def setupOutputs(self):
self.ReturnCode.meta.dtype = bool
self.ReturnCode.meta.shape = (1,)
self._closeFiles()
self._primaryBlockwiseFileset = BlockwiseFileset( self.OutputFilesetDescription.value, 'a' )
self._secondaryBlockwiseFilesets = []
for slot in self.SecondaryOutputDescriptions:
descriptionPath = slot.value
self._secondaryBlockwiseFilesets.append( BlockwiseFileset( descriptionPath, 'a' ) )
def setupClass(cls):
if platform.system() == 'Windows':
# On windows, there are errors, and we make no attempt to solve them (at the moment).
raise nose.SkipTest
testConfig = \
"""
{
"_schema_name" : "blockwise-fileset-description",
"_schema_version" : 1.0,
"name" : "synapse_small",
"format" : "hdf5",
"axes" : "txyzc",
"shape" : [1,400,400,200,1],
"dtype" : "numpy.uint8",
"compression" : "lzf",
"block_shape" : [1, 50, 50, 50, 100],
"block_file_name_format" : "cube{roiString}.h5/volume/data"
}
"""
cls.tempDir = tempfile.mkdtemp()
cls.description_path = os.path.join(cls.tempDir, "description.json")
with open(cls.description_path, 'w') as f:
f.write(testConfig)
logger.debug("Loading config file...")
cls.bfs = BlockwiseFileset(cls.description_path, 'a')
cls.dataShape = tuple(cls.bfs.description.shape)
logger.debug("Creating random test data...")
cls.data = numpy.random.randint(255,
size=cls.dataShape).astype(numpy.uint8)
def setupOutputs(self):
if not os.path.exists(self.DescriptionFilePath.value):
raise OpBlockwiseFilesetReader.MissingDatasetError(
"Dataset description not found: {}".format(
self.DescriptionFilePath.value))
# Load up the class that does the real work
self._blockwiseFileset = BlockwiseFileset(
self.DescriptionFilePath.value)
# Check for errors in the description file
descriptionFields = self._blockwiseFileset.description
axes = descriptionFields.axes
assert False not in map(
lambda a: a in 'txyzc',
axes), "Unknown axis type. Known axes: txyzc Your axes:".format(
axes)
self.Output.meta.shape = tuple(descriptionFields.view_shape)
self.Output.meta.dtype = descriptionFields.dtype
self.Output.meta.axistags = vigra.defaultAxistags(
descriptionFields.axes)
drange = descriptionFields.drange
if drange is not None:
self.Output.meta.drange = drange
def setupOutputs(self):
self.ReturnCode.meta.dtype = bool
self.ReturnCode.meta.shape = (1, )
self._closeFiles()
self._primaryBlockwiseFileset = BlockwiseFileset(
self.OutputFilesetDescription.value, 'a')
def setUp(self):
"""
Create a blockwise fileset to test with.
"""
if platform.system() == 'Windows':
# On windows, there are errors, and we make no attempt to solve them (at the moment).
raise nose.SkipTest
try:
BlockwiseFileset._prepare_system()
except ValueError:
# If the system isn't configured to allow lots of open files, we can't run this test.
raise nose.SkipTest
testConfig = \
"""
{
"_schema_name" : "blockwise-fileset-description",
"_schema_version" : 1.0,
"name" : "synapse_small",
"format" : "hdf5",
"axes" : "txyzc",
"shape" : [1,400,400,100,1],
"dtype" : "numpy.uint8",
"block_shape" : [1, 50, 50, 50, 100],
"block_file_name_format" : "cube{roiString}.h5/volume/data"
}
"""
self.tempDir = tempfile.mkdtemp()
self.configpath = os.path.join(self.tempDir, "config.json")
logger.debug("Loading config file...")
with open(self.configpath, 'w') as f:
f.write(testConfig)
logger.debug("Creating random test data...")
bfs = BlockwiseFileset(self.configpath, 'a')
dataShape = tuple(bfs.description.shape)
self.data = numpy.random.randint(255,
size=dataShape).astype(numpy.uint8)
logger.debug("Writing test data...")
datasetRoi = ([0, 0, 0, 0, 0], dataShape)
bfs.writeData(datasetRoi, self.data)
block_starts = getIntersectingBlocks(bfs.description.block_shape,
datasetRoi)
for block_start in block_starts:
bfs.setBlockStatus(block_start, BlockwiseFileset.BLOCK_AVAILABLE)
bfs.close()
def setupClass(cls):
if platform.system() == 'Windows':
# On windows, there are errors, and we make no attempt to solve them (at the moment).
raise nose.SkipTest
try:
BlockwiseFileset._prepare_system()
except ValueError:
# If the system isn't configured to allow lots of open files, we can't run this test.
raise nose.SkipTest
testConfig = \
"""
{
"_schema_name" : "blockwise-fileset-description",
"_schema_version" : 1.0,
"name" : "synapse_small",
"format" : "hdf5",
"axes" : "txyzc",
"shape" : [1,10,20,5,1],
"dtype" : "object",
"block_shape" : [1, 5, 4, 1, 100],
"block_file_name_format" : "cube{roiString}.h5/volume/data"
}
"""
cls.tempDir = tempfile.mkdtemp()
cls.description_path = os.path.join(cls.tempDir, "config.json")
with open(cls.description_path, 'w') as f:
f.write(testConfig)
logger.debug("Loading config file...")
cls.bfs = BlockwiseFileset(cls.description_path, 'a')
cls.dataShape = tuple(cls.bfs.description.shape)
def make_dummy_dict(x):
return {str(x): numpy.array([x, x])}
vec_make_dummy_dict = numpy.vectorize(make_dummy_dict)
int_data = numpy.random.randint(255,
size=cls.dataShape).astype(numpy.uint8)
dict_data = vec_make_dummy_dict(int_data)
cls.data = dict_data
def test_6_TestExportSubset(self):
roi = ((0, 0, 50, 100, 0), (1, 100, 200, 200, 1))
exportDir = tempfile.mkdtemp()
self.bfs.close()
self.bfs.reopen('r')
exported_description_path = self.bfs.exportSubset(roi, exportDir)
try:
exported_bfs = BlockwiseFileset(exported_description_path, 'r')
assert os.path.exists(
exported_description_path
), "Couldn't even find the exported description file."
read_data = exported_bfs.readData(roi)
expected_data = self.data[roiToSlice(*roi)]
assert read_data.shape == expected_data.shape, "Exported data had wrong shape"
assert read_data.dtype == expected_data.dtype, "Exported data had wrong dtype"
assert (read_data == expected_data
).all(), "Exported data did not match expected data"
finally:
shutil.rmtree(exportDir)
def test_9_TestView(self):
"""
Load some of the dataset again; this time with an offset view.
Note: The original blockwise fileset must be closed before this test starts.
"""
# Create a copy of the original description, but specify a translated (and smaller) view
desc = BlockwiseFileset.readDescription(self.description_path)
desc.view_origin = [0, 300, 200, 100, 0]
desc.view_shape = [1, 50, 50, 50, 1]
offsetConfigPath = self.description_path + '_offset'
BlockwiseFileset.writeDescription(offsetConfigPath, desc)
# Open the fileset using the special description file
bfs = BlockwiseFileset(offsetConfigPath, 'r')
try:
assert (bfs.description.view_origin == desc.view_origin).all()
assert (bfs.description.view_shape == desc.view_shape).all()
# Read some data
logger.debug("Reading data...")
disk_slicing = numpy.s_[:, 300:350, 200:250, 100:150, :]
view_slicing = numpy.s_[:, 0:50, 0:50, 0:50, :]
roi = sliceToRoi(view_slicing, self.dataShape)
roiShape = roi[1] - roi[0]
read_data = numpy.zeros(tuple(roiShape), dtype=numpy.uint8)
bfs.readData(roi, read_data)
# The data we read should match the correct part of the original dataset.
logger.debug("Checking data...")
assert self.data[disk_slicing].shape == read_data.shape
assert (self.data[disk_slicing] == read_data
).all(), "Data didn't match."
finally:
bfs.close()
def _prepareDestination(self):
"""
- If the result file doesn't exist yet, create it (and the dataset)
- If the result file already exists, return a list of the rois that
are NOT needed (their data already exists in the final output)
"""
originalDescription = BlockwiseFileset.readDescription(
self.OutputDatasetDescription.value)
datasetDescription = copy.deepcopy(originalDescription)
# Modify description fields as needed
# -- axes
datasetDescription.axes = "".join(
self.Input.meta.getTaggedShape().keys())
assert set(originalDescription.axes) == set( datasetDescription.axes ), \
"Can't prepare destination dataset: original dataset description listed " \
"axes as {}, but actual output axes are {}".format( originalDescription.axes, datasetDescription.axes )
# -- shape
datasetDescription.view_shape = list(self.Input.meta.shape)
# -- block_shape
assert originalDescription.block_shape is not None
originalBlockDims = collections.OrderedDict(
zip(originalDescription.axes, originalDescription.block_shape))
datasetDescription.block_shape = map(lambda a: originalBlockDims[a],
datasetDescription.axes)
datasetDescription.block_shape = map(
min, zip(datasetDescription.block_shape, self.Input.meta.shape))
# -- chunks
if originalDescription.chunks is not None:
originalChunkDims = collections.OrderedDict(
zip(originalDescription.axes, originalDescription.chunks))
datasetDescription.chunks = map(lambda a: originalChunkDims[a],
datasetDescription.axes)
datasetDescription.chunks = map(
min, zip(datasetDescription.chunks, self.Input.meta.shape))
# -- dtype
if datasetDescription.dtype != self.Input.meta.dtype:
dtype = self.Input.meta.dtype
if type(dtype) is numpy.dtype:
dtype = dtype.type
datasetDescription.dtype = dtype().__class__.__name__
# Create a unique hash for this blocking scheme.
# If it changes, we can't use any previous data.
sha = hashlib.sha1()
sha.update(str(tuple(datasetDescription.block_shape)))
sha.update(datasetDescription.axes)
sha.update(datasetDescription.block_file_name_format)
datasetDescription.hash_id = sha.hexdigest()
if datasetDescription != originalDescription:
descriptionFilePath = self.OutputDatasetDescription.value
logger.info("Overwriting dataset description: {}".format(
descriptionFilePath))
BlockwiseFileset.writeDescription(descriptionFilePath,
datasetDescription)
with open(descriptionFilePath, 'r') as f:
logger.info(f.read())
# Now open the dataset
blockwiseFileset = BlockwiseFileset(
self.OutputDatasetDescription.value)
taskInfos = self._prepareTaskInfos(blockwiseFileset.getAllBlockRois())
if blockwiseFileset.description.hash_id != originalDescription.hash_id:
# Something about our blocking scheme changed.
# Make sure all blocks are marked as NOT available.
# (Just in case some were left over from a previous run.)
for roi in taskInfos.keys():
blockwiseFileset.setBlockStatus(
roi[0], BlockwiseFileset.BLOCK_NOT_AVAILABLE)
return blockwiseFileset, taskInfos
