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148 | #!/usr/bin/env python
import time
import sys
import os.path
import numpy
import mayavi.mlab
import Queue
import scipy.fftpack as fftpack
import multiprocessing
use_saved = False
def worker(myslice,q,A):
if myslice[1] >= A.shape[1]:
myslice[1] = A.shape[1]-1
for a in range(myslice[0],myslice[1]):
for b in range(A.shape[2]):
for c in range(A.shape[3]):
# ra is the position where the fields shall be
# calculated.
ra = numpy.array([x[a,b,c],y[a,b,c],z[a,b,c]])
# Calculation of the vector potential and magnetic
# field.
a_sum = numpy.array((0,0,0),dtype='float')
for d in range(m.shape[1]):
for e in range(m.shape[2]):
for f in range(m.shape[3]):
rm = numpy.array((x[d,e,f],y[d,e,f],z[d,e,f]))
M = m[:,d,e,f]
R = ra - rm
cube = betrag(R)**3
if cube.all() != 0:
a_sum += kreuzprodukt(M,R)/cube
else:
a_sum += numpy.zeros(3)
A[:,a,b,c] = a_sum
a_sum = numpy.zeros_like(a_sum)
q.put((myslice,A))
print "Finished!"
return None
def partial(A,x=0):
"Calculate partial derivative of a 3D pylab array along one axis."
A_prime = numpy.zeros_like(A)
l = list(A.shape)
if len(l) > x: del l[x]
for i in range(l[0]):
for j in range(l[1]):
if x==0:
s = A[:,i,j].copy()
A_prime[:,i,j] = fftpack.diff(s)
elif x==1:
s = A[i,:,j].copy()
A_prime[i,:,j] = fftpack.diff(s)
elif x==2:
s = A[i,j,:].copy()
A_prime[i,j,:] = fftpack.diff(s)
else:
raise ValueError, "No valid direction: %s" % x
return A_prime
def betrag(a):
return numpy.sqrt(abs(numpy.dot(a,a)))
def kreuzprodukt(a,b):
tmp = numpy.array([
a[1]*b[2] - a[2]*b[1],
a[2]*b[0] - a[0]*b[2],
a[0]*b[1] - a[1]*b[1]
])
return tmp
data_file = "vector_field_A__switch_multiproc.npy"
# Queue for splitting the A compontents for passing to Threads
# Shape of queue elements: [begin,end]
try:
max_threads = multiprocessing.cpu_count()
except Exception, e:
print e
max_threads = 2
print "No of Processes:", max_threads
# The coordinate grid
x,y,z = numpy.mgrid[-6:6:17j,-6:6:17j,-6:6:9j]
# The distribution of magnetic moments
m = numpy.array([
numpy.zeros_like(x),
numpy.zeros_like(y),
numpy.select([x**2+y**2<9],[numpy.select([abs(z)<2,abs(z)>=2],[numpy.sign(x),0])])
])
if use_saved and os.path.isfile(data_file):
A = numpy.load(data_file)
else:
# The magnetic vector potential
A = numpy.zeros_like(m)
a = A.shape[1]/max_threads+1
q = multiprocessing.Queue()
for i in range(max_threads):
myslice = [i*a,i*a+a]
print myslice
w = multiprocessing.Process(target=worker,args=(myslice,q,A))
w.start()
time.sleep(60)
qItems = 0
while multiprocessing.active_children():
time.sleep(5)
print q.qsize()
try:
myslice,A2 = q.get(True,timeout=10)
except Exception,e:
print "Caught exception:", e
if qItems >=max_threads: break
qItems += 1
if myslice[1]> A.shape[1]: myslice[1] = A.shape[1]-1
print myslice
A[:,myslice[0]:myslice[1],:,:] = A2[:,myslice[0]:myslice[1],:,:].copy()
numpy.save(data_file, A)
B = [
partial(A[1],2) - partial(A[2],1),
partial(A[2],0) - partial(A[0],2),
partial(A[0],1) - partial(A[1],0)
]
mayavi.mlab.figure(size=(1280,800))
# Using plot functions
mayavi.mlab.quiver3d(x,y,z,m[0],m[1],m[2],name="Magnetic Moments")
mayavi.mlab.quiver3d(x,y,z,A[0],A[1],A[2],name="Vector Potential")
#mayavi.mlab.quiver3d(X,Y,Z,B[0],B[1],B[2],name="Magnetic Field")
# Creating the plot using the pipeline
src = mayavi.mlab.pipeline.vector_field(x,y,z,B[0],B[1],B[2],name="Magnetic Field")
mayavi.mlab.pipeline.vectors(src, mask_points=1, scale_factor=2.)
mayavi.mlab.pipeline.vector_cut_plane(src, mask_points=1, scale_factor=2.)
mayavi.mlab.outline()
mayavi.mlab.colorbar()
mayavi.mlab.show()
#mayavi.mlab.savefig("bla.png")
|