Function fill_labeled_holes has a Cognitive Complexity of 18 (exceeds 5 allowed). Consider refactoring.

Open

def fill_labeled_holes(labels, mask=None, size_fn=None):
    """Fill all background pixels that are holes inside the foreground
 
    A pixel is a hole inside a foreground object if
    

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Function table_lookup has a Cognitive Complexity of 17 (exceeds 5 allowed). Consider refactoring.

Open

def table_lookup(image, table, border_value, iterations=None):
    """Perform a morphological transform on an image, directed by its neighbors
    
    image - a binary image
    table - a 512-element table giving the transform of each pixel given

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Function euler_number has 56 lines of code (exceeds 25 allowed). Consider refactoring.

Open

def euler_number(labels, indexes=None):
    """Calculate the Euler number of each label
    
    labels - a label matrix
    indexes - the indexes of the labels to measure or None to

Function feret_diameter has 53 lines of code (exceeds 25 allowed). Consider refactoring.

Open

def feret_diameter(chulls, counts, indexes):
    """Return the minimum and maximum Feret diameter for each object
    
    This function takes the convex hull data, as generated by convex_hull
    and returns the minimum and maximum Feret diameter for each convex hull.

Function get_mog_threshold has a Cognitive Complexity of 16 (exceeds 5 allowed). Consider refactoring.

Open

def get_mog_threshold(image, mask=None, object_fraction=0.2):
    """Compute a background using a mixture of gaussians
    
    This function finds a suitable
    threshold for the input image Block. It assumes that the pixels in the

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Function convex_hull_transform has a Cognitive Complexity of 16 (exceeds 5 allowed). Consider refactoring.

Open

def convex_hull_transform(
    image, levels=256, mask=None, chunksize=CONVEX_HULL_CHUNKSIZE, pass_cutoff=16
):
    """Perform the convex hull transform of this image

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Function draw_line has a Cognitive Complexity of 16 (exceeds 5 allowed). Consider refactoring.

Open

def draw_line(labels, pt0, pt1, value=1):
    """Draw a line between two points
    
    pt0, pt1 are in i,j format which is the reverse of x,y format
    Uses the Bresenham algorithm

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Function stretch has a Cognitive Complexity of 15 (exceeds 5 allowed). Consider refactoring.

Open

def stretch(image, mask=None):
    """Normalize an image to make the minimum zero and maximum one

    image - pixel data to be normalized
    mask  - optional mask of relevant pixels. None = don't mask

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Function prcntiles has a Cognitive Complexity of 14 (exceeds 5 allowed). Consider refactoring.

Open

def prcntiles(x, percents):
    """Equivalent to matlab prctile(x,p), uses linear interpolation."""
    x = np.array(x).flatten()
    listx = np.sort(x)
    xpcts = []

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Consider simplifying this complex logical expression.

Open

            value
            if (
                fn(i, 0, 0, 0)
                and fn(i, 1, 0, 1)
                and fn(i, 2, 0, 2)

Function convex_hull_ijv has 40 lines of code (exceeds 25 allowed). Consider refactoring.

Open

def convex_hull_ijv(pixel_labels, indexes, fast=True):
    """Return the convex hull for each label using an ijv labeling
    
    pixel_labels: the labeling of the pixels in i,j,v form where
                  i & j are the coordinates of a pixel and v is

Function get_otsu_threshold has a Cognitive Complexity of 13 (exceeds 5 allowed). Consider refactoring.

Open

def get_otsu_threshold(
    image,
    mask=None,
    two_class_otsu=True,
    use_weighted_variance=True,

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Function color_labels has a Cognitive Complexity of 13 (exceeds 5 allowed). Consider refactoring.

Open

def color_labels(labels, distance_transform=False):
    """Color a labels matrix so that no adjacent labels have the same color
    
    distance_transform - if true, distance transform the labels to find out
         which objects are closest to each other.

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Function get_outline_pts has 38 lines of code (exceeds 25 allowed). Consider refactoring.

Open

def get_outline_pts(labels, idxs):
    """Get the outline points of objects in clockwise order
    
    Given a labels matrix of contiguously-labeled objects, trace
    the exteriors of those objects to get the points of the outline

Function lapjv has 37 lines of code (exceeds 25 allowed). Consider refactoring.

Open

def lapjv(i, j, costs, wants_dual_variables=False, augmenting_row_reductions=2):
    """Sparse linear assignment solution using Jonker-Volgenant algorithm
    
    i,j - similarly-sized vectors that pair the object at index i[n] with
          the object at index j[j]

Function associate_by_distance has a Cognitive Complexity of 12 (exceeds 5 allowed). Consider refactoring.

Open

def associate_by_distance(labels_a, labels_b, distance):
    """Find the objects that are within a given distance of each other
    
    Given two labels matrices and a distance, find pairs of objects that
    are within the given distance of each other where the distance is

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Function automode has a Cognitive Complexity of 12 (exceeds 5 allowed). Consider refactoring.

Open

def automode(data):
    """Tries to guess if the image contains dark objects on a bright background (1)
or if the image contains bright objects on a dark background (-1),
or if it contains both dark and bright objects on a gray background (0)."""

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Function bilateral_filter has 34 lines of code (exceeds 25 allowed). Consider refactoring.

Open

def bilateral_filter(
    image, mask, sigma_spatial, sigma_range, sampling_spatial=None, sampling_range=None
):
    """Bilateral filter of an image

Function calculate_convex_hull_areas has 34 lines of code (exceeds 25 allowed). Consider refactoring.

Open

def calculate_convex_hull_areas(labels, indexes=None):
    """Calulculate the area of the convex hull of each labeled object
    
    labels - a label matrix
    indexes - None: calculate convex hull area over entire image

Function pairwise_permutations has 34 lines of code (exceeds 25 allowed). Consider refactoring.

Open

def pairwise_permutations(i, j):
    """Return all permutations of a set of groups
    
    This routine takes two vectors:
    i - the label of each group