Skip to content

modify path #22

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
AStupidBear wants to merge 1 commit into
base: master
Choose a base branch
from
Open

modify path #22

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion classifiers/inception.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@

class Classifier_INCEPTION:

def __init__(self, output_directory, input_shape, nb_classes, verbose=False, build=True, batch_size=64,
def __init__(self, output_directory, input_shape, nb_classes, verbose=True, build=True, batch_size=64,
nb_filters=32, use_residual=True, use_bottleneck=True, depth=6, kernel_size=41, nb_epochs=1500):

self.output_directory = output_directory
Expand Down
4 changes: 2 additions & 2 deletions classifiers/nne.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@

class Classifier_NNE:

def create_classifier(self, model_name, input_shape, nb_classes, output_directory, verbose=False,
def create_classifier(self, model_name, input_shape, nb_classes, output_directory, verbose=True,
build=True):
if self.check_if_match('inception*', model_name):
from classifiers import inception
Expand All @@ -22,7 +22,7 @@ def check_if_match(self, rex, name2):
pattern = re.compile(rex)
return pattern.match(name2)

def __init__(self, output_directory, input_shape, nb_classes, verbose=False, nb_iterations=5,
def __init__(self, output_directory, input_shape, nb_classes, verbose=True, nb_iterations=5,
clf_name='inception'):
self.classifiers = [clf_name]
out_add = ''
Expand Down
6 changes: 3 additions & 3 deletions utils/constants.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -18,8 +18,8 @@

UNIVARIATE_DATASET_NAMES = ['Meat', 'Coffee']

UNIVARIATE_ARCHIVE_NAMES = ['TSC', 'InlineSkateXPs', 'SITS']
UNIVARIATE_ARCHIVE_NAMES = ['TSC']
UNIVARIATE_ARCHIVE_NAMES = ['Univariate_arff','mts_archive', 'coto_data', 'InlineSkateXPs', 'SITS']


SITS_DATASETS = ['SatelliteFull_TRAIN_c301', 'SatelliteFull_TRAIN_c200', 'SatelliteFull_TRAIN_c451',
'SatelliteFull_TRAIN_c89', 'SatelliteFull_TRAIN_c677', 'SatelliteFull_TRAIN_c59',
Expand All @@ -29,6 +29,6 @@
'InlineSkate-256', 'InlineSkate-512', 'InlineSkate-1024',
'InlineSkate-2048']

dataset_names_for_archive = {'TSC': UNIVARIATE_DATASET_NAMES,
dataset_names_for_archive = {'Univariate_arff': UNIVARIATE_DATASET_NAMES,
'SITS': SITS_DATASETS,
'InlineSkateXPs': InlineSkateXPs_DATASETS}
44 changes: 33 additions & 11 deletions utils/utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -28,9 +28,11 @@ def check_if_file_exits(file_name):


def readucr(filename, delimiter=','):
data = np.loadtxt(filename, delimiter=delimiter)
Y = data[:, 0]
X = data[:, 1:]
data = np.loadtxt(filename)
Y = data[:,0]
X = data[:,1:]
print(X.shape, Y.shape)
print(X[0], Y[0])
return X, Y


Expand All @@ -56,11 +58,31 @@ def create_directory(directory_path):
def read_dataset(root_dir, archive_name, dataset_name):
datasets_dict = {}

file_name = root_dir + '/archives/' + archive_name + '/' + dataset_name + '/' + dataset_name
x_train, y_train = readucr(file_name + '_TRAIN')
x_test, y_test = readucr(file_name + '_TEST')
datasets_dict[dataset_name] = (x_train.copy(), y_train.copy(), x_test.copy(),
y_test.copy())
if archive_name == 'coto_data':
file_name = root_dir+'/archives/'+archive_name+'/'+dataset_name+'/'
x_train = np.load(file_name + 'x_train.npy')
y_train = np.load(file_name + 'y_train.npy')
x_test = np.load(file_name + 'x_test.npy')
y_test = np.load(file_name + 'y_test.npy')

datasets_dict[dataset_name] = (x_train.copy(), y_train.copy(), x_test.copy(),
y_test.copy())
elif archive_name == 'mts_archive':
file_name = root_dir+'/archives/'+archive_name+'/'+dataset_name+'/'
x_train = np.load(file_name + 'x_train.npy')
y_train = np.load(file_name + 'y_train.npy')
x_test = np.load(file_name + 'x_test.npy')
y_test = np.load(file_name + 'y_test.npy')

datasets_dict[dataset_name] = (x_train.copy(), y_train.copy(), x_test.copy(),
y_test.copy())

else:
file_name = root_dir + '/archives/' + archive_name + '/' + dataset_name + '/' + dataset_name
x_train, y_train = readucr(file_name + '_TRAIN.txt')
x_test, y_test = readucr(file_name + '_TEST.txt')
datasets_dict[dataset_name] = (x_train.copy(), y_train.copy(), x_test.copy(),
y_test.copy())

return datasets_dict

Expand All @@ -70,12 +92,12 @@ def read_all_datasets(root_dir, archive_name):

dataset_names_to_sort = []

if archive_name == 'TSC':
if archive_name == 'Univariate_arff':
for dataset_name in DATASET_NAMES:
root_dir_dataset = root_dir + '/archives/' + archive_name + '/' + dataset_name + '/'
file_name = root_dir_dataset + dataset_name
x_train, y_train = readucr(file_name + '_TRAIN')
x_test, y_test = readucr(file_name + '_TEST')
x_train, y_train = readucr(file_name + '_TRAIN.txt')
x_test, y_test = readucr(file_name + '_TEST.txt')

datasets_dict[dataset_name] = (x_train.copy(), y_train.copy(), x_test.copy(),
y_test.copy())
Expand Down