def blockSums(data, blocks=None, processes=defaultProcesses):
"""Sums of evenly spaced blocks in array
Arguments:
data : array
array to perform the block sums on
blocks : int or None
number of blocks to split array into
processes : None or int
number of processes, if None use number of cpus
Returns:
array
sums of the values in the different blocks
"""
if processes is None:
processes = defaultProcesses
if blocks is None:
blocks = processes * defaultBlocksPerProcess
d = data.reshape(-1, order='A')
if data.dtype == bool:
d = d.view('uint8')
return code.blockSums1d(d, blocks=blocks, processes=processes)
def where(data,
out=None,
blocks=None,
cutoff=defaultCutoff,
processes=defaultProcesses):
"""Returns the indices of the non-zero entries of the array
Arguments:
data : array
array to search for nonzero indices
out : array or None
if not None results is written into this array
blocks : int or None
number of blocks to split array into for parallel processing
cutoff : int
number of elements below whih to switch to numpy.where
processes : None or int
number of processes, if None use number of cpus
Returns:
array
positions of the nonzero entries of the input array
Note:
Uses numpy.where if there is no match of dimension implemented!
"""
if data.ndim != 1 and data.ndim != 3:
raise Warning('Using numpy where for dimension %d and type %s!' %
(data.ndim, data.dtype))
return np.vstack(np.where(data)).T
if cutoff is None:
cutoff = 1
cutoff = min(1, cutoff)
if data.size <= cutoff:
return np.vstack(np.where(data)).T
if processes is None:
processes = defaultProcesses
if blocks is None:
blocks = processes * defaultBlocksPerProcess
if data.dtype == bool:
d = data.view('uint8')
else:
d = data
if out is None:
if d.ndim == 1:
sums = code.blockSums1d(d, blocks=blocks, processes=processes)
else:
sums = code.blockSums3d(d, blocks=blocks, processes=processes)
out = np.squeeze(np.zeros((np.sum(sums), data.ndim), dtype=np.int))
else:
sums = None
if d.ndim == 1:
code.where1d(d, out=out, sums=sums, blocks=blocks, processes=processes)
else: # d.ndim == 3:
code.where3d(d, out=out, sums=sums, blocks=blocks, processes=processes)
return out