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)
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
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)
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)
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)
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)
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)
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)
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)
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.")
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 __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)
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 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)
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
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()
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()