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import numpy as np
import cython
DTYPE = np.intc
@cython.cfunc
def clip(a: cython.int, min_value: cython.int, max_value: cython.int) -> cython.int:
return min(max(a, min_value), max_value)
def compute(array_1: cython.int[:, :], array_2: cython.int[:, :],
a: cython.int, b: cython.int, c: cython.int):
x_max: cython.Py_ssize_t = array_1.shape[0]
y_max: cython.Py_ssize_t = array_1.shape[1]
# array_1.shape is now a C array, no it's not possible
# to compare it simply by using == without a for-loop.
# To be able to compare it to array_2.shape easily,
# we convert them both to Python tuples.
assert tuple(array_1.shape) == tuple(array_2.shape)
result = np.zeros((x_max, y_max), dtype=DTYPE)
result_view: cython.int[:, :] = result
tmp: cython.int
x: cython.Py_ssize_t
y: cython.Py_ssize_t
for x in range(x_max):
for y in range(y_max):
tmp = clip(array_1[x, y], 2, 10)
tmp = tmp * a + array_2[x, y] * b
result_view[x, y] = tmp + c
return result
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