Fixed database typo and removed unnecessary class identifier.

venv/Lib/site-packages/skimage/measure/tests/test_simple_metrics.py

@@ -0,0 +1,84 @@
+import numpy as np
+
+import skimage.data
+from skimage.measure import compare_nrmse, compare_psnr, compare_mse
+
+from skimage._shared import testing
+from skimage._shared.testing import assert_equal, assert_almost_equal
+from skimage._shared._warnings import expected_warnings
+
+
+np.random.seed(5)
+cam = skimage.data.camera()
+sigma = 20.0
+cam_noisy = np.clip(cam + sigma * np.random.randn(*cam.shape), 0, 255)
+cam_noisy = cam_noisy.astype(cam.dtype)
+
+
+def test_PSNR_vs_IPOL():
+    # Tests vs. imdiff result from the following IPOL article and code:
+    # https://www.ipol.im/pub/art/2011/g_lmii/
+    p_IPOL = 22.4497
+    with expected_warnings(['DEPRECATED']):
+        p = compare_psnr(cam, cam_noisy)
+    assert_almost_equal(p, p_IPOL, decimal=4)
+
+
+def test_PSNR_float():
+    with expected_warnings(['DEPRECATED']):
+        p_uint8 = compare_psnr(cam, cam_noisy)
+        p_float64 = compare_psnr(cam / 255., cam_noisy / 255.,
+                                 data_range=1)
+    assert_almost_equal(p_uint8, p_float64, decimal=5)
+
+    # mixed precision inputs
+    with expected_warnings(['DEPRECATED']):
+        p_mixed = compare_psnr(cam / 255., np.float32(cam_noisy / 255.),
+                               data_range=1)
+    assert_almost_equal(p_mixed, p_float64, decimal=5)
+
+    # mismatched dtype results in a warning if data_range is unspecified
+    with expected_warnings(['Inputs have mismatched dtype', 'DEPRECATED']):
+        p_mixed = compare_psnr(cam / 255., np.float32(cam_noisy / 255.))
+    assert_almost_equal(p_mixed, p_float64, decimal=5)
+
+
+def test_PSNR_errors():
+    with expected_warnings(['DEPRECATED']):
+        # shape mismatch
+        with testing.raises(ValueError):
+            compare_psnr(cam, cam[:-1, :])
+
+
+def test_NRMSE():
+    x = np.ones(4)
+    y = np.asarray([0., 2., 2., 2.])
+    with expected_warnings(['DEPRECATED']):
+        assert_equal(compare_nrmse(y, x, 'mean'), 1 / np.mean(y))
+        assert_equal(compare_nrmse(y, x, 'Euclidean'), 1 / np.sqrt(3))
+        assert_equal(compare_nrmse(y, x, 'min-max'), 1 / (y.max() - y.min()))
+
+        # mixed precision inputs are allowed
+        assert_almost_equal(compare_nrmse(y, np.float32(x), 'min-max'),
+                            1 / (y.max() - y.min()))
+
+
+def test_NRMSE_no_int_overflow():
+    camf = cam.astype(np.float32)
+    cam_noisyf = cam_noisy.astype(np.float32)
+    with expected_warnings(['DEPRECATED']):
+        assert_almost_equal(compare_mse(cam, cam_noisy),
+                            compare_mse(camf, cam_noisyf))
+        assert_almost_equal(compare_nrmse(cam, cam_noisy),
+                            compare_nrmse(camf, cam_noisyf))
+
+
+def test_NRMSE_errors():
+    x = np.ones(4)
+    with expected_warnings(['DEPRECATED']):
+        # shape mismatch
+        with testing.raises(ValueError):
+            compare_nrmse(x[:-1], x)
+        # invalid normalization name
+        with testing.raises(ValueError):
+            compare_nrmse(x, x, norm_type='foo')