def rendJitTriang(x, y, n, jsig, mcp, imageBounds, pixelSize):
sizeX = int((imageBounds.x1 - imageBounds.x0) / pixelSize)
sizeY = int((imageBounds.y1 - imageBounds.y0) / pixelSize)
im = shmarray.zeros((sizeX, sizeY))
x = shmarray.create_copy(x)
y = shmarray.create_copy(y)
if type(jsig) == numpy.ndarray:
jsig = shmarray.create_copy(jsig)
nCPUs = multiprocessing.cpu_count()
tasks = (n / nCPUs) * numpy.ones(nCPUs, 'i')
tasks[:(n % nCPUs)] += 1
processes = [
multiprocessing.Process(target=rendJitTri,
args=(im, x, y, jsig, mcp, imageBounds,
pixelSize, nIt)) for nIt in tasks
]
for p in processes:
p.start()
for p in processes:
p.join()
return im / n
def rendJitTriang(x,y,n,jsig, mcp, imageBounds, pixelSize):
sizeX = int((imageBounds.x1 - imageBounds.x0)/pixelSize)
sizeY = int((imageBounds.y1 - imageBounds.y0)/pixelSize)
im = shmarray.zeros((sizeX, sizeY))
x = shmarray.create_copy(x)
y = shmarray.create_copy(y)
if type(jsig) == numpy.ndarray:
jsig = shmarray.create_copy(jsig)
nCPUs = multiprocessing.cpu_count()
tasks = (n/nCPUs)*numpy.ones(nCPUs, 'i')
tasks[:(n%nCPUs)] += 1
processes = [multiprocessing.Process(target = rendJitTri, args=(im, x, y, jsig, mcp, imageBounds, pixelSize, nIt)) for nIt in tasks]
for p in processes:
p.start()
for p in processes:
p.join()
return im/n
def rendJitTriang2(x,y,n,jsig, mcp, imageBounds, pixelSize):
#import threading
sizeX = int((imageBounds.x1 - imageBounds.x0)/pixelSize)
sizeY = int((imageBounds.y1 - imageBounds.y0)/pixelSize)
im = shmarray.zeros((sizeX, sizeY))
im1 = shmarray.zeros((sizeX, sizeY))
x = shmarray.create_copy(x)
y = shmarray.create_copy(y)
if type(jsig) == numpy.ndarray:
jsig = shmarray.create_copy(jsig)
#pool = multiprocessing.Pool()
#Ts = pool.map(gJitTriang, range(n))
nCPUs = multiprocessing.cpu_count()
tasks = (n/nCPUs)*numpy.ones(nCPUs, 'i')
tasks[:(n%nCPUs)] += 1
processes = [multiprocessing.Process(target = rendJitTri2, args=(im, im1, x, y, jsig, mcp, imageBounds, pixelSize, nIt)) for nIt in tasks]
for p in processes:
p.start()
for p in processes:
p.join()
imn = im/(im1 + 1) #n
print imn.min(), imn.max()
return imn
def rendJitTet(x,y,z,n,jsig, jsigz, mcp, imageBounds, pixelSize, zb,sliceSize=100):
#import gen3DTriangs
sizeX = (imageBounds.x1 - imageBounds.x0)/pixelSize
sizeY = (imageBounds.y1 - imageBounds.y0)/pixelSize
x = (x - imageBounds.x0)/pixelSize
y = (y - imageBounds.y0)/pixelSize
jsig = jsig/pixelSize
jsigz = jsigz/sliceSize
z = (z - zb[0])/sliceSize
sizeZ = floor((zb[1] + sliceSize - zb[0])/sliceSize)
#im = numpy.zeros((sizeX, sizeY, sizeZ), order='F')
im = shmarray.zeros((sizeX, sizeY, sizeZ), order='F')
x = shmarray.create_copy(x)
y = shmarray.create_copy(y)
z = shmarray.create_copy(z)
if type(jsig) == numpy.ndarray:
jsig = shmarray.create_copy(jsig)
if type(jsigz) == numpy.ndarray:
jsigz = shmarray.create_copy(jsigz)
#pool = multiprocessing.Pool()
#Ts = pool.map(gJitTriang, range(n))
nCPUs = multiprocessing.cpu_count()
tasks = (n/nCPUs)*numpy.ones(nCPUs, 'i')
tasks[:(n%nCPUs)] += 1
processes = [multiprocessing.Process(target = rendJTet, args=(im, y, x,z, jsig, jsigz, mcp, nIt)) for nIt in tasks]
for p in processes:
p.start()
for p in processes:
p.join()
return im/n