def test_index_dataset():
"""
Tests the index_dataset function using a numpy array to approximate
a dataset.
"""
data = np.arange(1000)
mask = np.unique(np.random.randint(0, 1000, 100))
true = data[mask]
assert (index_dataset(data, mask) == true).all()
def test_index_dataset_h5py():
"""
Tests the index_dataset function on a real HDF5 dataset.
"""
file = create_in_memory_hdf5()
data = np.arange(100000)
mask = np.unique(np.random.randint(0, 100000, 10000))
dataset = file.create_dataset("Test", data=data)
assert (index_dataset(dataset, mask) == data[mask]).all()
def test_index_dataset_h5py():
"""
Tests the index_dataset function on a real HDF5 dataset.
"""
# This creates an in-memory file
file = h5py.File(name='f1', driver='core', backing_store=False)
data = np.arange(100000)
mask = np.unique(np.random.randint(0, 100000, 10000))
dataset = file.create_dataset("Test", data=data)
assert (index_dataset(dataset, mask) == data[mask]).all()
def test_index_dataset():
"""
Tests the index_dataset function using a numpy array to approximate
a dataset.
"""
file = create_in_memory_hdf5()
data = file.create_dataset("test", data=np.arange(1000))
mask = np.unique(np.random.randint(0, 1000, 100))
true = data[list(mask)]
assert (index_dataset(data, mask) == true).all()
file.close()