def setupOutputs(self):
# Create a RESTfulVolume object to read the description file and do the downloads.
self._volumeObject = RESTfulVolume(self.DescriptionFilePath.value)
self._axes = self._volumeObject.description.axes
outputShape = tuple(self._volumeObject.description.shape)
# If the dataset has no channel axis, add one.
if 'c' not in self._axes:
outputShape += (1, )
self._axes += 'c'
self.Output.meta.shape = outputShape
self.Output.meta.dtype = self._volumeObject.description.dtype
self.Output.meta.axistags = vigra.defaultAxistags(self._axes)
def __init__(self, compositeDescriptionPath):
"""
Constructor. Uses `readDescription` interally.
:param compositeDescriptionPath: The path to a JSON file that describes both the remote
volume and local storage structure. The JSON file schema is specified by
:py:data:`RESTfulBlockwiseFileset.DescriptionFields`.
"""
# Parse the description file, which contains sub-configs for the blockwise description and RESTful description
self.compositeDescription = RESTfulBlockwiseFileset.readDescription(
compositeDescriptionPath)
self.localDescription = self.compositeDescription.local_description
self.remoteDescription = self.compositeDescription.remote_description
super(RESTfulBlockwiseFileset,
self).__init__(compositeDescriptionPath,
'r',
preparsedDescription=self.localDescription)
self._remoteVolume = RESTfulVolume(
preparsedDescription=self.remoteDescription)
try:
if not self.localDescription.block_file_name_format.endswith(
self.remoteDescription.hdf5_dataset):
msg = "Your RESTful volume description file must specify an hdf5 internal dataset name that matches the one in your Blockwise Fileset description file!"
msg += "RESTful volume dataset name is '{}', but blockwise fileset format is '{}'".format(
self.remoteDescription.hdf5_dataset,
self.localDescription.block_file_name_format)
raise RuntimeError(msg)
if self.localDescription.axes != self.remoteDescription.axes:
raise RuntimeError(
"Your RESTful volume's axes must match the blockwise dataset axes. ('{}' does not match '{}')"
.format(self.remoteDescription.axes,
self.localDescription.axes))
if (numpy.array(self.localDescription.shape) > numpy.array(
self.remoteDescription.shape)).any():
raise RuntimeError(
"Your local blockwise volume shape must be smaller in all dimensions than the remote volume shape."
)
except:
logger.error("Error loading dataset from {}".format(
compositeDescriptionPath))
raise
def testBasic(self):
"""
Requires access to the Internet...
"""
# The openconnectome site appears to be down at the moment.
# This test fails when that happens...
import nose
raise nose.SkipTest
testConfig0 = """
{
"_schema_name" : "RESTful-volume-description",
"_schema_version" : 1.0,
"name" : "Bock11-level0",
"format" : "hdf5",
"axes" : "zyx",
"##NOTE":"The first z-slice of the bock dataset is 2917, so the origin_offset must be at least 2917",
"origin_offset" : [2917, 50000, 50000],
"bounds" : [4156, 135424, 119808],
"dtype" : "numpy.uint8",
"url_format" : "http://openconnecto.me/ocp/ca/bock11/hdf5/0/{x_start},{x_stop}/{y_start},{y_stop}/{z_start},{z_stop}/",
"hdf5_dataset" : "CUTOUT"
}
"""
testConfig4 = """
{
"_schema_name" : "RESTful-volume-description",
"_schema_version" : 1.0,
"name" : "Bock11-level4",
"format" : "hdf5",
"axes" : "zyx",
"##NOTE":"The first z-slice of the bock dataset is 2917, so the origin_offset must be at least 2917",
"origin_offset" : [2917, 50000, 50000],
"bounds" : [4156, 8704, 7680],
"dtype" : "numpy.uint8",
"url_format" : "http://openconnecto.me/ocp/ca/bock11/hdf5/4/{x_start},{x_stop}/{y_start},{y_stop}/{z_start},{z_stop}/",
"hdf5_dataset" : "CUTOUT"
}
"""
# Create the description file.
tempDir = tempfile.mkdtemp()
descriptionFilePath = os.path.join(tempDir, 'desc.json')
with open(descriptionFilePath, 'w') as descFile:
descFile.write(testConfig0)
# Create the volume object
volume = RESTfulVolume(descriptionFilePath)
#slicing = numpy.s_[0:100, 4000:4200, 4000:4200]
slicing = numpy.s_[0:25, 50000:50050, 50000:50075]
roi = sliceToRoi(slicing, volume.description.shape)
outputFile = os.path.join(tempDir, 'volume.h5')
datasetPath = outputFile + '/cube'
logger.debug("Downloading subvolume to: {}".format(datasetPath))
volume.downloadSubVolume(roi, datasetPath)
with h5py.File(outputFile, 'r') as hdf5File:
data = hdf5File['cube']
assert data.shape == (25, 50, 75)
shutil.rmtree(tempDir)
