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enose_2025
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ifiguero 2025-03-18 21:10:50 -03:00
parent 757946c078
commit ac1c6aecfa
2 changed files with 11 additions and 11 deletions
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18
TrainerClass.py
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@ -449,25 +449,25 @@ class eNoseTrainer:
if Y_discrete.ndim == 2:
Y_discrete = np.sum(Y_discrete, axis=1)
dataset = f'Conv1d-base-w{window}'
for i, (train_index, test_index) in enumerate(gss.split(X_conv1d, Y_discrete, G_conv1d)):
dataset = f'Conv1D-w{window}'
for i, (train_index, test_index) in enumerate(gss.split(X_Conv1d, Y_discrete, G_conv1d)):
self.logger.info("{:=^60}".format(f'CV {i+1}/{int(1/self.ratio)} {dataset}'))
os.makedirs('{}/{}/{}-w{}'.format(self.name, self.loader.target, dataset, window), exist_ok=True)
os.makedirs('{}/{}/{}'.format(self.name, self.loader.target, dataset), exist_ok=True)
X_train, X_test = X_conv1d[train_index], X_conv1d[test_index]
Y_train, Y_test = Y_conv1d[train_index], Y_conv1d[test_index]
G_train, G_test = G_conv1d[train_index], G_conv1d[test_index]
# self.logger.debug(f"X_train: {X_train.shape}")
# self.logger.debug(f"X_test: {X_test.shape}")
model_id = "Conv1d-base_{}".format(i)
model_id = "Conv1D_v1_{}".format(i)
self.trained += 1
if self.row_exists(dataset, model_id):
self.bar.update()
continue
model_file = '{}/{}/{}-w{}/{}'.format(self.name, self.loader.target, dataset, window, model_id )
model_file = '{}/{}/{}/{}'.format(self.name, self.loader.target, dataset, model_id )
X_train_sample, _, Y_train_sample, _ = train_test_split(X_train, Y_train, stratify=G_train, train_size=0.8*sample_size / len(X_train), random_state=get_seed())
X_test_sample, _, Y_test_sample, _ = train_test_split(X_test, Y_test, stratify=G_test, train_size=0.2*sample_size / len(X_test), random_state=get_seed())
@ -536,11 +536,11 @@ class eNoseTrainer:
if Y_discrete.ndim == 2:
Y_discrete = np.sum(Y_discrete, axis=1)
dataset = f'Conv1d-base-w{window}-{filter}'
dataset = f'Conv1d-w{window}-{self.loader.smooth}'
for i, (train_index, test_index) in enumerate(gss.split(X_conv1d, Y_discrete, G_conv1d)):
self.logger.info("{:=^60}".format(f'CV {i+1}/{int(1/self.ratio)} {dataset}'))
os.makedirs('{}/{}/{}-w{}'.format(self.name, self.loader.target, dataset, window), exist_ok=True)
os.makedirs('{}/{}/{}'.format(self.name, self.loader.target, dataset), exist_ok=True)
X_train, X_test = X_conv1d[train_index], X_conv1d[test_index]
Y_train, Y_test = Y_conv1d[train_index], Y_conv1d[test_index]
G_train, G_test = G_conv1d[train_index], G_conv1d[test_index]
@ -550,14 +550,14 @@ class eNoseTrainer:
self.logger.debug(f"Y_test: {Y_test.shape}")
model_id = "Conv1d-base_{}".format(i)
model_id = "Conv1d_v1_{}".format(i)
self.trained += 1
if self.row_exists(dataset, model_id):
self.bar.update()
continue
model_file = '{}/{}/{}-w{}/{}'.format(self.name, self.loader.target, dataset, window, model_id )
model_file = '{}/{}/{}/{}'.format(self.name, self.loader.target, dataset, model_id )
X_train_sample, _, Y_train_sample, _ = train_test_split(X_train, Y_train, stratify=G_train, train_size=0.8*sample_size / len(X_train), random_state=get_seed())
X_test_sample, _, Y_test_sample, _ = train_test_split(X_test, Y_test, stratify=G_test, train_size=0.2*sample_size / len(X_test), random_state=get_seed())

4
train_sequence.py
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@ -10,10 +10,10 @@ target_variables=['C2H2', 'CH4', 'C3H6', 'CO', 'C2H6', 'C3H8', 'C2H4', 'H2', 'O2
eNoseLoader = GasSensorDataLoader("enose_dataset", threshold=0.85, source_channels=source_channels, target_list=target_variables, debug=False)
eNose = eNoseTrainer(eNoseLoader, test_size=0.2, debug=False)
eNoseLoader.target_list=['H2',]
eNose.fit()
eNoseLoader.target_list=['H2', 'C2H2', 'CH4', 'C2H4', 'C2H6',]
eNose.fit()
eNoseLoader.target_list=['H2',]
eNose.fit()
eNoseLoader.target_list=['C2H2',]
eNose.fit()
eNoseLoader.target_list=['CH4',]