def plot_test_prediction(target, predictions, model_name, data_desc,
error_func):
save_plot = options.save_plot
if save_plot:
pp_path = get_path(options, "prediction_%s" % data_desc, "pdf")
pp = PdfPages(pp_path)
error = concat_and_calc_error(predictions, target, error_func)
if np.any(target == 0):
mapestr = "no MAPE due to 0's in observations"
else:
mapestr = 'MAPE: %3.2f' % concat_and_calc_error(
predictions, target, sg.utils.mape)
title = 'Test data prediction, %s, %s, %i days, model error: ' \
'%3.2f, RMSE: %3.2f, %s' % \
(model_name, data_desc, len(predictions), error,
concat_and_calc_error(predictions, target, Oger.utils.rmse), mapestr)
print "%s." % title
plt.figure()
plt.title(title)
plot_target_predictions(target, predictions)
if save_plot:
pp.savefig()
pp.close()
if not options.no_show_plot:
plt.ioff() # In case --live-plot is chosen, since that sets ion().
plt.show()
def test_plot_full_ar(self):
for std in [0.1]: #[0.01, 0.1, 0.5]:
(predictions, target, rmse) = self._test_ar_fake(
[self.param_lags, []], std)
plot_target_predictions(target, predictions)
plt.title('Fake data prediction, sin input only, std=%f. RMSE %f' % (std, rmse))
(predictions, target, rmse) = self._test_ar_fake(
[[], self.param_lags], std)
plot_target_predictions(target, predictions)
plt.title('Fake data prediction, cos input only, std=%f. RMSE %f' % (std, rmse))
(predictions, target, rmse) = self._test_ar_fake(
[self.param_lags, self.param_lags], std)
plot_target_predictions(target, predictions)
plt.title('Fake data prediction, sin+cos inputs, std=%f. RMSE %f' % (std, rmse))
self.cos = np.sin
(predictions, target, rmse) = self._test_ar_fake(
[self.param_lags, self.param_lags], std)
plot_target_predictions(target, predictions)
plt.title('Fake data prediction, sin+sin inputs, std=%f. RMSE %f' % (std, rmse))
self.cos = np.cos
self.hindsight = self.hindsight * 2
(predictions, target, rmse) = self._test_ar_fake(
[self.param_lags, []], std)
plot_target_predictions(target, predictions)
plt.title('Fake data prediction, double length sin, std=%f. RMSE %f' % (std, rmse))
self.hindsight = self.hindsight / 2
def plot_test_prediction(target, predictions,
model_name, data_desc, error_func):
save_plot = options.save_plot
if save_plot:
pp_path = get_path(options, "prediction_%s" % data_desc, "pdf")
pp = PdfPages(pp_path)
error = concat_and_calc_error(predictions, target, error_func)
if np.any(target == 0):
mapestr = "no MAPE due to 0's in observations"
else:
mapestr = 'MAPE: %3.2f' % concat_and_calc_error(predictions, target,
sg.utils.mape)
title = 'Test data prediction, %s, %s, %i days, model error: ' \
'%3.2f, RMSE: %3.2f, %s' % \
(model_name, data_desc, len(predictions), error,
concat_and_calc_error(predictions, target, Oger.utils.rmse), mapestr)
print "%s." % title
plt.figure()
plt.title(title)
plot_target_predictions(target, predictions)
if save_plot:
pp.savefig()
pp.close()
if not options.no_show_plot:
plt.ioff() # In case --live-plot is chosen, since that sets ion().
plt.show()
def test_plot_ar_ga_with_predefined_lags(self):
data = pd.DataFrame({'Load': self.data, 'Temperature': 0})
plt.figure()
plt.title("Prediction with varying number of AR indices")
for order, fmt in zip([1, 2, 3], ['r-', 'g-', 'c-']):
(predictions, target, rmse) = \
self._test_ar_ga_with_predefined_lags(data, [self.hindsight, order])
plot_target_predictions(target, predictions, fmt)