predictions_array = [
predictions_WITH_retraining, predictions_SCADANN,
predictions_multiple_vote, predictions_DANN, predictions_VADA,
predictions_dirt_t, predictions_AdaBN, predictions_no_retraining
]
text_legend_array = [
"Re-Calibration", "SCADANN", "MultipleVote", "DANN", "VADA", "DIRT-T",
"AdaBN", "No Calibration"
]
long_term_pointplot(ground_truths_in_array=ground_truths_array,
predictions_in_array=predictions_array,
text_for_legend_in_array=text_legend_array,
timestamps=training_datetimes,
number_of_seances_to_consider=2,
remove_transition_evaluation=False)
long_term_classification_graph(ground_truths_in_array=ground_truths_array,
predictions_in_array=predictions_array,
text_for_legend_in_array=text_legend_array,
timestamps=training_datetimes,
number_of_seances_to_consider=2,
remove_transition_evaluation=False)
fig, axs = create_confusion_matrix(ground_truth=ground_truths_SCADANN,
predictions=predictions_SCADANN,
class_names=classes,
title="ConvNet standard training",
fontsize=font_size)
plt.show()
create_long_term_classification_graph(ground_truths_first_algo=ground_truths_no_retraining,
predictions_first_algo=predictions_no_retraining,
ground_truths_second_algo=ground_truths_WITH_retraining,
predictions_second_algo=predictions_WITH_retraining,
timestamps=evaluation_datetimes)
fig, axs = create_confusion_matrix(ground_truth=ground_truths_no_retraining, predictions=predictions_no_retraining,
class_names=classes, title="ConvNet standard training", fontsize=font_size)
'''
# fig.suptitle("ConvNet using AdaDANN training", fontsize=28)
mng_no_retraining = plt.get_current_fig_manager()
# mng.window.state('zoomed') # works fine on Windows!
plt.tight_layout()
plt.gcf().subplots_adjust(bottom=0.13)
plt.gcf().subplots_adjust(top=0.90)
plt.show()
_, _ = create_confusion_matrix(ground_truth=ground_truths_WITH_retraining,
predictions=predictions_WITH_retraining,
class_names=classes,
title="ConvNet standard training",
fontsize=font_size)
# fig.suptitle("ConvNet using AdaDANN training", fontsize=28)
mng_retraining = plt.get_current_fig_manager()
# mng.window.state('zoomed') # works fine on Windows!
plt.tight_layout()
plt.gcf().subplots_adjust(bottom=0.13)
plt.gcf().subplots_adjust(top=0.90)
plt.show()