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analytics updated
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@tawabshakeel
tawabshakeel committed Dec 7, 2020
1 parent c52cb1b commit 72f238b
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Showing 2 changed files with 75 additions and 66 deletions.
19 changes: 14 additions & 5 deletions lib/analytics.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -9,17 +9,26 @@ def __init__(self):

@staticmethod
def finding_address():
val = get_mac()
return val
try:
val = get_mac()
return val
except Exception as e:
return ''

@staticmethod
def finding_ip():
val = socket.gethostbyname(socket.gethostname())
return val
try:
val = socket.gethostbyname(socket.gethostname())
return val
except Exception as e:
return ''

@staticmethod
def finding_system():
return platform.system()
try:
return platform.system()
except Exception as e:
return ''

def __setitem__(self, key, val):
self.dict[key] = val
Expand Down
122 changes: 61 additions & 61 deletions lib/dashboard.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -224,11 +224,10 @@ def dash(self, df, mode):
dbc.Col(dbc.NavItem(dbc.NavLink("Distributions", href="/apps/distribution")),
style={'width': "150px", 'fontSize': '10px'}),
dbc.Col(dbc.NavItem(dbc.NavLink("Cohort Analysis", href="/apps/cohort")),
style={'width': "150px", 'fontSize': '10px'})
style={'width': "150px", 'fontSize': '10px'})

],


no_gutters=True,
className="ml-auto flex-nowrap mt-3 mt-md-0",
align="center"
Expand Down Expand Up @@ -284,43 +283,49 @@ def display_page(pathname):
else:
return welcome_message


welcome_message = html.Div(
[
html.Div([
html.H3("Welcome to ExplainX.ai Explainable AI Dashboard"),
html.H4("Start explaining your model by exploring one of the following options.")
], style={'margin-left':"20px"}),
], style={'margin-left': "20px"}),
html.Div([
html.Div([
html.Img(src='https://lh3.googleusercontent.com/uNkpoLQRIza6SSDk9fQed6bu6c1Q9zDkDjZqkRtF3cU97Smf2rS0soKo2ZQm32gJe8FyLYvNRUYJ-hqM7zs4esIAFchdPmgC4sHgbpxTKkGjm4dRK-NagI56K8vnXg8FH4s_Jct2RaQ', className = "global_explanation_image"),
html.Img(
src='https://lh3.googleusercontent.com/uNkpoLQRIza6SSDk9fQed6bu6c1Q9zDkDjZqkRtF3cU97Smf2rS0soKo2ZQm32gJe8FyLYvNRUYJ-hqM7zs4esIAFchdPmgC4sHgbpxTKkGjm4dRK-NagI56K8vnXg8FH4s_Jct2RaQ',
className="global_explanation_image"),

dcc.Link("Global Explanation", href="/apps/global_explanation", className="link")
], className ="welcome_box", id="global_explanation_deets"),

], className="welcome_box", id="global_explanation_deets"),

html.Div([
html.Img(src='https://lh3.googleusercontent.com/LpM-N2QavBVxlMW6vKm5fmT5Qe3mYtI2q2OQc5kgZfW4kKOFlyidgrwT5C9zB3XHZncHvlGcFl82Si7bMDQN_PtLf4PThqdEUs1UwoUPeNHs0VYY6ICKlHi44ppZLZIMQvaWI4bMqm0', className = "global_explanation_image"),
html.Img(
src='https://lh3.googleusercontent.com/LpM-N2QavBVxlMW6vKm5fmT5Qe3mYtI2q2OQc5kgZfW4kKOFlyidgrwT5C9zB3XHZncHvlGcFl82Si7bMDQN_PtLf4PThqdEUs1UwoUPeNHs0VYY6ICKlHi44ppZLZIMQvaWI4bMqm0',
className="global_explanation_image"),

dcc.Link("Local Level Explanation", href="/apps/local_explanation", className="link")

], className="welcome_box", id="local_explanation_deets"),

html.Div([
html.Img(src='https://lh6.googleusercontent.com/GXnNtGlqQcsRXugwwlZ31SwrJda4Z1WVyIi5i13vZImrUY6YgIZvM81d7zrBOh8n2jK_Lqj3BB5IqS4dU5l680-rZuu40bMXa-EAd8ag3WDIU2SNYieg0DH3e_FwUq5f2-y-X_POE-k', className = "global_explanation_image"),
html.Img(
src='https://lh6.googleusercontent.com/GXnNtGlqQcsRXugwwlZ31SwrJda4Z1WVyIi5i13vZImrUY6YgIZvM81d7zrBOh8n2jK_Lqj3BB5IqS4dU5l680-rZuu40bMXa-EAd8ag3WDIU2SNYieg0DH3e_FwUq5f2-y-X_POE-k',
className="global_explanation_image"),

dcc.Link("Feature Interactions", href="/apps/feature_interaction", className="link" )
dcc.Link("Feature Interactions", href="/apps/feature_interaction", className="link")

], className="welcome_box", id="feature_interaction_deets"),

html.Div([
html.Img(src='https://uploads-ssl.webflow.com/5edc18e72f7ba21e1ed2efae/5f519fd99580494301e67b7b_pipeline.png', className = "global_explanation_image"),
html.Img(
src='https://uploads-ssl.webflow.com/5edc18e72f7ba21e1ed2efae/5f519fd99580494301e67b7b_pipeline.png',
className="global_explanation_image"),

dcc.Link("Cohort Analysis", href="/apps/cohort", className="link")

], className="welcome_box", id="cohort_analysis_deets")
], className="main_welcome_div"),

]

)
Expand All @@ -335,8 +340,8 @@ def display_page(pathname):
"Analyze using SQL",
id="collapse-button-2",
color="link",
style={'fontSize': '10px', 'margin-top':'0px'}), style={"margin-top":"0px"}),
style={"height":"50px"}),
style={'fontSize': '10px', 'margin-top': '0px'}), style={"margin-top": "0px"}),
style={"height": "50px"}),
dbc.Collapse(html.Div([
html.Div(dcc.Input(
id='input-on-submit',
Expand Down Expand Up @@ -366,8 +371,8 @@ def display_page(pathname):
"View Your Data",
id="collapse-button",
color="link",
style={'fontSize': '10px'}), style={"margin-top":"0px"}),
style={"height":"50px"}),
style={'fontSize': '10px'}), style={"margin-top": "0px"}),
style={"height": "50px"}),
dbc.Collapse(html.Div([
html.H4('',
style=style1),
Expand Down Expand Up @@ -463,42 +468,39 @@ def toggle_collapse(n, is_open):
return not is_open
return is_open

#Cohort Analysis - Callbacks
# Cohort Analysis - Callbacks
@app.callback(
Output("modal", "is_open"),
[Input("open", "n_clicks"), Input("close", "n_clicks")],
[State("modal", "is_open")],
prevent_initial_call=True)
Output("modal", "is_open"),
[Input("open", "n_clicks"), Input("close", "n_clicks")],
[State("modal", "is_open")],
prevent_initial_call=True)
def toggle_modal(n1, n2, is_open):
if n1 or n2:
return not is_open
return is_open

@app.callback(
[Output("cohort-metrics-div", "children"),
Output("cohort-details", "children"),
Output("cohort-graph", "children")],
[Input("add-cohort","n_clicks"),
Input("remove-cohort","n_clicks"),
Input("x-axis","value")],
[State("demo-dropdown","value"),
State("demo-operators", "value"),
State("demo-values", "value")])
[Output("cohort-metrics-div", "children"),
Output("cohort-details", "children"),
Output("cohort-graph", "children")],
[Input("add-cohort", "n_clicks"),
Input("remove-cohort", "n_clicks"),
Input("x-axis", "value")],
[State("demo-dropdown", "value"),
State("demo-operators", "value"),
State("demo-values", "value")])
def cohort_metrics_details(add_cohort, remove_cohort, x_axis, var_name, operator, value):
changed_id = [p['prop_id'] for p in dash.callback_context.triggered][0]
if 'remove-cohort' in changed_id:
ca.remove_cohort()
fig = ca.cohort_graph(x_axis)
return ca.cohort_metrics_details(), ca.cohort_details(), dcc.Graph(figure=fig),
return ca.cohort_metrics_details(), ca.cohort_details(), dcc.Graph(figure=fig),
else:
ca.add_cohort_metrics(df, var_name, operator,value, self.param["is_classification"])
ca.add_cohort_metrics(df, var_name, operator, value, self.param["is_classification"])
cohort = ca.add_cohort(df, x_axis, var_name, operator, value)
fig = ca.cohort_graph(x_axis)
return ca.cohort_metrics_details(), ca.cohort_details(), dcc.Graph(figure=fig)




# SQL - Data Input Callback
@app.callback(
dash.dependencies.Output('sql-query-button', 'children'),
Expand All @@ -507,7 +509,6 @@ def cohort_metrics_details(add_cohort, remove_cohort, x_axis, var_name, operator
def update_output(n_clicks, value):
sql_query = f'{value}'
return sql_query


# What-If Form CallBack
@app.callback(
Expand Down Expand Up @@ -555,25 +556,22 @@ def update_impact_graph(*values):
df.columns = self.param["columns"]
array = self.calculate_prediction_shap(df)

#Y_Pred
#Probability_
# Y_Pred
# Probability_
if self.param["is_classification"]:
y_and_prob=[]
y_and_prob = []
y_and_prob.append(int(array["y_prediction"]))
y_and_prob.append(round(float(array["Probability_"+str(int(array["y_prediction"])) ]),2))
y_and_prob.append(round(float(array["Probability_" + str(int(array["y_prediction"]))]), 2))
else:
y_and_prob = []
y_and_prob.append(round(float(array["y_prediction"]),2))
y_and_prob.append(round(float(array["y_prediction"]), 2))

# figure, dat = g.feature_impact_old(array)
figure, dat = g.local_feature_impact_graph(array)
message = self.insights.insight_2_local_feature_impact(dat, y_and_prob)



return figure, message[0], message[1], message[2], message[3]


# Prototypical Analysis
"""
Change this. Take input from what-if from
Expand Down Expand Up @@ -606,7 +604,7 @@ def update_table(*values):
sample_row = sample_row.to_frame()
sample_row.rename(columns={sample_row.columns[0]: "orig"}, inplace=True)
sample_row.reset_index(inplace=True)
#print(sample_row.columns)
# print(sample_row.columns)
dat = pd.merge(dat, sample_row, on=['index'], how='left')
dat['orig'] = dat['orig'].astype(float)
for i in list(dat.columns):
Expand Down Expand Up @@ -638,7 +636,7 @@ def update_graphs(sql_query, value):
graph_type = "feature_importance"
dff = self.caching_data_manager(df, sql_query, graph_type, g.feature_importance)
message = self.insights.insight_1_feature_imp(dff)
figure = g.global_feature_importance_graph(dff, self.param["is_classification"])
figure = g.global_feature_importance_graph(dff, self.param["is_classification"])
return figure, message[0]

# Global Feature Impact
Expand All @@ -661,7 +659,7 @@ def update_graphs(sql_query, value):
@app.callback(
Output('indicator-graphic', 'figure'),
[Input('xaxis-column', 'value'),
# Input('yaxis-column', 'value'),
# Input('yaxis-column', 'value'),
Input('third-axis', 'value'),
Input('sql-query-button', 'children')])
def update_graph(xaxis_column_name, third_axis_name, sql_query):
Expand All @@ -675,7 +673,7 @@ def update_graph(xaxis_column_name, third_axis_name, sql_query):
graph_type = 'pdp'
df3 = self.caching_data_manager(df, sql_query, graph_type, g.partial_dependence_plot)
print(df3)
fig = g.pdp_plot(df3, df3[xaxis_column_name], df3[xaxis_column_name+"_impact"], df3[third_axis_name])
fig = g.pdp_plot(df3, df3[xaxis_column_name], df3[xaxis_column_name + "_impact"], df3[third_axis_name])
return fig

# Summary Plot
Expand All @@ -684,7 +682,6 @@ def update_graph(xaxis_column_name, third_axis_name, sql_query):
[Input('sql-query-button', 'children'),
Input('xaxis-column-test', 'value')])
def update_graph2(sql_query, value):


g = plotly_graphs()
graph_type = 'summary_plot'
Expand All @@ -710,48 +707,52 @@ def update_graph2(xaxis_column_name, plot_type, sql_query):
num_variables.append(i)

if plot_type == "Histogram":

return px.histogram(df3, x=xaxis_column_name, marginal="box", template="plotly_white")
else:
for i in cat_variables:
return px.violin(df3, x=xaxis_column_name, box=True, points='all', template="plotly_white")
else:
return px.violin(df3, y=xaxis_column_name, box=True, points='all', template="plotly_white")


# Port Finder
port = 8080
debug_value= False

debug_value = False

if mode == "inline":
try:
app.run_server(mode="inline", port=port, debug=debug_value, dev_tools_ui=debug_value,
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging = True, dev_tools_hot_reload=True)
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging=True,
dev_tools_hot_reload=True)
except:
port = self.find_free_port()
app.run_server(mode="inline", port=port, debug=debug_value, dev_tools_ui=debug_value,
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging = True, dev_tools_hot_reload=True)
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging=True,
dev_tools_hot_reload=True)
else:
try:
app.run_server(host='0.0.0.0', port=port, debug=debug_value, dev_tools_ui=debug_value,
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging = True, dev_tools_hot_reload=True)
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging=True,
dev_tools_hot_reload=True)
except:
# try different ip in case 0.0.0.0 does not work
try:
try:
port = self.find_free_port()
app.run_server(host='0.0.0.0', port=port, debug=debug_value, dev_tools_ui=debug_value,
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging = True, dev_tools_hot_reload=True)
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging=True,
dev_tools_hot_reload=True)
except:
port = self.find_free_port()
app.run_server(host='0.0.0.0', port=port, debug=debug_value, dev_tools_ui=debug_value,
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging = True, dev_tools_hot_reload=True)
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging=True,
dev_tools_hot_reload=True)
except:
try:
port = self.find_free_port()
app.run_server(host='127.0.0.1', port=port, debug=debug_value, dev_tools_ui=debug_value,
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging = True, dev_tools_hot_reload=True)
dev_tools_props_check=debug_value, dev_tools_silence_routes_logging=True,
dev_tools_hot_reload=True)
except:
print("Please restart Jupyter Notebook or Python IDE.")
return False
Expand Down Expand Up @@ -812,7 +813,7 @@ def calculate_prediction_shap(self, df):
# prediction col
df_final["y_prediction"] = prediction_col

if is_classification==True:
if is_classification == True:

# find and add probabilities in the dataset.
prediction_col_prob = self.param["model"].predict_proba(df.to_numpy())
Expand All @@ -821,7 +822,6 @@ def calculate_prediction_shap(self, df):
for c in pd_prediction_col_prob.columns:
df_final["Probability_" + str(c)] = list(pd_prediction_col_prob[c])


return df_final

def calculate_prediction(self, df):
Expand Down

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