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https://github.com/wassname/scikit-image.git
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Nelle Varoquaux
142 lines
5.0 KiB
Python
142 lines
5.0 KiB
Python
import numpy as np
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from numpy.testing import *
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import skimage.graph.mcp as mcp
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a = np.ones((8,8), dtype=np.float32)
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a[1:-1, 1] = 0
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a[1, 1:-1] = 0
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## array([[ 1., 1., 1., 1., 1., 1., 1., 1.],
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## [ 1., 0., 0., 0., 0., 0., 0., 1.],
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## [ 1., 0., 1., 1., 1., 1., 1., 1.],
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## [ 1., 0., 1., 1., 1., 1., 1., 1.],
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## [ 1., 0., 1., 1., 1., 1., 1., 1.],
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## [ 1., 0., 1., 1., 1., 1., 1., 1.],
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## [ 1., 0., 1., 1., 1., 1., 1., 1.],
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## [ 1., 1., 1., 1., 1., 1., 1., 1.]], dtype=float32)
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def test_basic():
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m = mcp.MCP(a, fully_connected=True)
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costs, traceback = m.find_costs([(1,6)])
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return_path = m.traceback((7, 2))
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assert_array_equal(costs,
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[[ 1., 1., 1., 1., 1., 1., 1., 1.],
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[ 1., 0., 0., 0., 0., 0., 0., 1.],
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[ 1., 0., 1., 1., 1., 1., 1., 1.],
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[ 1., 0., 1., 2., 2., 2., 2., 2.],
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[ 1., 0., 1., 2., 3., 3., 3., 3.],
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[ 1., 0., 1., 2., 3., 4., 4., 4.],
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[ 1., 0., 1., 2., 3., 4., 5., 5.],
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[ 1., 1., 1., 2., 3., 4., 5., 6.]])
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assert_array_equal(return_path,
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[(1, 6),
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(1, 5),
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(1, 4),
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(1, 3),
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(1, 2),
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(2, 1),
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(3, 1),
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(4, 1),
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(5, 1),
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(6, 1),
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(7, 2)])
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def test_neg_inf():
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expected_costs = np.where(a==1, np.inf, 0)
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expected_path = [(1, 6),
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(1, 5),
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(1, 4),
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(1, 3),
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(1, 2),
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(2, 1),
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(3, 1),
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(4, 1),
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(5, 1),
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(6, 1)]
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test_neg = np.where(a==1, -1, 0)
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test_inf = np.where(a==1, np.inf, 0)
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m = mcp.MCP(test_neg, fully_connected=True)
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costs, traceback = m.find_costs([(1, 6)])
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return_path = m.traceback((6, 1))
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assert_array_equal(costs, expected_costs)
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assert_array_equal(return_path, expected_path)
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m = mcp.MCP(test_inf, fully_connected=True)
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costs, traceback = m.find_costs([(1, 6)])
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return_path = m.traceback((6, 1))
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assert_array_equal(costs, expected_costs)
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assert_array_equal(return_path, expected_path)
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def test_route():
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return_path, cost = mcp.route_through_array(a, (1,6), (7,2), geometric=True)
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assert_almost_equal(cost, np.sqrt(2)/2)
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assert_array_equal(return_path,
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[(1, 6),
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(1, 5),
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(1, 4),
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(1, 3),
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(1, 2),
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(2, 1),
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(3, 1),
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(4, 1),
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(5, 1),
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(6, 1),
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(7, 2)])
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def test_no_diagonal():
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m = mcp.MCP(a, fully_connected=False)
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costs, traceback = m.find_costs([(1,6)])
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return_path = m.traceback((7, 2))
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assert_array_equal(costs,
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[[ 2., 1., 1., 1., 1., 1., 1., 2.],
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[ 1., 0., 0., 0., 0., 0., 0., 1.],
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[ 1., 0., 1., 1., 1., 1., 1., 2.],
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[ 1., 0., 1., 2., 2., 2., 2., 3.],
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[ 1., 0., 1., 2., 3., 3., 3., 4.],
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[ 1., 0., 1., 2., 3., 4., 4., 5.],
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[ 1., 0., 1., 2., 3., 4., 5., 6.],
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[ 2., 1., 2., 3., 4., 5., 6., 7.]])
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assert_array_equal(return_path,
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[(1, 6),
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(1, 5),
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(1, 4),
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(1, 3),
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(1, 2),
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(1, 1),
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(2, 1),
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(3, 1),
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(4, 1),
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(5, 1),
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(6, 1),
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(7, 1),
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(7, 2)])
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def test_crashing():
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for shape in [(100, 100), (5, 8, 13, 17)]:
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yield _test_random, shape
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def _test_random(shape):
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# Just tests for crashing -- not for correctness.
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np.random.seed(0)
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a = np.random.random(shape).astype(np.float32)
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starts = [[0]*len(shape), [-1]*len(shape),
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(np.random.random(len(shape))*shape).astype(int)]
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ends = [(np.random.random(len(shape))*shape).astype(int) for i in range(4)]
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m = mcp.MCP(a, fully_connected=True)
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costs, offsets = m.find_costs(starts)
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for point in [(np.random.random(len(shape))*shape).astype(int)
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for i in range(4)]:
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m.traceback(point)
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m._reset()
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m.find_costs(starts, ends)
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for end in ends:
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m.traceback(end)
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return a, costs, offsets
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if __name__ == "__main__":
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run_module_suite()
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