def plot_trainingdata(self):
count = self.trainingdata_count()
fig, ax = PlotUtils.prepare_figure(len(count))
ax.bar(range(0, len(count)), count, width=0.7)
ax.bar(range(0, len(count)), count, width=0.7)
plt.ylabel(_("Number of training data"))
return fig
def plot_y_stats(self):
norm = self.y.norm()
stdev = self.y.stdev_s()
upper = [norm[i] + stdev[i] for i in range(0, len(stdev))]
lower = [norm[i] - stdev[i] for i in range(0, len(stdev))]
fig, ax = PlotUtils.prepare_figure(len(stdev))
[
ax.plot(self.y.data_by_year(year).values,
label='individual years',
color='blue',
alpha=.2)
for year in range(self.y.timeseries.index[0].year,
self.y.timeseries.index[-1].year + 1)
]
ax.plot(upper, color='black')
ax.plot(lower, color='black', label="+/- STDEV")
ax.plot(norm, label="NORM", color='red')
handles, labels = ax.get_legend_handles_labels()
ax.legend(handles[-3:], labels[-3:])
plt.ylabel(self.y.label)
return fig