I have created a graph with 8 subplots corresponding to the energy production of each wind turbine in a farm per year. Each subplot corresponds to a different year of operation. I managed to get a nice colorscale applied to each of the subplots but each of the colorscales has a different range (based on the data in each of the subplots).
I would like to make one where there is a “global” colorscale and the values in each plot correspond to the fixed colours. I would be grateful for your suggestions.
def aep_turbine_subplot_fig(years, AEP):
fig = make_subplots(rows = 4, cols = 2, subplot_titles = years)
fig.add_trace(go.Bar(x = get_turbine_names(),
y = AEP.iloc[0,:],
name = '2012',
marker = {'color': AEP.iloc[0,:],
'colorscale': 'RdBu'}),
row = 1, col = 1)
fig.add_trace(go.Bar(x = get_turbine_names(),
y = AEP.iloc[1,:],
name = '2013',
marker = {'color': AEP.iloc[1,:],
'colorscale': 'RdBu'}),
row = 1, col = 2)
fig.add_trace(go.Bar(x = get_turbine_names(),
y = AEP.iloc[2,:],
name = '2014',
marker = {'color': AEP.iloc[2,:],
'colorscale': 'RdBu'}),
row = 2, col = 1)
fig.add_trace(go.Bar(x = get_turbine_names(),
y = AEP.iloc[3,:],
name = '2015',
marker = {'color': AEP.iloc[3,:],
'colorscale': 'RdBu'}),
row = 2, col = 2)
fig.add_trace(go.Bar(x = get_turbine_names(),
y = AEP.iloc[4,:],
name = '2016',
marker = {'color': AEP.iloc[4,:],
'colorscale': 'RdBu'}),
row = 3, col = 1)
fig.add_trace(go.Bar(x = get_turbine_names(),
y = AEP.iloc[5,:],
name = '2017',
marker = {'color': AEP.iloc[5,:],
'colorscale': 'RdBu'}),
row = 3, col = 2)
fig.add_trace(go.Bar(x = get_turbine_names(),
y = AEP.iloc[6,:],
name = '2018',
marker = {'color': AEP.iloc[6,:],
'colorscale': 'RdBu'}),
row = 4, col = 1)
fig.add_trace(go.Bar(x = get_turbine_names(),
y = AEP.iloc[7,:],
name = '2019 (Jan to Jun)',
marker = {'color': AEP.iloc[7,:],
'colorscale': 'RdBu'}),
row = 4, col = 2)
# editing the yaxes in each subplot
fig.update_yaxes(title_text='AEP [GWh] in 2012', title_font = dict(size = 14), row=1, col=1, range = [0,8.2])
fig.update_yaxes(title_text='AEP [GWh] in 2013', title_font = dict(size = 14), row=1, col=2, range = [0,8.2])
fig.update_yaxes(title_text='AEP [GWh] in 2014', title_font = dict(size = 14), row=2, col=1, range = [0,8.2])
fig.update_yaxes(title_text='AEP [GWh] in 2015', title_font = dict(size = 14), row=2, col=2, range = [0,8.2])
fig.update_yaxes(title_text='AEP [GWh] in 2016', title_font = dict(size = 14), row=3, col=1, range = [0,8.2])
fig.update_yaxes(title_text='AEP [GWh] in 2017', title_font = dict(size = 14), row=3, col=2, range = [0,8.2])
fig.update_yaxes(title_text='AEP [GWh] in 2018', title_font = dict(size = 14), row=4, col=1, range = [0,8.2])
fig.update_yaxes(title_text='AEP [GWh] in 2019', title_font = dict(size = 14), row=4, col=2, range = [0,8.2])
# LAYOUT
fig.update_layout(
title = 'AEP per turbine',
xaxis_tickfont_size = 14,
barmode='group',
bargap=0.15, # gap between bars of adjacent location coordinates.
bargroupgap=0.1, # gap between bars of the same location coordinate.
showlegend = False,
plot_bgcolor ='rgb(160,160,160)',
)
fig.write_image(get_fig_dir() + 'AEP_perTurbine.png', width = 800, height = 800)
fig.show(renderer = 'png', width = 800, height = 1000)
return plot(fig, auto_open = True)
coloraxis
参数正是针对这个用例: https : coloraxis
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