def test_view_peak_indices():
"""Prints dataset information to the console.
"""
dataset_file = join(get_test_data_path(), 'gclda_dataset.pkl')
dset = Dataset.load(dataset_file)
captured_output = StringIO() # Create StringIO object
sys.stdout = captured_output # and redirect stdout.
dset.view_peak_indices(n_peak_indices=5) # Call unchanged function.
sys.stdout = sys.__stdout__ # Reset redirect.
assert len(captured_output.getvalue()) > 0
def test_save_dataset2():
"""Test gclda.dataset.Dataset.save with gzipped file.
"""
dataset_file = join(get_test_data_path(), 'gclda_dataset.pklz')
temp_file = join(get_test_data_path(), 'temp.pklz')
dset = Dataset.load(dataset_file)
dset.save(temp_file)
file_found = isfile(temp_file)
assert file_found
# Perform cleanup
remove(temp_file)
def test_init():
"""Smoke test for Model class.
"""
dataset_file = join(get_test_data_path(), 'gclda_dataset.pkl')
dset = Dataset.load(dataset_file)
model = Model(dset,
n_topics=50,
n_regions=1,
symmetric=False,
alpha=.1,
beta=.01,
gamma=.01,
delta=1.,
dobs=25,
roi_size=10.,
seed_init=1)
assert isinstance(model, Model)
def test_symmetric():
"""Test running a model with symmetric ROIs.
"""
dataset_file = join(get_test_data_path(), 'gclda_dataset.pkl')
dset = Dataset.load(dataset_file)
model = Model(dset,
n_topics=50,
n_regions=2,
symmetric=True,
alpha=.1,
beta=.01,
gamma=.01,
delta=1.,
dobs=25,
roi_size=10.,
seed_init=1)
initial_iter = model.iter
model.run_complete_iteration()
assert model.iter == initial_iter + 1
def test_init():
"""Smoke test for Dataset class.
"""
dataset_dir = get_test_data_path()
dset = Dataset('dataset_files', dataset_dir)
assert isinstance(dset, Dataset)
def test_load_dataset2():
"""Test gclda.dataset.Dataset.load with gzipped file.
"""
dataset_file = join(get_test_data_path(), 'gclda_dataset.pklz')
dset = Dataset.load(dataset_file)
assert isinstance(dset, Dataset)
"""
###############################################################################
# Start with the necessary imports
# --------------------------------
from os.path import join
from gclda.dataset import Dataset
from gclda.model import Model
from gclda.utils import get_resource_path
###############################################################################
# Initialize dataset
# ----------------------------------
dataset_label = 'Neurosynth2015Filtered2_1000docs'
dataset_dir = join(get_resource_path(), 'datasets')
dataset = Dataset(dataset_label, dataset_dir)
dataset.display_dataset_summary()
###############################################################################
# Initialize model
# ----------------------
model = Model(dataset,
n_topics=200,
n_regions=2,
alpha=.1,
beta=.01,
gamma=.01,
delta=1.0,
dobs=25,
roi_size=50,
symmetric=True,