Hi,
I have a very large dictionary that must be shared across processes and does
not fit in RAM. I need access to this object to be fast. The key is an integer
ID and the value is a list containing two elements, both of them numpy arrays
(one has ints, the other has floats). The key is
Hi,
I have a matrix whose entries I must raise to a certain power and then
normalize by row. After I do that, when I pass some rows to
numpy.random.choice, I get a ValueError: probabilities do not sum to 1.
I understand that floating point is not perfect, and my matrix is so large that
I