How multiarray.correlate2(a, v, mode) is actually implemented?

The speed of python code can be very poor compared to other languages like c. numpy aims to provide highly performant operations on arrays, therefore the developers decided to implement some operations in c.

Unfortunately, won't find a python implementation of correlate in numpy's code base, but if you are familiar with C and python's extension modules, you can have find the relevant code here.

The different modes just specify the length of the output array.You can simulate them by transforming your inputs:

import numpy as npa = [1, 2, 3]v = [0, 1, 0.5]np.correlate(a, v, mode="full")

returns:

array([ 0.5,  2. ,  3.5,  3. ,  0. ])

You can get the same result by filling v with zeros:

np.correlate(a, [0, 0] + v + [0, 0])

returns the same result:

array([ 0.5,  2. ,  3.5,  3. ,  0. ])

np.core.multiarray.correlate2dir(np.core.multiarray.correlate2) # to inspectprint (numpy.__version__) print numpy.__version__ # python 2

found it! it might be a private API, can't find the docs after first search with numpy.multiarray or with the newly discovered 'correct' name.optimal search query is 'np.core.multiarray.correlate2 github'

return multiarray.correlate2(a, v, mode) # mode is int data type

if you're plan to customize the code for your purposes, be careful.

/* * simulates a C-style 1-3 dimensional array which can be accessed using * ptr[i]  or ptr[i][j] or ptr[i][j][k] -- requires pointer allocation * for 2-d and 3-d. * * For 2-d and up, ptr is NOT equivalent to a statically defined * 2-d or 3-d array.  In particular, it cannot be passed into a * function that requires a true pointer to a fixed-size array. *//*NUMPY_API * Simulate a C-array * steals a reference to typedescr -- can be NULL */NPY_NO_EXPORT intPyArray_AsCArray(PyObject **op, void *ptr, npy_intp *dims, int nd,                 PyArray_Descr* type# NPY_NO_EXPORT int NPY_NUMUSERTYPES = 0;# omit code    switch(mode) {    case 0:        length = length - n + 1;        n_left = n_right = 0;        break;    case 1:        n_left = (npy_intp)(n/2);        n_right = n - n_left - 1;        break;    case 2:        n_right = n - 1;        n_left = n - 1;        length = length + n - 1;        break;    default:        PyErr_SetString(PyExc_ValueError, "mode must be 0, 1, or 2");        return NULL;    }

don't mess with the internal APIs if this is your first crack at the codebase and you are on a deadline. Too late for me.