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Add conversion to list before padding, extend length of result #38

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Add conversion to list before padding, extend length of result #38

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c4c8953
Add conversion to list before padding, extend length of result to pad…
giuliabaldini Sep 21, 2020
5ed8f02
Fix tests by adding constraints in get cost function
giuliabaldini Sep 22, 2020
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6 changes: 3 additions & 3 deletions munkres.py
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Original file line number Diff line number Diff line change
Expand Up @@ -100,7 +100,7 @@ def pad_matrix(self, matrix: Matrix, pad_value: int=0) -> Matrix:
new_matrix = []
for row in matrix:
row_len = len(row)
new_row = row[:]
new_row = list(row[:])
if total_rows > row_len:
# Row too short. Pad it.
new_row += [pad_value] * (total_rows - row_len)
Expand Down Expand Up @@ -163,8 +163,8 @@ def compute(self, cost_matrix: Matrix) -> Sequence[Tuple[int, int]]:

# Look for the starred columns
results = []
for i in range(self.original_length):
for j in range(self.original_width):
for i in range(self.n):
for j in range(self.n):
if self.marked[i][j] == 1:
results += [(i, j)]

Expand Down
89 changes: 64 additions & 25 deletions test/test_munkres.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,9 +4,11 @@

m = Munkres()


def _get_cost(matrix):
indices = m.compute(matrix)
return sum([matrix[row][column] for row, column in indices])
return sum([matrix[row][column] for row, column in indices if row < len(matrix) and column < len(matrix[0])])


def test_documented_example():
'''
Expand All @@ -18,6 +20,7 @@ def test_documented_example():
cost = _get_cost(matrix)
assert cost == 12


def float_example():
'''
Test a matrix with float values
Expand All @@ -28,6 +31,7 @@ def float_example():
cost = _get_cost(matrix)
assert cost == pytest.approx(13.5)


def test_5_x_5():
matrix = [[12, 9, 27, 10, 23],
[7, 13, 13, 30, 19],
Expand All @@ -37,6 +41,7 @@ def test_5_x_5():
cost = _get_cost(matrix)
assert cost == 51


def test_5_x_5_float():
matrix = [[12.01, 9.02, 27.03, 10.04, 23.05],
[7.06, 13.07, 13.08, 30.09, 19.1],
Expand All @@ -61,6 +66,7 @@ def test_10_x_10():
cost = _get_cost(matrix)
assert cost == 66


def test_10_x_10_float():
matrix = [[37.001, 34.002, 29.003, 26.004, 19.005, 8.006, 9.007, 23.008, 19.009, 29.01],
[9.011, 28.012, 20.013, 8.014, 18.015, 20.016, 14.017, 33.018, 23.019, 14.02],
Expand All @@ -75,6 +81,7 @@ def test_10_x_10_float():
cost = _get_cost(matrix)
assert cost == pytest.approx(66.505)


def test_20_x_20():
matrix = [[5, 4, 3, 9, 8, 9, 3, 5, 6, 9, 4, 10, 3, 5, 6, 6, 1, 8, 10, 2],
[10, 9, 9, 2, 8, 3, 9, 9, 10, 1, 7, 10, 8, 4, 2, 1, 4, 8, 4, 8],
Expand All @@ -99,27 +106,49 @@ def test_20_x_20():
cost = _get_cost(matrix)
assert cost == 22


def test_20_x_20_float():
matrix = [[5.0001, 4.0002, 3.0003, 9.0004, 8.0005, 9.0006, 3.0007, 5.0008, 6.0009, 9.001, 4.0011, 10.0012, 3.0013, 5.0014, 6.0015, 6.0016, 1.0017, 8.0018, 10.0019, 2.002],
[10.0021, 9.0022, 9.0023, 2.0024, 8.0025, 3.0026, 9.0027, 9.0028, 10.0029, 1.003, 7.0031, 10.0032, 8.0033, 4.0034, 2.0035, 1.0036, 4.0037, 8.0038, 4.0039, 8.004],
[10.0041, 4.0042, 4.0043, 3.0044, 1.0045, 3.0046, 5.0047, 10.0048, 6.0049, 8.005, 6.0051, 8.0052, 4.0053, 10.0054, 7.0055, 2.0056, 4.0057, 5.0058, 1.0059, 8.006],
[2.0061, 1.0062, 4.0063, 2.0064, 3.0065, 9.0066, 3.0067, 4.0068, 7.0069, 3.007, 4.0071, 1.0072, 3.0073, 2.0074, 9.0075, 8.0076, 6.0077, 5.0078, 7.0079, 8.008],
[3.0081, 4.0082, 4.0083, 1.0084, 4.0085, 10.0086, 1.0087, 2.0088, 6.0089, 4.009, 5.0091, 10.0092, 2.0093, 2.0094, 3.0095, 9.0096, 10.0097, 9.0098, 9.0099, 10.01],
[1.0101, 10.0102, 1.0103, 8.0104, 1.0105, 3.0106, 1.0107, 7.0108, 1.0109, 1.011, 2.0111, 1.0112, 2.0113, 6.0114, 3.0115, 3.0116, 4.0117, 4.0118, 8.0119, 6.012],
[1.0121, 8.0122, 7.0123, 10.0124, 10.0125, 3.0126, 4.0127, 6.0128, 1.0129, 6.013, 6.0131, 4.0132, 9.0133, 6.0134, 9.0135, 6.0136, 4.0137, 5.0138, 4.0139, 7.014],
[8.0141, 10.0142, 3.0143, 9.0144, 4.0145, 9.0146, 3.0147, 3.0148, 4.0149, 6.015, 4.0151, 2.0152, 6.0153, 7.0154, 7.0155, 4.0156, 4.0157, 3.0158, 4.0159, 7.016],
[1.0161, 3.0162, 8.0163, 2.0164, 6.0165, 9.0166, 2.0167, 7.0168, 4.0169, 8.017, 10.0171, 8.0172, 10.0173, 5.0174, 1.0175, 3.0176, 10.0177, 10.0178, 2.0179, 9.018],
[2.0181, 4.0182, 1.0183, 9.0184, 2.0185, 9.0186, 7.0187, 8.0188, 2.0189, 1.019, 4.0191, 10.0192, 5.0193, 2.0194, 7.0195, 6.0196, 5.0197, 7.0198, 2.0199, 6.02],
[4.0201, 5.0202, 1.0203, 4.0204, 2.0205, 3.0206, 3.0207, 4.0208, 1.0209, 8.021, 8.0211, 2.0212, 6.0213, 9.0214, 5.0215, 9.0216, 6.0217, 3.0218, 9.0219, 3.022],
[3.0221, 1.0222, 1.0223, 8.0224, 6.0225, 8.0226, 8.0227, 7.0228, 9.0229, 3.023, 2.0231, 1.0232, 8.0233, 2.0234, 4.0235, 7.0236, 3.0237, 1.0238, 2.0239, 4.024],
[5.0241, 9.0242, 8.0243, 6.0244, 10.0245, 4.0246, 10.0247, 3.0248, 4.0249, 10.025, 10.0251, 10.0252, 1.0253, 7.0254, 8.0255, 8.0256, 7.0257, 7.0258, 8.0259, 8.026],
[1.0261, 4.0262, 6.0263, 1.0264, 6.0265, 1.0266, 2.0267, 10.0268, 5.0269, 10.027, 2.0271, 6.0272, 2.0273, 4.0274, 5.0275, 5.0276, 3.0277, 5.0278, 1.0279, 5.028],
[5.0281, 6.0282, 9.0283, 10.0284, 6.0285, 6.0286, 10.0287, 6.0288, 4.0289, 1.029, 5.0291, 3.0292, 9.0293, 5.0294, 2.0295, 10.0296, 9.0297, 9.0298, 5.0299, 1.03],
[10.0301, 9.0302, 4.0303, 6.0304, 9.0305, 5.0306, 3.0307, 7.0308, 10.0309, 1.031, 6.0311, 8, 1.0312, 1.0313, 10.0314, 9.0315, 5.0316, 7.0317, 7.0318, 5.0319, 1.032],
[2.0321, 6.0322, 6.0323, 6.0324, 6.0325, 2.0326, 9.0327, 4.0328, 7.0329, 5.033, 3.0331, 2.0332, 10.0333, 3.0334, 4.0335, 5.0336, 10.0337, 9.0338, 1.0339, 7.034],
[5.0341, 2.0342, 4.0343, 9.0344, 8.0345, 4.0346, 8.0347, 2.0348, 4.0349, 1.035, 3.0351, 7.0352, 6.0353, 8.0354, 1.0355, 6.0356, 8.0357, 8.0358, 10.0359, 10.036],
[9.0361, 6.0362, 3.0363, 1.0364, 8.0365, 5.0366, 7.0367, 8.0368, 7.0369, 2.037, 1.0371, 8.0372, 2.0373, 8.0374, 3.0375, 7.0376, 4.0377, 8.0378, 7.0379, 7.038],
[8.0381, 4.0382, 4.0383, 9.0384, 7.0385, 10.0386, 6.0387, 2.0388, 1.0389, 5.039, 8.0391, 5.0392, 1.0393, 1.0394, 1.0395, 9.0396, 1.0397, 3.0398, 5.0399, 3.04]]
matrix = [
[5.0001, 4.0002, 3.0003, 9.0004, 8.0005, 9.0006, 3.0007, 5.0008, 6.0009, 9.001, 4.0011, 10.0012, 3.0013, 5.0014,
6.0015, 6.0016, 1.0017, 8.0018, 10.0019, 2.002],
[10.0021, 9.0022, 9.0023, 2.0024, 8.0025, 3.0026, 9.0027, 9.0028, 10.0029, 1.003, 7.0031, 10.0032, 8.0033,
4.0034, 2.0035, 1.0036, 4.0037, 8.0038, 4.0039, 8.004],
[10.0041, 4.0042, 4.0043, 3.0044, 1.0045, 3.0046, 5.0047, 10.0048, 6.0049, 8.005, 6.0051, 8.0052, 4.0053,
10.0054, 7.0055, 2.0056, 4.0057, 5.0058, 1.0059, 8.006],
[2.0061, 1.0062, 4.0063, 2.0064, 3.0065, 9.0066, 3.0067, 4.0068, 7.0069, 3.007, 4.0071, 1.0072, 3.0073, 2.0074,
9.0075, 8.0076, 6.0077, 5.0078, 7.0079, 8.008],
[3.0081, 4.0082, 4.0083, 1.0084, 4.0085, 10.0086, 1.0087, 2.0088, 6.0089, 4.009, 5.0091, 10.0092, 2.0093,
2.0094, 3.0095, 9.0096, 10.0097, 9.0098, 9.0099, 10.01],
[1.0101, 10.0102, 1.0103, 8.0104, 1.0105, 3.0106, 1.0107, 7.0108, 1.0109, 1.011, 2.0111, 1.0112, 2.0113, 6.0114,
3.0115, 3.0116, 4.0117, 4.0118, 8.0119, 6.012],
[1.0121, 8.0122, 7.0123, 10.0124, 10.0125, 3.0126, 4.0127, 6.0128, 1.0129, 6.013, 6.0131, 4.0132, 9.0133,
6.0134, 9.0135, 6.0136, 4.0137, 5.0138, 4.0139, 7.014],
[8.0141, 10.0142, 3.0143, 9.0144, 4.0145, 9.0146, 3.0147, 3.0148, 4.0149, 6.015, 4.0151, 2.0152, 6.0153, 7.0154,
7.0155, 4.0156, 4.0157, 3.0158, 4.0159, 7.016],
[1.0161, 3.0162, 8.0163, 2.0164, 6.0165, 9.0166, 2.0167, 7.0168, 4.0169, 8.017, 10.0171, 8.0172, 10.0173,
5.0174, 1.0175, 3.0176, 10.0177, 10.0178, 2.0179, 9.018],
[2.0181, 4.0182, 1.0183, 9.0184, 2.0185, 9.0186, 7.0187, 8.0188, 2.0189, 1.019, 4.0191, 10.0192, 5.0193, 2.0194,
7.0195, 6.0196, 5.0197, 7.0198, 2.0199, 6.02],
[4.0201, 5.0202, 1.0203, 4.0204, 2.0205, 3.0206, 3.0207, 4.0208, 1.0209, 8.021, 8.0211, 2.0212, 6.0213, 9.0214,
5.0215, 9.0216, 6.0217, 3.0218, 9.0219, 3.022],
[3.0221, 1.0222, 1.0223, 8.0224, 6.0225, 8.0226, 8.0227, 7.0228, 9.0229, 3.023, 2.0231, 1.0232, 8.0233, 2.0234,
4.0235, 7.0236, 3.0237, 1.0238, 2.0239, 4.024],
[5.0241, 9.0242, 8.0243, 6.0244, 10.0245, 4.0246, 10.0247, 3.0248, 4.0249, 10.025, 10.0251, 10.0252, 1.0253,
7.0254, 8.0255, 8.0256, 7.0257, 7.0258, 8.0259, 8.026],
[1.0261, 4.0262, 6.0263, 1.0264, 6.0265, 1.0266, 2.0267, 10.0268, 5.0269, 10.027, 2.0271, 6.0272, 2.0273,
4.0274, 5.0275, 5.0276, 3.0277, 5.0278, 1.0279, 5.028],
[5.0281, 6.0282, 9.0283, 10.0284, 6.0285, 6.0286, 10.0287, 6.0288, 4.0289, 1.029, 5.0291, 3.0292, 9.0293,
5.0294, 2.0295, 10.0296, 9.0297, 9.0298, 5.0299, 1.03],
[10.0301, 9.0302, 4.0303, 6.0304, 9.0305, 5.0306, 3.0307, 7.0308, 10.0309, 1.031, 6.0311, 8, 1.0312, 1.0313,
10.0314, 9.0315, 5.0316, 7.0317, 7.0318, 5.0319, 1.032],
[2.0321, 6.0322, 6.0323, 6.0324, 6.0325, 2.0326, 9.0327, 4.0328, 7.0329, 5.033, 3.0331, 2.0332, 10.0333, 3.0334,
4.0335, 5.0336, 10.0337, 9.0338, 1.0339, 7.034],
[5.0341, 2.0342, 4.0343, 9.0344, 8.0345, 4.0346, 8.0347, 2.0348, 4.0349, 1.035, 3.0351, 7.0352, 6.0353, 8.0354,
1.0355, 6.0356, 8.0357, 8.0358, 10.0359, 10.036],
[9.0361, 6.0362, 3.0363, 1.0364, 8.0365, 5.0366, 7.0367, 8.0368, 7.0369, 2.037, 1.0371, 8.0372, 2.0373, 8.0374,
3.0375, 7.0376, 4.0377, 8.0378, 7.0379, 7.038],
[8.0381, 4.0382, 4.0383, 9.0384, 7.0385, 10.0386, 6.0387, 2.0388, 1.0389, 5.039, 8.0391, 5.0392, 1.0393, 1.0394,
1.0395, 9.0396, 1.0397, 3.0398, 5.0399, 3.04]]
cost = _get_cost(matrix)
'''
Here, it becomes mandatory to set "places" argument, otherwise test might
Expand All @@ -128,20 +157,23 @@ def test_20_x_20_float():
'''
assert cost == pytest.approx(20.362, rel=1e-3)


def test_disallowed():
matrix = [[5, 9, DISALLOWED],
[10, DISALLOWED, 2],
[8, DISALLOWED, 4]]
cost = _get_cost(matrix)
assert cost == 19


def test_disallowed_float():
matrix = [[5.1, 9.2, DISALLOWED],
[10.3, DISALLOWED, 2.4],
[8.5, DISALLOWED, 4.6]]
cost = _get_cost(matrix)
assert cost == pytest.approx(20.1)


def test_profit():
profit_matrix = [[94, 66, 100, 18, 48],
[51, 63, 97, 79, 11],
Expand All @@ -156,6 +188,7 @@ def test_profit():
profit = sum([profit_matrix[row][column] for row, column in indices])
assert profit == 392


def test_profit_float():
profit_matrix = [[94.01, 66.02, 100.03, 18.04, 48.05],
[51.06, 63.07, 97.08, 79.09, 11.1],
Expand All @@ -170,6 +203,7 @@ def test_profit_float():
profit = sum([profit_matrix[row][column] for row, column in indices])
assert profit == pytest.approx(362.65)


def test_irregular():
matrix = [[12, 26, 17],
[49, 43, 36, 10, 5],
Expand All @@ -180,6 +214,7 @@ def test_irregular():
cost = _get_cost(matrix)
assert cost == 43


def test_irregular_float():
matrix = [[12.01, 26.02, 17.03],
[49.04, 43.05, 36.06, 10.07, 5.08],
Expand All @@ -190,6 +225,7 @@ def test_irregular_float():
cost = _get_cost(matrix)
assert cost == pytest.approx(43.42)


def test_rectangular():
matrix = [[34, 26, 17, 12],
[43, 43, 36, 10],
Expand All @@ -203,6 +239,7 @@ def test_rectangular():
assert padded_cost == cost
assert cost == 70


def test_rectangular_float():
matrix = [[34.01, 26.02, 17.03, 12.04],
[43.05, 43.06, 36.07, 10.08],
Expand All @@ -216,16 +253,18 @@ def test_rectangular_float():
assert padded_cost == pytest.approx(cost)
assert cost == pytest.approx(70.42)


def test_unsolvable():
with pytest.raises(UnsolvableMatrix):
matrix = [[5, 9, DISALLOWED],
[10, DISALLOWED, 2],
[DISALLOWED, DISALLOWED, DISALLOWED]]
[10, DISALLOWED, 2],
[DISALLOWED, DISALLOWED, DISALLOWED]]
m.compute(matrix)


def test_unsolvable_float():
with pytest.raises(UnsolvableMatrix):
matrix = [[5.1, 9.2, DISALLOWED],
[10.3, DISALLOWED, 2.4],
[DISALLOWED, DISALLOWED, DISALLOWED]]
[10.3, DISALLOWED, 2.4],
[DISALLOWED, DISALLOWED, DISALLOWED]]
m.compute(matrix)