def make_sector_fig(df, name, metadata):
fig = PredictionFigure(
sector_name=name,
unit_name='kt',
title=metadata['name'],
smoothing=True,
# allow_nonconsecutive_years=True,
fill=True,
stacked=True,
)
if len(df.columns) == 2:
fig.add_series(df=df, trace_name='Päästöt', column_name='')
else:
fig.legend = True
fig.legend_x = 0.8
column_names = list(df.columns)
column_names.remove('Forecast')
colors = generate_color_scale(metadata['color'], len(column_names))
for idx, col_name in enumerate(column_names):
subsector = metadata['subsectors'][col_name]
fig.add_series(df=df,
trace_name=subsector['name'],
column_name=col_name,
historical_color=colors[idx])
return fig.get_figure()
def make_sector_fig(self, df, name, metadata, base_color):
lang = get_active_locale()
fig = PredictionFigure(
sector_name=name,
unit_name='kt',
title=metadata.get('name_%s' % lang, metadata['name']),
smoothing=True,
# allow_nonconsecutive_years=True,
fill=True,
stacked=True,
)
if len(df.columns) == 2:
fig.add_series(df=df,
trace_name=_('Emissions'),
column_name='',
historical_color=base_color)
else:
fig.legend = True
fig.legend_x = 0.8
column_names = list(df.columns)
column_names.remove('Forecast')
colors = generate_color_scale(base_color, len(column_names))
for idx, col_name in enumerate(column_names):
subsector = metadata['subsectors'][col_name]
fig.add_series(df=df,
trace_name=subsector.get(
'name_%s' % lang, metadata['name']),
column_name=col_name,
historical_color=colors[idx])
return fig.get_figure()