Modify warning

iohub/convert.py

@@ -7,6 +7,7 @@
 from dask.array import to_zarr
 from tqdm import tqdm
 from tqdm.contrib.itertools import product
+from tqdm.contrib.logging import logging_redirect_tqdm
 
 from iohub._version import version as iohub_version
 from iohub.ngff import Position, TransformationMeta, open_ome_zarr
@@ -336,14 +337,17 @@ def _convert_image_plane_metadata(self, fov, zarr_name: str):
                     if self.reader.str_channel_axis
                     else c_idx
                 )
+            missing_data_warning_issued = False
             for z_idx in range(self.z):
                 metadata = fov.frame_metadata(t=t_idx, c=c_key, z=z_idx)
                 if metadata is None:
-                    _logger.warning(
-                        f"Cannot load data at timepoint {t_idx},  channel "
-                        f"{c_idx}, filling with zeros. Raw data may be "
-                        "incomplete."
-                    )
+                    if not missing_data_warning_issued:
+                        missing_data_warning_issued = True
+                        _logger.warning(
+                            f"Cannot load data at P: {zarr_name}, T: {t_idx}, "
+                            f"C: {c_idx}, filling with zeros. Raw data may be "
+                            "incomplete."
+                        )
                     continue
                 if not sorted_keys:
                     # Sort keys, ordering keys without dashes first
@@ -375,16 +379,17 @@ def __call__(self) -> None:
         self._init_zarr_arrays()
         # Run through every coordinate and convert in acquisition order
         _logger.debug("Converting images.")
-        for zarr_pos_name, (_, fov) in tqdm(
-            zip(self.zarr_position_names, self.reader, strict=True),
-            total=len(self.reader),
-            desc="Converting images",
-            unit="FOV",
-            ncols=80,
-        ):
-            zarr_img = self.writer[zarr_pos_name]["0"]
-            to_zarr(fov.xdata.data.rechunk(self.chunks), zarr_img)
-            self._convert_image_plane_metadata(fov, zarr_img.path)
+        with logging_redirect_tqdm():
+            for zarr_pos_name, (_, fov) in tqdm(
+                zip(self.zarr_position_names, self.reader, strict=True),
+                total=len(self.reader),
+                desc="Converting images",
+                unit="FOV",
+                ncols=80,
+            ):
+                zarr_img = self.writer[zarr_pos_name]["0"]
+                to_zarr(fov.xdata.data.rechunk(self.chunks), zarr_img)
+                self._convert_image_plane_metadata(fov, zarr_img.path)
         self.writer.zgroup.attrs.update(self.metadata)
         self.writer.close()
         self.reader.close()

tests/ngff/test_ngff.py

@@ -200,7 +200,7 @@ def test_write_ome_zarr(channels_and_random_5d, arr_name):
         # round-trip test with the offical reader implementation
         ext_reader = Reader(parse_url(dataset.zgroup.store.path))
         node = list(ext_reader())[0]
-        assert node.metadata["name"] == channel_names
+        assert node.metadata["channel_names"] == channel_names
         assert node.specs[0].datasets == [arr_name]
         assert node.data[0].shape == random_5d.shape
         assert node.data[0].dtype == random_5d.dtype