def loadImagesOCP(self,
bucketName,
resolution,
server='ocp.me',
startIdx=None,
stopIdx=None,
minBound=None,
maxBound=None):
"""
Load Images from OCP (Open Connectome Project).
The OCP is a web service for access to EM brain images and other neural image data.
The web-service can be accessed at http://www.openconnectomeproject.org/.
Parameters
----------
bucketName: string
Token name for the project in OCP. This name should exist on the server from which data is loaded.
resolution: nonnegative int
Resolution of the data in OCP
server: string, optional, default = 'ocp.me'
Name of the OCP server with the specified token.
startIdx: nonnegative int, optional, default = None
Convenience parameters to read only a subset of input files. Uses python slice conventions
(zero-based indexing with exclusive final position).
stopIdx: nonnegative int, optional
See startIdx.
minBound, maxBound: tuple of nonnegative int, optional, default = None
X,Y,Z bounds of the data to fetch from OCP. minBound contains the (xMin,yMin,zMin) while
maxBound contains (xMax,yMax,zMax).
Returns
-------
data: thunder.rdds.Images
An Images object, wrapping an RDD of with (int) : (numpy array) pairs
"""
from thunder.rdds.fileio.imagesloader import ImagesLoader
loader = ImagesLoader(self._sc)
# Checking StartIdx is smaller or equal to StopIdx
if startIdx is not None and stopIdx is not None and startIdx > stopIdx:
raise Exception(
"Error. startIdx {} is larger than stopIdx {}".format(
startIdx, stopIdx))
data = loader.fromOCP(bucketName,
resolution=resolution,
server=server,
startIdx=startIdx,
stopIdx=stopIdx,
minBound=minBound,
maxBound=maxBound)
return data
def loadImagesOCP(
self, bucketName, resolution, server="ocp.me", startIdx=None, stopIdx=None, minBound=None, maxBound=None
):
"""
Load Images from OCP (Open Connectome Project).
The OCP is a web service for access to EM brain images and other neural image data.
The web-service can be accessed at http://www.openconnectomeproject.org/.
Parameters
----------
bucketName: string
Token name for the project in OCP. This name should exist on the server from which data is loaded.
resolution: nonnegative int
Resolution of the data in OCP
server: string, optional, default = 'ocp.me'
Name of the OCP server with the specified token.
startIdx: nonnegative int, optional, default = None
Convenience parameters to read only a subset of input files. Uses python slice conventions
(zero-based indexing with exclusive final position).
stopIdx: nonnegative int, optional
See startIdx.
minBound, maxBound: tuple of nonnegative int, optional, default = None
X,Y,Z bounds of the data to fetch from OCP. minBound contains the (xMin,yMin,zMin) while
maxBound contains (xMax,yMax,zMax).
Returns
-------
data: thunder.rdds.Images
An Images object, wrapping an RDD of with (int) : (numpy array) pairs
"""
from thunder.rdds.fileio.imagesloader import ImagesLoader
loader = ImagesLoader(self._sc)
# Checking StartIdx is smaller or equal to StopIdx
if startIdx is not None and stopIdx is not None and startIdx > stopIdx:
raise Exception("Error. startIdx {} is larger than stopIdx {}".format(startIdx, stopIdx))
data = loader.fromOCP(
bucketName,
resolution=resolution,
server=server,
startIdx=startIdx,
stopIdx=stopIdx,
minBound=minBound,
maxBound=maxBound,
)
return data
