pyodide/benchmark/benchmarks/multiple_sum.py

# from http://stackoverflow.com/questions/77999777799977/numpy-vs-cython-speed
# pythran export multiple_sum(float[][])
# setup: import numpy as np ; r = np.random.rand(100,100)
# run: multiple_sum(r)
import numpy as np


def multiple_sum(array):

    rows = array.shape[0]
    cols = array.shape[1]

    out = np.zeros((rows, cols))

    for row in range(0, rows):
        out[row, :] = np.sum(array - array[row, :], 0)

    return out