def f():
"""
Self-contained profile function for this library
Compares cython array sum vs. numpy.sum vs. pure python implementation
Can be used to identify possible areas to re-write as c/c++ extensions
"""
import numpy as np
from cython_example_proj import array_sum
def array_sum2(A):
m, n = A.shape
result = 0
for i in range(n):
for j in range(n):
result += A[i, j]
A = np.random.randn(5000, 5000)
array_sum(A)
A.sum()
array_sum2(A)
def test_array_sum(self):
A = np.random.randn(500, 500)
result = array_sum(A)
self.assertAlmostEqual(A.sum(), result)
results[idx + 1, 3:6] = this_pt
results[idx + 1, 6:9] = bottom_left
results[idx + 1, 9:] = bottom_right
return results
if __name__ == "__main__":
A = np.random.randn(5000, 5000)
print(59 * "-")
print("Initialized array for sum; starting comparison:")
print(59 * "-")
t = time.time()
array_sum(A)
print("cython finished :", time.time() - t, "s")
t = time.time()
A.sum()
print("numpy finished :", time.time() - t, "s")
t = time.time()
array_sum_python(A)
print("python finished :", time.time() - t, "s")
print()
A = np.random.randn(1024, 1024)
print(59 * "-")
print("Initialized array for tessellate; starting comparison:")
def test_array_sum(self):
A = np.random.randn(500, 500)
result = array_sum(A)
self.assertAlmostEqual(A.sum(), result)
results[idx, 9:] = bottom_right
results[idx + 1, 3:6] = this_pt
results[idx + 1, 6:9] = bottom_left
results[idx + 1, 9:] = bottom_right
return results
if __name__ == "__main__":
A = np.random.randn(5000, 5000)
print(59 * "-")
print("Initialized array for sum; starting comparison:")
print(59 * "-")
t = time.time()
array_sum(A)
print("cython finished :", time.time() - t, "s")
t = time.time()
A.sum()
print("numpy finished :", time.time() - t, "s")
t = time.time()
array_sum_python(A)
print("python finished :", time.time() - t, "s")
print()
A = np.random.randn(1024, 1024)
print(59 * "-")
print("Initialized array for tessellate; starting comparison:")
