pythonplotlyplotly-dash
Include figure parameters as a callback option - Dash
I've got a callback function that changes a figure to various spatial maps. When hexbin is selected, I'm aiming to include parameters to alter the figure.
Is it possible to only insert these parameters when the hexbin option is selected?
import dash
from dash import dcc
from dash import html
from dash.dependencies import Input, Output
import dash_bootstrap_components as dbc
import plotly.express as px
import plotly.graph_objs as go
import pandas as pd
import numpy as np
import plotly.figure_factory as ff
data = pd.DataFrame({
'Cat': ['t','y','y','y','f','f','j','k','k','k','s','s','s','s'],
'LAT': [5,6,4,5,4,7,8,9,5,6,18,17,15,16],
'LON': [10,11,9,11,10,8,8,5,8,7,18,16,16,17],
})
N = 30
data = pd.concat([data] * N, ignore_index=True)
data['Color'] = data['Cat'].map(dict(zip(data['Cat'].unique(), px.colors.qualitative.Plotly[:len(data['Cat'].unique())])))
Color = data['Color'].unique()
Type_Category = data['Cat'].unique()
Type_cats = dict(zip(Type_Category, Color))
external_stylesheets = [dbc.themes.SPACELAB, dbc.icons.BOOTSTRAP]
app = dash.Dash(__name__, external_stylesheets = external_stylesheets)
filtering = html.Div(children=[
html.Div(children=[
html.Label('Cats', style = {'paddingTop': '2rem', 'display': 'inline-block'}),
dcc.Checklist(
id = 'Cats',
options = [
{'label': 't', 'value': 't'},
{'label': 'y', 'value': 'y'},
{'label': 'f', 'value': 'f'},
{'label': 'j', 'value': 'j'},
{'label': 'k', 'value': 'k'},
{'label': 's', 'value': 's'},
],
value = ['t', 'y', 'f', 'j', 'k', 's'],
),
html.Label('Type', style = {'paddingTop': '2rem', 'display': 'inline-block'}),
dcc.RadioItems(['Scatter', 'Heatmap', 'Hexbin'], 'Scatter',
inline = True, id = 'maps'),
html.Label('Opacity', style = {'paddingTop': '2rem', 'display': 'inline-block'}),
dcc.Slider(0, 1, 0.1,
value = 0.5,
id = 'my-slider'),
html.Label('nx_hexagon', style = {'paddingTop': '2rem', 'display': 'inline-block'}),
dcc.Slider(0, 40, 5,
value = 20,
id = 'my-slider'),
html.Label('min count', style = {'paddingTop': '2rem', 'display': 'inline-block'}),
dcc.Slider(0, 5, 1,
value = 0,
id = 'my-slider'
),
],
)
])
app.layout = dbc.Container([
dbc.Row([
dbc.Col([
html.Div(filtering),
], width = 2),
dbc.Col([
html.Div(dcc.Graph())
]),
dbc.Col([
html.Div(dcc.Graph(id = 'chart'))
])
])
], fluid = True)
df = data
@app.callback(
Output('chart', 'figure'),
[Input("Cats", "value"),
Input("maps", "value")])
def scatter_chart(cats,maps):
if maps == 'Scatter':
dff = df[df['Cat'].isin(cats)]
data = px.scatter_mapbox(data_frame = dff,
lat = 'LAT',
lon = 'LON',
color = 'Cat',
color_discrete_map = Type_cats,
zoom = 3,
mapbox_style = 'carto-positron',
)
fig = go.Figure(data = data)
elif maps == 'Heatmap':
dff = df[df['Cat'].isin(cats)]
# Creating 2-D grid of features
[X, Y] = np.meshgrid(dff['LAT'], dff['LON'])
Z = np.cos(X / 2) + np.sin(Y / 4)
fig = go.Figure(data =
go.Densitymapbox(lat = dff['LON'],
lon = dff['LAT'],
z = Z,
)
)
fig.update_layout(mapbox_style = "carto-positron")
else:
dff = df[df['Cat'].isin(cats)]
fig = ff.create_hexbin_mapbox(data_frame = dff,
lat = "LAT",
lon = "LON",
)
return fig
if __name__ == '__main__':
app.run_server(debug=True, port = 8051)
Intended output when hexbin is selected:
Solution
I think you just use slider value as Input and then when you choosing Hexbin, you can pass it to graph setting. Something as below:
import dash
from dash import dcc
from dash import html
from dash.dependencies import Input, Output
import dash_bootstrap_components as dbc
import plotly.express as px
import plotly.graph_objs as go
import pandas as pd
import numpy as np
import plotly.figure_factory as ff
data = pd.DataFrame({
'Cat': ['t', 'y', 'y', 'y', 'f', 'f', 'j', 'k', 'k', 'k', 's', 's', 's', 's'],
'LAT': [5, 6, 4, 5, 4, 7, 8, 9, 5, 6, 18, 17, 15, 16],
'LON': [10, 11, 9, 11, 10, 8, 8, 5, 8, 7, 18, 16, 16, 17],
})
N = 30
data = pd.concat([data] * N, ignore_index=True)
data['Color'] = data['Cat'].map(
dict(zip(data['Cat'].unique(), px.colors.qualitative.Plotly[:len(data['Cat'].unique())])))
Color = data['Color'].unique()
Type_Category = data['Cat'].unique()
Type_cats = dict(zip(Type_Category, Color))
external_stylesheets = [dbc.themes.SPACELAB, dbc.icons.BOOTSTRAP]
app = dash.Dash(__name__, external_stylesheets=external_stylesheets,suppress_callback_exceptions=True)
app.layout = dbc.Container([
dbc.Row([
dbc.Col([html.Label('Cats', style={'paddingTop': '2rem', 'display': 'inline-block'}),
dcc.Checklist(
id='Cats',
options=[
{'label': 't', 'value': 't'},
{'label': 'y', 'value': 'y'},
{'label': 'f', 'value': 'f'},
{'label': 'j', 'value': 'j'},
{'label': 'k', 'value': 'k'},
{'label': 's', 'value': 's'},
],
value=['t', 'y', 'f', 'j', 'k', 's'],
),
html.Label('Type', style={'paddingTop': '2rem', 'display': 'inline-block'}),
dcc.RadioItems(['Scatter', 'Heatmap', 'Hexbin'], 'Scatter',
inline=True, id='maps'),
html.Div(id='filter')
], width=2),
dbc.Col([
html.Div(dcc.Graph())
], width=5),
dbc.Col([
html.Div(dcc.Graph(id='chart'))
], width=5)
])
], fluid=True)
df = data
@app.callback(
Output('filter', 'children'),
[Input("maps", "value")])
def update_slider(maps):
if maps == 'Hexbin':
return html.Div([html.Label('Opacity', style={'paddingTop': '2rem', 'display': 'inline-block'}),
dcc.Slider(0, 1, 0.1,
value=0.5,
id='my-slider'),
html.Label('nx_hexagon', style={'paddingTop': '2rem', 'display': 'inline-block'}),
dcc.Slider(0, 40, 5,
value=20,
id='my-slider2'),
html.Label('min count', style={'paddingTop': '2rem', 'display': 'inline-block'}),
dcc.Slider(0, 5, 1,
value=0,
id='my-slider3'
)])
else:
return html.Div([html.Div(id='my-slider'),
html.Div(id='my-slider2'),
html.Div(id='my-slider3')])
@app.callback(
Output('chart', 'figure'),
[Input("Cats", "value"),
Input("maps", "value"),
Input("my-slider", "value"),
Input("my-slider2", "value"),
Input("my-slider3", "value")],prevent_initial_call=True)
def scatter_chart(cats, maps, my_slider, my_slider2, my_slider3):
if maps == 'Scatter':
dff = df[df['Cat'].isin(cats)]
data = px.scatter_mapbox(data_frame=dff,
lat='LAT',
lon='LON',
color='Cat',
color_discrete_map=Type_cats,
zoom=3,
mapbox_style='carto-positron',
)
fig = go.Figure(data=data)
return fig
elif maps == 'Heatmap':
dff = df[df['Cat'].isin(cats)]
# Creating 2-D grid of features
[X, Y] = np.meshgrid(dff['LAT'], dff['LON'])
Z = np.cos(X / 2) + np.sin(Y / 4)
fig = go.Figure(data=
go.Densitymapbox(lat=dff['LON'],
lon=dff['LAT'],
z=Z,
)
)
fig.update_layout(mapbox_style="carto-positron")
return fig
elif maps == 'Hexbin':
dff = df[df['Cat'].isin(cats)]
try:
fig = ff.create_hexbin_mapbox(data_frame=dff,
lat="LAT",
lon="LON",
opacity=my_slider,
nx_hexagon=my_slider2,
min_count=my_slider3)
fig.update_layout(mapbox_style="open-street-map")
return fig
except TypeError:
pass
if __name__ == '__main__':
app.run_server(debug=True, port=8051)
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