tests

tests/transforms/test_transform.py

@@ -1,9 +1,9 @@
-import pytest
 from typing import Sequence
 
 import numpy as np
+import pytest
 
-from sslt.transforms import Flip, TransformPipeline, _Transform
+from sslt.transforms import Flip, PerlinMasker, TransformPipeline, _Transform
 
 
 def test_transform_pipeline():
@@ -59,3 +59,40 @@ def test_flip_invalid_axes():
     # Check if an AssertionError is raised when applying the transform
     with pytest.raises(AssertionError):
         flipped_x = flip_transform(x)
+
+
+def test_perlin_masker():
+    # Create a dummy input
+    x = np.random.rand(10, 20)
+
+    # Apply the PerlinMasker transform
+    perlin_masker = PerlinMasker(octaves=3, scale=2)
+    masked_x = perlin_masker(x)
+
+    # Check if the masked data has the same shape as the input
+    assert masked_x.shape == x.shape
+
+    # Check if the masked data has zeros at the positions where Perlin noise is negative
+    noise = perlin_masker.noise
+    denom = perlin_masker.scale * max(x.shape)
+    for pos in np.ndindex(*x.shape):
+        expected_value = (noise([i/denom for i in pos]) < 0)
+        assert masked_x[pos] == pytest.approx(x[pos] * expected_value)
+
+def test_perlin_masker_invalid_octaves():
+    # Create a dummy input
+    x = np.random.rand(10, 20)
+
+    # Check if a ValueError is raised when using invalid octaves
+    with pytest.raises(ValueError):
+        perlin_masker = PerlinMasker(octaves=-1)
+        masked_x = perlin_masker(x)
+
+def test_perlin_masker_invalid_scale():
+    # Create a dummy input
+    x = np.random.rand(10, 20)
+
+    # Check if a ValueError is raised when using invalid scale
+    with pytest.raises(ValueError):
+        perlin_masker = PerlinMasker(octaves=3, scale=0)
+        masked_x = perlin_masker(x)