Merge branch 'master' into contour-nan-fix

mesmerize_core/algorithms/mcorr.py

@@ -112,7 +112,7 @@ def run_algo(batch_path, uuid, data_path: str = None):
             y_shifts = mc.y_shifts_els
             shifts = [x_shifts, y_shifts]
             if hasattr(mc, 'z_shifts_els'):
-                shifts += mc.z_shifts_els
+                shifts.append(mc.z_shifts_els)
             shift_path = output_dir.joinpath(f"{uuid}_shifts.npy")
             np.save(str(shift_path), shifts)
         else:

mesmerize_core/caiman_extensions/mcorr.py

@@ -5,7 +5,6 @@
 from caiman import load_memmap
 
 from ._utils import validate
-from typing import *
 
 
 @pd.api.extensions.register_series_accessor("mcorr")
@@ -92,9 +91,7 @@ def get_output(self, mode: str = "r") -> np.ndarray:
         return mc_movie
 
     @validate("mcorr")
-    def get_shifts(
-        self, pw_rigid: bool = False
-    ) -> Tuple[List[np.ndarray], List[np.ndarray]]:
+    def get_shifts(self, pw_rigid) -> list[np.ndarray]:
         """
         Gets file path to shifts array (.npy file) for item, processes shifts array
         into a list of x and y shifts based on whether rigid or nonrigid
@@ -107,26 +104,16 @@ def get_shifts(
             False = Rigid
         Returns:
         --------
-        List of Processed X and Y shifts arrays
+        List of Processed X and Y [and Z] shifts arrays
+        - For rigid correction, each element is a vector of length n_frames
+        - For pw_rigid correction, each element is an n_frames x n_patches matrix
         """
         path = self._series.paths.resolve(self._series["outputs"]["shifts"])
         shifts = np.load(str(path))
 
         if pw_rigid:
-            n_pts = shifts.shape[1]
-            n_lines = shifts.shape[2]
-            xs = [np.linspace(0, n_pts, n_pts)]
-            ys = []
-
-            for i in range(shifts.shape[0]):
-                for j in range(n_lines):
-                    ys.append(shifts[i, :, j])
+            shifts_by_dim = list(shifts)  # dims-length list of n_frames x n_patches matrices
         else:
-            n_pts = shifts.shape[0]
-            n_lines = shifts.shape[1]
-            xs = [np.linspace(0, n_pts, n_pts)]
-            ys = []
-
-            for i in range(n_lines):
-                ys.append(shifts[:, i])
-        return xs, ys
+            shifts_by_dim = list(shifts.T)  # dims-length list of n_frames-length vectors
+
+        return shifts_by_dim

tests/test_core.py

@@ -44,7 +44,7 @@
 
 def _download_ground_truths():
     print(f"Downloading ground truths")
-    url = f"https://zenodo.org/records/13298934/files/ground_truths.zip"
+    url = f"https://zenodo.org/record/13732996/files/ground_truths.zip"
 
     # basically from https://stackoverflow.com/questions/37573483/progress-bar-while-download-file-over-http-with-requests/37573701
     response = requests.get(url, stream=True)
@@ -252,6 +252,15 @@ def test_mcorr():
     )
     )
 
+    # test to check shifts output path
+    assert (
+        batch_dir.joinpath(df.iloc[-1]["outputs"]["shifts"])
+        == df.paths.resolve(df.iloc[-1]["outputs"]["shifts"])
+        == batch_dir.joinpath(
+            str(df.iloc[-1]["uuid"]), f'{df.iloc[-1]["uuid"]}_shifts.npy'
+        )
+    )
+
     # test to check mean-projection output path
     assert (
             batch_dir.joinpath(df.iloc[-1]["outputs"]["mean-projection-path"])
@@ -303,6 +312,15 @@ def test_mcorr():
     )
     numpy.testing.assert_array_equal(mcorr_output, mcorr_output_actual)
 
+
+    # test to check mcorr get_shifts()
+    mcorr_shifts = df.iloc[-1].mcorr.get_shifts(pw_rigid=test_params[algo]["main"]["pw_rigid"])
+    mcorr_shifts_actual = numpy.load(
+        ground_truths_dir.joinpath("mcorr", "mcorr_shifts.npy")
+    )
+    numpy.testing.assert_array_equal(mcorr_shifts, mcorr_shifts_actual)
+
+
     # test to check caiman get_input_movie_path()
     assert df.iloc[-1].caiman.get_input_movie_path() == get_full_raw_data_path(
         df.iloc[0]["input_movie_path"]