numpy.memmap map to save file

Question

I'm trying to create random matrix and save it in binary file using numpy.save

Then I try to map this file using numpy.memmap, but it seems it maps it wrong.

How to fix it?

It seems it read .npy header and I need to scip some bytes from begining.

rows=6
cols=4

def create_matrix(rows,cols):
    data = (np.random.rand(rows,cols)*100).astype('uint8') #type for image [0 255] int8?
    return data

def save_matrix(filename, data):
    np.save(filename, data)

def load_matrix(filename):
    data= np.load(filename)
    return data

def test_mult_ram():
    A= create_matrix(rows,cols)
    A[1][2]= 42
    save_matrix("A.npy", A)
    A= load_matrix("A.npy")
    print A
    B= create_matrix(cols,rows)
    save_matrix("B.npy", B)
    B= load_matrix("B.npy")
    print B




fA = np.memmap('A.npy', dtype='uint8', mode='r', shape=(rows,cols))
fB = np.memmap('B.npy', dtype='uint8', mode='r', shape=(cols,rows))
print fA
print fB

UPDATE:

I just found that already np.lib.format.open_memmap function exist.

usage: a = np.lib.format.open_memmap('A.npy', dtype='uint8', mode='r+')

Answer 1

If your goal is to open arrays you saved with np.save as memmaps, then you can just use np.load with the option mmap_mode:

fA = np.load('A.npy', mmap_mode='r')
fB = np.load('B.npy', mmap_mode='r')

This way you actually benefit from the header stored in the .npy files, in the sense that it keeps track of the shape and dtype of the array.