[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

draugr/drawers/mpl_drawers/discrete_scroll_plot.py

@@ -25,7 +25,8 @@
 class DiscreteScrollPlot(MplDrawer):
     """
     Waterfall plot
-    only supports a single trajectory at a time, do not supply parallel trajectories to draw method, will get truncated to num actions, effectively dropping actions for other envs than the first."""
+    only supports a single trajectory at a time, do not supply parallel trajectories to draw method, will get truncated to num actions, effectively dropping actions for other envs than the first.
+    """
 
     @passes_kws_to(MplDrawer.__init__)
     def __init__(
@@ -43,7 +44,6 @@ def __init__(
         figure_size: Tuple[int, int] = None,
         **kwargs
     ):
-
         super().__init__(render=render, figure_size=figure_size, **kwargs)
         if not render:
             return

draugr/drawers/mpl_drawers/spectral/fast_fourier_transform_spectrogram.py

@@ -26,7 +26,8 @@
 class FastFourierTransformSpectrogramPlot(MplDrawer):
     """
     TODO: CENTER Align fft maybe, to mimick librosa stft
-    Short Time Fourier Transform (STFT), with step size of 1 and window lenght of n_fft, and no window function ( TODO: Hanning Smoothing)"""
+    Short Time Fourier Transform (STFT), with step size of 1 and window lenght of n_fft, and no window function ( TODO: Hanning Smoothing)
+    """
 
     def __init__(
         self,

draugr/drawers/opencv_drawers/opencv_image_stream.py

@@ -28,7 +28,6 @@ class OpencvImageStream(Drawer):
     def __init__(
         self, title: str = "NoName", render: bool = True, **kwargs: MutableMapping
     ):
-
         super().__init__(**kwargs)
         if not render:
             return

draugr/matlab_utilities/conversion.py

@@ -12,10 +12,8 @@
 from typing import Any
 
 try:
-
     import matlab
 except ImportError:
-
     raise ImportError("Matlab engine not installed")
 import numpy
 from scipy import sparse
@@ -181,7 +179,6 @@ def ndarray_to_matlab(numpy_array):
         order = "C"
 
     if numpy.iscomplexobj(numpy_array):  # complex case
-
         matlab_array = matlab.double(
             initializer=None, size=(1, num_elements), is_complex=True
         )  # create empty matlab.mlarray

draugr/metrics/metric_collection.py

@@ -52,10 +52,10 @@ def append(self, *args: Sequence, **kwargs: MutableMapping):
         :type args:
         :param kwargs:
         :type kwargs:"""
-        for (arg, (k, v)) in zip(args, self._metrics.items()):
+        for arg, (k, v) in zip(args, self._metrics.items()):
             self._metrics[k].append(arg)
 
-        for (k, v) in kwargs:
+        for k, v in kwargs:
             self._metrics[k].append(v)
 
     def remove_metric(self, name):

draugr/multiprocessing_utilities/pooled_queue_processor.py

@@ -55,7 +55,8 @@ class PooledQueueProcessor(object):
     This is a workaround of Pythons extremely slow interprocess communication pipes.
     The ideal solution would be to use a multiprocessing.queue, but it apparently communication is band
     limited.
-    This solution has processes complete tasks (batches) and a thread add the results to a queue.queue."""
+    This solution has processes complete tasks (batches) and a thread add the results to a queue.queue.
+    """
 
     def __init__(
         self,
@@ -68,7 +69,6 @@ def __init__(
         fill_at_construction=True,
         blocking=True,
     ):
-
         if kwargs is None:
             kwargs = {}
 

draugr/opencv_utilities/color_space/edge.py

@@ -43,7 +43,6 @@ def to_edge(
 
     ksize = kwargs.get("ksize", max(next_odd(max(*(img.shape)) // 100), 5))
     if method == ToEdgeMethodEnum.morph_gradient:
-
         return cv2.morphologyEx(
             img,
             MorphTypeEnum.gradient.value,

draugr/opencv_utilities/color_space/noise.py

@@ -45,7 +45,6 @@ def noise_filter(
             sigmaSpace=kwargs.get("sigmaSpace", 17),
         )
     elif method == NoiseFilterMethodEnum.gaussian_blur:
-
         return cv2.GaussianBlur(
             img,
             ksize=(ksize, ksize),

draugr/opencv_utilities/drawing/masks/gauss_circles.py

@@ -39,6 +39,7 @@ def ellipse_bbox(h, k, a, b, theta):
 
 # ----------------------------------------------------------------------------
 
+
 # Rotated elliptical gradient - slow, Python-only approach
 def make_gradient_v1(width, height, h, k, a, b, theta):
     """
@@ -76,6 +77,7 @@ def make_gradient_v1(width, height, h, k, a, b, theta):
 
 # ----------------------------------------------------------------------------
 
+
 # Rotated elliptical gradient - faster, vectorized numpy approach
 def make_gradient_v2(width, height, h, k, a, b, theta):
     """
@@ -111,7 +113,6 @@ def make_gradient_v2(width, height, h, k, a, b, theta):
 
 # ============================================================================
 if __name__ == "__main__":
-
     from pathlib import Path
     from warg import ensure_existence
     from draugr.opencv_utilities import show_image

draugr/opencv_utilities/windows/color_picker.py

@@ -56,7 +56,6 @@ def interactive_hsv_color_picker(
         img = cv2.imread(str(p))
         output = img
         while 1:
-
             h_min = cv2.getTrackbarPos(hmin_label, window_label)
             h_max = cv2.getTrackbarPos(hmax_label, window_label)