def project_deficit_days_annual_csv(request, project_id):
project = get_object_or_404(Project, pk=project_id)
result = __get_deficit_days_comparison(project,
lambda d, g, t: analysis.annual_deficit_pct(d, g), "Annual Average").mean()
response = HttpResponse(content_type="text/csv")
result.to_csv(response, index_label="Scenario", header=['Annual Average'])
return response
def project_deficit_days_annual_csv(request, project_id):
project = get_object_or_404(Project, pk=project_id)
result = __get_deficit_days_comparison(
project, lambda d, g, t: analysis.annual_deficit_pct(d, g),
"Annual Average").mean()
response = HttpResponse(content_type="text/csv")
result.to_csv(response, index_label="Scenario", header=['Annual Average'])
return response
def plot_drought_temporal_deficit(scenario, quantile=0.1):
flowdata = scenario.get_data()
gap_attribute = scenario.get_gap_attribute_name()
temporal_deficit = flow_analysis.annual_deficit_pct(flowdata[gap_attribute])
plot = plot_drought_deficit(scenario, temporal_deficit, quantile)
plot.y_range = Range1d(0, 1)
plot._yaxis.formatter = NumeralTickFormatter(format="00%")
plot.title = "Temporal deficit during drought"
plot._yaxis.axis_label = "Temporal Deficit (% days)"
return plot
def plot_drought_temporal_deficit(scenario, quantile=0.1):
flowdata = scenario.get_data()
gap_attribute = scenario.get_gap_attribute_name()
temporal_deficit = flow_analysis.annual_deficit_pct(
flowdata[gap_attribute])
plot = plot_drought_deficit(scenario, temporal_deficit, quantile)
plot.y_range = Range1d(0, 1)
plot._yaxis.formatter = NumeralTickFormatter(format="00%")
plot.title = "Temporal deficit during drought"
plot._yaxis.axis_label = "Temporal Deficit (% days)"
return plot
def project_deficit_days_csv(request, project_id):
project = get_object_or_404(Project, pk=project_id)
monthly_result = __get_deficit_days_comparison(project,
lambda d, g, t: analysis.monthly_deficit_pct(d, g),
"Month")
annual_result = __get_deficit_days_comparison(project,
lambda d, g, t: analysis.annual_deficit_pct(d, g), "Annual Average").mean()
annual_result.name = "Annual Average"
result = pd.concat([monthly_result, annual_result.to_frame().transpose()], axis=0)
result.index.name = "Month"
response = HttpResponse(content_type="text/csv")
result.to_csv(response)
return response
def project_deficit_days_csv(request, project_id):
project = get_object_or_404(Project, pk=project_id)
monthly_result = __get_deficit_days_comparison(
project, lambda d, g, t: analysis.monthly_deficit_pct(d, g), "Month")
annual_result = __get_deficit_days_comparison(
project, lambda d, g, t: analysis.annual_deficit_pct(d, g),
"Annual Average").mean()
annual_result.name = "Annual Average"
result = pd.concat(
[monthly_result, annual_result.to_frame().transpose()], axis=0)
result.index.name = "Month"
response = HttpResponse(content_type="text/csv")
result.to_csv(response)
return response
def get_data(self, request, scenario_id):
scenario = get_object_or_404(Scenario, pk=scenario_id)
data = analysis.annual_deficit_pct(scenario.get_data(), scenario.get_gap_attribute_name())
return data.reset_index()
def plot_drought_temporal_deficit_mpl(scenario, quantile=0.1):
flowdata = scenario.get_data()
gap_attribute = scenario.get_gap_attribute_name()
temporal_deficit = flow_analysis.annual_deficit_pct(flowdata[gap_attribute])
return plot_drought_deficit_mpl(scenario, temporal_deficit, quantile)
def plot_drought_temporal_deficit_mpl(scenario, quantile=0.1):
flowdata = scenario.get_data()
gap_attribute = scenario.get_gap_attribute_name()
temporal_deficit = flow_analysis.annual_deficit_pct(
flowdata[gap_attribute])
return plot_drought_deficit_mpl(scenario, temporal_deficit, quantile)
