Mathematical Operations on a Jython array

Question

I am trying to do simple math operations on every element of a Jython array in the following manner:

import math

for i in xrange (x*y*z):
    medfiltArray[i] = 2 * math.sqrt(medfiltArray[i] + (3.0/8.0)  )
    InputImgArray[i] = 2 * math.sqrt(InputImgArray[i] + (3.0/8.0)  )

The problem is that my array is large (8388608 elements) and the process takes a little more than 12 seconds. Is there a more efficient way to do this whole process? I found a slightly more faster way (about 7 seconds):

medfiltArray = map(lambda x: 2 * math.sqrt(x + (3.0/8.0)  ) ,  medfiltArray)    

The advantage of the for loop over this method is that I can modify several arrays of the same size simultaneously and therefore save up on net time. But despite all this, this is still very slow. In MATLAB modifying a matrix would take less than a second:

img = 2 * sqrt(img + (3/8));

Any tips on modifying arrays in Jython would be very appreciated. Thanks !!!

Answer 1

There is a fast vector and matrix java library called Vectorz. Vectorz can be imported in Jython and does the computation described in my question in about 200 ms. The user will have to switch over from the python (or java) arrays in Jython and use Vectorz arrays. There is also another solution, if you are doing image processing (like me), there is a program called ImageJ and it has extensive functionality. I am working on an ImageJ plugin and to do these math operations you can also use internal ImageJ math commands:

IJ.run(InputImg, "32-bit", ""); 
IJ.run(InputImg, "Add...", "value=0.375 stack"); 
IJ.run(InputImg, "Square Root", "stack"); 
IJ.run(InputImg, "Multiply...", "value=2 stack"); 

This takes only .1 sec.