Merge remote-tracking branch 'origin/master'

# Conflicts:
#	simba/sandbox/unsupervised/cluster_frequentist_stats.py

simba/mixins/statistics_mixin.py

@@ -18,13 +18,15 @@
                    types)
 from scipy import stats
 from scipy.stats.distributions import chi2
-from statsmodels.stats.libqsturng import psturng
-from statsmodels.stats.multicomp import pairwise_tukeyhsd
 from sklearn.covariance import EllipticEnvelope
 from sklearn.ensemble import IsolationForest
+from statsmodels.stats.libqsturng import psturng
+from statsmodels.stats.multicomp import pairwise_tukeyhsd
 
 from simba.mixins.feature_extraction_mixin import FeatureExtractionMixin
-from simba.utils.checks import (check_float, check_int, check_str, check_valid_array, check_valid_dataframe, check_valid_lst)
+from simba.utils.checks import (check_float, check_int, check_str,
+                                check_valid_array, check_valid_dataframe,
+                                check_valid_lst)
 from simba.utils.data import bucket_data, fast_mean_rank
 from simba.utils.enums import Formats, Options
 from simba.utils.errors import CountError, InvalidInputError

simba/sandbox/bg_remover.py

@@ -4,17 +4,20 @@
 
 import cv2
 import numpy as np
+
 try:
     from typing import Literal
 except:
     from typing_extensions import Literal
 
-from simba.utils.checks import (check_file_exist_and_readable,check_if_dir_exists)
+from simba.utils.checks import (check_file_exist_and_readable,
+                                check_if_dir_exists)
 from simba.utils.enums import Formats
 from simba.utils.printing import SimbaTimer, stdout_success
-from simba.utils.read_write import (get_fn_ext, get_video_meta_data)
+from simba.utils.read_write import get_fn_ext, get_video_meta_data
 from simba.video_processors.video_processing import create_average_frm
 
+
 def video_bg_subtraction(video_path: Union[str, os.PathLike],
                          bg_video_path: Optional[Union[str, os.PathLike]] = None,
                          bg_start_frm: Optional[int] = None,

simba/sandbox/bout_aggregator.py

@@ -1,17 +1,22 @@
 import os
 from copy import deepcopy
-from typing import Literal, Optional, List, Union
+from typing import List, Literal, Optional, Union
+
 try:
     from typing import Literal
 except:
     from typing_extensions import Literal
+
 import pandas as pd
-from simba.utils.checks import check_valid_lst, check_int, check_str, check_valid_dataframe, check_instance
-from simba.utils.read_write import find_core_cnt, read_video_info
-from simba.utils.printing import SimbaTimer
-from simba.utils.enums import Formats
+
+from simba.utils.checks import (check_instance, check_int, check_str,
+                                check_valid_dataframe, check_valid_lst)
 from simba.utils.data import detect_bouts, read_df
+from simba.utils.enums import Formats
 from simba.utils.errors import InvalidInputError
+from simba.utils.printing import SimbaTimer
+from simba.utils.read_write import find_core_cnt, read_video_info
+
 
 def video_bout_aggregator(data: Union[str, os.PathLike, pd.DataFrame],
                           clfs: List[str],

simba/sandbox/direction_reversals.py

@@ -1,7 +1,6 @@
 import numpy as np
 
 
-
 def direction_switches(x: np.ndarray, switch_degree: int = 180):
 
     idx = 0

simba/sandbox/felzenszwalb.py

@@ -1,16 +1,20 @@
-from typing import Union, Optional, List, Tuple
-import os
-import numpy as np
-import cv2
-
-from simba.utils.read_write import (get_video_meta_data,  find_core_cnt, get_fn_ext, read_frm_of_video, concatenate_videos_in_folder)
+import functools
 #from simba.utils.checks import
 import multiprocessing
-import functools
-from simba.utils.enums import Defaults, Formats
+import os
+from typing import List, Optional, Tuple, Union
+
+import cv2
+import numpy as np
 from skimage.color import label2rgb
 from skimage.segmentation import felzenszwalb
+
+from simba.utils.enums import Defaults, Formats
 from simba.utils.printing import SimbaTimer
+from simba.utils.read_write import (concatenate_videos_in_folder,
+                                    find_core_cnt, get_fn_ext,
+                                    get_video_meta_data, read_frm_of_video)
+
 
 def _felzenszwalb_helper(frm_range: Tuple[int, List[int]],
                          scale: int,

simba/sandbox/gibbs_sampler.py

@@ -1,10 +1,13 @@
 import os
-from typing import Union, Tuple
+from typing import Tuple, Union
+
 import numpy as np
 import pandas as pd
 
+from simba.utils.checks import (check_float, check_if_dir_exists, check_int,
+                                check_valid_array)
 from simba.utils.printing import SimbaTimer, stdout_success
-from simba.utils.checks import check_valid_array, check_float, check_int, check_if_dir_exists
+
 
 class GibbSampler():
     def __init__(self,

simba/sandbox/img_edge_distance_flexible.py

@@ -1,7 +1,6 @@
 import numpy as np
 
 
-
 def img_edge_distances_flexible(data: np.ndarray,
                                 edge_distances: np.ndarray,
                                 pixels_per_mm: float,

simba/sandbox/preferred_turning_direction.py

@@ -1,9 +1,10 @@
 import numpy as np
+
+from simba.mixins.circular_statistics import CircularStatisticsMixin
 from simba.utils.checks import check_valid_array
+from simba.utils.data import get_mode
 from simba.utils.enums import Formats
 from simba.utils.errors import InvalidInputError
-from simba.mixins.circular_statistics import CircularStatisticsMixin
-from simba.utils.data import get_mode
 
 
 def preferred_turning_direction(x: np.ndarray) -> int:

simba/sandbox/radial_dispersion.py

@@ -1,8 +1,10 @@
 import numpy as np
+
 from simba.mixins.statistics_mixin import Statistics
 from simba.utils.checks import check_valid_array
 from simba.utils.enums import Formats
 
+
 def radial_dispersion_index(x: np.ndarray, reference_point: np.ndarray) -> float:
     """
     Compute the Radial Dispersion Index (RDI) for a set of points relative to a reference point.

simba/sandbox/radial_eccentricity.py

@@ -1,8 +1,10 @@
 import numpy as np
+
 from simba.mixins.statistics_mixin import Statistics
 from simba.utils.checks import check_valid_array
 from simba.utils.enums import Formats
 
+
 def radial_eccentricity(x: np.ndarray, reference_point: np.ndarray):
     """
     Compute the radial eccentricity of a set of points relative to a reference point.

simba/sandbox/regression_errors.py

@@ -1,8 +1,11 @@
 from typing import Optional
+
 import numpy as np
-from simba.utils.checks import check_valid_array, check_float
+
+from simba.utils.checks import check_float, check_valid_array
 from simba.utils.enums import Formats
 
+
 def mean_absolute_percentage_error(y_true: np.ndarray,
                                    y_pred: np.ndarray,
                                    epsilon=1e-10,

simba/sandbox/sliding_descriptive_statistics_cuda.py

@@ -1,15 +1,21 @@
+from typing import Tuple
+
 import numpy as np
 from numba import cuda
-from typing import Tuple
+
 try:
     from typing import Literal
 except:
     from typing_extensions import Literal
-from simba.utils.checks import check_valid_array, check_valid_tuple, check_float
-from simba.utils.enums import Formats
-from simba.data_processors.cuda.utils import _cuda_mean
+
 import math
 
+from simba.data_processors.cuda.utils import _cuda_mean
+from simba.utils.checks import (check_float, check_valid_array,
+                                check_valid_tuple)
+from simba.utils.enums import Formats
+
+
 def _cuda_variance(x: np.ndarray):
     #mean = _cuda_mean(x=x)
     mean = np.mean(x)

simba/sandbox/sliding_preferred_turning_direction.py

@@ -1,9 +1,10 @@
 import numpy as np
-from simba.utils.checks import check_valid_array, check_float
-from simba.utils.enums import Formats
-from simba.utils.errors import InvalidInputError
+
 from simba.mixins.circular_statistics import CircularStatisticsMixin
+from simba.utils.checks import check_float, check_valid_array
 from simba.utils.data import get_mode
+from simba.utils.enums import Formats
+from simba.utils.errors import InvalidInputError
 
 
 def sliding_preferred_turning_direction(x: np.ndarray,

simba/sandbox/snap.py

@@ -1,6 +1,8 @@
 import numpy as np
+
 from simba.utils.read_write import read_df
 
+
 def snap(x: np.ndarray, sample_rate: float, pixels_per_mm: float):
     """
     :example: