def render_sector(s, sector_path, level):
sector_emissions = s.sum(level=0).sort_values(ascending=False)
for subsector_name, emissions in sector_emissions.iteritems():
if not subsector_name:
continue
subsector_path = tuple([*sector_path, subsector_name])
next_metadata = SECTORS
for sp in subsector_path:
metadata = next_metadata[sp]
next_metadata = metadata.get('subsectors', {})
if current_sector == subsector_path:
active = True
else:
active = False
page = get_page_for_emission_sector(*subsector_path)
name = metadata.get('name_%s' % get_active_locale())
if name is None:
name = metadata['name']
item = _make_nav_item(name, emissions, level, page, active=active)
items.append(item)
ss = s[subsector_name]
if isinstance(ss, pd.Series):
render_sector(ss, subsector_path, level + 1)
def render_page():
cols = []
edf = predict_emissions().dropna(axis=1, how='all')
forecast = edf.pop('Forecast')
graph = PredictionFigure(sector_name=None,
unit_name='kt',
title='Päästöt yhteensä',
smoothing=True,
fill=True,
stacked=True,
legend=True,
legend_x=0.8)
for sector_name, sector_metadata in SECTORS.items():
df = pd.DataFrame(edf[sector_name])
df['Forecast'] = forecast
fig = make_sector_fig(df, sector_name, sector_metadata)
sector_page = get_page_for_emission_sector(sector_name, None)
card = GraphCard(id='emissions-%s' % sector_name,
graph=dict(figure=fig),
link_to_page=sector_page)
cols.append(dbc.Col(card.render(), md=6))
# Add the summed sector to the all emissions graph
df = df.drop(columns=['Forecast'])
s = df.sum(axis=1)
s.name = 'Emissions'
df = pd.DataFrame(s)
df['Forecast'] = forecast
graph.add_series(df=df,
trace_name=sector_metadata['name'],
column_name='Emissions',
historical_color=sector_metadata['color'])
target_year = get_variable('target_year')
ref_year = get_variable('ghg_reductions_reference_year')
perc_off = get_variable('ghg_reductions_percentage_in_target_year')
last_hist_year = edf.loc[~forecast].index.max()
last_hist = edf.loc[last_hist_year].sum()
end_emissions = edf.loc[target_year].sum()
ref_emissions = edf.loc[ref_year].sum()
target_emissions = ref_emissions * (1 - perc_off / 100)
target_year_emissions = edf.loc[target_year].sum()
sticky = StickyBar(
label='Päästövähennykset yhteensä',
goal=last_hist - target_emissions,
value=last_hist - end_emissions,
unit='kt',
below_goal_good=False,
)
card = GraphCard(id='emissions-total',
graph=dict(figure=graph.get_figure()))
return html.Div(
[dbc.Row(dbc.Col(card.render())),
dbc.Row(cols),
sticky.render()])
def get_content(self):
lang = get_active_locale()
main_sector_name = self.emission_sector[0]
main_sector_metadata = SECTORS[main_sector_name]
cols = []
edf = predict_emissions().dropna(axis=1, how='all')
forecast = edf.pop('Forecast')
edf = edf[main_sector_name]
subsectors = main_sector_metadata['subsectors']
colors = generate_color_scale(main_sector_metadata['color'],
len(subsectors))
graph = PredictionFigure(sector_name=main_sector_name,
unit_name='kt',
title=_('Total emissions'),
smoothing=True,
fill=True,
stacked=True,
legend=True,
legend_x=0.8)
for idx, (sector_name,
sector_metadata) in enumerate(subsectors.items()):
df = pd.DataFrame(edf[sector_name])
df['Forecast'] = forecast
fig = self.make_sector_fig(df, sector_name, sector_metadata,
colors[idx])
sector_page = get_page_for_emission_sector(main_sector_name,
sector_name)
card = GraphCard(id='emissions-%s-%s' %
(main_sector_name, sector_name),
graph=dict(figure=fig),
link_to_page=sector_page)
cols.append(dbc.Col(card.render(), md=6))
# Add the summed sector to the all emissions graph
df = df.drop(columns=['Forecast'])
s = df.sum(axis=1)
s.name = 'Emissions'
df = pd.DataFrame(s)
df['Forecast'] = forecast
graph.add_series(df=df,
trace_name=sector_metadata.get(
'name_%s' % lang, sector_metadata['name']),
column_name='Emissions',
historical_color=colors[idx])
self.total_emissions = edf.iloc[-1].sum()
card = GraphCard(id='%s-emissions-total' % main_sector_name,
graph=dict(figure=graph.get_figure()))
return html.Div([
dbc.Row(dbc.Col(card.render())),
dbc.Row(cols),
])
def render(self, is_top_row: bool = True) -> dbc.Card:
graph = Graph(self.id, self.graph, self.slider)
classes = self.get_classes(is_top_row)
graph_el = html.Div(graph.render(), className="slider-card__content")
if self.link_to_page:
if isinstance(self.link_to_page, tuple):
from pages.routing import get_page_for_emission_sector
page = get_page_for_emission_sector(*self.link_to_page)
else:
page = self.link_to_page
graph_el = dcc.Link(children=graph_el, href=page.path)
card = dbc.Card(
dbc.CardBody(children=[
graph_el,
dbc.Row(id=self.id + '-description'),
self.extra_content,
]),
className=' '.join(classes),
)
return card
def render(self, is_top_row: bool = True) -> dbc.Card:
graph = Graph(self.id, self.graph, self.slider)
classes = self.get_classes(is_top_row)
graph_el = html.Div(graph.render(), className="slider-card__content")
language = get_active_locale()
title = self.title_i18n.get(language, self.title)
if title:
header_content = dbc.CardHeader(html.H4(title))
else:
header_content = None
if self.link_to_page:
if isinstance(self.link_to_page, tuple):
from pages.routing import get_page_for_emission_sector
page = get_page_for_emission_sector(*self.link_to_page)
else:
page = self.link_to_page
link_el = dcc.Link(html.H5('[+]'),
href=page.path,
className="card-header__link")
header_el = html.Div([link_el, header_content])
else:
header_el = header_content
card = dbc.Card(
[
header_el,
dbc.CardBody(children=[
graph_el,
dbc.Row(children=self.render_description(),
id=self.id + '-description'),
self.extra_content,
])
],
className=' '.join(classes),
)
return card
_('Emission reductions according to scenario') + ' %s–%s' %
(self.last_historical_year, self.target_year)),
self._render_emissions_bar()
],
md=6)
emissions_summary = self._render_value_summary(
self.scenario_emissions, self.target_emissions,
_('Total net emissions'), _('kt/year'), True)
emissions_summary = dbc.Col(emissions_summary, md=3)
if self.value is not None:
summary = self._render_value_summary(self.value, self.goal,
self.label, self.unit,
self.below_goal_good)
summary = dbc.Col(summary, md=3)
else:
summary = dbc.Col(md=3)
return dbc.Alert([dbc.Row([pötkylä, summary, emissions_summary])],
className="page-summary fixed-bottom")
if __name__ == '__main__':
# from calc.geothermal import get_historical_production
# get_historical_production()
from pages.routing import get_page_for_emission_sector
page = get_page_for_emission_sector('BuildingHeating', 'DistrictHeat')
assert page is not None
StickyBar(current_page=page).render()
