[Numpy-discussion] some vectorization help
Eric Carlson
ecarlson@eng.ua....
Sun Sep 16 09:10:55 CDT 2012
Hello All,
I have a bit of code that nicely accomplishes what I need for a course I
am teaching. I'd like to extend this for larger 3D grids, and I suspect
that the looping will be a brutal performance hit. Even if my suspicions
are not confirmed, I still would like to know if it's possible to
vectorize the following code:
from scipy import shape, prod, array, zeros,ravel, reshape,sin, mgrid
from scipy.misc import derivative
def gradient2D_vect(func,x,y):
the_shape = shape(x)
x1=ravel(x)
y1=ravel(y)
N = prod(the_shape)
the_result = zeros([N,2])
for k in range(N):
func_x=lambda x: func(x,y1[k])
func_y=lambda y: func(x1[k],y)
the_result[k,:]= array([derivative(func_x,x1[k],dx=.01, order=5),
derivative(func_y,y1[k],dx=.01, order=5)])
if prod(shape(the_shape))==1:
return the_result
else:
return reshape(the_result,[the_shape[0],the_shape[1],2])
fxy = lambda x,y: sin(x*y) #just a little test
x,y=mgrid[0:5,0:4]
the_gradient = gradient2D_vect(fxy, x,y)
Cheers,
Eric Carlson
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