def saveAsBinarySeries(self, outputDirPath, overwrite=False):
"""Writes out Series-formatted data.
Subclasses are *not* expected to override this method.
Parameters
----------
outputdirname : string path or URI to directory to be created
Output files will be written underneath outputdirname. This directory must not yet exist
(unless overwrite is True), and must be no more than one level beneath an existing directory.
It will be created as a result of this call.
overwrite : bool
If true, outputdirname and all its contents will be deleted and recreated as part
of this call.
"""
from thunder.rdds.fileio.writers import getParallelWriterForPath
from thunder.rdds.fileio.seriesloader import writeSeriesConfig
from thunder.utils.common import AWSCredentials
if not overwrite:
self._checkOverwrite(outputDirPath)
overwrite = True # prevent additional downstream checks for this path
awsCredentialsOverride = AWSCredentials.fromContext(self.rdd.ctx)
writer = getParallelWriterForPath(outputDirPath)(outputDirPath, overwrite=overwrite,
awsCredentialsOverride=awsCredentialsOverride)
binseriesRdd = self.toBinarySeries()
binseriesRdd.foreach(writer.writerFcn)
writeSeriesConfig(outputDirPath, len(self.dims), self.nimages, keyType='int16', valueType=self.dtype,
overwrite=overwrite, awsCredentialsOverride=awsCredentialsOverride)
def __init__(self, sparkContext):
"""Initialize a new ImagesLoader object.
Parameters
----------
sparkcontext: SparkContext
The pyspark SparkContext object used by the current Thunder environment.
"""
from thunder.utils.common import AWSCredentials
self.sc = sparkContext
self.awsCredentialsOverride = AWSCredentials.fromContext(sparkContext)
def __init__(self, sparkContext):
"""Initialize a new ImagesLoader object.
Parameters
----------
sparkcontext: SparkContext
The pyspark SparkContext object used by the current Thunder environment.
"""
from thunder.utils.common import AWSCredentials
self.sc = sparkContext
self.awsCredentialsOverride = AWSCredentials.fromContext(sparkContext)
def exportAsPngs(self, outputDirPath, filePrefix="export", overwrite=False,
collectToDriver=True):
"""
Write out basic png files for two-dimensional image data.
Files will be written into a newly-created directory on the local file system given by outputdirname.
All workers must be able to see the output directory via an NFS share or similar.
Parameters
----------
outputDirPath : string
Path to output directory to be created. Exception will be thrown if this directory already
exists, unless overwrite is True. Directory must be one level below an existing directory.
filePrefix : string
String to prepend to all filenames. Files will be named <fileprefix>00000.png, <fileprefix>00001.png, etc
overwrite : bool
If true, the directory given by outputdirname will first be deleted if it already exists.
collectToDriver : bool, default True
If true, images will be collect()'ed at the driver first before being written out, allowing
for use of a local filesystem at the expense of network overhead. If false, images will be written
in parallel by each executor, presumably to a distributed or networked filesystem.
"""
dims = self.dims
if not len(dims) == 2:
raise ValueError("Only two-dimensional images can be exported as .png files; image is %d-dimensional." %
len(dims))
from matplotlib.pyplot import imsave
from io import BytesIO
from thunder.rdds.fileio.writers import getParallelWriterForPath, getCollectedFileWriterForPath
from thunder.utils.common import AWSCredentials
def toFilenameAndPngBuf(kv):
key, img = kv
fname = filePrefix+"%05d.png" % int(key)
bytebuf = BytesIO()
imsave(bytebuf, img, format="png")
return fname, bytebuf.getvalue()
bufRdd = self.rdd.map(toFilenameAndPngBuf)
awsCredentials = AWSCredentials.fromContext(self.rdd.ctx)
if collectToDriver:
writer = getCollectedFileWriterForPath(outputDirPath)(outputDirPath, overwrite=overwrite,
awsCredentialsOverride=awsCredentials)
writer.writeCollectedFiles(bufRdd.collect())
else:
writer = getParallelWriterForPath(outputDirPath)(outputDirPath, overwrite=overwrite,
awsCredentialsOverride=awsCredentials)
bufRdd.foreach(writer.writerFcn)
def __init__(self, sparkContext, minPartitions=None):
"""Initialize a new SeriesLoader object.
Parameters
----------
sparkcontext: SparkContext
The pyspark SparkContext object used by the current Thunder environment.
minPartitions: int
minimum number of partitions to use when loading data. (Used by fromText, fromMatLocal, and fromNpyLocal)
"""
from thunder.utils.common import AWSCredentials
self.sc = sparkContext
self.minPartitions = minPartitions
self.awsCredentialsOverride = AWSCredentials.fromContext(sparkContext)
def saveAsBinaryImages(self,
outputDirPath,
filePrefix="export",
overwrite=False):
"""
Write out images or volumes as flat binary files.
Files will be written into a newly-created directory given by outputdirname.
Parameters
----------
outputDirPath : string
Path to output directory to be created. Exception will be thrown if this directory already
exists, unless overwrite is True. Directory must be one level below an existing directory.
filePrefix : string
String to prepend to all filenames. Files will be named <fileprefix>-00000.bin, <fileprefix>-00001.bin, etc
overwrite : bool
If true, the directory given by outputdirname will first be deleted if it already exists.
"""
from thunder.rdds.fileio.writers import getParallelWriterForPath
from thunder.rdds.fileio.imagesloader import writeBinaryImagesConfig
from thunder.utils.common import AWSCredentials
dimsTotal = list(asarray(self.dims.max) - asarray(self.dims.min) + 1)
def toFilenameAndBinaryBuf(kv):
key, img = kv
fname = filePrefix + "-" + "%05d.bin" % int(key)
return fname, img.transpose().copy()
bufRdd = self.rdd.map(toFilenameAndBinaryBuf)
awsCredentials = AWSCredentials.fromContext(self.rdd.ctx)
writer = getParallelWriterForPath(outputDirPath)(
outputDirPath,
overwrite=overwrite,
awsCredentialsOverride=awsCredentials)
bufRdd.foreach(writer.writerFcn)
writeBinaryImagesConfig(outputDirPath,
dims=dimsTotal,
dtype=self.dtype,
overwrite=overwrite,
awsCredentialsOverride=awsCredentials)
def saveAsBinarySeries(self, outputDirPath, overwrite=False):
"""Writes out Series-formatted data.
Subclasses are *not* expected to override this method.
Parameters
----------
outputdirname : string path or URI to directory to be created
Output files will be written underneath outputdirname. This directory must not yet exist
(unless overwrite is True), and must be no more than one level beneath an existing directory.
It will be created as a result of this call.
overwrite : bool
If true, outputdirname and all its contents will be deleted and recreated as part
of this call.
"""
from thunder.rdds.fileio.writers import getParallelWriterForPath
from thunder.rdds.fileio.seriesloader import writeSeriesConfig
from thunder.utils.common import AWSCredentials
if not overwrite:
self._checkOverwrite(outputDirPath)
overwrite = True # prevent additional downstream checks for this path
awsCredentialsOverride = AWSCredentials.fromContext(self.rdd.ctx)
writer = getParallelWriterForPath(outputDirPath)(
outputDirPath,
overwrite=overwrite,
awsCredentialsOverride=awsCredentialsOverride)
binseriesRdd = self.toBinarySeries()
binseriesRdd.foreach(writer.writerFcn)
writeSeriesConfig(outputDirPath,
len(self.dims),
self.nimages,
keyType='int16',
valueType=self.dtype,
overwrite=overwrite,
awsCredentialsOverride=awsCredentialsOverride)
def saveAsBinaryImages(self, outputDirPath, filePrefix="export", overwrite=False):
"""
Write out images or volumes as flat binary files.
Files will be written into a newly-created directory given by outputdirname.
Parameters
----------
outputDirPath : string
Path to output directory to be created. Exception will be thrown if this directory already
exists, unless overwrite is True. Directory must be one level below an existing directory.
filePrefix : string
String to prepend to all filenames. Files will be named <fileprefix>-00000.bin, <fileprefix>-00001.bin, etc
overwrite : bool
If true, the directory given by outputdirname will first be deleted if it already exists.
"""
from thunder.rdds.fileio.writers import getParallelWriterForPath
from thunder.rdds.fileio.imagesloader import writeBinaryImagesConfig
from thunder.utils.common import AWSCredentials
dimsTotal = list(asarray(self.dims.max)-asarray(self.dims.min)+1)
def toFilenameAndBinaryBuf(kv):
key, img = kv
fname = filePrefix+"-"+"%05d.bin" % int(key)
return fname, img.transpose().copy()
bufRdd = self.rdd.map(toFilenameAndBinaryBuf)
awsCredentials = AWSCredentials.fromContext(self.rdd.ctx)
writer = getParallelWriterForPath(outputDirPath)(outputDirPath, overwrite=overwrite,
awsCredentialsOverride=awsCredentials)
bufRdd.foreach(writer.writerFcn)
writeBinaryImagesConfig(outputDirPath, dims=dimsTotal, dtype=self.dtype,
overwrite=overwrite, awsCredentialsOverride=awsCredentials)
def saveAsBinarySeries(self, outputDirPath, overwrite=False):
"""
Writes out Series-formatted data.
This method (Series.saveAsBinarySeries) writes out binary series files using the current partitioning
of this Series object. (That is, if mySeries.rdd.getNumPartitions() == 5, then 5 files will be written
out, one per partition.) The records will not be resorted; the file names for each partition will be
taken from the key of the first Series record in that partition. If the Series object is already
sorted and no records have been removed by filtering, then the resulting output should be equivalent
to what one would get from calling myImages.saveAsBinarySeries().
If all one wishes to do is to save out Images data in a binary series format, then
tsc.convertImagesToSeries() will likely be more efficient than
tsc.loadImages().toSeries().saveAsBinarySeries().
Parameters
----------
outputDirPath : string path or URI to directory to be created
Output files will be written underneath outputdirname. This directory must not yet exist
(unless overwrite is True), and must be no more than one level beneath an existing directory.
It will be created as a result of this call.
overwrite : bool
If true, outputdirname and all its contents will be deleted and recreated as part
of this call.
"""
import cStringIO as StringIO
import struct
from thunder.rdds.imgblocks.blocks import SimpleBlocks
from thunder.rdds.fileio.writers import getParallelWriterForPath
from thunder.rdds.fileio.seriesloader import writeSeriesConfig
from thunder.utils.common import AWSCredentials
if not overwrite:
self._checkOverwrite(outputDirPath)
overwrite = True # prevent additional downstream checks for this path
def partitionToBinarySeries(kvIter):
""" Collects all Series records in a partition into a single binary series record. """
keypacker = None
firstKey = None
buf = StringIO.StringIO()
for seriesKey, series in kvIter:
if keypacker is None:
keypacker = struct.Struct('h' * len(seriesKey))
firstKey = seriesKey
# print >> sys.stderr, seriesKey, series, series.tostring().encode('hex')
buf.write(keypacker.pack(*seriesKey))
buf.write(series.tostring())
val = buf.getvalue()
buf.close()
# we might have an empty partition, in which case firstKey will still be None
if firstKey is None:
return iter([])
else:
label = SimpleBlocks.getBinarySeriesNameForKey(
firstKey) + ".bin"
return iter([(label, val)])
awsCredentials = AWSCredentials.fromContext(self.rdd.ctx)
writer = getParallelWriterForPath(outputDirPath)(
outputDirPath,
overwrite=overwrite,
awsCredentialsOverride=awsCredentials)
binseriesrdd = self.rdd.mapPartitions(partitionToBinarySeries)
binseriesrdd.foreach(writer.writerFcn)
# TODO: all we really need here are the number of keys and number of values, which could in principle
# be cached in _nkeys and _nvals attributes, removing the need for this .first() call in most cases.
firstKey, firstVal = self.first()
writeSeriesConfig(outputDirPath,
len(firstKey),
len(firstVal),
keyType='int16',
valueType=self.dtype,
overwrite=overwrite,
awsCredentialsOverride=awsCredentials)
def saveAsBinarySeries(self, outputDirPath, overwrite=False):
"""
Writes out Series-formatted data.
This method (Series.saveAsBinarySeries) writes out binary series files using the current partitioning
of this Series object. (That is, if mySeries.rdd.getNumPartitions() == 5, then 5 files will be written
out, one per partition.) The records will not be resorted; the file names for each partition will be
taken from the key of the first Series record in that partition. If the Series object is already
sorted and no records have been removed by filtering, then the resulting output should be equivalent
to what one would get from calling myImages.saveAsBinarySeries().
If all one wishes to do is to save out Images data in a binary series format, then
tsc.convertImagesToSeries() will likely be more efficient than
tsc.loadImages().toSeries().saveAsBinarySeries().
Parameters
----------
outputDirPath : string path or URI to directory to be created
Output files will be written underneath outputdirname. This directory must not yet exist
(unless overwrite is True), and must be no more than one level beneath an existing directory.
It will be created as a result of this call.
overwrite : bool
If true, outputdirname and all its contents will be deleted and recreated as part
of this call.
"""
import cStringIO as StringIO
import struct
from thunder.rdds.imgblocks.blocks import SimpleBlocks
from thunder.rdds.fileio.writers import getParallelWriterForPath
from thunder.rdds.fileio.seriesloader import writeSeriesConfig
from thunder.utils.common import AWSCredentials
if not overwrite:
self._checkOverwrite(outputDirPath)
overwrite = True # prevent additional downstream checks for this path
def partitionToBinarySeries(kvIter):
""" Collects all Series records in a partition into a single binary series record. """
keypacker = None
firstKey = None
buf = StringIO.StringIO()
for seriesKey, series in kvIter:
if keypacker is None:
keypacker = struct.Struct('h'*len(seriesKey))
firstKey = seriesKey
# print >> sys.stderr, seriesKey, series, series.tostring().encode('hex')
buf.write(keypacker.pack(*seriesKey))
buf.write(series.tostring())
val = buf.getvalue()
buf.close()
# we might have an empty partition, in which case firstKey will still be None
if firstKey is None:
return iter([])
else:
label = SimpleBlocks.getBinarySeriesNameForKey(firstKey) + ".bin"
return iter([(label, val)])
awsCredentials = AWSCredentials.fromContext(self.rdd.ctx)
writer = getParallelWriterForPath(outputDirPath)(outputDirPath, overwrite=overwrite,
awsCredentialsOverride=awsCredentials)
binseriesrdd = self.rdd.mapPartitions(partitionToBinarySeries)
binseriesrdd.foreach(writer.writerFcn)
# TODO: all we really need here are the number of keys and number of values, which could in principle
# be cached in _nkeys and _nvals attributes, removing the need for this .first() call in most cases.
firstKey, firstVal = self.first()
writeSeriesConfig(outputDirPath, len(firstKey), len(firstVal), keyType='int16', valueType=self.dtype,
overwrite=overwrite, awsCredentialsOverride=awsCredentials)
def exportAsPngs(self,
outputDirPath,
filePrefix="export",
overwrite=False,
collectToDriver=True):
"""
Write out basic png files for two-dimensional image data.
Files will be written into a newly-created directory on the local file system given by outputdirname.
All workers must be able to see the output directory via an NFS share or similar.
Parameters
----------
outputDirPath : string
Path to output directory to be created. Exception will be thrown if this directory already
exists, unless overwrite is True. Directory must be one level below an existing directory.
filePrefix : string
String to prepend to all filenames. Files will be named <fileprefix>00000.png, <fileprefix>00001.png, etc
overwrite : bool
If true, the directory given by outputdirname will first be deleted if it already exists.
collectToDriver : bool, default True
If true, images will be collect()'ed at the driver first before being written out, allowing
for use of a local filesystem at the expense of network overhead. If false, images will be written
in parallel by each executor, presumably to a distributed or networked filesystem.
"""
dims = self.dims
if not len(dims) == 2:
raise ValueError(
"Only two-dimensional images can be exported as .png files; image is %d-dimensional."
% len(dims))
from matplotlib.pyplot import imsave
from io import BytesIO
from thunder.rdds.fileio.writers import getParallelWriterForPath, getCollectedFileWriterForPath
from thunder.utils.common import AWSCredentials
def toFilenameAndPngBuf(kv):
key, img = kv
fname = filePrefix + "%05d.png" % int(key)
bytebuf = BytesIO()
imsave(bytebuf, img, format="png")
return fname, bytebuf.getvalue()
bufRdd = self.rdd.map(toFilenameAndPngBuf)
awsCredentials = AWSCredentials.fromContext(self.rdd.ctx)
if collectToDriver:
writer = getCollectedFileWriterForPath(outputDirPath)(
outputDirPath,
overwrite=overwrite,
awsCredentialsOverride=awsCredentials)
writer.writeCollectedFiles(bufRdd.collect())
else:
writer = getParallelWriterForPath(outputDirPath)(
outputDirPath,
overwrite=overwrite,
awsCredentialsOverride=awsCredentials)
bufRdd.foreach(writer.writerFcn)
def _checkOverwrite(self, outputDirPath):
""" Checks for existence of outputDirPath, raising ValueError if it already exists """
from thunder.utils.common import AWSCredentials, raiseErrorIfPathExists
awsCredentialOverride = AWSCredentials.fromContext(self.rdd.ctx)
raiseErrorIfPathExists(outputDirPath,
awsCredentialsOverride=awsCredentialOverride)
def _checkOverwrite(self, outputDirPath):
""" Checks for existence of outputDirPath, raising ValueError if it already exists """
from thunder.utils.common import AWSCredentials, raiseErrorIfPathExists
awsCredentialOverride = AWSCredentials.fromContext(self.rdd.ctx)
raiseErrorIfPathExists(outputDirPath, awsCredentialsOverride=awsCredentialOverride)