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)