def __dataframe_barplot_helper(request,
                               project_id,
                               title,
                               analysis_f,
                               units=None,
                               formatter=None,
                               xlim=None,
                               ylim=None):
    project = get_object_or_404(Project, pk=project_id)
    data = __get_deficit_stats_comparison(project, analysis_f, units)
    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    data.plot(kind='bar', ax=ax, table=False)
    ax.set_title(title)
    if formatter:
        ax.yaxis.set_major_formatter(formatter)
    ylabel = "Volume"
    ax.set_ylabel("Volume (%s)" % units)

    if xlim:
        ax.set_xlim(xlim)
    if ylim:
        ax.set_ylim(ylim)

    return plot_to_response(fig)
Ejemplo n.º 2
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def plot_drought_deficit_mpl(scenario, annual_data, quantile):
    flowdata = scenario.get_data()
    if scenario.critical_season_begin and scenario.critical_season_end:
        season = (
            scenario.critical_season_begin,
            scenario.critical_season_end
        )
    else:
        season = None
    drought_analysis = analysis.DroughtYearFromFlowAnalysis(
        flowdata[scenario.get_attribute_name()],
        quantile,
        season = season
    )
    data = annual_data.to_frame(name='Annual').merge(
        drought_analysis.label_years().to_frame("In Drought"),
        how='left',
        left_index=True,
        right_index=True
    ).dropna()
    fig, ax = new_figure()
    data['Annual'].plot(
        kind='bar',
        ax=ax,
        color=data['In Drought'].map({True: 'r', False: 'g'}),
        # legend=True,
    )

    # Put in the legend to signal drought and non-drought years.
    nodrought = plt.Rectangle((0, 1), 50, 50, color='g')
    drought = plt.Rectangle((0, 1), 50, 50, color='r')
    ax.legend([nodrought, drought], ["Non-Drought Year", "Drought Year"])

    return fig, ax
Ejemplo n.º 3
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def right_plot(request, scenario_id):
    scenario = get_object_or_404(Scenario, pk=scenario_id)
    plotdata = target_comparison_data(scenario)
    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    plotdata.plot(ax=ax)
    ax.set_xlabel("Month")
    ax.set_ylabel(__label_scenario_attribute(scenario))
    plotting.label_months(ax)
    return plot_to_response(fig)
Ejemplo n.º 4
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def deficit_days_plot(request, scenario_id):
    scenario = get_object_or_404(Scenario, pk=scenario_id)
    data = scenario.get_data()
    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    title = "Monthly Temporal Deficit"
    ax = plotting.deficit_days_plot(data, scenario.get_gap_attribute_name(),
                                    title, fig, ax)
    ax.yaxis.set_major_formatter(FuncFormatter(to_percent))
    ax.set_ylim([0.0, 1.0])
    return plot_to_response(fig)
def project_low_flow_plot(request, project_id):
    low_flows = get_low_flows(project_id)
    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    low_flows.plot(kind='bar', fig=fig, ax=ax)
    #ax.yaxis.set_major_formatter(FuncFormatter(to_percent))
    ax.set_title("7-day Minimum Flow Trend")
    labels = ax.get_xticklabels()
    for label in labels:
        label.set_rotation(0)
    return plot_to_response(fig)
Ejemplo n.º 6
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def project_low_flow_plot(request, project_id):
    low_flows = get_low_flows(project_id)
    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    low_flows.plot(kind='bar', fig=fig, ax=ax)
    #ax.yaxis.set_major_formatter(FuncFormatter(to_percent))
    ax.set_title("7-day Minimum Flow Trend")
    labels = ax.get_xticklabels()
    for label in labels:
        label.set_rotation(0)
    return plot_to_response(fig)
def project_deficit_days_plot(request, project_id):
    project = get_object_or_404(Project, pk=project_id)
    data = __get_deficit_days_comparison(
        project, lambda d, g, t: analysis.monthly_deficit_pct(d, g), "Month")
    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    data.plot(kind='bar', ax=ax, table=False)
    ax.set_title("Deficit days comparison")
    ax.yaxis.set_major_formatter(FuncFormatter(to_percent))
    ax.set_ylim([0.0, 1.0])
    return plot_to_response(fig)
Ejemplo n.º 8
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def deficit_days_plot(request, scenario_id):
    scenario = get_object_or_404(Scenario, pk=scenario_id)
    data = scenario.get_data()
    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    title = None
    ax = plotting.deficit_days_plot(data, scenario.get_gap_attribute_name(), title, fig, ax)
    ax.yaxis.set_major_formatter(FuncFormatter(to_percent))
    ax.set_ylim([0.0, 1.0])
    ax.set_ylabel("Percent of Days")
    ax.set_xlabel("Month")
    return plot_to_response(fig)
Ejemplo n.º 9
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def project_deficit_days_plot(request, project_id):
    project = get_object_or_404(Project, pk=project_id)
    data = __get_deficit_days_comparison(
        project,
        lambda d, g, t: analysis.monthly_deficit_pct(d, g),
        "Month"
    )
    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    data.plot(kind='bar', ax=ax, table=False)
    ax.set_title("Deficit days comparison")
    ax.yaxis.set_major_formatter(FuncFormatter(to_percent))
    ax.set_ylim([0.0, 1.0])
    return plot_to_response(fig)
Ejemplo n.º 10
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def long_term_minimum_plot(request, scenario_id):
    scenario = get_object_or_404(Scenario, pk=scenario_id)
    data = scenario.get_data()

    column = scenario.get_attribute_name()
    min_data = analysis.annual_minimum(data[column], 7, True)
    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    plotting.plot_with_trendline_ols(
        min_data,
        title=None,
        fig=fig, ax=ax)
    ax.set_xlabel("Year")
    ax.set_ylabel(__label_scenario_attribute(scenario))
    return plot_to_response(fig)
Ejemplo n.º 11
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def long_term_minimum_plot(request, scenario_id):
    scenario = get_object_or_404(Scenario, pk=scenario_id)
    data = scenario.get_data()

    column = scenario.get_attribute_name()
    min_data = analysis.annual_minimum(data[column], 7, True)
    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    plotting.plot_with_trendline_ols(min_data,
                                     title="7-day Minimum Flow",
                                     fig=fig,
                                     ax=ax)
    ax.set_xlabel("Year")
    ax.set_ylabel(__label_scenario_attribute(scenario))
    return plot_to_response(fig)
Ejemplo n.º 12
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 def get(self, request, scenario_id):
     scenario = get_object_or_404(Scenario, pk=scenario_id)
     if scenario.instream_flow_rights:
         targetdata = scenario.get_data()[scenario.get_target_attribute_name()]
         flowdata = scenario.get_data()[scenario.get_attribute_name()]
         ratedata = self.get_rate_data(
             scenario.instream_flow_rights,
             targetdata.index.min(),
             targetdata.index.max()
         )
         plt.style.use(DEFAULT_PLOT_STYLE)
         fig, ax = new_figure()
         self.plot(ax, targetdata, flowdata, ratedata)
         return plot_to_response(fig)
     else:
         raise Http404("Scenario has no instream flow rights.")
Ejemplo n.º 13
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 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.")
Ejemplo n.º 14
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def __dataframe_barplot_helper(request, project_id, title, analysis_f,
    units=None, formatter=None, xlim=None, ylim=None):
    project = get_object_or_404(Project, pk=project_id)
    data = __get_deficit_stats_comparison(project, analysis_f, units)
    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    data.plot(kind='bar', ax=ax, table=False)
    ax.set_title(title)
    if formatter:
        ax.yaxis.set_major_formatter(formatter)
    ylabel = "Volume"
    ax.set_ylabel("Volume (%s)" % units)

    if xlim:
        ax.set_xlim(xlim)
    if ylim:
        ax.set_ylim(ylim)

    return plot_to_response(fig)
Ejemplo n.º 15
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 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.")
Ejemplo n.º 16
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def right_plot(request, scenario_id):
    scenario = get_object_or_404(Scenario, pk=scenario_id)
    data = scenario.get_data()

    daygroups = data.groupby(lambda x: x.dayofyear)
    low = daygroups[scenario.get_attribute_name()].quantile(0.2)
    median = daygroups[scenario.get_attribute_name()].quantile(0.5)
    high = daygroups[scenario.get_attribute_name()].quantile(0.8)
    target = daygroups[scenario.get_target_attribute_name()].mean()

    plotdata = pd.concat([low, median, high, target], axis=1)
    plotdata.columns = ["80% Exceedance", "Median", "20% Exceedance", "Target"]

    plt.style.use(DEFAULT_PLOT_STYLE)
    fig, ax = new_figure()
    plotdata.plot(ax=ax)
    ax.set_xlabel("Month")
    ax.set_ylabel(__label_scenario_attribute(scenario))
    plotting.label_months(ax)
    return plot_to_response(fig)
Ejemplo n.º 17
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def plot_drought_deficit_mpl(scenario, annual_data, quantile):
    flowdata = scenario.get_data()
    if scenario.critical_season_begin and scenario.critical_season_end:
        season = (scenario.critical_season_begin, scenario.critical_season_end)
    else:
        season = None
    drought_analysis = analysis.DroughtYearFromFlowAnalysis(
        flowdata[scenario.get_attribute_name()], quantile, season=season)
    data = annual_data.to_frame(name='Annual').merge(
        drought_analysis.label_years().to_frame("In Drought"),
        how='left',
        left_index=True,
        right_index=True).dropna()
    fig, ax = new_figure()
    data['Annual'].plot(
        kind='bar',
        ax=ax,
        color=data['In Drought'].map({
            True: 'r',
            False: 'g'
        }),
        legend=True,
    )
    return fig, ax
Ejemplo n.º 18
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def __setup_scenario_plot(scenario_id):
    scenario = get_object_or_404(Scenario, pk=scenario_id)
    plt.style.use(DEFAULT_PLOT_STYLE)
    return scenario, new_figure()
Ejemplo n.º 19
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def __setup_scenario_plot(scenario_id):
    scenario = get_object_or_404(Scenario, pk=scenario_id)
    plt.style.use(DEFAULT_PLOT_STYLE)
    return scenario, new_figure()