From 09e7fa2e650abf166a641a9c12881d19e5475e50 Mon Sep 17 00:00:00 2001
From: Caroline DE POURTALES <cdepourt@montana.irit.fr>
Date: Tue, 14 Jun 2022 10:46:07 +0200
Subject: [PATCH] adding callbacks chnaged with buttons
---
app.py | 37 +---
assets/header.css | 15 ++
callbacks.py | 335 +++++++++++++++++--------------
pages/application/application.py | 33 ++-
requirements.txt | 5 +-
5 files changed, 217 insertions(+), 208 deletions(-)
diff --git a/app.py b/app.py
index 41087dc..d04a864 100644
--- a/app.py
+++ b/app.py
@@ -1,50 +1,17 @@
# Run this app with `python app.py` and
# visit http://127.0.0.1:8050/ in your web browser.
-import json
-
import dash
import dash_bootstrap_components as dbc
from dash import dcc, html
-
from callbacks import register_callbacks
-from pages.application.application import Application, Model, View
-from utils import extract_data
app = dash.Dash(__name__, external_stylesheets=[dbc.themes.LUX], suppress_callback_exceptions=True,
meta_tags=[{'name': 'viewport', 'content': 'width=device-width, initial-scale=1'}])
+app.config.suppress_callback_exceptions = True
#################################################################################
############################# Layouts ###########################################
#################################################################################
-models_data = open('data_retriever.json')
-data = json.load(models_data)["data"]
-
-# For home directory
-welcome_message = html.Div(html.Iframe(
- src=app.get_asset_url("welcome.html"),
- style={"height": "1067px", "width": "100%"},
-))
-page_home = dbc.Row([welcome_message])
-
-# For course directory
-course_data_format = html.Div(html.Iframe(
- src=app.get_asset_url("course_data_format.html"),
- style={"height": "1067px", "width": "100%"},
-))
-course_decision_tree = html.Iframe(
- src="assets/course_decision_tree.html",
- style={"height": "1067px", "width": "100%"},
-)
-main_course = dcc.Tabs(children=[
- dcc.Tab(label='Data format', children=[course_data_format]),
- dcc.Tab(label='Course Decision Tree', children=[course_decision_tree])])
-page_course = dbc.Row([main_course])
-
-# For the application
-names_models, dict_components, dic_solvers, dic_xtypes = extract_data(data)
-model_application = Model(names_models, dict_components, dic_solvers, dic_xtypes)
-view_application = View(model_application)
-page_application = Application(view_application)
server = app.server
@@ -67,7 +34,7 @@ app.layout = html.Div([
#################################################################################
################################# Callback for the app ##########################
#################################################################################
-register_callbacks(page_home, page_course, page_application, app)
+register_callbacks(app)
#################################################################################
################################# Launching app #################################
diff --git a/assets/header.css b/assets/header.css
index 9005062..97a186c 100644
--- a/assets/header.css
+++ b/assets/header.css
@@ -80,6 +80,21 @@ div.sidebar.col-3 {
background-color: rgb(26,26,26);
}
+.sidebar .button{
+ display: block;
+ margin-left: auto;
+ margin-right: auto;
+ width: 50%;
+ height: 30px;
+ border-width: 1px;
+ border-radius: 5px;
+ text-align: center;
+ align: center;
+ color:rgb(255, 255, 255);
+ font-weight: 400;
+ background-color: rgb(26,26,26);
+}
+
.sidebar .has-value.Select--single > .Select-control .Select-value .Select-value-label, .has-value.is-pseudo-focused.Select--single > .sidebar .Select-control .Select-value .Select-value-label {
color:rgb(255, 255, 255);
}
diff --git a/callbacks.py b/callbacks.py
index 4894d75..47e3897 100644
--- a/callbacks.py
+++ b/callbacks.py
@@ -1,38 +1,51 @@
import ast
-
+import json
import dash
from dash.dependencies import Input, Output, State
import dash_bootstrap_components as dbc
from dash import Input, Output, State, html
+from dash import dcc
from utils import parse_contents_graph, parse_contents_instance, parse_contents_data
+from pages.application.application import Model, View
+from utils import extract_data
from pages.application.RandomForest.utils import xrf
from pages.application.RandomForest.utils.xrf import *
-
sys.modules['xrf'] = xrf
-def register_callbacks(page_home, page_course, page_application, app):
+def register_callbacks(app):
page_list = ['home', 'course', 'application']
- ####### Creates alerts when callback fails #########
+ # For home directory
+ page_home = dbc.Row([])
+ # For course directory
+ main_course = dcc.Tabs(children=[
+ dcc.Tab(label='Data format', children=[]),
+ dcc.Tab(label='Course Decision Tree', children=[])])
+ page_course = dbc.Row([main_course])
+
+ models_data = open('data_retriever.json')
+ data = json.load(models_data)["data"]
+ # For the application
+ names_models, dict_components, dic_solvers, dic_xtypes = extract_data(data)
+ model_application = Model(names_models, dict_components, dic_solvers, dic_xtypes)
+ view_application = View(model_application)
+ ####### Creates alerts when callback fails #########
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, ), ])
-
warning_selection_data = html.Div([dbc.Alert("You uploaded the model, now upload the data.",
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,
@@ -44,7 +57,17 @@ def register_callbacks(page_home, page_course, page_application, app):
color='danger',
duration=10000, ), ])
- alert_version_model = []
+ reinit = html.Div([dbc.Alert(
+ "Reinitialization caused by changing model type or pkl or data or instance.",
+ is_open=True,
+ color='info',
+ duration=5000, ), ])
+
+ init_network = html.Div([dbc.Alert(
+ "Initialization.",
+ is_open=True,
+ color='info',
+ duration=5000, ), ])
######################################################
@@ -55,7 +78,7 @@ def register_callbacks(page_home, page_course, page_application, app):
if pathname == '/':
return page_home
if pathname == '/application':
- return page_application.view.layout
+ return view_application.layout
if pathname == '/course':
return page_course
@@ -67,6 +90,7 @@ def register_callbacks(page_home, page_course, page_application, app):
active_link = ([pathname == f'/{i}' for i in page_list])
return active_link[0], active_link[1], active_link[2]
+ # region mltype
@app.callback(Output('solver_sat', 'options'),
Output('solver_sat', 'value'),
Output('explanation_type', 'options'),
@@ -74,211 +98,217 @@ def register_callbacks(page_home, page_course, page_application, app):
Input('ml_model_choice', 'value'),
prevent_initial_call=True
)
- def update_ml_type_options(value_ml_model):
- model_application = page_application.model
- model_application.update_ml_model(value_ml_model)
+ def update_ml_type_options(ml_type):
+ model_application.update_ml_model(ml_type)
return model_application.solvers, model_application.solvers[0], model_application.xtypes, [
list(model_application.xtypes.keys())[0]]
- @app.callback(Output('pretrained_model_filename', 'children'),
- Input('ml_model_choice', 'value'),
- Input('ml_pretrained_model_choice', 'filename'),
- prevent_initial_call=True
- )
- def update_model_pretrained_name(value_ml_model, pretrained_model_filename):
+ # endregion
+
+ # region pretrained model
+ @app.callback(
+ Output('pretrained_model_filename', 'children'),
+ Input('ml_model_choice', 'value'),
+ Input('ml_pretrained_model_choice', 'contents'),
+ State('ml_pretrained_model_choice', 'filename'),
+ prevent_initial_call=True)
+ def select_model(ml_type, model, filename):
ctx = dash.callback_context
if ctx.triggered:
- ihm_id = ctx.triggered[0]['prop_id'].split('.')[0]
+ ihm_id = ctx.triggered_id
if ihm_id == 'ml_model_choice':
return None
else:
- return pretrained_model_filename
+ graph = parse_contents_graph(model, filename)
+ model_application.update_pretrained_model(graph)
+ return filename
+
+ # endregion
+
+ # region data
+ @app.callback(
+ Output('add_info_model_choice', 'on'),
+ Input('ml_model_choice', 'value'),
+ prevent_initial_call=True
+ )
+ def delete_info(ml_type):
+ model_application.update_info_needed(False)
+ return False
+
+ @app.callback(
+ Output('choice_info_div', 'hidden'),
+ Input('add_info_model_choice', 'on'),
+ prevent_initial_call=True
+ )
+ def add_model_info(add_info_model_choice):
+ model_application.update_info_needed(add_info_model_choice)
+ if add_info_model_choice:
+ return False
+ else:
+ return True
@app.callback(Output('info_filename', 'children'),
+ Output('intermediate-value-data', 'data'),
Input('ml_model_choice', 'value'),
- Input('model_info_choice', 'filename'),
+ Input('model_info_choice', 'contents'),
+ State('model_info_choice', 'filename'),
prevent_initial_call=True
)
- def update_model_info_filename(value_ml_model, model_info_filename):
+ def select_data(ml_type, data, filename):
ctx = dash.callback_context
if ctx.triggered:
- ihm_id = ctx.triggered[0]['prop_id'].split('.')[0]
+ ihm_id = ctx.triggered_id
if ihm_id == 'ml_model_choice':
- return None
+ return None, None
else:
- return model_info_filename
+ model_info = parse_contents_data(data, filename)
+ model_application.update_info(model_info)
+ return filename, model_info
+
+ # endregion
+ # region instance
@app.callback(Output('instance_filename', 'children'),
Input('ml_model_choice', 'value'),
Input('ml_pretrained_model_choice', 'contents'),
- Input('ml_instance_choice', 'filename'),
+ Input('ml_instance_choice', 'contents'),
+ State('ml_instance_choice', 'filename'),
+ Input('number_explanations', 'value'),
+ Input('explanation_type', 'value'),
+ Input('solver_sat', 'value'),
prevent_initial_call=True
)
- def update_instance_filename(value_ml_model, model_info_filename, instance_filename):
+ def select_instance(ml_type, model, instance, filename, enum, xtype, solver):
ctx = dash.callback_context
if ctx.triggered:
- ihm_id = ctx.triggered[0]['prop_id'].split('.')[0]
- if ihm_id == 'ml_model_choice':
- return None
- elif ihm_id == 'ml_pretrained_model_choice':
+ ihm_id = ctx.triggered_id
+ if ihm_id == 'ml_model_choice' or ihm_id == 'ml_pretrained_model_choice':
return None
else:
- return instance_filename
+ # Choice of number of expls
+ if ihm_id == 'number_explanations':
+ model_application.update_enum(enum)
+ # Choice of AxP or CxP
+ elif ihm_id == 'explanation_type':
+ model_application.update_xtype(xtype)
+ # Choice of solver
+ elif ihm_id == 'solver_sat':
+ model_application.update_solver(solver)
+ else:
+ instance = parse_contents_instance(instance, filename)
+ model_application.update_instance(instance)
+ return filename
- @app.callback(
- Output('choice_info_div', 'hidden'),
- Input('add_info_model_choice', 'on'),
- prevent_initial_call=True
- )
- def add_model_info(add_info_model_choice):
- model_application = page_application.model
- model_application.update_info_needed(add_info_model_choice)
- if add_info_model_choice:
- return False
- else:
- return True
+ # endregion
+ # region draw
@app.callback(
Output('graph', 'children'),
- Output('explanation', 'children'),
Input('ml_model_choice', 'value'),
Input('ml_pretrained_model_choice', 'contents'),
- State('ml_pretrained_model_choice', 'filename'),
- Input('model_info_choice', 'contents'),
+ Input('submit-model', 'n_clicks'),
State('model_info_choice', 'filename'),
- Input('ml_instance_choice', 'contents'),
- State('ml_instance_choice', 'filename'),
- Input('number_explanations', 'value'),
- Input('explanation_type', 'value'),
- Input('solver_sat', 'value'),
Input('expl_choice', 'value'),
Input('cont_expl_choice', 'value'),
Input('choice_tree', 'value'),
- prevent_initial_call=True
- )
- def update_ml_type(value_ml_model, pretrained_model_contents, pretrained_model_filename, model_info,
- model_info_filename, instance_contents, instance_filename, enum, xtype, solver, expl_choice,
- cont_expl_choice, id_tree):
+ prevent_initial_call=True)
+ def draw_model(ml_type, model, click, model_info_filename, expl_choice, cont_expl_choice, id_tree):
ctx = dash.callback_context
- if ctx.triggered:
- ihm_id = ctx.triggered[0]['prop_id'].split('.')[0]
- model_application = page_application.model
-
- # Choice of model
- if ihm_id == 'ml_model_choice':
- 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.update_info(model_info)
+ try:
+ if ctx.triggered:
+ ihm_id = ctx.triggered_id
+ if ihm_id == "ml_model_choice" :
+ return reinit
+ elif ihm_id == "ml_pretrained_model_choice":
+ return init_network
+ elif ihm_id == "submit-model":
if model_application.ml_model is None:
- return warning_selection_model, None
- elif model_application.pretrained_model is not None:
- model_application.update_pretrained_model_layout_with_info(model_info_filename)
- return model_application.component.network, None
- else:
- return warning_selection_model, None
- except:
- return warning_selection_pretrained_model, None
-
- # Choice of pkl pretrained model
- elif ihm_id == 'ml_pretrained_model_choice':
- try:
- graph = parse_contents_graph(pretrained_model_contents, pretrained_model_filename)
- model_application.update_pretrained_model(graph)
- if not model_application.add_info:
+ return warning_selection_model
+ elif not model_application.add_info:
model_application.update_pretrained_model_layout()
- return model_application.component.network, None
+ return model_application.component.network
elif model_application.model_info is not None:
model_application.update_pretrained_model_layout_with_info(model_info_filename)
- return model_application.component.network, None
+ return model_application.component.network
else:
- return warning_selection_data, None
- except:
- return alert_network, None
-
- # Choice of instance to explain
- elif ihm_id == 'ml_instance_choice':
- 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 model_application.component.network, alert_explanation
-
- # Choice of number of expls
- elif ihm_id == 'number_explanations':
- 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':
- 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':
- try:
- model_application.update_solver(solver)
- return model_application.component.network, model_application.component.explanation
- except:
- return model_application.component.network, alert_explanation
+ return warning_selection_data
- # Choice of AxP to draw
- elif ihm_id == 'expl_choice':
- try:
+ elif ihm_id == 'expl_choice':
model_application.update_expl(expl_choice)
- return model_application.component.network, model_application.component.explanation
- except:
- return alert_network, model_application.component.explanation
+ return model_application.component.network
- # Choice of CxP to draw
- elif ihm_id == 'cont_expl_choice':
- try:
+ # Choice of CxP to draw
+ elif ihm_id == 'cont_expl_choice':
model_application.update_cont_expl(cont_expl_choice)
- return model_application.component.network, model_application.component.explanation
- except:
- return alert_network, model_application.component.explanation
+ return model_application.component.network
- # In the case of RandomForest, id of tree to choose to draw tree
- elif ihm_id == 'choice_tree':
- try:
+ # In the case of RandomForest, id of tree to choose to draw tree
+ elif ihm_id == 'choice_tree':
model_application.update_tree_to_plot(id_tree)
- return model_application.component.network, model_application.component.explanation
- except:
- return alert_network, model_application.component.explanation
+ return model_application.component.network
+ except:
+ return alert_network
+
+ # endregion
+
+ # region explanation
@app.callback(
Output('explanation', 'hidden'),
- Input('explanation', 'children'),
- Input('explanation_type', 'value'),
+ Input('submit-instance', 'n_clicks'),
+ Input('ml_model_choice', 'value'),
+ Input('ml_pretrained_model_choice', 'contents'),
+ Input('ml_instance_choice', 'contents'),
prevent_initial_call=True
)
- def show_explanation_window(explanation, explanation_type):
- if explanation is None or len(explanation_type) == 0:
- return True
- else:
- return False
+ def show_explanation_window(click, ml_type, model, instance):
+ ctx = dash.callback_context
+ if ctx.triggered:
+ ihm_id = ctx.triggered_id
+ if ihm_id == "ml_model_choice" or ihm_id == "ml_pretrained_model_choice" or ihm_id == "ml_instance_choice":
+ return True
+ elif ihm_id == "submit-instance":
+ return False
+ else :
+ return True
+
+ @app.callback(
+ Output('explanation', 'children'),
+ Input('ml_model_choice', 'value'),
+ Input('ml_pretrained_model_choice', 'contents'),
+ Input('ml_instance_choice', 'contents'),
+ Input('submit-instance', 'n_clicks'),
+ prevent_initial_call=True)
+ def run_explanation(ml_type, model, instance, click):
+ ctx = dash.callback_context
+ if ctx.triggered:
+ ihm_id = ctx.triggered_id
+ if ihm_id == "ml_model_choice" or ihm_id == "ml_pretrained_model_choice" or ihm_id == "ml_instance_choice":
+ return reinit
+ elif ihm_id == "submit-instance":
+ try:
+ if model_application.ml_model is None:
+ return warning_selection_model
+ elif model_application.pretrained_model is None:
+ return warning_selection_pretrained_model
+ elif model_application.instance is not None:
+ return model_application.component.explanation
+ else:
+ return warning_selection_data
+ except:
+ return alert_explanation
+
+ # endregion
########### RandomForest ###########
@app.callback(
Output('choosing_tree', 'hidden'),
Input('ml_model_choice', 'value'),
- Input('graph', 'children'),
prevent_initial_call=True
)
- def choose_tree_in_forest(ml_type, graph):
- if ml_type == "RandomForest" and graph is not None:
+ def choose_tree_in_forest(ml_type):
+ if ml_type == "RandomForest":
return False
else:
return True
@@ -318,5 +348,4 @@ def register_callbacks(page_home, page_course, page_application, app):
if not bool_draw:
return True, {}, {}
else:
- model_application = page_application.model
return False, model_application.options_expls, model_application.options_cont_expls
diff --git a/pages/application/application.py b/pages/application/application.py
index 4ce38fb..d952c3a 100644
--- a/pages/application/application.py
+++ b/pages/application/application.py
@@ -5,14 +5,6 @@ import dash_daq as daq
from pages.application.DecisionTree.DecisionTreeComponent import DecisionTreeComponent
from pages.application.RandomForest.RandomForestComponent import RandomForestComponent
-
-
-class Application:
- def __init__(self, view):
- self.view = view
- self.model = view.model
-
-
class Model:
def __init__(self, names_models, dict_components, dic_solvers, dic_xtypes):
@@ -55,7 +47,7 @@ class Model:
self.xtypes = self.dic_xtypes[self.ml_model]
self.xtype = [list(self.xtypes.keys())[0]]
- #init all params
+ # init all params
self.component = None
self.pretrained_model = None
self.model_info = None
@@ -77,6 +69,8 @@ class Model:
self.cont_expl = None
def update_info_needed(self, add_info):
+ if not add_info:
+ self.model_info = None
self.add_info = add_info
def update_info(self, model_info):
@@ -95,7 +89,7 @@ class Model:
def update_instance(self, instance):
self.instance = instance
list_expls, list_cont_expls = self.component.update_with_explicability(self.instance, self.enum,
- self.xtype, self.solver)
+ self.xtype, self.solver)
self.options_expls = {}
self.options_cont_expls = {}
for i in range(len(list_expls)):
@@ -106,7 +100,7 @@ class Model:
def update_enum(self, enum):
self.enum = enum
list_expls, list_cont_expls = self.component.update_with_explicability(self.instance, self.enum,
- self.xtype, self.solver)
+ self.xtype, self.solver)
self.options_expls = {}
self.options_cont_expls = {}
for i in range(len(list_expls)):
@@ -114,11 +108,10 @@ class Model:
for i in range(len(list_cont_expls)):
self.options_cont_expls[str(list_cont_expls[i])] = list_cont_expls[i]
-
def update_xtype(self, xtype):
self.xtype = xtype
list_expls, list_cont_expls = self.component.update_with_explicability(self.instance, self.enum,
- self.xtype, self.solver)
+ self.xtype, self.solver)
self.options_expls = {}
self.options_cont_expls = {}
for i in range(len(list_expls)):
@@ -129,7 +122,7 @@ class Model:
def update_solver(self, solver):
self.solver = solver
list_expls, list_cont_expls = self.component.update_with_explicability(self.instance, self.enum,
- self.xtype, self.solver)
+ self.xtype, self.solver)
self.options_expls = {}
self.options_cont_expls = {}
for i in range(len(list_expls)):
@@ -241,8 +234,12 @@ class View:
self.ml_menu_models,
self.add_model_info_choice,
self.model_info,
+ dcc.Store(id='intermediate-value-data'),
self.pretrained_model_upload,
- self.instance_upload], className="sidebar"),
+ html.Button('Submit model', id='submit-model', n_clicks=0, className="button"),
+ html.Hr(),
+ self.instance_upload,
+ html.Button('Submit instance', id='submit-instance', n_clicks=0, className="button"),], className="sidebar"),
dcc.Tab(label='Advanced Parameters', children=[
html.Br(),
self.num_explanation,
@@ -251,9 +248,9 @@ class View:
], className="sidebar")])
self.switch = html.Div(id="div_switcher_draw_expl", hidden=True,
- children=[html.Label("Draw explanations ?"),
- html.Br(),
- daq.BooleanSwitch(id='drawing_expl', on=False, color="#FFFFFF", )])
+ children=[html.Label("Draw explanations ?"),
+ html.Br(),
+ daq.BooleanSwitch(id='drawing_expl', on=False, color="#FFFFFF", )])
self.expl_choice = html.Div(id="interaction_graph", hidden=True,
children=[html.H5("Navigate through the explanations and plot them on the tree : "),
diff --git a/requirements.txt b/requirements.txt
index 7ea8eec..165350a 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -7,7 +7,7 @@ shap==0.40.0
anchor-exp==0.0.2.0
pysmt==0.9.0
anytree==2.8.0
-dash==2.1.0
+dash==2.4.0
dash_bootstrap_components==1.0.3
dash_daq==0.5.0
dash_interactive_graphviz==0.3.0
@@ -21,4 +21,5 @@ scikit_learn==1.0.2
six==1.16.0
gunicorn==20.1.0
Werkzeug==2.0.1
-pydot==1.4.2
\ No newline at end of file
+pydot==1.4.2
+Flask-Caching==1.8
\ No newline at end of file
--
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