Optimizations

src/napari_ndev/__init__.py

@@ -3,19 +3,13 @@
 except ImportError:
     __version__ = "unknown"
 
+from . import helpers
 from ._apoc_container import ApocContainer
 from ._apoc_feature_stack import ApocFeatureStack
 from ._plate_mapper import PlateMapper
 from ._rescale_by import RescaleBy
 from ._utilities_container import UtilitiesContainer
 from ._workflow_container import WorkflowContainer
-from .helpers import (
-    check_for_missing_files,
-    get_channel_names,
-    get_directory_and_files,
-    get_squeezed_dim_order,
-    setup_logger,
-)
 
 __all__ = [
     "WorkflowContainer",
@@ -24,9 +18,5 @@
     "ApocFeatureStack",
     "RescaleBy",
     "PlateMapper",
-    "get_directory_and_files",
-    "check_for_missing_files",
-    "setup_logger",
-    "get_squeezed_dim_order",
-    "get_channel_names",
+    "helpers",
 ]

src/napari_ndev/_apoc_container.py

@@ -3,12 +3,8 @@
 from enum import Enum
 from typing import TYPE_CHECKING
 
-import apoc
 import numpy as np
 import pandas as pd
-import pyclesperanto_prototype as cle
-from aicsimageio import AICSImage
-from aicsimageio.writers import OmeTiffWriter
 from magicgui.widgets import (
     CheckBox,
     ComboBox,
@@ -24,13 +20,19 @@
     Table,
     create_widget,
 )
-from napari import layers
+from pyclesperanto_prototype import set_wait_for_kernel_finish
 
 from napari_ndev import helpers
 
 if TYPE_CHECKING:
     import napari
 
+# Lazy Imports:
+# from aicsimageio import AICSImage
+# from aicsimageio.writers import OmeTiffWriter
+# from napari import layers
+# import apoc
+
 
 class ApocContainer(Container):
     """
@@ -155,6 +157,15 @@ def __init__(
         # viewer = napari_viewer
     ):
         super().__init__()
+
+        ##############################
+        # Lazy Imports
+        ##############################
+        import apoc
+        from napari.layers import Image as ImageLayer
+
+        self.apoc = apoc
+
         ##############################
         # Attributes
         ##############################
@@ -250,7 +261,7 @@ def __init__(
 
         def current_layers(_):
             return [
-                x for x in self._viewer.layers if isinstance(x, layers.Image)
+                x for x in self._viewer.layers if isinstance(x, ImageLayer)
             ]
 
         self._image_layer = Select(
@@ -308,6 +319,8 @@ def current_layers(_):
         self._predict_image_layer.clicked.connect(self.image_predict)
 
     def _update_metadata_from_file(self):
+        from aicsimageio import AICSImage
+
         _, files = helpers.get_directory_and_files(self._image_directory.value)
         img = AICSImage(files[0])
         self._image_channels.choices = helpers.get_channel_names(img)
@@ -389,20 +402,20 @@ def _get_feature_set(self):
         if self._predefined_features.value.value == 1:
             return self._custom_features.value
         else:
-            return apoc.PredefinedFeatureSet[
+            return self.apoc.PredefinedFeatureSet[
                 self._predefined_features.value.name
             ].value
 
     def _get_training_classifier_instance(self):
         if self._classifier_type.value == "PixelClassifier":
-            return apoc.PixelClassifier(
+            return self.apoc.PixelClassifier(
                 opencl_filename=self._classifier_file.value,
                 max_depth=self._max_depth.value,
                 num_ensembles=self._num_trees.value,
             )
 
         if self._classifier_type.value == "ObjectSegmenter":
-            return apoc.ObjectSegmenter(
+            return self.apoc.ObjectSegmenter(
                 opencl_filename=self._classifier_file.value,
                 positive_class_identifier=self._positive_class_id.value,
                 max_depth=self._max_depth.value,
@@ -420,6 +433,8 @@ def _get_channel_image(self, img, channel_index_list):
         return channel_img
 
     def batch_train(self):
+        from aicsimageio import AICSImage
+
         image_directory, image_files = helpers.get_directory_and_files(
             self._image_directory.value
         )
@@ -442,14 +457,14 @@ def batch_train(self):
         )
 
         # https://github.com/clEsperanto/pyclesperanto_prototype/issues/163
-        cle.set_wait_for_kernel_finish(True)
+        set_wait_for_kernel_finish(True)
 
         self._progress_bar.label = f"Training on {len(image_files)} Images"
         self._progress_bar.value = 0
         self._progress_bar.max = len(image_files)
 
         if not self._continue_training:
-            apoc.erase_classifier(self._classifier_file.value)
+            self.apoc.erase_classifier(self._classifier_file.value)
 
         custom_classifier = self._get_training_classifier_instance()
         feature_set = self._get_feature_set()
@@ -506,10 +521,10 @@ def image_train(self):
         label = self._label_layer.value.data
 
         # https://github.com/clEsperanto/pyclesperanto_prototype/issues/163
-        cle.set_wait_for_kernel_finish(True)
+        set_wait_for_kernel_finish(True)
 
         if not self._continue_training:
-            apoc.erase_classifier(self._classifier_file.value)
+            self.apoc.erase_classifier(self._classifier_file.value)
 
         custom_classifier = self._get_training_classifier_instance()
         feature_set = self._get_feature_set()
@@ -535,6 +550,9 @@ def _get_prediction_classifier_instance(self):
             return None
 
     def batch_predict(self):
+        from aicsimageio import AICSImage
+        from aicsimageio.writers import OmeTiffWriter
+
         image_directory, image_files = helpers.get_directory_and_files(
             dir=self._image_directory.value,
         )
@@ -552,7 +570,7 @@ def batch_predict(self):
         )
 
         # https://github.com/clEsperanto/pyclesperanto_prototype/issues/163
-        cle.set_wait_for_kernel_finish(True)
+        set_wait_for_kernel_finish(True)
 
         self._progress_bar.label = f"Predicting {len(image_files)} Images"
         self._progress_bar.value = 0
@@ -583,7 +601,7 @@ def batch_predict(self):
                 self._progress_bar.value = idx + 1
                 continue
 
-            save_data = cle.pull(result)
+            save_data = np.asarray(result)
             if save_data.max() > 65535:
                 save_data = save_data.astype(np.int32)
             else:
@@ -607,7 +625,7 @@ def image_predict(self):
         layer_name = self._image_layer.value[0].name
         print(f"Predicting {layer_name}")
         # https://github.com/clEsperanto/pyclesperanto_prototype/issues/163
-        cle.set_wait_for_kernel_finish(True)
+        set_wait_for_kernel_finish(True)
 
         image_list = [image.data for image in self._image_layer.value]
         image_stack = np.stack(image_list, axis=0)

src/napari_ndev/_apoc_feature_stack.py

@@ -1,6 +1,5 @@
 from typing import TYPE_CHECKING
 
-import apoc
 from magicgui.widgets import (
     CheckBox,
     Container,
@@ -113,8 +112,10 @@ def process_feature(prefix, input_str):
         self._feature_string.value = " ".join(feature_list)
 
     def layer_to_feature_stack(self):
+        from apoc import generate_feature_stack
+
         image = self._image_layer.value.data
-        feature_stack = apoc.generate_feature_stack(
+        feature_stack = generate_feature_stack(
             image, self._feature_string.value
         )
 

src/napari_ndev/_plate_mapper.py

@@ -2,7 +2,6 @@
 import string
 
 import pandas as pd
-import seaborn as sns
 
 
 class PlateMapper:
@@ -145,14 +144,16 @@ def get_styled_plate_map(self, treatment, palette="colorblind"):
             map DataFrame with different background colors for each unique
             value.
         """
+        from seaborn import color_palette
+
         self.plate_map_pivot = self.get_pivoted_plate_map(treatment)
 
         unique_values = pd.unique(self.plate_map_pivot.values.flatten())
         unique_values = unique_values[pd.notna(unique_values)]
 
-        color_palette = sns.color_palette(palette).as_hex()
+        color_palette_hex = color_palette(palette).as_hex()
         # Create an infinite iterator that cycles through the palette
-        palette_cycle = itertools.cycle(color_palette)
+        palette_cycle = itertools.cycle(color_palette_hex)
         # Use next() to get the next color
         color_dict = {value: next(palette_cycle) for value in unique_values}
 

src/napari_ndev/_tests/test_apoc_container.py

@@ -186,7 +186,7 @@ def test_batch_predict_normal_operation(make_napari_viewer, tmp_path):
     container._image_directory.value = image_directory
     container._output_directory.value = output_directory
     # container._image_channels.value = ["IBA1"] # images need fixed
-    container._image_channels.value = ['Labels']
+    container._image_channels.value = ["Labels"]
     container._classifier_file.value = classifier
 
     container.batch_predict()
@@ -210,7 +210,7 @@ def test_update_metadata_from_file(make_napari_viewer):
         )
 
         # Mock the AICSImage class to return sample channel names
-        with patch("napari_ndev._apoc_container.AICSImage") as mock_AICSImage:
+        with patch("aicsimageio.AICSImage") as mock_AICSImage:
             mock_AICSImage.return_value.channel_names = ["C0", "C1", "C2"]
 
             # Call the _update_metadata_from_file method
@@ -236,7 +236,7 @@ def test_batch_predict_exception_logging(make_napari_viewer, tmp_path):
     container._image_directory.value = image_directory
     container._output_directory.value = output_directory
     # container._image_channels.value = ["IBA1"] # fix these images
-    container._image_channels.value = ['Labels']
+    container._image_channels.value = ["Labels"]
 
     # Mock the custom_classifier.predict() method to raise an exception
     class MockClassifier:

src/napari_ndev/_utilities_container.py

@@ -3,9 +3,6 @@
 from typing import TYPE_CHECKING, List, Union
 
 import numpy as np
-from aicsimageio import AICSImage
-from aicsimageio.types import PhysicalPixelSizes
-from aicsimageio.writers import OmeTiffWriter
 from magicgui.widgets import (
     CheckBox,
     Container,
@@ -18,12 +15,12 @@
     TextEdit,
     create_widget,
 )
-from napari import layers
 
 from napari_ndev import helpers
 
 if TYPE_CHECKING:
     import napari
+    from napari.layers import Image as ImageLayer
 
 
 class UtilitiesContainer(Container):
@@ -117,6 +114,7 @@ def __init__(
         viewer: "napari.viewer.Viewer",
     ):
         super().__init__()
+
         ##############################
         # Attributes
         ##############################
@@ -182,8 +180,10 @@ def __init__(
         # Use a function for layer inputs so that it is constantly updated
         # when the dependency changes
         def current_layers(_):
+            from napari.layers import Image as ImageLayer
+
             return [
-                x for x in self._viewer.layers if isinstance(x, layers.Image)
+                x for x in self._viewer.layers if isinstance(x, ImageLayer)
             ]
 
         self._image_layer = Select(
@@ -285,13 +285,14 @@ def _update_metadata(self, img):
         self._physical_pixel_sizes_x.value = img.physical_pixel_sizes.X
 
     def update_metadata_from_file(self):
+        from aicsimageio import AICSImage
+
         img = AICSImage(self._files.value[0])
         self._img = img
         self._update_metadata(img)
         self._save_name.value = str(self._files.value[0].stem + ".tiff")
         self._scenes.value = len(img.scenes)
 
-
     def update_metadata_from_layer(self):
         try:
             img = self._image_layer.value[0].metadata["aicsimage"]
@@ -308,8 +309,10 @@ def concatenate_images(
         concatenate_files: bool,
         files: List[Union[str, Path]],
         concatenate_layers: bool,
-        layers: List[layers.Image],
+        layers: List["ImageLayer"],
     ):
+        from aicsimageio import AICSImage
+
         array_list = []
         if concatenate_files:
             for file in files:
@@ -338,6 +341,8 @@ def concatenate_images(
 
     @property
     def p_sizes(self):
+        from aicsimageio.types import PhysicalPixelSizes
+
         return PhysicalPixelSizes(
             self._physical_pixel_sizes_z.value,
             self._physical_pixel_sizes_y.value,
@@ -357,6 +362,8 @@ def _common_save_logic(
         channel_names: List[str],
         layer: str,
     ) -> None:
+        from aicsimageio.writers import OmeTiffWriter
+
         # AICSImage does not allow saving labels as np.int64
         # napari generates labels differently depending on the OS
         # so we need to convert to np.int32 in case np.int64 generated
@@ -393,6 +400,8 @@ def _common_save_logic(
         return
 
     def save_scenes_ome_tiff(self) -> None:
+        from aicsimageio import AICSImage
+
         img = AICSImage(self._files.value[0])
         scenes = self._scenes_to_extract.value
         scenes_list = ast.literal_eval(scenes) if scenes else None
@@ -401,8 +410,10 @@ def save_scenes_ome_tiff(self) -> None:
         for scene in scenes_list:
             img.set_scene(scene)
 
-            img_save_name = (f'{self._save_name.value.split(".")[0]}'
-                             f'_scene_{img.current_scene}.ome.tiff')
+            img_save_name = (
+                f'{self._save_name.value.split(".")[0]}'
+                f"_scene_{img.current_scene}.ome.tiff"
+            )
             img_save_loc = save_directory / img_save_name
 
             # get channel names from widget if truthy