def test_metadata_round_trip(self):
# Create dummy image stack
sample = th.gen_img_shared_array_with_val(42.)
images = Images(sample)
images.metadata['message'] = 'hello, world!'
# Save image stack
saver.save(images, self.output_directory)
# Load image stack back
dataset = loader.load(self.output_directory)
loaded_images = dataset.sample
# Ensure properties have been preserved
self.assertEqual(loaded_images.metadata, images.metadata)
loaded_images.free_memory()
if dataset.dark_before:
dataset.dark_before.free_memory()
if dataset.dark_after:
dataset.dark_after.free_memory()
if dataset.flat_before:
dataset.flat_before.free_memory()
if dataset.flat_after:
dataset.flat_after.free_memory()
def do_preproc(self,
img_format,
loader_indices=None,
expected_len=None,
saver_indices=None,
data_as_stack=False):
expected_images = th.generate_images()
# saver indices only affects the enumeration of the data
if saver_indices:
# crop the original images to make sure the tests is correct
expected_images.data = expected_images.data[
saver_indices[0]:saver_indices[1]]
# saver.save_preproc_images(expected_images)
saver.save(expected_images,
self.output_directory,
out_format=img_format,
indices=saver_indices)
self.assert_files_exist(
os.path.join(self.output_directory,
saver.DEFAULT_NAME_PREFIX), img_format, data_as_stack,
expected_images.data.shape[0], saver_indices)
# this does not load any flats or darks as they were not saved out
dataset = loader.load(self.output_directory,
in_format=img_format,
indices=loader_indices)
loaded_images = dataset.sample
if loader_indices:
assert len(loaded_images.data) == expected_len, \
"The length of the loaded data does not " \
"match the expected length! Expected: {0}, " \
"Got {1}".format(expected_len, len(
loaded_images.data))
expected_images.data = expected_images.data[
loader_indices[0]:loader_indices[1]]
npt.assert_equal(loaded_images.data, expected_images.data)
loaded_images.free_memory()
if dataset.dark_before:
dataset.dark_before.free_memory()
if dataset.dark_after:
dataset.dark_after.free_memory()
if dataset.flat_before:
dataset.flat_before.free_memory()
if dataset.flat_after:
dataset.flat_after.free_memory()
def test_metadata_round_trip(self):
# Create dummy image stack
sample = th.gen_img_numpy_rand()
images = Images(sample)
images.metadata['message'] = 'hello, world!'
# Save image stack
saver.save(images, self.output_directory)
# Load image stack back
dataset = loader.load(self.output_directory)
loaded_images = dataset.sample
# Ensure properties have been preserved
self.assertEqual(loaded_images.metadata, images.metadata)
def do_saving(self, stack_uuid, output_dir, name_prefix, image_format, overwrite, progress):
svp = self.get_stack_visualiser(stack_uuid).presenter
filenames = saver.save(svp.images,
output_dir=output_dir,
name_prefix=name_prefix,
overwrite_all=overwrite,
out_format=image_format,
progress=progress)
svp.images.filenames = filenames
return True
def do_images_saving(self, images_id, output_dir, name_prefix,
image_format, overwrite, pixel_depth, progress):
images = self.get_images_by_uuid(images_id)
if images is None:
self.raise_error_when_images_not_found(images_id)
filenames = saver.save(images,
output_dir=output_dir,
name_prefix=name_prefix,
overwrite_all=overwrite,
out_format=image_format,
pixel_depth=pixel_depth,
progress=progress)
images.filenames = filenames
return True
def test_load_sample_flat_and_dark(self,
img_format='tiff',
loader_indices=None,
expected_len=None,
saver_indices=None):
images = th.generate_images()
flat_before = th.generate_images()
dark_before = th.generate_images()
flat_after = th.generate_images()
dark_after = th.generate_images()
# this only affects enumeration
saver._indices = saver_indices
# saver indices only affects the enumeration of the data
if saver_indices:
# crop the original images to make sure the test is checking the
# indices that were actually saved out
images.data = images.data[saver_indices[0]:saver_indices[1]]
saver.save(images, self.output_directory, out_format=img_format)
flat_before_dir = os.path.join(self.output_directory,
"imgIOTest_flat_before")
saver.save(flat_before, flat_before_dir, out_format=img_format)
flat_after_dir = os.path.join(self.output_directory,
"imgIOTest_flat_after")
saver.save(flat_after, flat_after_dir, out_format=img_format)
dark_before_dir = os.path.join(self.output_directory,
"imgIOTest_dark_before")
saver.save(dark_before, dark_before_dir, out_format=img_format)
dark_after_dir = os.path.join(self.output_directory,
"imgIOTest_dark_after")
saver.save(dark_after, dark_after_dir, out_format=img_format)
data_as_stack = False
self.assert_files_exist(
os.path.join(self.output_directory, saver.DEFAULT_NAME_PREFIX),
img_format, data_as_stack, images.data.shape[0])
flat_before_dir = os.path.join(flat_before_dir,
saver.DEFAULT_NAME_PREFIX)
self.assert_files_exist(flat_before_dir, img_format, data_as_stack,
flat_before.data.shape[0])
flat_after_dir = os.path.join(flat_after_dir,
saver.DEFAULT_NAME_PREFIX)
self.assert_files_exist(flat_after_dir, img_format, data_as_stack,
flat_after.data.shape[0])
dark_before_dir = os.path.join(dark_before_dir,
saver.DEFAULT_NAME_PREFIX)
self.assert_files_exist(dark_before_dir, img_format, data_as_stack,
dark_before.data.shape[0])
dark_after_dir = os.path.join(dark_after_dir,
saver.DEFAULT_NAME_PREFIX)
self.assert_files_exist(dark_after_dir, img_format, data_as_stack,
dark_after.data.shape[0])
flat_before_filename = f"{flat_before_dir}_{''.zfill(saver.DEFAULT_ZFILL_LENGTH)}.{img_format}"
flat_after_filename = f"{flat_after_dir}_{''.zfill(saver.DEFAULT_ZFILL_LENGTH)}.{img_format}"
dark_before_filename = f"{dark_before_dir}_{''.zfill(saver.DEFAULT_ZFILL_LENGTH)}.{img_format}"
dark_after_filename = f"{dark_after_dir}_{''.zfill(saver.DEFAULT_ZFILL_LENGTH)}.{img_format}"
dataset = loader.load(self.output_directory,
input_path_flat_before=flat_before_filename,
input_path_flat_after=flat_after_filename,
input_path_dark_before=dark_before_filename,
input_path_dark_after=dark_after_filename,
in_format=img_format,
indices=loader_indices)
loaded_images = dataset.sample
if loader_indices:
assert len(loaded_images.data) == expected_len, \
"The length of the loaded data doesn't " \
"match the expected length: {0}, " \
"Got: {1}".format(
expected_len, len(loaded_images.data))
# crop the original images to make sure the tests is correct
images.data = images.data[loader_indices[0]:loader_indices[1]]
npt.assert_equal(loaded_images.data, images.data)
# we only check the first image because they will be
# averaged out when loaded! The initial images are only 3s
npt.assert_equal(dataset.flat_before.data, flat_before.data)
npt.assert_equal(dataset.dark_before.data, dark_before.data)
npt.assert_equal(dataset.flat_after.data, flat_after.data)
npt.assert_equal(dataset.dark_after.data, dark_after.data)
loaded_images.free_memory()
if dataset.dark_before:
dataset.dark_before.free_memory()
if dataset.flat_before:
dataset.flat_before.free_memory()
if dataset.dark_after:
dataset.dark_after.free_memory()
if dataset.flat_after:
dataset.flat_after.free_memory()
