Assume I have a very big numpy memory mapped array:
fp = np.memmap("bigarray.mat", dtype='float32', mode='w+', shape=(5000000,5000))
Now after some manipulation, etc, I want to remove column 10:
fp = np.delete(fp,10,1)
This results in a out of memory error, because (??) the returned array is an in memory array. What I want is a pure memory mapped delete operation.
What is the most efficient way to delete columns in full memory mapped mode?