Merge pull request #189 from yfukai/fixing_row_col_def

Fixing row col def

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "m2stitch"
-version = "0.5.0"
+version = "0.5.1"
 description = "M2Stitch"
 authors = ["Yohsuke Fukai <[email protected]>"]
 license = "MIT"

src/m2stitch/stitching.py

@@ -46,10 +46,10 @@ def stitch_images(
         the images to stitch.
 
     rows : list, optional
-        the row indices (tile position in the last dimension) of the images.
+        the row indices (tile position in the second last dimension) of the images.
 
     cols : list, optional
-        the column indices (tile position in the second last dimension) of the images
+        the column indices (tile position in the last dimension) of the images
 
     position_indices : np.ndarray, optional
         the tile position indices in each dimension.
@@ -89,9 +89,9 @@ def stitch_images(
             warnings.warn(
                 "row_col_transpose is True. The default value will be changed to False in the major release."
             )
-            position_indices = np.array([rows, cols]).T
-        else:
             position_indices = np.array([cols, rows]).T
+        else:
+            position_indices = np.array([rows, cols]).T
     position_indices = np.array(position_indices)
     assert images.shape[0] == position_indices.shape[0]
     assert position_indices.shape[1] == images.ndim - 1
@@ -100,7 +100,7 @@ def stitch_images(
         assert images.shape[0] == position_indices.shape[0]
         assert position_initial_guess.shape[1] == images.ndim - 1
     assert 0 <= overlap_diff_threshold and overlap_diff_threshold <= 100
-    _cols, _rows = position_indices.T
+    _rows, _cols = position_indices.T
 
     sizeY, sizeX = images.shape[1:]
 
@@ -175,6 +175,8 @@ def get_lims(dimension, size):
 
     predictor = EllipticEnvelope(contamination=0.4)
     # TODO make threshold adjustable
+    assert np.any(grid["top_ncc_first"] > 0.5), "there is no good top pair"
+    assert np.any(grid["left_ncc_first"] > 0.5), "there is no good left pair"
     left_displacement = compute_image_overlap2(
         grid[grid["left_ncc_first"] > 0.5], "left", sizeY, sizeX, predictor
     )

tests/test_stitching.py

@@ -48,3 +48,30 @@ def test_stitching_init_guess(
     assert np.array_equal(result_df.index, props.index)
     assert all(np.abs(result_df["y_pos"] - props["y_pos"]) <= props["allowed_error"])
     assert all(np.abs(result_df["x_pos"] - props["x_pos"]) <= props["allowed_error"])
+
+
+def test_stitching_with_pos(test_image_path: Tuple[npt.NDArray, pd.DataFrame]) -> None:
+    testimages, props = test_image_path
+    """It exits with a status code of zero."""
+    poss = props[["y_pos", "x_pos"]].values
+
+    def get_pos(vals):
+        vals2 = np.round(np.array(vals) / 500).astype(np.int64)
+        sorted_vals = np.sort(np.unique(vals2))
+        d = dict(zip(sorted_vals, np.arange(len(sorted_vals))))
+        return list(map(d.get, vals2))
+
+    pos_indices = np.array(
+        [
+            get_pos(poss[:, 0]),
+            get_pos(poss[:, 1]),
+        ]
+    ).T
+    assert all(pos_indices[:, 0] == props["row"])
+    assert all(pos_indices[:, 1] == props["col"])
+    result_df, _ = stitch_images(
+        testimages, position_indices=pos_indices, row_col_transpose=False
+    )
+    assert np.array_equal(result_df.index, props.index)
+    assert all(np.abs(result_df["y_pos"] - props["y_pos"]) <= props["allowed_error"])
+    assert all(np.abs(result_df["x_pos"] - props["x_pos"]) <= props["allowed_error"])