44 lines
1.5 KiB
Python
44 lines
1.5 KiB
Python
import numpy as np
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from tests.node_tests._shared import make_field
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def test_output_shape():
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from backend.nodes.presentation_ops import PresentationOps
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node = PresentationOps()
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field = make_field(shape=(32, 32))
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result, = node.process(field, "logscale", blend_factor=0.5)
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assert result.data.shape == field.data.shape
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def test_logscale():
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from backend.nodes.presentation_ops import PresentationOps
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node = PresentationOps()
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data = np.array([[1.0, 10.0], [100.0, 1000.0]])
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field = make_field(data=data)
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result, = node.process(field, "logscale", blend_factor=0.5)
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assert np.all(np.isfinite(result.data))
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# logscale should preserve ordering
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assert result.data[0, 0] < result.data[0, 1] < result.data[1, 0] < result.data[1, 1]
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def test_blend_at_zero():
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from backend.nodes.presentation_ops import PresentationOps
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node = PresentationOps()
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field = make_field(data=np.array([[1.0, 2.0], [3.0, 4.0]]))
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overlay = make_field(data=np.array([[10.0, 20.0], [30.0, 40.0]]))
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result, = node.process(field, "blend", blend_factor=0.0, overlay=overlay)
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assert np.allclose(result.data, field.data)
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def test_blend_at_one():
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from backend.nodes.presentation_ops import PresentationOps
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node = PresentationOps()
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field = make_field(data=np.array([[1.0, 2.0], [3.0, 4.0]]))
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overlay = make_field(data=np.array([[10.0, 20.0], [30.0, 40.0]]))
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result, = node.process(field, "blend", blend_factor=1.0, overlay=overlay)
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assert np.allclose(result.data, overlay.data)
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