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Commit 38025bc8 authored by Caroline DE POURTALES's avatar Caroline DE POURTALES
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adding alerts

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with 62 additions and 56 deletions
callbacks.py
+ 62
− 56
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import dash
from dash.dependencies import Input, Output, State
from dash.exceptions import PreventUpdate
import dash_bootstrap_components as dbc
from dash import Input, Output, State, html
......@@ -13,10 +12,16 @@ sys.modules['xrf'] = xrf
####### Creates alerts when callback fails #########
alert_selection_model = html.Div([dbc.Alert("You didn't choose a king of Machine Learning model first..",
warning_selection_model = html.Div([dbc.Alert("You didn't choose a king of Machine Learning model first.",
is_open=True,
color='warning',
duration=10000, ), ])
warning_selection_pretrained_model = html.Div([dbc.Alert("You uploaded the data, now upload the pretrained model.",
is_open=True,
color='warning',
duration=10000, ), ])
alert_network = html.Div([dbc.Alert("There was a problem while computing the graph, read the documentation. \
You might have forgotten to upload the data for Random Forest or you tried to upload an unknown format.",
is_open=True,
......@@ -120,89 +125,90 @@ def register_callbacks(page_home, page_course, page_application, app):
model_application.update_ml_model(value_ml_model)
return None, None
# Choice of information for the model - data, feature mapping ...
elif ihm_id == 'model_info_choice':
try :
model_info = parse_contents_data(model_info, model_info_filename)
model_application.model_info = model_info
if model_application.ml_model is None:
return warning_selection_model, None
model_application.update_pretrained_model_layout_with_info(model_info, model_info_filename)
return model_application.component.network, None
except:
return warning_selection_pretrained_model, None
# Choice of pkl pretrained model
elif ihm_id == 'ml_pretrained_model_choice':
if model_application.ml_model is None:
return alert_selection_model, None
else:
try:
graph = parse_contents_graph(pretrained_model_contents, pretrained_model_filename)
model_application.update_pretrained_model(graph)
if not model_application.add_info:
model_application.update_pretrained_model_layout()
return model_application.component.network, None
else:
if model_application.model_info is None:
return alert_network, None
else:
model_application.update_pretrained_model_layout_with_info(model_application.model_info,
model_info_filename)
return model_application.component.network, None
except:
return alert_network, None
# Choice of information for the model
elif ihm_id == 'model_info_choice':
model_info = parse_contents_data(model_info, model_info_filename)
model_application.model_info = model_info
if model_application.ml_model is None or model_application.pretrained_model is None:
raise PreventUpdate
model_application.update_pretrained_model_layout_with_info(model_info, model_info_filename)
return model_application.component.network, None
try:
graph = parse_contents_graph(pretrained_model_contents, pretrained_model_filename)
model_application.update_pretrained_model(graph)
if not model_application.add_info:
model_application.update_pretrained_model_layout()
return model_application.component.network, None
else:
model_application.update_pretrained_model_layout_with_info(model_application.model_info,
model_info_filename)
return model_application.component.network, None
except:
return alert_network, None
# Choice of instance to explain
elif ihm_id == 'ml_instance_choice':
if model_application.ml_model is None or model_application.pretrained_model is None or model_application.enum <= 0 or model_application.xtype is None:
raise PreventUpdate
try:
instance = parse_contents_instance(instance_contents, instance_filename)
model_application.update_instance(instance)
return model_application.component.network, model_application.component.explanation
except:
return alert_network, alert_explanation
return model_application.component.network, alert_explanation
# Choice of number of expls
elif ihm_id == 'number_explanations':
if model_application.ml_model is None or model_application.pretrained_model is None or model_application.instance is None or model_application.solver is None or model_application.xtype is None:
raise PreventUpdate
model_application.update_enum(enum)
return model_application.component.network, model_application.component.explanation
try:
model_application.update_enum(enum)
return model_application.component.network, model_application.component.explanation
except:
return model_application.component.network, alert_explanation
# Choice of AxP or CxP
elif ihm_id == 'explanation_type':
if model_application.ml_model is None or model_application.pretrained_model is None or model_application.instance is None or model_application.enum <= 0 or model_application.solver is None:
raise PreventUpdate
model_application.update_xtype(xtype)
return model_application.component.network, model_application.component.explanation
try:
model_application.update_xtype(xtype)
return model_application.component.network, model_application.component.explanation
except:
return model_application.component.network, alert_explanation
# Choice of solver
elif ihm_id == 'solver_sat':
if model_application.ml_model is None or model_application.pretrained_model is None or model_application.instance is None or model_application.enum <= 0 or model_application.xtype is None:
raise PreventUpdate
model_application.update_solver(solver)
return model_application.component.network, model_application.component.explanation
try:
model_application.update_solver(solver)
return model_application.component.network, model_application.component.explanation
except:
return model_application.component.network, alert_explanation
# Choice of AxP to draw
elif ihm_id == 'expl_choice':
if model_application.ml_model is None or model_application.pretrained_model is None or model_application.instance is None or model_application.enum <= 0 or model_application.xtype is None:
raise PreventUpdate
model_application.update_expl(expl_choice)
return model_application.component.network, model_application.component.explanation
try :
model_application.update_expl(expl_choice)
return model_application.component.network, model_application.component.explanation
except:
return model_application.component.network, alert_explanation
# Choice of CxP to draw
elif ihm_id == 'cont_expl_choice':
if model_application.ml_model is None or model_application.pretrained_model is None or model_application.instance is None or model_application.enum <= 0 or model_application.xtype is None:
raise PreventUpdate
model_application.update_cont_expl(cont_expl_choice)
return model_application.component.network, model_application.component.explanation
try:
model_application.update_cont_expl(cont_expl_choice)
return model_application.component.network, model_application.component.explanation
except:
return model_application.component.network, alert_explanation
# In the case of RandomForest, id of tree to choose to draw tree
elif ihm_id == 'choice_tree':
if model_application.ml_model is None or model_application.pretrained_model is None:
raise PreventUpdate
model_application.update_tree_to_plot(id_tree)
return model_application.component.network, model_application.component.explanation
try :
model_application.update_tree_to_plot(id_tree)
return model_application.component.network, model_application.component.explanation
except:
return model_application.component.network, alert_explanation
@app.callback(
Output('explanation', 'hidden'),
......
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