| |
|
|
| import pytest |
| import numpy as np |
|
|
| from astropy.visualization.stretch import (LinearStretch, SqrtStretch, PowerStretch, |
| PowerDistStretch, SquaredStretch, LogStretch, |
| AsinhStretch, SinhStretch, HistEqStretch, |
| ContrastBiasStretch) |
|
|
|
|
| DATA = np.array([0.00, 0.25, 0.50, 0.75, 1.00]) |
|
|
| RESULTS = {} |
| RESULTS[LinearStretch()] = np.array([0.00, 0.25, 0.50, 0.75, 1.00]) |
| RESULTS[LinearStretch(intercept=0.5) + LinearStretch(slope=0.5)] = \ |
| np.array([0.5, 0.625, 0.75, 0.875, 1.]) |
| RESULTS[SqrtStretch()] = np.array([0., 0.5, 0.70710678, 0.8660254, 1.]) |
| RESULTS[SquaredStretch()] = np.array([0., 0.0625, 0.25, 0.5625, 1.]) |
| RESULTS[PowerStretch(0.5)] = np.array([0., 0.5, 0.70710678, 0.8660254, 1.]) |
| RESULTS[PowerDistStretch()] = np.array([0., 0.004628, 0.030653, 0.177005, 1.]) |
| RESULTS[LogStretch()] = np.array([0., 0.799776, 0.899816, 0.958408, 1.]) |
| RESULTS[AsinhStretch()] = np.array([0., 0.549402, 0.77127, 0.904691, 1.]) |
| RESULTS[SinhStretch()] = np.array([0., 0.082085, 0.212548, 0.46828, 1.]) |
| RESULTS[ContrastBiasStretch(contrast=2., bias=0.4)] = np.array([-0.3, 0.2, |
| 0.7, 1.2, |
| 1.7]) |
| RESULTS[HistEqStretch(DATA)] = DATA |
| RESULTS[HistEqStretch(DATA[::-1])] = DATA |
| RESULTS[HistEqStretch(DATA ** 0.5)] = np.array([0., 0.125, 0.25, 0.5674767, |
| 1.]) |
|
|
|
|
| class TestStretch: |
|
|
| @pytest.mark.parametrize('stretch', RESULTS.keys()) |
| def test_no_clip(self, stretch): |
| np.testing.assert_allclose(stretch(DATA, clip=False), |
| RESULTS[stretch], atol=1.e-6) |
|
|
| @pytest.mark.parametrize('ndim', [2, 3]) |
| @pytest.mark.parametrize('stretch', RESULTS.keys()) |
| def test_clip_ndimensional(self, stretch, ndim): |
| new_shape = DATA.shape + (1,) * ndim |
|
|
| np.testing.assert_allclose(stretch(DATA.reshape(new_shape), |
| clip=True).ravel(), |
| np.clip(RESULTS[stretch], 0., 1), |
| atol=1.e-6) |
|
|
| @pytest.mark.parametrize('stretch', RESULTS.keys()) |
| def test_clip(self, stretch): |
| np.testing.assert_allclose(stretch(DATA, clip=True), |
| np.clip(RESULTS[stretch], 0., 1), |
| atol=1.e-6) |
|
|
| @pytest.mark.parametrize('stretch', RESULTS.keys()) |
| def test_inplace(self, stretch): |
| data_in = DATA.copy() |
| result = np.zeros(DATA.shape) |
| stretch(data_in, out=result, clip=False) |
| np.testing.assert_allclose(result, RESULTS[stretch], atol=1.e-6) |
| np.testing.assert_allclose(data_in, DATA) |
|
|
| @pytest.mark.parametrize('stretch', RESULTS.keys()) |
| def test_round_trip(self, stretch): |
| np.testing.assert_allclose(stretch.inverse(stretch(DATA, clip=False), |
| clip=False), DATA) |
|
|
| @pytest.mark.parametrize('stretch', RESULTS.keys()) |
| def test_inplace_roundtrip(self, stretch): |
| result = np.zeros(DATA.shape) |
| stretch(DATA, out=result, clip=False) |
| stretch.inverse(result, out=result, clip=False) |
| np.testing.assert_allclose(result, DATA) |
|
|
| @pytest.mark.parametrize('stretch', RESULTS.keys()) |
| def test_double_inverse(self, stretch): |
| np.testing.assert_allclose(stretch.inverse.inverse(DATA), |
| stretch(DATA), atol=1.e-6) |
|
|
| def test_inverted(self): |
| stretch_1 = SqrtStretch().inverse |
| stretch_2 = PowerStretch(2) |
| np.testing.assert_allclose(stretch_1(DATA), |
| stretch_2(DATA)) |
|
|
| def test_chaining(self): |
| stretch_1 = SqrtStretch() + SqrtStretch() |
| stretch_2 = PowerStretch(0.25) |
| stretch_3 = PowerStretch(4.) |
|
|
| np.testing.assert_allclose(stretch_1(DATA), |
| stretch_2(DATA)) |
|
|
| np.testing.assert_allclose(stretch_1.inverse(DATA), |
| stretch_3(DATA)) |
|
|
|
|
| def test_clip_invalid(): |
| stretch = SqrtStretch() |
|
|
| values = stretch([-1., 0., 0.5, 1., 1.5]) |
| np.testing.assert_allclose(values, [0., 0., 0.70710678, 1., 1.]) |
|
|
| values = stretch([-1., 0., 0.5, 1., 1.5], clip=False) |
| np.testing.assert_allclose(values, [np.nan, 0., 0.70710678, 1., 1.2247448]) |
|
|
