slight warning cleanup + sort + lint

Author: C-Achard

napari_cellseg3d/log_utility.py

@@ -34,7 +34,7 @@ def print_and_log(self, text):
         self.lock.acquire()
         try:
             print(text)
-            # causes issues if you clik on terminal (tied to CMD QuickEdit mode)
+            # causes issue if you clik on terminal (tied to CMD QuickEdit mode)
             self.moveCursor(QTextCursor.End)
             self.insertPlainText(f"\n{text}")
             self.verticalScrollBar().setValue(

napari_cellseg3d/model_workers.py

@@ -39,13 +39,12 @@
 from qtpy.QtCore import Signal
 from tifffile import imwrite
 
-# local
-from napari_cellseg3d.model_instance_seg import (
-    binary_watershed,
-    binary_connected,
-)
 from napari_cellseg3d import utils
 
+# local
+from napari_cellseg3d.model_instance_seg import binary_connected
+from napari_cellseg3d.model_instance_seg import binary_watershed
+
 """
 Writing something to log messages from outside the main thread is rather problematic (plenty of silent crashes...)
 so instead, following the instructions in the guides below to have a worker with custom signals, I implemented
@@ -490,7 +489,7 @@ def __init__(
         do_augmentation,
         deterministic,
     ):
-        """Initializes a worker for inference with the arguments needed by the :py:func:`~train` function.
+        """Initializes a worker for inference with the arguments needed by the :py:func:`~train` function. Note: See :py:func:`~train`
 
         Args:
             * device : device to train on, cuda or cpu
@@ -525,7 +524,7 @@ def __init__(
 
             * deterministic : dict with "use deterministic" : bool, whether to use deterministic training, "seed": seed for RNG
 
-           Note: See :py:func:`~train`
+
         """
 
         print("init")

napari_cellseg3d/plugin_convert.py

@@ -1,5 +1,6 @@
 import os
 
+import napari
 from tifffile import imwrite
 
 import napari_cellseg3d.interface as ui
@@ -142,7 +143,7 @@ def build(self):
         ui.add_blank(layout=layout, widget=self)
         #############################################################
         small_group_w, small_group_l = ui.make_group(
-            "Remove small objects", l, t, r, b,parent=None
+            "Remove small objects", l, t, r, b, parent=None
         )
 
         ui.add_widgets(

napari_cellseg3d/plugin_dock.py

@@ -3,6 +3,7 @@
 from datetime import datetime
 from pathlib import Path
 
+import napari
 import pandas as pd
 
 # Qt

napari_cellseg3d/plugin_helper.py

@@ -1,7 +1,6 @@
 import napari
 
 # Qt
-from qtpy.QtWidgets import QSizePolicy
 from qtpy.QtWidgets import QVBoxLayout
 from qtpy.QtWidgets import QWidget
 

napari_cellseg3d/plugin_metrics.py

@@ -1,4 +1,5 @@
 import matplotlib.pyplot as plt
+import napari
 import numpy as np
 from matplotlib.backends.backend_qt5agg import (
     FigureCanvasQTAgg as FigureCanvas,

napari_cellseg3d/plugin_model_inference.py

@@ -98,9 +98,10 @@ def __init__(self, viewer: "napari.viewer.Viewer"):
         ###########################
         # interface
 
-        self.view_results_container, self.view_results_layout = ui.make_container(
-            T=7, B=0, parent=self
-        )
+        (
+            self.view_results_container,
+            self.view_results_layout,
+        ) = ui.make_container(T=7, B=0, parent=self)
 
         self.view_checkbox = ui.make_checkbox(
             "View results in napari", self.toggle_display_number
@@ -357,12 +358,7 @@ def build(self):
         # model group
 
         model_group_w, model_group_l = ui.make_group(
-            "Model choice",
-            L,
-            T,
-            R,
-            B,
-         parent = self
+            "Model choice", L, T, R, B, parent=self
         )  # model choice
 
         ui.add_widgets(

napari_cellseg3d/utils.py

@@ -465,7 +465,7 @@ def save_stack(images, out_path, filetype=".png", check_warnings=False):
     """Saves the files in labels at location out_path as a stack of len(labels) .png files
 
     Args:
-        labels: array of label images
+        images: array of label images
         out_path: path to the directory for saving
     """
     num = images.shape[0]