def test_czi_parallel_processor(filename):
mock_ssm().start()
mock_s3().start()
init_ssm()
# init task
for x in range(2):
for y in range(2):
for z in range(2):
for c in range(2):
for t in range(2):
# Create sub_region file
open(
'sub_x_{}_2_y_{}_2_z_{}_2_c_{}_2_t_{}_2.txt'.
format(x, y, z, c, t), 'w').write("")
# Setup task with inputs
inputs = {
'file':
os.path.join('/test-resources', filename),
'sub_region_file':
'sub_x_{}_2_y_{}_2_z_{}_2_c_{}_2_t_{}_2.txt'.
format(x, y, z, c, t)
}
task = CZIProcessor(inputs=inputs)
setup_processor(task)
# run
task.run()
mock_s3().stop()
mock_ssm().stop()
def test_standard_image_processor(filename):
mock_ssm().start()
mock_s3().start()
init_ssm()
# init task
inputs = {'file': os.path.join('/test-resources', filename)}
task = StandardImageProcessor(inputs=inputs)
setup_processor(task)
# run
task.run()
# Check outputs
assert os.path.isfile('view_asset_info.json')
json_dict = json.load(open('view_asset_info.json'))
print json_dict
if 'huge' in filename or 'tif' in filename.lower():
assert os.path.isdir('view')
assert os.path.isfile('view/slide.dzi')
assert os.path.isfile('view/dimensions.json')
elif filename.endswith('.jp2'):
assert os.path.isfile('output.png')
else:
assert not os.path.isdir('view')
assert not os.path.isfile('view/slide.dzi')
assert os.path.isfile('metadata.json')
def test_sub_region_standard_image_processor(filename):
mock_ssm().start()
mock_s3().start()
init_ssm()
# init task
for a in range(1):
for b in range(1):
open('{}_{}.txt'.format(
a,
b,
), 'w').write("4,4")
inputs = {
'file': os.path.join('/test-resources', filename),
'sub_region_file': '{}_{}.txt'.format(
a,
b,
)
}
task = StandardImageProcessor(inputs=inputs)
setup_processor(task)
# run
task.run()
assert os.path.isdir('view')
assert os.path.isfile('view/slide.dzi')
def test_ometiff_processor(filename):
mock_ssm().start()
mock_s3().start()
init_ssm()
# init task
inputs = {'file': os.path.join('/test-resources', filename)}
task = OMETIFFProcessor(inputs=inputs)
setup_processor(task)
# run
task.run()
# Check outputs
assert os.path.isfile('view_asset_info.json')
json_dict = json.load(open('view_asset_info.json'))
assert 'size' in json_dict.keys()
assert 'fileType' in json_dict.keys()
assert os.path.isdir('%s-zoomed' %
os.path.basename(task.outputs[0].file_path))
assert os.path.isfile('%s-zoomed/dimensions.json' %
os.path.basename(task.outputs[0].file_path))
assert os.path.isfile('metadata.json')
# Check hack for backwards compatibility with viewer
assert os.path.isfile('%s-zoomed/slide.dzi' %
os.path.basename(task.outputs[0].file_path))
# assert os.path.isfile('%s-zoomed/slide.png' % os.path.basename(task.outputs[0].file_path))
mock_s3().stop()
mock_ssm().stop()
def test_czi_processor(filename):
mock_ssm().start()
mock_s3().start()
init_ssm()
# init task
inputs = {
'file': os.path.join('/test-resources', filename),
'optimize_view': "y"
}
task = CZIProcessor(inputs=inputs)
setup_processor(task)
# run
task.run()
# Check outputs
first_slice_set = sorted(
glob.glob('%s-zoomed/*.dzi' % os.path.basename(task.file)))[0]
assert os.path.isfile('%s-zoomed/slide.dzi' % os.path.basename(task.file))
assert os.path.isfile('metadata.json')
mock_s3().stop()
mock_ssm().stop()
def test_extract_structure_as_json(filename):
inputs = {'file': os.path.join('/test-resources', filename)}
mock_ssm().start()
mock_s3().start()
init_ssm()
task = HDF5StructureProcessor(inputs=inputs)
setup_processor(task)
task.run()
# Verify the payload JSON is written out:
assert task.payload_output_path and os.path.exists(
task.payload_output_path)
with open(task.payload_output_path, 'r') as f:
payload = json.load(f)
assert len(payload) > 0
entry = payload[0]
assert 'path' in entry and isinstance(entry['path'], list)
assert 'path_key' in entry and isinstance(entry['path_key'],
string_types)
assert 'name' in entry and isinstance(entry['name'], string_types)
assert 'metadata' in entry and isinstance(entry['metadata'], list)
assert 'type' in entry and isinstance(entry['type'],
(dict, string_types))
if isinstance(entry['type'], dict) and \
entry['type']['dimensions'] == 1 and \
entry['type']['size'] == 1:
assert 'value' in entry
# Verify the asset JSON is written out:
assert task.asset_output_path and os.path.exists(task.asset_output_path)
with open(task.asset_output_path, 'r') as f:
asset_info = json.load(f)
print(asset_info)
def test_explode_assets(filename):
print "~" * 60
print " Using test file %s to test exploding PNG assets " % filename
print "~" * 60
mock_dynamodb2().start()
mock_ssm().start()
mock_s3().start()
init_ssm()
# init task
inputs = {'file': os.path.join('/test-resources', filename)}
task = OMETIFFProcessor(inputs=inputs)
setup_processor(task)
# Load image
output_file = OMETIFFOutputFile()
output_file.file_path = task.file
output_file.load_and_save_assets(output_file.file_path,
i_xyzct=(-1, -1, -1, -1, -1),
n_xyzct=(-1, -1, -1, -1, -1),
asset_format='png')
# Since we know first two dimensions are are X and Y
assert output_file.img_dimensions['dimensions'][0]['assignment'] == 'X'
assert output_file.img_dimensions['dimensions'][1]['assignment'] == 'Y'
# Get number of files generated
num_png_files = len(
glob.glob('%s-zoomed/*.png' % os.path.basename(output_file.file_path)))
print glob.glob('%s-zoomed/*.png' %
os.path.basename(output_file.file_path))
# Ensure correct number of png outputs
if output_file.isRGB:
# Compute combinatorial number of files expected
shape = [
output_file.SizeX, output_file.SizeY, output_file.SizeZ,
output_file.SizeC, output_file.SizeT
]
# Remove RGB dimension from combinatorial count
shape.pop(output_file.RGBDimension)
else:
# Compute combinatorial number of files expected
shape = [
output_file.SizeX, output_file.SizeY, output_file.SizeZ,
output_file.SizeC, output_file.SizeT
]
total_count = np.prod(shape[2:])
print shape, output_file.isRGB
# Make sure same number of files generated
assert num_png_files == total_count
# Save to local storage output deepzoom files
output_file.load_and_save_assets(output_file.file_path,
i_xyzct=(-1, -1, -1, -1, -1),
n_xyzct=(-1, -1, -1, -1, -1),
asset_format='dzi')
# Get number of files generated
num_dzi_files = len(
glob.glob('%s-zoomed/*.dzi' % os.path.basename(output_file.file_path)))
print glob.glob('%s-zoomed/*.dzi' %
os.path.basename(output_file.file_path))
# Ensure correct number of dzi outputs
if output_file.isRGB:
# Compute combinatorial number of files expected
shape = [
output_file.SizeX, output_file.SizeY, output_file.SizeZ,
output_file.SizeC, output_file.SizeT
]
# Remove RGB dimension from combinatorial count
shape.pop(output_file.RGBDimension)
else:
# Compute combinatorial number of files expected
shape = [
output_file.SizeX, output_file.SizeY, output_file.SizeZ,
output_file.SizeC, output_file.SizeT
]
total_count = np.prod(shape[2:])
print shape
# Make sure same number of files generated
assert num_dzi_files == total_count
# Clean up
os.system('rm %s-zoomed/*.png' % os.path.basename(output_file.file_path))
os.system('rm %s-zoomed/*.dzi' % os.path.basename(output_file.file_path))
mock_s3().stop()
mock_ssm().stop()
mock_dynamodb2().stop()