def toimages(self, chunk_size='auto'):
"""
Converts to images data.
This method is equivalent to series.toblocks(size).toimages().
Parameters
----------
chunk_size : str or tuple, size of series chunk used during conversion, default = 'auto'
String interpreted as memory size (in kilobytes, e.g. '64').
The exception is the string 'auto', which will choose a chunk size to make the
resulting blocks ~100 MB in size. Int interpreted as 'number of elements'.
Only valid in spark mode.
"""
from thunder.images.images import Images
if chunk_size is 'auto':
chunk_size = str(max([int(1e5 / prod(self.baseshape)), 1]))
n = len(self.shape) - 1
if self.mode == 'spark':
return Images(
self.values.swap(tuple(range(n)), (0, ), size=chunk_size))
if self.mode == 'local':
return Images(self.values.transpose((n, ) + tuple(range(0, n))))
def toimages(self, size='150'):
"""
Converts Series to Images.
Equivalent to calling series.toBlocks(size).toImages()
Parameters
----------
size : str, optional, default = "150M"
String interpreted as memory size.
"""
from thunder.images.images import Images
n = len(self.shape) - 1
if self.mode == 'spark':
return Images(self.values.swap(tuple(range(n)), (0, ), size=size))
if self.mode == 'local':
return Images(self.values.transpose((n, ) + tuple(range(0, n))))
def toimages(self):
"""
Convert blocks to images.
"""
from thunder.images.images import Images
if self.mode == 'spark':
values = self.values.values_to_keys((0, )).unchunk()
if self.mode == 'local':
values = self.values.unchunk()
return Images(values)