def plot_drought_volume_deficit_mpl(scenario, quantile=0.1):
flowdata = scenario.get_data()
gap_attribute = scenario.get_gap_attribute_name()
volume_deficit = flow_analysis.annual_volume_deficit(
flowdata, gap_attribute
).abs()
return plot_drought_deficit_mpl(scenario, volume_deficit, quantile)
def get_data(self, request, scenario_id):
scenario = get_object_or_404(Scenario, pk=scenario_id)
data = analysis.annual_volume_deficit(
scenario.get_data(),
scenario.get_gap_attribute_name(),
analysis.CFS_TO_AFD
)
return data.reset_index()
def plot_drought_volume_deficit(scenario, quantile=0.1):
volume_deficit = flow_analysis.annual_volume_deficit(
scenario.get_data(), scenario.get_gap_attribute_name()).abs()
plot = plot_drought_deficit(scenario, volume_deficit, quantile)
plot._yaxis.formatter = NumeralTickFormatter(format="0,0")
plot._yaxis.axis_label = "Deficit (AF)"
plot.title = "Volume deficit during drought"
return plot
def plot_drought_volume_deficit(scenario, quantile=0.1):
volume_deficit = flow_analysis.annual_volume_deficit(
scenario.get_data(), scenario.get_gap_attribute_name()).abs()
plot = plot_drought_deficit(scenario, volume_deficit, quantile)
plot._yaxis.formatter = NumeralTickFormatter(format="0,0")
plot._yaxis.axis_label = "Deficit (AF)"
plot.title = "Volume deficit during drought"
return plot
def project_deficit_stats_csv(request, project_id):
project = get_object_or_404(Project, pk=project_id)
monthly_result = __get_deficit_stats_comparison(
project,
lambda d, g, t: analysis.monthly_volume_deficit(d, g, CFS_TO_AFD).mean().abs(),
"af")
annual_result = __get_deficit_stats_comparison(
project,
lambda d, g, t: analysis.annual_volume_deficit(d, g, CFS_TO_AFD),
"af").mean().abs()
annual_result.name = "Annual Average"
response = HttpResponse(content_type="text/csv")
result = pd.concat([monthly_result, annual_result.to_frame().transpose()], axis=0)
result.to_csv(response)
return response
def project_deficit_stats_csv(request, project_id):
project = get_object_or_404(Project, pk=project_id)
monthly_result = __get_deficit_stats_comparison(
project, lambda d, g, t: analysis.monthly_volume_deficit(
d, g, CFS_TO_AFD).mean().abs(), "af")
annual_result = __get_deficit_stats_comparison(
project,
lambda d, g, t: analysis.annual_volume_deficit(d, g, CFS_TO_AFD),
"af").mean().abs()
annual_result.name = "Annual Average"
response = HttpResponse(content_type="text/csv")
result = pd.concat(
[monthly_result, annual_result.to_frame().transpose()], axis=0)
result.to_csv(response)
return response
def project_deficit_stats_annual_csv(request, project_id):
return __dataframe_annual_csv_helper(request, project_id,
lambda d, g, t: analysis.annual_volume_deficit(d, g, CFS_TO_AFD), "af")
def test_annual_volume_deficit_unit_convert(self):
data = test_data()
result = analysis.annual_volume_deficit(data, 0, unit_multiplier=2.0)
self.assertItemsEqual([-46, -38], result)
def test_annual_volume_deficit(self):
data = test_data()
result = analysis.annual_volume_deficit(data, 0)
self.assertItemsEqual([-23, -19], result)
def project_deficit_stats_annual_csv(request, project_id):
return __dataframe_annual_csv_helper(
request, project_id,
lambda d, g, t: analysis.annual_volume_deficit(d, g, CFS_TO_AFD), "af")
def test_annual_volume_deficit_unit_convert(self):
data = test_data()
result = analysis.annual_volume_deficit(data, 0, unit_multiplier=2.0)
self.assertItemsEqual([-46, -38], result)
def test_annual_volume_deficit(self):
data = test_data()
result = analysis.annual_volume_deficit(data, 0)
self.assertItemsEqual([-23, -19], result)
def plot_drought_volume_deficit_mpl(scenario, quantile=0.1):
flowdata = scenario.get_data()
gap_attribute = scenario.get_gap_attribute_name()
volume_deficit = flow_analysis.annual_volume_deficit(
flowdata, gap_attribute).abs()
return plot_drought_deficit_mpl(scenario, volume_deficit, quantile)
