Fix algorithm

src/histogram_transfer/apply_histogram.py

@@ -1,4 +1,4 @@
-from typing import Optional
+from typing import Optional, Any
 import numpy as np
 from utils import generate_rotation_matrices, compute_histogram
 from histogram_transfer.pdf_transfer_1d import pdf_transfer_1d
@@ -6,10 +6,11 @@ from histogram_transfer.regrain import regrain
 
 
 def apply_histogram(
-    source_img: np.ndarray,
+    source_img: np.ndarray | Any,
     target_histogram: np.ndarray,
     *,
     iterations: int = 25,
+    alpha: float = 0.3,
     source_histogram: Optional[np.ndarray] = None,
     should_regrain: bool = True,
 ):
@@ -38,6 +39,7 @@ def apply_histogram(
         ]  # we ignore colours without occurences
     ).T  # unique rgb colours, 3xN
     source_colours_original = source_colours.copy()
+
     source_counts = np.array(
         [value for value in np.nditer(source_histogram) if value > 0]
     )  # cardinality of each rgb colour in source_colours, N
@@ -49,8 +51,8 @@ def apply_histogram(
         [value for value in np.nditer(target_histogram) if value > 0]
     )
 
-    for rotation in generate_rotation_matrices(iterations):
     source_colour_adjustment = np.zeros_like(source_colours)
+    for iteration, rotation in enumerate(generate_rotation_matrices(iterations)):
         rotated_source_colours = rotation @ source_colours
         rotated_target_histogram_colours = rotation @ target_histogram_colours
 
@@ -58,23 +60,23 @@ def apply_histogram(
         rotated_target_histogram_colours.round(out=rotated_target_histogram_colours)
 
         assert rotation.shape[0] == 3
-        for i in range(rotation.shape[0]):  # for each axis (rgb)
+        for axis in range(rotation.shape[0]):  # for each axis (rgb)
             sorted_source_colours = sorted(
                 enumerate(source_counts),
-                key=lambda x: rotated_source_colours[i, x[0]],
+                key=lambda x: rotated_source_colours[axis, x[0]],
             )
-            sorted_source_counts = [v for _, v in sorted_source_colours]
             sorted_source_indices = [i for i, _ in sorted_source_colours]
+            sorted_source_counts = [v for _, v in sorted_source_colours]
 
             sorted_target_histogram_counts = [
                 v
                 for _, v in sorted(
                     enumerate(target_histogram_counts),
-                    key=lambda x: rotated_target_histogram_colours[i, x[0]],
+                    key=lambda x: rotated_target_histogram_colours[axis, x[0]],
                 )
             ]
             sorted_target_histogram_colours = [
-                v for v in sorted(rotated_target_histogram_colours[i, :])
+                v for v in sorted(rotated_target_histogram_colours[axis, :])
             ]
 
             sorted_new_source_colours = pdf_transfer_1d(
@@ -82,24 +84,22 @@ def apply_histogram(
                 sorted_target_histogram_counts,
                 sorted_target_histogram_colours,
             )
-            source_colour_adjustment[i, :] = [
+            source_colour_adjustment[axis, :] = [
                 v
                 for _, v in sorted(
                     enumerate(sorted_new_source_colours),
                     key=lambda x: sorted_source_indices[x[0]],
                 )
             ]
-
+        source_colours = source_colours + (1 - (iteration / iterations) ** alpha) * (
-        source_colours = source_colours + (
             rotation.T @ (source_colour_adjustment - rotated_source_colours)
         )
-        source_colours.clip(0, bins, out=source_colours)
 
-    lut = np.zeros((256, 256, 256, 3), dtype=np.uint8)
     scale = 256 // bins
     source_colours = source_colours.T * scale
-    source_colours.clip(0, 256, out=source_colours)
+    source_colours.clip(0, 255, out=source_colours)
-    source_colours.round(out=source_colours)
+    lut = np.zeros((256, 256, 256, 3), dtype=np.uint8)
+
     for old, new in zip(source_colours_original.T, source_colours):
         for x in range(scale):
             for y in range(scale):

src/utils/generate_rotation_matrices.py

@@ -53,14 +53,10 @@ def _rotation_matrix(
 
 def _check_rotation_matrix(R: NDArray[np.float64]):
     # Check if the matrix is square
-    if R.shape != (3, 3):
+    assert R.shape == (3, 3), "Matrix must be 3x3"
-        raise ValueError("Matrix must be 3x3.")
 
     # Check orthogonality: R.T * R should be close to the identity matrix
     I = np.eye(3)
-    if not np.allclose(np.dot(R.T, R), I):
+    assert np.allclose(np.dot(R.T, R), I)
-        raise ValueError("allclose")
 
-    # Check determinant: Should be +1
+    assert np.isclose(np.linalg.det(R), 1.0), f"det {np.linalg.det(R)}"
-    if not np.isclose(np.linalg.det(R), 1.0):
-        raise ValueError(f"det {np.linalg.det(R)}")