matei jordache
d4c5cf4670
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47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
import numpy as np
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from tests.node_tests._shared import make_field
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def test_zero_mean():
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from backend.nodes.zero_value import ZeroMean
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node = ZeroMean()
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data = np.random.default_rng(42).standard_normal((64, 64)) + 100.0
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field = make_field(data=data)
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(result,) = node.process(field)
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assert result.data.shape == field.data.shape
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assert abs(result.data.mean()) < 1e-10
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def test_zero_mean_preserves_variation():
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from backend.nodes.zero_value import ZeroMean
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node = ZeroMean()
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data = np.random.default_rng(7).standard_normal((32, 32)) + 50.0
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field = make_field(data=data)
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(result,) = node.process(field)
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assert np.allclose(result.data - result.data.mean(), data - data.mean())
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def test_zero_maximum():
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from backend.nodes.zero_value import ZeroMaximum
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node = ZeroMaximum()
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data = np.random.default_rng(42).standard_normal((64, 64)) + 100.0
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field = make_field(data=data)
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(result,) = node.process(field)
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assert result.data.shape == field.data.shape
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assert abs(result.data.max()) < 1e-10
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assert result.data.min() < 0
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def test_zero_maximum_preserves_differences():
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from backend.nodes.zero_value import ZeroMaximum
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node = ZeroMaximum()
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data = np.array([[1.0, 3.0], [2.0, 5.0]])
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field = make_field(data=data)
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(result,) = node.process(field)
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expected = data - 5.0
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assert np.allclose(result.data, expected)
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