refactor: added option to directly calculate correction factor from i…

…mage

siapy/utils/images.py

@@ -6,6 +6,7 @@
 import spectral as sp
 
 from siapy.core import logger
+from siapy.core.exceptions import InvalidInputError
 from siapy.core.types import ImageDataType, ImageType
 from siapy.entities import SpectralImage
 from siapy.transformations.image import rescale
@@ -187,14 +188,27 @@ def convert_radiance_image_to_reflectance(
 def calculate_correction_factor_from_panel(
     image: SpectralImage,
     panel_reference_reflectance: float,
-    panel_shape_label: str = "reference_panel",
-) -> np.ndarray | None:
-    panel_shape = image.geometric_shapes.get_by_name(panel_shape_label)
-    if panel_shape is None:
-        return None
-
-    panel_signatures = image.to_signatures(panel_shape.convex_hull())
-    panel_radiance_mean = panel_signatures.signals.mean()
+    panel_shape_label: str | None = None,
+) -> np.ndarray:
+    if panel_shape_label:
+        panel_shape = image.geometric_shapes.get_by_name(panel_shape_label)
+        if not panel_shape:
+            raise InvalidInputError(
+                input_value={"panel_shape_label": panel_shape_label},
+                message="Panel shape label not found.",
+            )
+        panel_signatures = image.to_signatures(panel_shape.convex_hull())
+        panel_radiance_mean = panel_signatures.signals.mean()
+
+    else:
+        temp_mean = image.mean(axis=(0, 1))
+        if not isinstance(temp_mean, np.ndarray):
+            raise InvalidInputError(
+                input_value={"image": image},
+                message=f"Expected image.mean(axis=(0, 1)) to return np.ndarray, but got {type(temp_mean).__name__}.",
+            )
+        panel_radiance_mean = temp_mean
+
     panel_reflectance_mean = np.full(image.bands, panel_reference_reflectance)
     panel_correction = panel_reflectance_mean / panel_radiance_mean
     return panel_correction

tests/utils/test_utils_images.py

@@ -142,7 +142,7 @@ def shape(self) -> tuple[int, int, int]:
         assert save_path.exists()
 
 
-def test_calculate_correction_factor_from_panel(spectral_images):
+def test_calculate_correction_factor_from_panel_with_label(spectral_images):
     pixels = Pixels.from_iterable([(900, 1150), (1050, 1300)])
     rect = Shape.from_shape_type(
         shape_type="rectangle", pixels=pixels, label="reference_panel"
@@ -156,7 +156,6 @@ def test_calculate_correction_factor_from_panel(spectral_images):
         panel_shape_label="reference_panel",
     )
 
-    assert panel_correction is not None
     assert isinstance(panel_correction, np.ndarray)
     assert panel_correction.shape == (image_vnir.bands,)
 
@@ -168,6 +167,18 @@ def test_calculate_correction_factor_from_panel(spectral_images):
     )
 
 
+def test_calculate_correction_factor_from_panel_without_label(spectral_images):
+    image_vnir = spectral_images.vnir
+    panel_correction = calculate_correction_factor_from_panel(
+        image=image_vnir,
+        panel_reference_reflectance=0.3,
+    )
+    direct_panel_calculation = np.full(image_vnir.bands, 0.3) / image_vnir.mean(
+        axis=(0, 1)
+    )
+    assert np.array_equal(direct_panel_calculation, panel_correction)
+
+
 def test_convert_radiance_image_to_reflectance_without_saving(spectral_images):
     image_vnir = spectral_images.vnir
     panel_correction = np.random.default_rng().random(image_vnir.bands)