


"""simple docstring"""







from __future__ import annotations

import random

# Adjacency list representation of this graph:
# https://en.wikipedia.org/wiki/File:Single_run_of_Karger%E2%80%99s_Mincut_algorithm.svg
lowerCamelCase_     :     Any    		=						{
    '1': ['2', '3', '4', '5'],
    '2': ['1', '3', '4', '5'],
    '3': ['1', '2', '4', '5', '10'],
    '4': ['1', '2', '3', '5', '6'],
    '5': ['1', '2', '3', '4', '7'],
    '6': ['7', '8', '9', '10', '4'],
    '7': ['6', '8', '9', '10', '5'],
    '8': ['6', '7', '9', '10'],
    '9': ['6', '7', '8', '10'],
    '10': ['6', '7', '8', '9', '3'],
}
def _A		(		lowercase	):







				"""simple docstring"""
				a					={node: {node} for node in graph}

				a					={node: graph[node][:] for node in graph}

				while len(_A	) > 2:
								# Choose a random edge.
								a					=random.choice(list(graph_copy.keys()	)	)
								a					=random.choice(graph_copy[u]	)

								# Contract edge (u, v) to new node uv
								a					=u + v
								a					=list(set(graph_copy[u] + graph_copy[v]	)	)
								uv_neighbors.remove(_A	)
								uv_neighbors.remove(_A	)
								a					=uv_neighbors
								for neighbor in uv_neighbors:
												graph_copy[neighbor].append(_A	)

								a					=set(contracted_nodes[u].union(contracted_nodes[v]	)	)

								# Remove nodes u and v.
								del graph_copy[u]
								del graph_copy[v]
								for neighbor in uv_neighbors:
												if u in graph_copy[neighbor]:
																graph_copy[neighbor].remove(_A	)
												if v in graph_copy[neighbor]:
																graph_copy[neighbor].remove(_A	)

    # Find cutset.
				a					=[contracted_nodes[node] for node in graph_copy]
				return {
				    (node, neighbor)
				    for node in groups[0]
				    for neighbor in graph[node]
				    if neighbor in groups[1]
				}


if __name__ == "__main__":
							print(partition_graph(TEST_GRAPH))



"""simple docstring"""







from cva import destroyAllWindows, imread, imshow, waitKey
def _A		(		lowercase ,					lowercase	):







    """simple docstring"""
    a	,   a					=img.shape[0], img.shape[1]

    def to_grayscale(lowercase ,					lowercase ,					lowercase	):
        return 0.2126 * red + 0.587 * green + 0.114 * blue

    def normalize(lowercase	):
        return min(lowercase ,					2_55	)

    for i in range(lowercase	):
        for j in range(lowercase	):
            a					=int(to_grayscale(*img[i][j]	)	)
            a					=[
                normalize(lowercase	),
                normalize(greyscale + factor	),
                normalize(greyscale + 2 * factor	),
            ]

    return img


if __name__ == "__main__":
       # read original image
       lowerCamelCase_     :     Any    		=						{
           percentage: imread("""image_data/lena.jpg""", 1) for percentage in (1_0, 2_0, 3_0, 4_0)
       }

       for percentage, img in images.items():
              make_sepia(img, percentage)

       for percentage, img in images.items():
              imshow(F'Original image with sepia (factor: {percentage})', img)

       waitKey(0)
       destroyAllWindows()