Remove cmapy dependency

pyproject.toml

@@ -24,7 +24,7 @@ classifiers = [
 ]
 dependencies = [
     "appdirs == 1.4.4",
-    "cmapy == 0.6.6",  # TODO(ecyoung3): Replace with own implementation
+    "matplotlib == 3.8.*",
     "numpy == 1.26.*",
     "opencv-python == 4.9.0.*",
     "PyQt6 == 6.7.*",

requirements-dev.txt

@@ -1,45 +1,41 @@
 # This file was autogenerated by uv via the following command:
 #    uv pip compile pyproject.toml -o requirements-dev.txt --extra dev
 appdirs==1.4.4
-cmapy==0.6.6
 colorama==0.4.6
     # via pytest
-contourpy==1.1.1
+contourpy==1.2.1
     # via matplotlib
 cycler==0.12.1
     # via matplotlib
 exceptiongroup==1.2.1
     # via pytest
-fonttools==4.43.1
+fonttools==4.51.0
     # via matplotlib
 iniconfig==2.0.0
     # via pytest
 kiwisolver==1.4.5
     # via matplotlib
-matplotlib==3.8.0
-    # via cmapy
+matplotlib==3.8.4
 mypy==1.10.0
 mypy-extensions==1.0.0
     # via mypy
 numpy==1.26.1
     # via
-    #   cmapy
     #   contourpy
     #   matplotlib
     #   opencv-python
     #   pyqtgraph
     #   scipy
 opencv-python==4.9.0.80
-    # via cmapy
 packaging==23.2
     # via
     #   matplotlib
     #   pytest
-pillow==10.1.0
+pillow==10.3.0
     # via matplotlib
 pluggy==1.5.0
     # via pytest
-pyparsing==3.1.1
+pyparsing==3.1.2
     # via matplotlib
 pyqt6==6.7.0
 pyqt6-qt6==6.7.0
@@ -48,7 +44,7 @@ pyqt6-sip==13.6.0
     # via pyqt6
 pyqtgraph==0.13.3
 pytest==8.2.0
-python-dateutil==2.8.2
+python-dateutil==2.9.0.post0
     # via matplotlib
 ruff==0.4.3
 scipy==1.13.0

requirements.txt

@@ -1,40 +1,36 @@
 # This file was autogenerated by uv via the following command:
 #    uv pip compile pyproject.toml -o requirements.txt
 appdirs==1.4.4
-cmapy==0.6.6
-contourpy==1.1.1
+contourpy==1.2.1
     # via matplotlib
 cycler==0.12.1
     # via matplotlib
-fonttools==4.43.1
+fonttools==4.51.0
     # via matplotlib
 kiwisolver==1.4.5
     # via matplotlib
-matplotlib==3.8.0
-    # via cmapy
+matplotlib==3.8.4
 numpy==1.26.1
     # via
-    #   cmapy
     #   contourpy
     #   matplotlib
     #   opencv-python
     #   pyqtgraph
     #   scipy
 opencv-python==4.9.0.80
-    # via cmapy
-packaging==23.2
+packaging==24.0
     # via matplotlib
-pillow==10.1.0
+pillow==10.3.0
     # via matplotlib
-pyparsing==3.1.1
+pyparsing==3.1.2
     # via matplotlib
 pyqt6==6.7.0
 pyqt6-qt6==6.7.0
     # via pyqt6
 pyqt6-sip==13.6.0
     # via pyqt6
 pyqtgraph==0.13.3
-python-dateutil==2.8.2
+python-dateutil==2.9.0.post0
     # via matplotlib
 scipy==1.13.0
 six==1.16.0

src/frheed/image_processing.py

@@ -2,7 +2,6 @@
 Assorted image processing operations.
 """
 
-import cmapy
 import cv2
 import numpy as np
 from matplotlib import pyplot as plt
@@ -42,19 +41,18 @@ def normalize(arr: np.ndarray) -> np.ndarray:
     return arr.astype(np.uint8, copy=True)
 
 
-def apply_cmap(arr: np.ndarray, cmap: str) -> np.ndarray:
+def apply_cmap(arr: np.ndarray, cmap_name: str, bgr_order: bool = False) -> np.ndarray:
     """
-    Apply a named colormap to an array. This function uses the cmapy library
-    to convert matplotlib colormaps to cv2 colormaps, since cv2.applyColormap is
-    approximately 5x faster than using matplotlib/numpy methods
-    (tested using uint8 2048 x 1536 arrays, ~30ms vs ~6ms).
+    Apply a named colormap to an array.
 
     Parameters
     ----------
     arr : np.ndarray
         The array to apply the colormap to. The array must be single-channel (not RGB).
     cmap : str
         The name of the colormap to apply (any valid matplotlib colormap).
+    rgbA_order : bool
+        Whether the provided array is in BGR order instead of RGB order.
 
     Returns
     -------
@@ -65,8 +63,20 @@ def apply_cmap(arr: np.ndarray, cmap: str) -> np.ndarray:
         and width of the input array.
 
     """
-    colorized_arr: np.ndarray = cmapy.colorize(normalize(arr), cmap, rgb_order=True)
-    return colorized_arr
+    cmap = plt.get_cmap(cmap_name, 256)
+    rgba_data = plt.cm.ScalarMappable(cmap=cmap).to_rgba(np.arange(0, 1, 1 / 256), bytes=True)
+    rgba_data = rgba_data[:, 0:-1].reshape((256, 1, 3))
+
+    # Convert to 3-channel RGB/BGR uint8 for OpenCV
+    cmap_data = np.zeros((256, 1, 3), np.uint8)
+
+    # Remove the alpha channel and optionally reverse RGB to BGR
+    if bgr_order:
+        cmap_data[:, :, :] = rgba_data[:, :, ::-1]
+    else:
+        cmap_data[:, :, :] = rgba_data[:, :, :]
+
+    return cv2.applyColorMap(arr, cmap_data)
 
 
 def to_grayscale(array: np.ndarray) -> np.ndarray:
@@ -124,4 +134,4 @@ def extend_image(image: np.ndarray, new_col: np.ndarray) -> np.ndarray:
 
 
 def get_valid_colormaps() -> list[str]:
-    return plt.colormaps()
+    return list(plt.colormaps())