Merge pull request #212 from siapy/fix

Author: janezlapajne

README.md

@@ -70,7 +70,7 @@ data_dir = "~/data"
 header_paths = sorted(Path(data_dir).rglob("*.hdr"))
 image_paths = sorted(Path(data_dir).rglob("*.img"))
 
-imageset = SpectralImageSet.from_paths(
+imageset = SpectralImageSet.spy_open(
     header_paths=header_paths,
     image_paths=image_paths,
 )

siapy/entities/images/spimage.py

@@ -124,17 +124,17 @@ def to_signatures(self, pixels: "Pixels") -> Signatures:
 
     def to_subarray(self, pixels: "Pixels") -> NDArray[np.floating[Any]]:
         image_arr = self.to_numpy()
-        u_max = pixels.u().max()
-        u_min = pixels.u().min()
-        v_max = pixels.v().max()
-        v_min = pixels.v().min()
+        u_max = pixels.x().max()
+        u_min = pixels.x().min()
+        v_max = pixels.y().max()
+        v_min = pixels.y().min()
         # create new image
         image_arr_area = np.nan * np.ones((int(v_max - v_min + 1), int(u_max - u_min + 1), self.bands))
         # convert original coordinates to coordinates for new image
-        v_norm = pixels.v() - v_min
-        u_norm = pixels.u() - u_min
+        v_norm = pixels.y() - v_min
+        u_norm = pixels.x() - u_min
         # write values from original image to new image
-        image_arr_area[v_norm, u_norm, :] = image_arr[pixels.v(), pixels.u(), :]
+        image_arr_area[v_norm, u_norm, :] = image_arr[pixels.y(), pixels.x(), :]
         return image_arr_area
 
     def mean(self, axis: int | tuple[int, ...] | Sequence[int] | None = None) -> float | NDArray[np.floating[Any]]:

siapy/entities/pixels.py

@@ -77,11 +77,10 @@ def df_homogenious(self) -> pd.DataFrame:
         df_homo[self.coords.H] = 1
         return df_homo
 
-    def u(self) -> "pd.Series[float]":
-        # TODO: change to u -> x
+    def x(self) -> "pd.Series[float]":
         return self.df[self.coords.X]
 
-    def v(self) -> "pd.Series[float]":
+    def y(self) -> "pd.Series[float]":
         return self.df[self.coords.Y]
 
     def to_numpy(self) -> NDArray[np.floating[Any]]:

siapy/entities/signatures.py

@@ -87,8 +87,8 @@ def from_dict(cls, data: dict[str, Any]) -> "Signatures":
     @classmethod
     def from_array_and_pixels(cls, image: NDArray[np.floating[Any]], pixels: Pixels) -> "Signatures":
         pixels = pixels.as_type(int)
-        u = pixels.u()
-        v = pixels.v()
+        u = pixels.x()
+        v = pixels.y()
 
         if image.ndim != 3:
             raise InvalidInputError(f"Expected a 3-dimensional array, but got {image.ndim}-dimensional array.")

siapy/utils/plots.py

@@ -142,8 +142,8 @@ def display_image_with_areas(
 
     for pixels in areas:
         ax.scatter(
-            pixels.u(),
-            pixels.v(),
+            pixels.x(),
+            pixels.y(),
             lw=0,
             marker="o",
             c=color,
@@ -180,8 +180,8 @@ def display_multiple_images_with_areas(
 
         for pixels in selected_areas:
             ax.scatter(
-                pixels.u(),
-                pixels.v(),
+                pixels.x(),
+                pixels.y(),
                 lw=0,
                 marker="o",
                 c=color,

tests/entities/test_entities_pixels.py

@@ -86,14 +86,14 @@ def test_u():
     df = pd.DataFrame(iterable, columns=[Pixels.coords.X, Pixels.coords.Y])
     pixels = Pixels(df)
     expected_x = pd.Series([1, 3, 5], name=Pixels.coords.X)
-    assert pixels.u().equals(expected_x)
+    assert pixels.x().equals(expected_x)
 
 
 def test_v():
     df = pd.DataFrame(iterable, columns=[Pixels.coords.X, Pixels.coords.Y])
     pixels = Pixels(df)
     expected_y = pd.Series([2, 4, 6], name=Pixels.coords.Y)
-    assert pixels.v().equals(expected_y)
+    assert pixels.y().equals(expected_y)
 
 
 def test_to_numpy():

tests/entities/test_entities_signatures.py

@@ -186,7 +186,7 @@ def test_signatures_from_array_and_pixels():
     from_array_and_pixels = Signatures.from_array_and_pixels(image, pixels)
 
     assert from_array_and_pixels.pixels == pixels
-    assert from_array_and_pixels.signals.df.equals(pd.DataFrame(list(image[pixels.v(), pixels.u(), :])))
+    assert from_array_and_pixels.signals.df.equals(pd.DataFrame(list(image[pixels.y(), pixels.x(), :])))
 
 
 def test_signatures_from_array_and_pixels_invalid_dimensions():

tests/utils/test_utils_images.py

@@ -159,7 +159,7 @@ def test_calculate_correction_factor_from_panel_with_label(spectral_images):
 
     a = image_vnir.to_numpy()
     pixels = get_signatures_within_convex_hull(image_vnir, rect)[0].pixels
-    c = a[pixels.v(), pixels.u(), :]
+    c = a[pixels.y(), pixels.x(), :]
     assert np.array_equal(
         np.full(image_vnir.bands, 0.2),
         np.round(c.mean(axis=0) * panel_correction, 2),