With the first question, I think you should find the max value and min value of your data and then pass it to zmin and zmax as Abdel’s suggestions. Something as below:
For second question, I think you should add one more Dropdown, and then use value from other Dropdown to return its value and then pass it to colorscale setting of your fig.
Full code as below:
import dash
import dash_html_components as html
import plotly.graph_objects as go
import dash_core_components as dcc
from dash.dependencies import Input, Output
import pandas as pd
import dash_bootstrap_components as dbc
import numpy as np
import plotly.express as px
import dash_table
#############################################################################################################################################
df1 = pd.read_excel('2022_RGT.xlsx')
#####################
colorscales = px.colors.named_colorscales()
#############################################################################################################################################
app = dash.Dash(external_stylesheets=[dbc.themes.BOOTSTRAP])
PLOTLY_LOGO = "https://ifc.nkn.uidaho.edu/static/img/ifc_logo_official.png"
app.title = 'IFC RGT DASH'
server = app.server
navbar = dbc.Navbar( id = 'navbar', children = [
dbc.Row([
dbc.Col(html.Img(src = PLOTLY_LOGO, height = "100px")),
dbc.Col(
dbc.NavbarBrand('#UNDER CONSTRUCTION', style = {'color':'RED', 'fontSize':'20px','fontFamily':'Lato','textAlign':'center'}
), align="center"
)
],align = "center"
# no_gutters = True
),
], color = '#ffffff')
card_content_dropdwn = [
dbc.CardBody(
[
html.H4('DASHBOARD', style = {'textAlign':'center','color':'#ffffff'}),
dbc.Row([
dbc.Col([
html.H6('Year',style = {'color':'#ffffff'}),
dcc.Dropdown( id = 'dropdown_year',
options = [
{'label':i, 'value':i } for i in df1['Year'].unique()
],
value = 2022,
)
]),
dbc.Col([
html.H6('Installation',style = {'color':'#ffffff'}),
dcc.Dropdown( id = 'dropdown_Installation',
options = [
{'label':i, 'value':i } for i in df1['Installation'].unique()
],
value = 'HOODOO',
)
]),
dbc.Col([
html.H6('Metric',style = {'color':'#ffffff'}),
dcc.Dropdown( id = 'dropdown_metric',
options = [
{'label':i, 'value':i } for i in df1['Metric'].unique()
],
value = 'CAL22SP (mm)',
)
]),
dbc.Col([
html.H6('Colorscale',style = {'color':'#ffffff'}),
dcc.Dropdown( id = 'dropdown_colorscale',
options = colorscales,
value = [],
)
]),
])
]
)
]
body_app = dbc.Container([
#Link
html.Div(id = 'link_div',children = [html.A(id = 'link', children = 'IFC HOMEPAGE', href = 'https://www.uidaho.edu/cnr/intermountain-forestry-cooperative', style = {'fontSize':15})],\
style = {'textAlign':'right','font-family':'sans-serif'}),
html.H2(id = 'H1', children = 'REALIZED GENETIC GAIN TRIALS',style = {'textAlign':'center','fontWeight':'bold','font-family':'sans-serif','width':'100%','color':'#16467a'}),
html.P('(Relationship of Woods Run vs Improved Douglas-fir to Site Growth Factors)',style = {'textAlign':'center','font-family':'sans-serif','width':'100%','color':'#16467a','fontSize':'20px'}),
dbc.Row([html.Div(html.P( 'A study on the differential effects of site type on woods run and improved Douglas-fir growth and mortality. The proposed study is designed to meet the needs of IFC members identified in the Spring 2020 Research Survey. In that survey, IFC members listed Stand Establishment as their primary silvicultural research need, with understanding site effects on growth and mortality as number one priority. IFC members further wished that the IFC and IETIC could find common research areas to collaborate. We have developed a study plan to meet these expressed research needs, one which will contain three study components: 1) evaluation of site growth factors on seedling survival and growth, 2) realized gains in survival and growth as a function of first-generation improved seed, and 3) assess seedling performance following transfer from warmer/drier to cooler/moister climes.'),)],style = {'color':'#4F4F4F','font-family':'sans-serif', 'margin':5}),
dbc.Row([
dbc.Col([dbc.Card(card_content_dropdwn,style={'height':'100px'},color = '#16467a')],width=6),
], justify="center",),
html.Br(),
html.Br(),
dbc.Row([html.Div(html.H4(' Experimental Trial Plots'),
style = {'textAlign':'center','fontWeight':'bold','width':'100%','color':'#1C1C1C','font-family':'sans-serif'})]),
dbc.Row([html.Div(html.H5('Woods Run Seedlot'),
style = {'textAlign':'center','fontWeight':'bold','font-family':'sans-serif','width':'100%','color':'#363636'})]),
dbc.Row([
dbc.Col([dbc.Card(id = 'card_num1',color='#ffffff',style={'height':'350px'})],xl=3,lg=3,md = 12,sm=12,xs = 12),
dbc.Col([dbc.Card(id = 'card_num2',color='#ffffff',style={'height':'350px'})],xl=3,lg=3,md = 12,sm=12,xs = 12),
dbc.Col([dbc.Card(id = 'card_num3',color='#ffffff',style={'height':'350px'})],xl=3,lg=3,md = 12,sm=12,xs = 12),
]),
html.Br(),
dbc.Row([html.Div(html.H5('Improved Seedlot'),
style = {'textAlign':'center','fontWeight':'bold','font-family':'sans-serif','width':'100%','color':'#363636'})]),
dbc.Row([
dbc.Col([dbc.Card(id = 'card_num4',color='#ffffff',style={'height':'350px'})],xl=3,lg=3,md = 12,sm=12,xs = 12),
dbc.Col([dbc.Card(id = 'card_num5',color='#ffffff',style={'height':'350px'})],xl=3,lg=3,md = 12,sm=12,xs = 12),
dbc.Col([dbc.Card(id = 'card_num6',color='#ffffff',style={'height':'350px'})],xl=3,lg=3,md = 12,sm=12,xs = 12),
]),
html.Br(),
html.Br(),
],
style = {'backgroundColor':'#ffffff'},
fluid = True)
app.layout = html.Div(id = 'parent', children = [navbar,body_app])
@app.callback(Output('dropdown_colorscale', 'value'),
[Input('dropdown_metric','value')])
def update_color_scales(metric):
if metric == 'CAL22SP (mm)':
return 'viridis'
else:
return 'agsunset'
@app.callback([Output('card_num1', 'children'),
Output('card_num2', 'children'),
Output('card_num3', 'children'),
Output('card_num4', 'children'),
Output('card_num5', 'children'),
Output('card_num6', 'children'),
],
[Input('dropdown_year','value'),
Input('dropdown_Installation','value'),
Input('dropdown_metric','value'),
Input('dropdown_colorscale', 'value')])
def update_cards(Year,Installation,Metric,colorscales):
df1_a = df1.loc[(df1['Year']==Year)&(df1['Installation']==Installation)&(df1['Metric']==Metric)&(df1['PLOT']==1) ].reset_index()
df2_a = df1.loc[(df1['Year']==Year)&(df1['Installation']==Installation)&(df1['Metric']==Metric)&(df1['PLOT']==2)].reset_index()
df3_a = df1.loc[(df1['Year']==Year)&(df1['Installation']==Installation)&(df1['Metric']==Metric)&(df1['PLOT']==3)].reset_index()
df4_a = df1.loc[(df1['Year']==Year)&(df1['Installation']==Installation)&(df1['Metric']==Metric)&(df1['PLOT']==4)].reset_index()
df5_a = df1.loc[(df1['Year']==Year)&(df1['Installation']==Installation)&(df1['Metric']==Metric)&(df1['PLOT']==5)].reset_index()
df6_a = df1.loc[(df1['Year']==Year)&(df1['Installation']==Installation)&(df1['Metric']==Metric)&(df1['PLOT']==6)].reset_index()
value_1_max = df1_a['Value'].max()
value_2_max = df2_a['Value'].max()
value_3_max = df3_a['Value'].max()
value_4_max = df4_a['Value'].max()
value_5_max = df5_a['Value'].max()
value_6_max = df6_a['Value'].max()
value_1_min = df1_a['Value'].min()
value_2_min = df2_a['Value'].min()
value_3_min = df3_a['Value'].min()
value_4_min = df4_a['Value'].min()
value_5_min = df5_a['Value'].min()
value_6_min = df6_a['Value'].min()
max_value=max([value_1_max,value_2_max,value_3_max,value_4_max,value_5_max,value_6_max])
min_value=max([value_1_min,value_2_min,value_3_min,value_4_min,value_5_min,value_6_min])
fig = go.Figure(data=go.Heatmap(
z=df1_a['Value'],zmin=min_value, zmax=max_value,
x=df1_a['Seedlot'],
y=df1_a['Replication'],
text=df1_a['Treetag'],
colorscale=colorscales, hoverongaps = True, hovertemplate='Seedlot: %{x}<br>Tree Tag: %{text}<br>Replication: %{y}<br>Value: %{z}<extra></extra>'))
fig['layout']['yaxis']['autorange'] = "reversed"
fig.update_layout(template="plotly_white",
margin=dict(l = 20, r = 5, t = 10, b = 10),
yaxis_nticks=10,
)
fig.update_xaxes(side="top", tickangle = 270)
fig1 = go.Figure(data=go.Heatmap(
z=df2_a['Value'],zmin=min_value, zmax=max_value,
x=df2_a['Seedlot'],
y=df2_a['Replication'],
text=df2_a['Treetag'],
colorscale=colorscales, hoverongaps = True, hovertemplate='Seedlot: %{x}<br>Tree Tag: %{text}<br>Replication: %{y}<br>Value: %{z}<extra></extra>'))
fig1['layout']['yaxis']['autorange'] = "reversed"
fig1.update_layout(template="plotly_white",
margin=dict(l = 20, r = 5, t = 10, b = 10),
yaxis_nticks=10,
)
fig1.update_xaxes(side="top", tickangle = 270)
fig2 = go.Figure(data=go.Heatmap(
z=df3_a['Value'],zmin=min_value, zmax=max_value,
x=df3_a['Seedlot'],
y=df3_a['Replication'],
text=df3_a['Treetag'],
colorscale=colorscales, hoverongaps = True, hovertemplate='Seedlot: %{x}<br>Tree Tag: %{text}<br>Replication: %{y}<br>Value: %{z}<extra></extra>'))
fig2['layout']['yaxis']['autorange'] = "reversed"
fig2.update_layout(template="plotly_white",
margin=dict(l = 20, r = 5, t = 10, b = 10),
yaxis_nticks=10,
)
fig2.update_xaxes(side="top", tickangle = 270)
fig3 = go.Figure(data=go.Heatmap(
z=df4_a['Value'],zmin=min_value, zmax=max_value,
x=df4_a['Seedlot'].astype('category'),
y=df4_a['Replication'],
text=df4_a['Treetag'],
colorscale=colorscales, hoverongaps = True, hovertemplate='Seedlot: %{x}<br>Tree Tag: %{text}<br>Replication: %{y}<br>Value: %{z}<extra></extra>'))
fig3['layout']['yaxis']['autorange'] = "reversed"
fig3.update_layout(template="plotly_white",
margin=dict(l = 20, r = 5, t = 10, b = 10),
yaxis_nticks=10,
)
fig3.update_xaxes(side="top", tickangle = 270,type='category')
fig4 = go.Figure(data=go.Heatmap(
z=df5_a['Value'],zmin=min_value, zmax=max_value,
x=df5_a['Seedlot'],
y=df5_a['Replication'],
text=df5_a['Treetag'],
colorscale=colorscales, hoverongaps = True, hovertemplate='Seedlot: %{x}<br>Tree Tag: %{text}<br>Replication: %{y}<br>Value: %{z}<extra></extra>'))
fig4['layout']['yaxis']['autorange'] = "reversed"
fig4.update_layout(template="plotly_white",
margin=dict(l = 20, r = 5, t = 10, b = 10),
yaxis_nticks=10,
)
fig4.update_xaxes(side="top", tickangle = 270,type='category')
fig5 = go.Figure(data=go.Heatmap(
z=df6_a['Value'],zmin=min_value, zmax=max_value,
x=df6_a['Seedlot'],
y=df6_a['Replication'],
text=df6_a['Treetag'],
colorscale=colorscales, hoverongaps = True, hovertemplate='Seedlot: %{x}<br>Tree Tag: %{text}<br>Replication: %{y}<br>Value: %{z}<extra></extra>'))
fig5['layout']['yaxis']['autorange'] = "reversed"
fig5.update_layout(template="plotly_white",
margin=dict(l = 20, r = 5, t = 10, b = 10),
yaxis_nticks=10,
)
fig5.update_xaxes(side="top", tickangle = 270,type='category')
card_content1 = [
dbc.CardBody(
[
html.H6('Plot 1 ' , style = {'color':' #4F4F4F','fontWeight':'bold', 'textAlign':'center'}),
dcc.Graph(figure = fig, style = {'height':'300px'})
]
)
]
card_content2 = [
dbc.CardBody(
[
html.H6('Plot 2 ' , style = {'color':' #4F4F4F','fontWeight':'bold', 'textAlign':'center'}),
dcc.Graph(figure = fig1, style = {'height':'300px'})
]
)
]
card_content3 = [
dbc.CardBody(
[
html.H6('Plot 3 ' , style = {'color':'#4F4F4F','fontWeight':'bold', 'textAlign':'center'}),
dcc.Graph(figure = fig2, style = {'height':'300px'})
]
)
]
card_content4 = [
dbc.CardBody(
[
html.H6('Plot 4 ' , style = {'color':'#4F4F4F','fontWeight':'bold', 'textAlign':'center'}),
dcc.Graph(figure = fig3, style = {'height':'300px'})
]
)
]
card_content5 = [
dbc.CardBody(
[
html.H6('Plot 5 ' , style = {'color':'#4F4F4F','fontWeight':'bold', 'textAlign':'center'}),
dcc.Graph(figure = fig4, style = {'height':'300px'})
]
)
]
card_content6 = [
dbc.CardBody(
[
html.H6('Plot 6 ' , style = {'color':'#4F4F4F','fontWeight':'bold', 'textAlign':'center'}),
dcc.Graph(figure = fig5, style = {'height':'300px'})
]
)
]
return card_content1,card_content2,card_content3,card_content4,card_content5,card_content6
if __name__ == "__main__":
app.run_server(port=1120,debug = False)
