def get(self, request, scenario_id):
scenario = get_object_or_404(Scenario, pk=scenario_id)
plt.style.use(DEFAULT_PLOT_STYLE)
# Crop data.
if scenario.crop_mix:
crop_mix, data, years, commodities = read_crop_mix(
scenario.crop_mix.id)
groups = [
g.as_cropgroup() for g in crop_mix.cropmixgroup_set.all()
]
dataframe = self.data_function(data, groups)
fig, ax = new_figure()
self.plot_function(dataframe, ax)
ax.set_xlabel(self.xlabel)
ax.set_ylabel(self.ylabel)
return plot_to_response(fig)
else:
raise Http404("Scenario contains no agriculture data.")
def get(self, request, scenario_id):
scenario = get_object_or_404(Scenario, pk=scenario_id)
plt.style.use(DEFAULT_PLOT_STYLE)
# Crop data.
if scenario.crop_mix:
crop_mix, data, years, commodities = read_crop_mix(scenario.crop_mix.id)
groups = [g.as_cropgroup() for g in crop_mix.cropmixgroup_set.all()]
dataframe = self.data_function(crop_mix, data, groups)
if isinstance(dataframe, pd.DataFrame):
dataframe_reduced = waterkit.econ.analysis.select_top_n_columns(dataframe, 6)
else:
dataframe_reduced = dataframe
fig, ax = new_figure()
ax.set_xlabel(self.xlabel)
ax.set_ylabel(self.ylabel)
self.plot_function(dataframe_reduced, ax)
return plot_to_response(fig)
else:
raise Http404("Scenario contains no agriculture data.")
def _plot_crop_mix(self, crop_mix):
crop_mix, data, years, commodities = read_crop_mix(crop_mix.id)
groups = [g.as_cropgroup() for g in crop_mix.cropmixgroup_set.all()]
if groups:
revenue_table = data.get_derived_table("Revenue", groups)
revenue_table_cpi = econ_analysis.adjust_cpi(
revenue_table, get_bls_key(), crop_mix.cpi_adjustment_year,
ConsumerPriceIndexData.as_dataframe())
niwr_table = data.get_derived_table("NIWR", groups)
labor_table = data.get_derived_table("Labor", groups)
revenue_af_plot = econ.plots.plot_revenue_af_table(
revenue_table_cpi, niwr_table)
labor_plot = econ.plots.plot_labor_table(labor_table)
return self.EconPlots(crop_mix.name, revenue_af_plot, labor_plot)
else:
# Just do the best we can with what we have and return only the
# acreages.
acre_plot = econ.plots.plot_acres(data, groups)
acre_fraction_plot = econ.plots.plot_acre_fractions(data, groups)
return self.EconPlots(crop_mix.name, acre_plot, acre_fraction_plot)
def _plot_crop_mix(self, crop_mix):
crop_mix, data, years, commodities = read_crop_mix(crop_mix.id)
groups = [g.as_cropgroup() for g in crop_mix.cropmixgroup_set.all()]
if groups:
revenue_table = data.get_derived_table("Revenue", groups)
revenue_table_cpi = econ_analysis.adjust_cpi(
revenue_table,
get_bls_key(),
crop_mix.cpi_adjustment_year,
ConsumerPriceIndexData.as_dataframe()
)
niwr_table = data.get_derived_table("NIWR", groups)
labor_table = data.get_derived_table("Labor", groups)
revenue_af_plot = econ.plots.plot_revenue_af_table(revenue_table_cpi, niwr_table)
labor_plot = econ.plots.plot_labor_table(labor_table)
return self.EconPlots(crop_mix.name, revenue_af_plot, labor_plot)
else:
# Just do the best we can with what we have and return only the
# acreages.
acre_plot = econ.plots.plot_acres(data, groups)
acre_fraction_plot = econ.plots.plot_acre_fractions(data, groups)
return self.EconPlots(crop_mix.name, acre_plot, acre_fraction_plot)
