def eval_model(self, name, signal_id=1, file_name=''):
losses = {}
test_bgs_data, test_signal_data = self.load_test_data(signal_id=signal_id)
predict_bgs_test = self.predict(test_bgs_data)
predict_signal_test = self.predict(test_signal_data)
losses['test_bgs_data'] = test_bgs_data
losses['test_signal_data'] = test_signal_data
losses['predict_bgs_test'] = predict_bgs_test
losses['predict_signal_test'] = predict_signal_test
model_utils.print_predictions_loss(losses=losses)
title = '%s Background' % (name,)
model_utils.plot_prediction(self.autoencoder_model,
test_bgs_data[0:3],
self.original_shape,
title=title,
file_name=[file_name, '_bg'])
title = '%s Background + Signal' % (name,)
model_utils.plot_prediction(self.autoencoder_model,
test_signal_data[0:3],
self.original_shape,
title=title,
file_name=[file_name, '_bg_signal'])
def eval_model(self, name, m_5=6000, k=1000, file_name=''):
losses = {}
test_bgs_data, test_signal_data = self.load_test_data(m_5=m_5, k=k)
predict_bgs_test = self.predict(test_bgs_data)
predict_signal_test = self.predict(test_signal_data)
losses['test_bgs_data'] = test_bgs_data
losses['test_signal_data'] = test_signal_data
losses['predict_bgs_test'] = predict_bgs_test.reshape(losses['test_bgs_data'].shape)
losses['predict_signal_test'] = predict_signal_test.reshape(losses['test_signal_data'].shape)
model_utils.print_predictions_loss(losses=losses)
def eval_model(self, signal_id=1):
losses = {}
test_bgs_data, test_signal_data = self.load_test_data(
signal_id=signal_id)
predict_bgs_test = self.predict(test_bgs_data)
predict_signal_test = self.predict(test_signal_data)
losses['test_bgs_data'] = test_bgs_data
losses['test_signal_data'] = test_signal_data
losses['predict_bgs_test'] = predict_bgs_test
losses['predict_signal_test'] = predict_signal_test
model_utils.print_predictions_loss(losses=losses)