Dear numpy experts! I'm just trying to port some matlab algorithm to python which allows an image correction for color blind users. If I succeed this bit of code might be part of the MoinMoin wiki, the wikisoftware scipy.org uses (see for more on that http://moinmoin.wikiwikiweb.de/AccessibleMoin). Since I'm totally new to matlab and numpy it took me already hours to figure the basics out - without much success. So I decided to ask here on the mailing list for some help. I hope - as an exception - this is ok for you... Here's the part of the matlab code which should be translated. The last 5 lines actually cause the trouble (long version, see http://www.stanford.edu/~ofidaner/psych221_proj/colorblindness_project.htm): clear; file_name = 'grandparents' ; % transorm matrices rgb2lms = [17.8824 43.5161 4.11935; 3.45565 27.1554 3.86714; 0.0299566 0.184309 1.46709] ; lms2rgb = inv(rgb2lms) ; %read picture into RGB value RGB = double(imread(file_name,'jpeg')); sizeRGB = size(RGB) ; %transform to LMS space for i = 1:sizeRGB(1) for j = 1:sizeRGB(2) rgb = RGB(i,j,:); rgb = rgb(:); LMS(i,j,:) = rgb2lms * rgb; end end And that's what I did with numpy and PIL in Python. The last 2 lines seems to be wrong. But how to do it correct? im = Image.open(fpath) # fpath is the path to the image RGB = numpy.asarray(im) # checked: RGB is of shape[y,x,r/g/b] # Colorspace transformation matrices rgb2lms = numpy.array([[17.8824,43.5161,4.11935],[3.45565,27.1554,3.86714],[0.0299566,0.184309,1.46709]]) lms2rgb = numpy.linalg.inv(rgb2lms) # Transform to LMS space LMS = numpy.zeros_like(RGB) for i in range(RGB.shape[0]): for j in range(RGB.shape[1]): rgb = RGB[i,j,:2] LMS[i,j,:2] = numpy.dot(rgb2lms, rgb) This code fails in the last line with the error message "ValueError: matrices are not aligned". But how to align them? Any help would be highly appreciated. Many thanks in advance! With regards, Oliver Siemoneit