Fix Python – Better way to shuffle two numpy arrays in unison

I have two numpy arrays of different shapes, but with the same length (leading dimension). I want to shuffle each of them, such that corresponding elements continue to correspond — i.e. shuffle them in unison with respect to their leading indices.
This code works, and illustrates my goals:
def shuffle_in_unison(a, b):
assert len(a) == len(b)

Fix Python – How do I convert a PIL Image into a NumPy array?

How do I convert a PIL Image back and forth to a NumPy array so that I can do faster pixel-wise transformations than PIL’s PixelAccess allows? I can convert it to a NumPy array via:
pic =“foo.jpg”)
pix = numpy.array(pic.getdata()).reshape(pic.size[0], pic.size[1], 3)

But how do I load it back into the PIL Image after I’ve modified the….

Fix Python – What is the purpose of meshgrid in Python / NumPy?

Can someone explain to me what is the purpose of meshgrid function in Numpy? I know it creates some kind of grid of coordinates for plotting, but I can’t really see the direct benefit of it.
I am studying “Python Machine Learning” from Sebastian Raschka, and he is using it for plotting the decision borders. See input 11 here.
I have also tried thi….