value = type(value)
return value
@app.callback([Output(prefix + 'csv_file_upload_output', 'children'), Output(prefix + 'csv_file_path', 'value')],
[Input(prefix + 'csv_file_upload', 'filename')])
def update_output(csv_file, *args):
if csv_file is None or len(csv_file) == 0:
return '', ''
return html.Span(children=csv_file), DOWNLOADS_PATH + csv_file
@app.callback(
Output(prefix + 'results_container', 'children'),
[Input(prefix + 'button', 'n_clicks')],
gui_utils.get_states(parameters, False, prefix))
def run(n_clicks, *args):
csv_file = get_state_field('csv_file_path', prefix=prefix, type=str)
if csv_file == '':
return []
state_params = dash.callback_context.states
# remove prefix and .value from
params = {}
for key in state_params:
params[key.replace(prefix, '').replace('.value', '')] = state_params[key]
time_series_orig = pd.read_csv(csv_file, parse_dates=True, index_col=[0])
time_series = time_series_orig
locations = pd.read_csv(csv_file.split('.')[0] + '-locations.csv', parse_dates=True, index_col=[0])
res = two_step_regression_handler(time_series, 60, locations, csv_file)
"RespSupport": {"phrase": ("need respiratory support","needing"), "classifiers": (classifiers[12], classifiers[13])},
}
to_use = {"positive test": ["Hosp", "IC1", "Outcome1"], "hospitalized": ["IC2", "RespSupport","Outcome2"],
"intensive care": ["Outcome3"]}
translations = {"Hosp": "Hospitalization", "IC1": "Intensive Care", "IC2": "Intensive Care", "Outcome1": "Outcome",
"Outcome2": "Outcome", "Outcome3": "Outcome","RespSupport": "Respiratory Support"}
age_mean= 48.026216
age_std = 24.804093
''' ==========================='''
''' ====== C: UPDATE GUI ====== '''
''' =========================== '''
app = dash.Dash(__name__, assets_folder = 'assets', include_assets_files = True)
@app.callback(Output('result','children'),[Input('button','n_clicks')],gui_utils.get_states(parameters)) #[State('stage','value'),State('age','value'),State('gender','value'),State('comorbidities','value')])
def update_map(inp,*args):
states = dash.callback_context.states
print("states",states)
if inp is None: return result
stage = states['stage.value']
age = (int(states['age.value']) - age_mean) / age_std
gender = 0 if states['gender.value'] == "female" else 1
data = [age, gender]
sel_comorbidities = states['comorbidities.value']
#################################################
if stage == "hospitalized" or stage == "intensive care": data.append(1)
if stage == "intensive care": data.append(1)
for comorb in comorbidities:
if comorb in sel_comorbidities: data.append(1)
else: data.append(0)
hidden=True)
res.append(children)
return res
@app.callback([
Output(prefix + 'charts', 'children'),
Output(prefix + 'biclusters', 'options'),
Output(prefix + 'attributes', 'options'),
Output(prefix + 'biclusters_cache', 'value'),
Output(prefix + 'series_cache', 'value')
], [
Input(prefix + 'button', 'n_clicks'),
Input(prefix + 'attributes', 'value')
], gui_utils.get_states(parameters + get_all_method_params(), False, prefix))
def run_discovery(n_clicks, attributes, *args):
attributes_opts = []
if not n_clicks:
return [[], default_biclusters_options, attributes_opts, '', '']
trigger = dash.callback_context.triggered[0]
data_cached = False
if 'button' in trigger['prop_id']:
attributes = None
else:
data_cached = True
# Date range
start_date = pd.to_datetime(get_state_field('date', 'start_date', prefix))
end_date = pd.to_datetime(get_state_field('date', 'end_date', prefix))