def test_create_in_memory_hdf5():
"""
Tests the creation of an in-memory hdf5 file.
"""
file = create_in_memory_hdf5()
file.close()
return
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():
"""
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()
def test_read_ranges_from_file():
"""
Tests the reading of ranges from file using a numpy array as a stand in for
the dataset.
"""
# In memory hdf5 file
file_handle = create_in_memory_hdf5()
handle = file_handle.create_dataset("test", data=np.arange(1000))
ranges = np.array([[77, 79], [81, 81], [88, 98], [204, 204]])
output_size = 2 + 10
output_type = type(handle[0])
expected = np.array([77, 78, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97])
out = read_ranges_from_file(handle, ranges, output_size, output_type)
assert (out == expected).all()
file_handle.close()