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test_reduction.py
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test_reduction.py
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import pyclesperanto_prototype as cle
import numpy as np
def test_min():
example = np.asarray([[
[0, 0, 0, 1],
[0, 0, 3, 1],
],[
[0, 0, 3, 1],
[1, 1, 1, 1]
]])
gpu_example = cle.push(example)
assert gpu_example.min() == example.min()
def test_min_max_xyz():
example = np.asarray([[
[0, 0, 0, 1],
[0, 0, 3, 1],
],[
[0, 0, 3, 1],
[1, 1, 1, 1]
]])
gpu_example = cle.push(example)
print(gpu_example.min(axis=0))
print(example.min(axis=0))
print('---')
print(gpu_example.min(axis=1))
print(example.min(axis=1))
print('---')
print(gpu_example.min(axis=2))
print(example.min(axis=2))
print('---')
print(gpu_example.max(axis=0))
print(example.max(axis=0))
print('---')
print(gpu_example.max(axis=1))
print(example.max(axis=1))
print('---')
print(gpu_example.max(axis=2))
print(example.max(axis=2))
assert np.allclose(gpu_example.min(axis=0), example.min(axis=0))
assert np.allclose(gpu_example.min(axis=1), example.min(axis=1))
assert np.allclose(gpu_example.min(axis=2), example.min(axis=2))
assert np.allclose(gpu_example.min(), example.min())
assert np.allclose(gpu_example.max(axis=0), example.max(axis=0))
assert np.allclose(gpu_example.max(axis=1), example.max(axis=1))
assert np.allclose(gpu_example.max(axis=2), example.max(axis=2))
assert np.allclose(gpu_example.max(), example.max())
assert np.allclose(gpu_example.sum(axis=0), example.sum(axis=0))
assert np.allclose(gpu_example.sum(axis=1), example.sum(axis=1))
assert np.allclose(gpu_example.sum(axis=2), example.sum(axis=2))
assert np.allclose(gpu_example.sum(), example.sum())
def test_min_out():
example = np.asarray([[
[0, 0, 0, 1],
[0, 0, 3, 1],
], [
[0, 0, 3, 1],
[1, 1, 1, 1]
]])
gpu_example = cle.push(example)
minimum = example.min(axis=0)
copy = minimum.copy()
gpu_example.min(axis=0, out=copy)
assert np.allclose(minimum, copy)
minimum = example.min(axis=1)
copy = minimum.copy()
gpu_example.min(axis=1, out=copy)
assert np.allclose(minimum, copy)
minimum = example.min(axis=2)
copy = minimum.copy()
gpu_example.min(axis=2, out=copy)
assert np.allclose(minimum, copy)
def test_max_out():
example = np.asarray([[
[0, 0, 0, 1],
[0, 0, 3, 1],
], [
[0, 0, 3, 1],
[1, 1, 1, 1]
]])
gpu_example = cle.push(example)
maximum = example.max(axis=0)
copy = maximum.copy()
gpu_example.max(axis=0, out=copy)
assert np.allclose(maximum, copy)
maximum = example.max(axis=1)
copy = maximum.copy()
gpu_example.max(axis=1, out=copy)
assert np.allclose(maximum, copy)
maximum = example.max(axis=2)
copy = maximum.copy()
gpu_example.max(axis=2, out=copy)
assert np.allclose(maximum, copy)
def test_sum_out():
example = np.asarray([[
[0, 0, 0, 1],
[0, 0, 3, 1],
], [
[0, 0, 3, 1],
[1, 1, 1, 1]
]])
gpu_example = cle.push(example)
sum = example.sum(axis=0)
copy = sum.copy()
gpu_example.sum(axis=0, out=copy)
assert np.allclose(sum, copy)
sum = example.sum(axis=1)
copy = sum.copy()
gpu_example.sum(axis=1, out=copy)
assert np.allclose(sum, copy)
sum = example.sum(axis=2)
copy = sum.copy()
gpu_example.sum(axis=2, out=copy)
assert np.allclose(sum, copy)