cd5bc9a558
* Update test_label_tensor.py * adding test --------- Co-authored-by: Dario Coscia <dariocoscia@Dario-Coscia.local>
115 lines
3.1 KiB
Python
115 lines
3.1 KiB
Python
import torch
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import pytest
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from pina import LabelTensor
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data = torch.rand((20, 3))
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labels = ['a', 'b', 'c']
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def test_constructor():
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LabelTensor(data, labels)
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def test_wrong_constructor():
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with pytest.raises(ValueError):
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LabelTensor(data, ['a', 'b'])
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def test_labels():
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tensor = LabelTensor(data, labels)
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assert isinstance(tensor, torch.Tensor)
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assert tensor.labels == labels
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with pytest.raises(ValueError):
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tensor.labels = labels[:-1]
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def test_extract():
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label_to_extract = ['a', 'c']
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tensor = LabelTensor(data, labels)
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new = tensor.extract(label_to_extract)
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assert new.labels == label_to_extract
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assert new.shape[1] == len(label_to_extract)
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assert torch.all(torch.isclose(data[:, 0::2], new))
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def test_extract_onelabel():
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label_to_extract = ['a']
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tensor = LabelTensor(data, labels)
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new = tensor.extract(label_to_extract)
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assert new.ndim == 2
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assert new.labels == label_to_extract
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assert new.shape[1] == len(label_to_extract)
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assert torch.all(torch.isclose(data[:, 0].reshape(-1, 1), new))
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def test_wrong_extract():
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label_to_extract = ['a', 'cc']
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tensor = LabelTensor(data, labels)
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with pytest.raises(ValueError):
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tensor.extract(label_to_extract)
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def test_extract_order():
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label_to_extract = ['c', 'a']
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tensor = LabelTensor(data, labels)
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new = tensor.extract(label_to_extract)
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expected = torch.cat(
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(data[:, 2].reshape(-1, 1), data[:, 0].reshape(-1, 1)),
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dim=1)
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assert new.labels == label_to_extract
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assert new.shape[1] == len(label_to_extract)
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assert torch.all(torch.isclose(expected, new))
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def test_merge():
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tensor = LabelTensor(data, labels)
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tensor_a = tensor.extract('a')
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tensor_b = tensor.extract('b')
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tensor_c = tensor.extract('c')
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tensor_bc = tensor_b.append(tensor_c)
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assert torch.allclose(tensor_bc, tensor.extract(['b', 'c']))
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def test_merge2():
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tensor = LabelTensor(data, labels)
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tensor_b = tensor.extract('b')
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tensor_c = tensor.extract('c')
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tensor_bc = tensor_b.append(tensor_c)
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assert torch.allclose(tensor_bc, tensor.extract(['b', 'c']))
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def test_getitem():
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tensor = LabelTensor(data, labels)
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tensor_view = tensor['a']
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assert tensor_view.labels == ['a']
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assert torch.allclose(tensor_view.flatten(), data[:, 0])
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tensor_view = tensor['a', 'c']
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assert tensor_view.labels == ['a', 'c']
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assert torch.allclose(tensor_view, data[:, 0::2])
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def test_getitem2():
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tensor = LabelTensor(data, labels)
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tensor_view = tensor[:5]
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assert tensor_view.labels == labels
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assert torch.allclose(tensor_view, data[:5])
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def test_slice():
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tensor = LabelTensor(data, labels)
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tensor_view = tensor[:5, :2]
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assert tensor_view.labels == labels[:2]
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assert torch.allclose(tensor_view, data[:5, :2])
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tensor_view2 = tensor[3]
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assert tensor_view2.labels == labels
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assert torch.allclose(tensor_view2, data[3])
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tensor_view3 = tensor[:, 2]
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assert tensor_view3.labels == labels[2]
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assert torch.allclose(tensor_view3, data[:, 2].reshape(-1, 1))
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