dbc.ModalTitle(f"Run {jobnr}", style={"fontSize": 15}),
+ dbc.ModalTitle(f"{run2_label[language_id]} {jobnr}", style={"fontSize": 15}),
dbc.ModalHeader(dbc.ModalTitle(application_text[language_id][2])),
dbc.ModalBody(generate_eurad_scen_output_body(language_id)),
dbc.ModalFooter([dbc.Button(f"{close_label[language_id]}", id="eurad_scen_result_modal_close",
@@ -613,13 +641,17 @@ def get_my_jobs_from_db(user_id=None, language_id=0):
if user_id:
conn = sqlite3.connect(DATA_PATH.joinpath('destine_de370c_users.db'))
cur = conn.cursor()
- cur.execute(f"SELECT * FROM jobs WHERE user_id={user_id}")
+ cur.execute(f"SELECT application, status, start_date, forecast_length, region, creation_date, id FROM jobs WHERE user_id={user_id}")
data_rows_from_db = cur.fetchall()
for job in data_rows_from_db:
- data_from_db.append({jobs_columns[language_id][0]: job[0],
- jobs_columns[language_id][1]: status_text[language_id][job[3]],
- jobs_columns[language_id][2]: application_text[language_id][job[2]]})
+ data_from_db.append({jobs_columns[language_id][0]: application_text[language_id][job[0]],
+ jobs_columns[language_id][1]: status_text[language_id][job[1]],
+ jobs_columns[language_id][2]: dt.datetime.strptime(job[2],'%Y-%m-%d %H:%M').strftime(date_format2[language_id]),
+ jobs_columns[language_id][3]: "{} {}{}".format(job[3], day_label[language_id], day_plural_label[language_id] if job[3] > 1 else ""),
+ jobs_columns[language_id][4]: region_text[language_id][job[4]],
+ jobs_columns[language_id][5]: dt.datetime.strptime(job[5],'%Y-%m-%d %H:%M').strftime(date_format2[language_id]),
+ jobs_columns[language_id][6]: job[6]})
conn.close()
return data_from_db
@@ -739,7 +771,9 @@ layout = html.Div([
# dcc.Store stores the jobs information
dcc.Store(id='job-info'),
# dcc.Store stores the results information
- dcc.Store(id='results-info')
+ dcc.Store(id='results-info'),
+ # dcc.Store stores the plots information
+ dcc.Store(id='plot-info'),
])
@@ -820,6 +854,49 @@ def eurad_im_modal(open_button, close_button):
return False
+@callback(
+ Output("eurad_im_download_result", "data"),
+ Input("eurad_im_output_download", "n_clicks"),
+ [State("job-info", "data"),
+ State("plot-info", "data")],
+ prevent_initial_call=True
+)
+def eurad_im_output_download(download_button, job_dict, user_dict):
+ jobid = json.loads(job_dict)["jobnr"]
+ infile = str(DATA_PATH.joinpath(f'{jobid}.nc'))
+ return dcc.send_file(
+ infile
+ )
+
+
+@callback(
+ Output("eurad_im_download_plots", "data"),
+ Input("eurad_im_plots_download", "n_clicks"),
+ [State("job-info", "data"),
+ State("plot-info", "data")],
+ prevent_initial_call=True
+)
+def eurad_im_plots_download(download_button, job_dict, plot_dict):
+ jobid = json.loads(job_dict)["jobnr"]
+ station = json.loads(plot_dict)["station"]
+ species = json.loads(plot_dict)["variable"]
+ timestamp = json.loads(plot_dict)["time_step"]
+
+ # file names according to users selection
+ infile1 = f'job_{jobid}_station_{station}_species_{species}_time_{timestamp}.png'
+ infile2 = f'job_{jobid}_time_{timestamp}_species_{species}_station_{station}.png'
+ files = [infile1, infile2]
+ zipname = str(ASSETS_PATH.joinpath(f'job_{jobid}_time_{timestamp}_species_{species}_station_{station}.zip'))
+
+ zipf = zipfile.ZipFile(zipname, 'w', zipfile.ZIP_DEFLATED)
+ for file in files:
+ zipf.write(str(ASSETS_PATH.joinpath(file)),file)
+ zipf.close()
+ return dcc.send_file(
+ zipname
+ )
+
+
@callback(
Output("eurad_im_output_modal", "is_open"),
Input("eurad_im_output_close", "n_clicks"),
@@ -914,8 +991,8 @@ def postprocess_job(rows, derived_virtual_selected_rows, users_dict):
eurad_scen_output_modal_isopen = False
if derived_virtual_selected_rows != []:
status = rows[derived_virtual_selected_rows[0]][jobs_columns[language_id][1]]
- application = rows[derived_virtual_selected_rows[0]][jobs_columns[language_id][2]]
- jobnr = rows[derived_virtual_selected_rows[0]][jobs_columns[language_id][0]]
+ application = rows[derived_virtual_selected_rows[0]][jobs_columns[language_id][0]]
+ jobnr = rows[derived_virtual_selected_rows[0]][jobs_columns[language_id][6]]
if status == status_text[language_id][0]:
eurad_im_output_modal_isopen = (application == application_text[language_id][0])
ml_fcast_output_modal_isopen = (application == application_text[language_id][1])