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#!/usr/bin/env python |
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"""Tests for Subject.""" |
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import tempfile |
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import torch |
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from torchio import Subject, ScalarImage, RandomFlip |
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from ..utils import TorchioTestCase |
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class TestSubject(TorchioTestCase): |
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"""Tests for `Subject`.""" |
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def test_positional_args(self): |
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with self.assertRaises(ValueError): |
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with tempfile.NamedTemporaryFile() as f: |
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Subject(ScalarImage(f.name)) |
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def test_input_dict(self): |
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with tempfile.NamedTemporaryFile() as f: |
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input_dict = {'image': ScalarImage(f.name)} |
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Subject(input_dict) |
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Subject(**input_dict) |
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def test_no_sample(self): |
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with tempfile.NamedTemporaryFile() as f: |
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input_dict = {'image': ScalarImage(f.name)} |
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subject = Subject(input_dict) |
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with self.assertRaises(RuntimeError): |
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RandomFlip()(subject) |
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def test_history(self): |
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transformed = RandomFlip()(self.sample_subject) |
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self.assertIs(len(transformed.history), 1) |
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def test_inconsistent_shape(self): |
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subject = Subject( |
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a=ScalarImage(tensor=torch.rand(1, 2, 3, 4)), |
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b=ScalarImage(tensor=torch.rand(2, 2, 3, 4)), |
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) |
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subject.spatial_shape |
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with self.assertRaises(RuntimeError): |
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subject.shape |
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def test_inconsistent_spatial_shape(self): |
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subject = Subject( |
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a=ScalarImage(tensor=torch.rand(1, 3, 3, 4)), |
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b=ScalarImage(tensor=torch.rand(2, 2, 3, 4)), |
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) |
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with self.assertRaises(RuntimeError): |
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subject.spatial_shape |
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def test_plot(self): |
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self.sample_subject.plot( |
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show=False, |
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output_path=self.dir / 'figure.png', |
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cmap_dict=dict( |
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t2='viridis', |
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label={0: 'yellow', 1: 'blue'}, |
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), |
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) |
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def test_plot_one_image(self): |
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subject = Subject(t1=ScalarImage(self.get_image_path('t1_plot'))) |
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subject.plot(show=False) |
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fepegar /
torchio
