Merge branch 'colour-science:develop' into feature/metamerism

Author: lassefschmidt

colour/algebra/interpolation.py

@@ -64,10 +64,31 @@
 
 from __future__ import annotations
 
+import sys
 import typing
 from functools import reduce
+from unittest.mock import MagicMock
 
 import numpy as np
+
+from colour.utilities.requirements import is_scipy_installed
+from colour.utilities.verbose import usage_warning
+
+if not is_scipy_installed():  # pragma: no cover
+    try:
+        is_scipy_installed(raise_exception=True)
+    except ImportError as error:
+        usage_warning(str(error))
+
+    mock = MagicMock()
+    mock.__name__ = ""
+
+    for module in (
+        "scipy",
+        "scipy.interpolate",
+    ):
+        sys.modules[module] = mock
+
 import scipy.interpolate
 
 from colour.algebra import sdiv, sdiv_mode

colour/algebra/tests/test_extrapolation.py

@@ -13,7 +13,7 @@
     PchipInterpolator,
 )
 from colour.constants import TOLERANCE_ABSOLUTE_TESTS
-from colour.utilities import ignore_numpy_errors
+from colour.utilities import ignore_numpy_errors, is_scipy_installed
 
 __author__ = "Colour Developers"
 __copyright__ = "Copyright 2013 Colour Developers"
@@ -107,6 +107,9 @@ def test__call__(self) -> None:
         method.
         """
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         extrapolator = Extrapolator(
             LinearInterpolator(np.array([5, 6, 7]), np.array([5, 6, 7]))
         )

colour/algebra/tests/test_interpolation.py

@@ -37,7 +37,7 @@
 from colour.constants import TOLERANCE_ABSOLUTE_TESTS
 from colour.hints import NDArrayFloat, cast
 from colour.io import LUT3D, read_LUT
-from colour.utilities import ignore_numpy_errors
+from colour.utilities import ignore_numpy_errors, is_scipy_installed
 
 __author__ = "Colour Developers"
 __copyright__ = "Copyright 2013 Colour Developers"
@@ -835,6 +835,9 @@ class TestKernelInterpolator:
     def test_required_attributes(self) -> None:
         """Test the presence of required attributes."""
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         required_attributes = (
             "x",
             "y",
@@ -872,6 +875,9 @@ def test_y(self) -> None:
         property.
         """
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         x = y = np.linspace(0, 1, 10)
         kernel_interpolator = KernelInterpolator(x, y)
 
@@ -942,6 +948,9 @@ def test__call__(self) -> None:
         method.
         """
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         x = np.arange(11, 26, 1)
         y = np.sin(x / len(x) * np.pi * 6) / (x / len(x)) + np.pi
         x_i = np.linspace(11, 25, 25)
@@ -1176,6 +1185,9 @@ class unit tests methods.
     def test_required_attributes(self) -> None:
         """Test the presence of required attributes."""
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         required_attributes = ()
 
         for attribute in required_attributes:  # pragma: no cover
@@ -1212,6 +1224,9 @@ class TestLinearInterpolator:
     def test_required_attributes(self) -> None:
         """Test the presence of required attributes."""
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         required_attributes = ("x", "y")
 
         for attribute in required_attributes:
@@ -1240,6 +1255,9 @@ def test__call__(self) -> None:
         method.
         """
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         interval = 0.1
         x = np.arange(len(DATA_POINTS_A))
         linear_interpolator = LinearInterpolator(x, DATA_POINTS_A)
@@ -1300,6 +1318,9 @@ class TestSpragueInterpolator:
     def test_required_attributes(self) -> None:
         """Test the presence of required attributes."""
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         required_attributes = ("x", "y")
 
         for attribute in required_attributes:
@@ -1328,6 +1349,9 @@ def test__call__(self) -> None:
         method.
         """
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         interval = 0.1
         x = np.arange(len(DATA_POINTS_A))
         sprague_interpolator = SpragueInterpolator(x, DATA_POINTS_A)
@@ -1396,6 +1420,9 @@ def test__call__(self) -> None:
             and is assumed to be unit tested thoroughly.
         """
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         np.testing.assert_allclose(
             CubicSplineInterpolator(
                 np.linspace(0, 1, len(DATA_POINTS_A)), DATA_POINTS_A
@@ -1414,6 +1441,9 @@ class TestPchipInterpolator:
     def test_required_attributes(self) -> None:
         """Test the presence of required attributes."""
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         required_attributes = ("x", "y")
 
         for attribute in required_attributes:
@@ -1432,6 +1462,9 @@ def test_y(self) -> None:
         Test :attr:`colour.algebra.interpolation.PchipInterpolator.y` property.
         """
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         interpolator = PchipInterpolator(np.linspace(0, 1, 10), np.linspace(0, 1, 10))
 
         interpolator.y = np.linspace(0, 1, 10)
@@ -1448,6 +1481,9 @@ class TestNullInterpolator:
     def test_required_attributes(self) -> None:
         """Test the presence of required attributes."""
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         required_attributes = ("x", "y")
 
         for attribute in required_attributes:
@@ -1478,6 +1514,9 @@ def test_y(self) -> None:
         property.
         """
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         x = y = np.linspace(0, 1, 10)
         null_interpolator = NullInterpolator(x, y)
 
@@ -1531,6 +1570,9 @@ def test__call__(self) -> None:
         method.
         """
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         x = np.arange(len(DATA_POINTS_A))
         null_interpolator = NullInterpolator(x, DATA_POINTS_A)
         np.testing.assert_allclose(

colour/characterisation/aces_it.py

@@ -60,7 +60,6 @@
 import typing
 
 import numpy as np
-from scipy.optimize import minimize
 
 from colour.adaptation import matrix_chromatic_adaptation_VonKries
 from colour.algebra import euclidean_distance, vecmul
@@ -114,6 +113,7 @@
     as_float_scalar,
     from_range_1,
     optional,
+    required,
     runtime_warning,
     tsplit,
     zeros,
@@ -1000,6 +1000,7 @@ def matrix_idt(
 ) -> Tuple[NDArrayFloat, NDArrayFloat, NDArrayFloat, NDArrayFloat]: ...
 
 
+@required("SciPy")
 def matrix_idt(
     sensitivities: RGB_CameraSensitivities,
     illuminant: SpectralDistribution,
@@ -1107,6 +1108,8 @@ def matrix_idt(
     array([ 2.3414154...,  1.        ,  1.5163375...])
     """
 
+    from scipy.optimize import minimize  # noqa: PLC0415
+
     training_data = optional(training_data, read_training_data_rawtoaces_v1())
 
     cmfs, illuminant = handle_spectral_arguments(

colour/characterisation/tests/test_aces_it.py

@@ -41,7 +41,7 @@
 )
 from colour.constants import TOLERANCE_ABSOLUTE_TESTS
 from colour.io import read_sds_from_csv_file
-from colour.utilities import domain_range_scale
+from colour.utilities import domain_range_scale, is_scipy_installed
 
 __author__ = "Colour Developers"
 __copyright__ = "Copyright 2013 Colour Developers"
@@ -981,6 +981,9 @@ def test_matrix_idt(self) -> None:
         Test :func:`colour.characterisation.aces_it.matrix_idt` definition.
         """
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         # The *RAW to ACES* v1 matrix for the same camera and optimized by
         # `Ceres Solver <http://ceres-solver.org>`__ is as follows:
         #
@@ -1196,6 +1199,9 @@ def test_camera_RGB_to_ACES2065_1(self) -> None:
         definition.
         """
 
+        if not is_scipy_installed():  # pragma: no cover
+            return
+
         B, b = matrix_idt(MSDS_CANON_EOS_5DMARK_II, SDS_ILLUMINANTS["D55"])  # pyright: ignore
         np.testing.assert_allclose(
             camera_RGB_to_ACES2065_1(np.array([0.1, 0.2, 0.3]), B, b),

colour/colorimetry/dominant.py

@@ -26,7 +26,6 @@
 import typing
 
 import numpy as np
-import scipy.spatial.distance
 
 from colour.algebra import euclidean_distance, sdiv, sdiv_mode
 from colour.colorimetry import MultiSpectralDistributions, handle_spectral_arguments
@@ -36,7 +35,7 @@
     from colour.hints import ArrayLike, NDArrayFloat, NDArrayInt, Tuple
 
 from colour.models import XYZ_to_xy
-from colour.utilities import as_float_array
+from colour.utilities import as_float_array, required
 
 __author__ = "Colour Developers"
 __copyright__ = "Copyright 2013 Colour Developers"
@@ -54,6 +53,7 @@
 ]
 
 
+@required("SciPy")
 def closest_spectral_locus_wavelength(
     xy: ArrayLike, xy_n: ArrayLike, xy_s: ArrayLike, inverse: bool = False
 ) -> Tuple[NDArrayInt, NDArrayFloat]:
@@ -100,6 +100,8 @@ def closest_spectral_locus_wavelength(
     [ 0.6835474...  0.3162840...]
     """
 
+    import scipy.spatial.distance  # noqa: PLC0415
+
     xy = as_float_array(xy)
     xy_n = np.resize(xy_n, xy.shape)
     xy_s = as_float_array(xy_s)