mirror of
https://github.com/wassname/scikit-image.git
synced 2026-07-08 02:25:14 +08:00
Vighnesh Birodkar
31 lines
677 B
Python
31 lines
677 B
Python
import networkx as nx
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import numpy as np
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from scipy import sparse
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def DW_matrix(graph):
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W = nx.to_scipy_sparse_matrix(graph, format='csc')
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entries = W.sum(0)
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D = sparse.dia_matrix((entries, 0), shape=W.shape).tocsc()
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return D, W
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def ncut_cost(mask, D, W):
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mask = np.array(mask)
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mask_list = [np.logical_xor(mask[i], mask) for i in range(mask.shape[0])]
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mask_array = np.array(mask_list)
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cut = float(W[mask_array].sum() / 2.0)
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assoc_a = D.data[mask].sum()
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assoc_b = D.data[np.logical_not(mask)].sum()
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return (cut / assoc_a) + (cut / assoc_b)
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def normalize(a):
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mi = a.min()
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mx = a.max()
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return (a - mi) / (mx - mi)
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