IF YOU WOULD LIKE TO GET AN ACCOUNT, please write an email to s dot adaszewski at gmail dot com. User accounts are meant only to report issues and/or generate pull requests. This is a purpose-specific Git hosting for ADARED projects. Thank you for your understanding!
Você não pode selecionar mais de 25 tópicos Os tópicos devem começar com uma letra ou um número, podem incluir traços ('-') e podem ter até 35 caracteres.

test_data.py 4.1KB

4 anos atrás
4 anos atrás
4 anos atrás
4 anos atrás
4 anos atrás
4 anos atrás
4 anos atrás
4 anos atrás
4 anos atrás
4 anos atrás
4 anos atrás
4 anos atrás
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143
  1. #
  2. # Copyright (C) Stanislaw Adaszewski, 2020
  3. # License: GPLv3
  4. #
  5. from icosagon.data import Data, \
  6. _equal, \
  7. RelationFamily
  8. from icosagon.decode import DEDICOMDecoder
  9. import torch
  10. import pytest
  11. def test_equal_01():
  12. x = torch.rand((10, 10))
  13. y = torch.rand((10, 10)).round().to_sparse()
  14. print('x == x ?')
  15. assert torch.all(_equal(x, x))
  16. print('y == y ?')
  17. assert torch.all(_equal(y, y))
  18. print('x == y ?')
  19. with pytest.raises(ValueError):
  20. _equal(x, y)
  21. print('y == z ?')
  22. z = torch.rand((10, 10)).round().to_sparse()
  23. assert not torch.all(_equal(y, z))
  24. def test_relation_family_01():
  25. d = Data()
  26. d.add_node_type('Whatever', 10)
  27. fam = RelationFamily(d, 'Dummy-Dummy', 0, 0, True, DEDICOMDecoder)
  28. with pytest.raises(ValueError):
  29. fam.add_relation_type('Dummy-Dummy', None, None)
  30. with pytest.raises(ValueError):
  31. fam.add_relation_type('Dummy-Dummy', 'bad-value', None)
  32. with pytest.raises(ValueError):
  33. fam.add_relation_type('Dummy-Dummy', None, 'bad-value')
  34. with pytest.raises(ValueError):
  35. fam.add_relation_type('Dummy-Dummy', torch.rand((5, 5)), None)
  36. with pytest.raises(ValueError):
  37. fam.add_relation_type('Dummy-Dummy', None, torch.rand((5, 5)))
  38. with pytest.raises(ValueError):
  39. fam.add_relation_type('Dummy-Dummy', torch.rand((10, 10)), torch.rand((10, 10)))
  40. with pytest.raises(ValueError):
  41. fam.add_relation_type('Dummy-Dummy', torch.rand((10, 10)), None)
  42. def test_relation_family_02():
  43. d = Data()
  44. d.add_node_type('A', 10)
  45. d.add_node_type('B', 5)
  46. fam = RelationFamily(d, 'A-B', 0, 1, True, DEDICOMDecoder)
  47. with pytest.raises(ValueError):
  48. fam.add_relation_type('A-B', torch.rand((10, 5)).round(),
  49. torch.rand((5, 10)).round())
  50. def test_relation_family_03():
  51. d = Data()
  52. d.add_node_type('A', 10)
  53. d.add_node_type('B', 5)
  54. fam = RelationFamily(d, 'A-B', 0, 1, True, DEDICOMDecoder)
  55. fam.add_relation_type('A-B', torch.rand((10, 5)).round())
  56. assert torch.all(fam.relation_types[0].adjacency_matrix.transpose(0, 1) == \
  57. fam.relation_types[0].adjacency_matrix_backward)
  58. def test_data_01():
  59. d = Data()
  60. d.add_node_type('Gene', 1000)
  61. d.add_node_type('Drug', 100)
  62. dummy_0 = torch.zeros((100, 1000))
  63. dummy_1 = torch.zeros((1000, 100))
  64. dummy_2 = torch.zeros((100, 100))
  65. dummy_3 = torch.zeros((1000, 1000))
  66. fam = d.add_relation_family('Drug-Gene', 1, 0, True)
  67. fam.add_relation_type('Target', dummy_0)
  68. fam = d.add_relation_family('Gene-Gene', 0, 0, True)
  69. fam.add_relation_type('Interaction', dummy_3)
  70. fam = d.add_relation_family('Drug-Drug', 1, 1, True)
  71. fam.add_relation_type('Side Effect: Nausea', dummy_2)
  72. fam.add_relation_type('Side Effect: Infertility', dummy_2)
  73. fam.add_relation_type('Side Effect: Death', dummy_2)
  74. print(d)
  75. def test_data_02():
  76. d = Data()
  77. d.add_node_type('Gene', 1000)
  78. d.add_node_type('Drug', 100)
  79. dummy_0 = torch.zeros((100, 1000))
  80. dummy_1 = torch.zeros((1000, 100))
  81. dummy_2 = torch.zeros((100, 100))
  82. dummy_3 = torch.zeros((1000, 1000))
  83. fam = d.add_relation_family('Drug-Gene', 1, 0, True)
  84. with pytest.raises(ValueError):
  85. fam.add_relation_type('Target', dummy_1)
  86. fam = d.add_relation_family('Gene-Gene', 0, 0, True)
  87. with pytest.raises(ValueError):
  88. fam.add_relation_type('Interaction', dummy_2)
  89. fam = d.add_relation_family('Drug-Drug', 1, 1, True)
  90. with pytest.raises(ValueError):
  91. fam.add_relation_type('Side Effect: Nausea', dummy_3)
  92. with pytest.raises(ValueError):
  93. fam.add_relation_type('Side Effect: Infertility', dummy_3)
  94. with pytest.raises(ValueError):
  95. fam.add_relation_type('Side Effect: Death', dummy_3)
  96. print(d)
  97. def test_data_03():
  98. d = Data()
  99. d.add_node_type('Gene', 1000)
  100. d.add_node_type('Drug', 100)
  101. fam = d.add_relation_family('Drug-Gene', 1, 0, True)
  102. with pytest.raises(ValueError):
  103. fam.add_relation_type('Target', None)
  104. print(d)