def as_shared(source):
"""Convert array to a shared memory array
Arguments
---------
source : array
The source array to use as template.
copy : bool
If True, the data in source is copied.
order : C', 'F', or None
The order to use for an array if copied or not a shared array. If None, the order of the source is used.
Returns
-------
array : array
A shared memory array wrapped as ndarray based on the source array.
"""
if isinstance(source, (Source, VirtualSource)):
return source
elif sma.is_shared(source):
return Source(array=source)
elif isinstance(source, (list, tuple, np.ndarray)):
return Source(array=sma.as_shared(source))
else:
raise ValueError('Source %r cannot be transforemd to a shared array!' %
source)
def _test():
#from importlib import reload
import numpy as np
import ClearMap.ParallelProcessing.SharedMemoryArray as sma
#reload(sma)
n = 10
array = sma.zeros(n)
non_shared = np.zeros(n)
def propagate(arg):
i, a = arg
for j in range(1000):
array[i] = i
def propagate_non_shared(arg):
i, a = arg
for j in range(1000):
non_shared[i] = i
sma.is_shared(non_shared)
sma.is_shared(array)
pool = sma.mp.Pool(processes=4)
pp = pool.map(propagate, zip(range(n), [None] * n))
print(array)
pool = sma.mp.Pool(processes=4)
pp = pool.map(propagate_non_shared, zip(range(n), [None] * n))
#analysis:ignore
print(non_shared)
def _test():
#from importlib import reload
#import numpy as np #analysis:ignore
import ClearMap.IO.SMA as sma
n = 10
array = sma.zeros(n)
s = sma.Source(array=array)
print(s)
v = s.as_virtual()
print(v)
s2 = v.as_source()
def insert(array):
self = SharedMemmoryManager.instance()
# next handle
self.handle()
# convert to shared array and insert into handle
self.arrays[self.current] = sma.as_shared(array)
# update cnt
self.count += 1
return self.current
def zeros(shape, dtype=None, order=None):
self = SharedMemmoryManager.instance()
self.lock.acquire()
# next handle
self.handle()
# create array in shared memory segment and wrap with numpy
self.arrays[self.current] = sma.zeros(shape, dtype, order)
# update cnt
self.count += 1
self.lock.release()
return self.current
def _shared(shape=None, dtype=None, order=None, array=None, handle=None):
if handle is not None:
array = smm.get(handle)
if array is None:
return sma.array(shape=shape, dtype=dtype, order=order)
elif is_shared(array):
if shape is None and dtype is None and order is None:
return array
shape = shape if shape is not None else array.shape
dtype = dtype if dtype is not None else array.dtype
order = order if order is not None else npy.order(array)
if shape != array.shape:
raise ValueError('Shapes do not match!')
if np.dtype(dtype) == array.dtype and order == npy.order(array):
return array
else:
new = sma.array(shape=shape, dtype=dtype, order=order)
new[:] = array
return new
elif isinstance(array, (np.ndarray, list, tuple)):
array = np.asarray(array)
shape = shape if shape is not None else array.shape
dtype = dtype if dtype is not None else array.dtype
order = order if order is not None else npy.order(array)
if shape != array.shape:
raise ValueError('Shapes do not match!')
new = sma.array(shape=shape, dtype=dtype, order=order)
new[:] = array
return new
else:
raise ValueError('Cannot create shared array from array %r!' % array)
def is_shared(source):
"""Returns True if array is a shared memory array
Arguments
---------
source : array
The source array to use as template.
Returns
-------
is_shared : bool
True if the array is a shared memory array.
"""
if isinstance(source, (Source, VirtualSource)):
return True
else:
return sma.is_shared(source)