pycellfit package

Submodules

pycellfit.utils module

Top-level utility functions for pycellfit module.

pycellfit.utils.read_segmented_image(file_name, visualize=False)

Displays the segmented image using matplotlib

Parameters:

• file_name (str) – file name of a segmented image in .tif format
• visualize (bool) – if true, then image will be plotted using matplotlib.pyplot

Raises:

TypeError – only accepts tif/tiff files as input

Returns:

array of pixel values

Return type:

numpy.ndarray

pycellfit.junction module

class pycellfit.junction.Junction(coordinates, cells_set)

Bases: object

add_edge(edge_label)

Adds edge label to set of edge labels

cell_labels

coordinates

degree

edges

set of labels of edges connected to this node

id_iter = count(0)

plot(label=False)

plot_unit_vectors()

remove_edge(edge_label)

Remove an edge and tension vector connected to this node

Parameters:

• self –
• edge_label –

tension_vectors

returns list of Tension vectors connected to this node

x

y

pycellfit.edge module

class pycellfit.edge.Edge(start_node, end_node, intermediate_points, cells)

Bases: object

angular_position(coordinates)

given a (x,y) coordinate, the angular position in radians from 0 to 2*pi around the fit circle is returned

Parameters:coordinates – Returns:

calculate_edge_points()

center

circle_fit()

corresponding_tension_vector

cw_around_circle

true if the edge (start_node to end_node) goes clockwise around the fit circle, false if ccw

Returns:

end_node

end_tangent_angle(method='chord')

id_iter = count(0)

length

linear

location

map_unit_vectors_to_junctions()

outside(background)

plot(label=False)

plot_circle()

plot_tangent(c='y')

radius

split_line_multiple(length=None, n_pieces=None)

Splits a ogr wkbLineString into multiple sub-strings, either of a specified <<length>> or a specified <<n_pieces>>.

line should be an ogr LineString Geometry Length should be a float or int. n_pieces should be an int. Either length or n_pieces should be specified.

Returns a list of ogr wkbLineString Geometries.

split_line_single(line, length)

Returns two ogr line geometries, one which is the first length <<length>> of <<line>>, and one one which is the remainder.

line should be a ogr LineString Geometry. length should be an integer or float.

start_node

start_tangent_angle(method='chord')

xc

yc

pycellfit.edge.collinear(points, epsilon=0.01)

determine if three points are collinear

Parameters:

• epsilon –
• points (list of 3 2-member tuples) – list of 3 point tuples that might be collinear

Returns:

boolean to tell if the points are collinear or not

Return type:

bool

pycellfit.edge.distance(p1, p2)

pycellfit.tension_vector module

pycellfit.cell module

class pycellfit.cell.Cell(pixel_value)

Bases: object

add_edge_point(edge_point, neighboring_cell_label)

approximate_cell_center()

approximates the coordinates of the center of the cell by averaging the coordinates of points on the perimeter (edge) of the cell

Returns:approximate center of the cell Return type:tuple

generate_maze(neighboring_cell_label)

label

the label of a Cell is it’s unique pixel value. It is assigned when the Cell object is created.

Returns:

make_edges(master_set)

neighboring_cell_labels

number_of_edge_points

returns the number of edge points in edge_point_list

Returns:number of edge points

plot()

pycellfit.mesh module

class pycellfit.mesh.Mesh(array_of_pixels)

Bases: object

add_cell(cell_pixel_value)

add_edge_points_and_junctions(array_of_pixels)

circle_fit_all_edges()

find_cells_from_array()

generate_mesh(average_nodes_per_edge=4)

make_edges_for_all_cells()

number_of_cells

returns the number of cells in the mesh

Returns:number of cells in mesh Return type:int

number_of_edges

returns the number of edges in the mesh

Returns:number of edges in the mesh Return type:int

number_of_junctions

returns the number of junctions in the mesh

Returns:number of junctions in the mesh Return type:int

number_of_quad_junctions

returns the number of quad junctions in the mesh

Returns:number of edges in the mesh Return type:int

number_of_triple_junctions

counts and outputs the number of triple junctions in the mesh

:return number of triple junctions in mesh :rtype: int

plot()

plot_tensions()

remove_cell(cell_pixel_value)

solve_tensions()

solve_tensions_new()

solve_tensions_new2()

pycellfit.constrained_circle_fit module

pycellfit.circle_fit_helpers module

pycellfit.segmentation_transform module

functions to convert between watershed and skeleton segmented images

pycellfit.segmentation_transform.skeleton_to_watershed(skeleton_image_array, region_value=0, boundary_value=255, keep_boundaries=False)

converts a segmented skeleton image (all regions are same value with region boundaries being a second value) to a watershed segmented image (each region has a unique value and there are no boundary pixels, background region has value of zero)

Parameters:

• skeleton_image_array (np.ndarray) – 2D numpy array with pixel values of a skeleton segmented image
• region_value (float) – value of pixels in regions in skeleton_segmented images (default is 0)
• boundary_value (float) – value of boundary pixels of regions in skeleton_segmented images (default is 255)
• keep_boundaries (bool) – if True, watershed image will keep boundaries in returned result

Returns:

watershed_image_array

Rtype watershed_image_array:  

np.ndarray

pycellfit.segmentation_transform.watershed_to_skeleton(watershed_image_array, region_value=0, boundary_value=255)

converts a watershed segmented image (no boundaries between regions and each region has a different pixel value, background region has value of zero) to a skeleton segmented image (each region has the same pixel value and are separated by boundaries of a second value)

Parameters:

• watershed_image_array (numpy.ndarray) – 2D numpy array with pixel values of a watershed segmented image
• region_value (float) – desired value of all regions in the output (skeleton segmented) array
• boundary_value (float) – desired value of boundary pixels in the output (skeleton segmented) array

Returns:

skeleton_image_array

Rtype skeleton_image_array:  

np.ndarray

pycellfit.segmentation_transform_utils module

pycellfit.segmentation_transform_utils.fill_region(array_of_pixels, position, new_value)

fills a region of a 2D numpy array with the same value

Parameters:

• array_of_pixels (np.ndarray) – 2D numpy array of all pixel values
• position (tuple) – tuple with (row, col) location of pixel in the region to modify
• new_value (float) – new value for pixel at position and all pixels in same region

Returns:

None

pycellfit.segmentation_transform_utils.pad_with(vector, pad_width, iaxis, kwargs)

helper function that is called by np.pad to surround a nparray with a constant value Example: [[0,0],[0,0]] becomes [[-1,-1,-1, -1],[-1, 0, 0, -1],[-1, 0, 0, -1],[-1,-1,-1, -1]]

Module contents