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Cython: Buffer type mismatch, expected 'int' but got 'long'

I'm having trouble passing in this memoryview of integers into this (rather trivial) function. Python is giving me this error:

ValueError: Buffer dtype mismatch, expected 'int' but got 'long'

Can someone help me understand what's going on? Searching around stackoverflow, it seems that it has to do with how python interprets types, and how C interprets types.

%%cython
def myfunction(int [:] y):
    pass

# Python code
import numpy as np
y = np.array([0, 0, 1, 1])
myfunction(y)

This produces the ValueError from above.

EDIT: Here are some other things I've discovered.

To clarify, this error persists if I declare y the following ways:

y = np.array([0, 0, 1, 1], dtype='int')
y = np.array([0, 0, 1, 1], dtype=np.int)
y = np.array([0, 0, 1, 1], dtype=np.int64)

However, it works if I declare y with

y = np.array([0, 0, 1, 1], dtype=np.int32)

Does anyone want to give a suggestion why this is the case? Would throwing in np.int32 work on different computers? (I use a macbook pro retina, 2013.)

like image 654
hlin117 Avatar asked Aug 28 '15 03:08

hlin117


2 Answers

You are using Cython's int type, which is just C int. I think on Mac (or most architectures) it is int 32-bit. See wiki or intel or Does the size of an int depend on the compiler and/or processor?

On the other hand, long means int64. dtype='int' or dtype=np.int are all equivalent to np.int64.

I think you might just explicitly define it as one of the numpy type:

cimport numpy as np
import numpy as np
cdef myfunction(np.ndarray[np.int64_t, ndim=1] y):
     #do something
     pass

That way it reads more clear and there will not be any confusion later.

EDIT

The newer memoryviews syntax would be like this:

cdef myfunction(double[:] y):
    #do something with y
    pass
like image 117
CT Zhu Avatar answered Oct 17 '22 01:10

CT Zhu


I did what the error message told me: I changed the memoryview base type from int to long and it seemed to work.

%%cython
def fun(long[:] x):
    return x[0]

y=np.array([1,2,3],dtype=int)
fun(y)    # returns 1
like image 44
Yibo Yang Avatar answered Oct 17 '22 02:10

Yibo Yang