def test_ri_bad_type():
with pytest.raises(TypeError, match=r'.* is not a valid image type..*'):
ex = ri("tests/data/mri.nii.gz", "Garbage", "T1", "20000123",
["x", "y", "z"], [2, 2, 2])
with pytest.raises(IOError):
ex = ri("tests/data/blah.nii.gz", "MRI", "T1", "20000123",
["x", "y", "z"], [2, 2, 2])
def test_ris_acquisition_date_str_filter():
with pytest.raises(TypeError):
image1 = ri("tests/data/mri.nii.gz", "MRI", "T1", "20000123", ["x", "y", "z"], [2, 2, 2])
image2 = ri("tests/data/mri.nii.gz", "MRI", "T2", "20000123", ["x", "y", "z"], [0.5, 0.5, 4])
image3 = ri("tests/data/mri.nii.gz", "MRI", "T1+GAD", "20000123", ["x", "y", "z"], [1, 1, 1.5])
image_set = ris([image1, image2, image3])
image_set.filter_by_acquisition_date(1337) # 1337 is not a proper string format for date
def test_ris_contrast_filter():
with pytest.raises(TypeError):
image1 = ri("tests/data/mri.nii.gz", "MRI", "T1", "20000123", ["x", "y", "z"], [2, 2, 2])
image2 = ri("tests/data/mri.nii.gz", "MRI", "T2", "20000123", ["x", "y", "z"], [0.5, 0.5, 4])
image3 = ri("tests/data/mri.nii.gz", "MRI", "T1+GAD", "20000123", ["x", "y", "z"], [1, 1, 1.5])
image_set = ris([image1, image2, image3])
image_set.filter_by_contrast(1337) # 1337 is not a proper contrast
def test_ris_radiology_type_filter():
with pytest.raises(TypeError):
image1 = ri("tests/data/mri.nii.gz", "MRI", "T1", "20000123", ["x", "y", "z"], [2, 2, 2])
image2 = ri("tests/data/mri.nii.gz", "MRI", "T2", "20000123", ["x", "y", "z"], [0.5, 0.5, 4])
image3 = ri("tests/data/mri.nii.gz", "MRI", "T1+GAD", "20000123", ["x", "y", "z"], [1, 1, 1.5])
image_set = ris([image1, image2, image3])
image_set.filter_by_radiology_type('NIRS')
def test_ris_good_input():
image1 = ri("tests/data/mri.nii.gz", "MRI", "T1", "20000123", ["x", "y", "z"], [2, 2, 2])
image2 = ri("tests/data/mri.nii.gz", "MRI", "T2", "20000123", ["x", "y", "z"], [0.5, 0.5, 4])
image3 = ri("tests/data/mri.nii.gz", "MRI", "T1+GAD", "20000123", ["x", "y", "z"], [1, 1, 1.5])
image_set = ris([image1, image2, image3])
# Manually create filtered set after filtering by contrast for T2 images only
filtered_set2 = ris([image2])
assert image_set.radiology_images == [image1, image2, image3]
assert image_set.filter_by_radiology_type('MRI').radiology_images == image_set.radiology_images
assert image_set.filter_by_contrast('T2').radiology_images == filtered_set2.radiology_images
assert image_set.filter_by_acquisition_date('20000123').radiology_images == image_set.radiology_images
def test_ri_good_input():
ex = ri("tests/data/mri.nii.gz", "MRI", "T1", "20000123", ["x", "y", "z"],
[2, 2, 2])
assert ex.radiologic_type == "MRI"
assert ex.contrast == "T1"
assert ex.acquisition_date == "20000123"
assert ex.image_dimensions == ["x", "y", "z"]
assert ex.image_resolution == [2, 2, 2]
assert ex.image_units == ['mm', 'mm', 'mm']
def test_cis_computed_type_filter():
with pytest.raises(TypeError):
ri_ex = ri('tests/data/mri.nii.gz', 'MRI', 'T1', '20000123', ['x', 'y', 'z'], [2, 2, 2])
ci_ex1 = ci('tests/data/seg1.nii.gz', ri_ex, 'SegmentationImage', 'NA', 'NA',
command_used_to_generate='run1.sh')
ci_ex2 = ci('tests/data/seg2.nii.gz', ri_ex, 'RegistrationImage', 'MRI', 'T1',
command_used_to_generate='run2.sh')
image_set = cis([ci_ex1, ci_ex2])
image_set.filter_by_computed_type('Segmntation')
def test_ci_bad_type():
ri_good = ri('tests/data/mri.nii.gz', 'MRI', 'T1', '20000123', ['x', 'y', 'z'], [2, 2, 2])
with pytest.raises(IOError): # Test image_location format
ci_ex = ci('tests/data/blah.nii.gz', ri_good, 'SegmentationImage', 'NA', 'NA')
with pytest.raises(TypeError): # Reference radiologic image parameter with incorrect RadiologicImage input format
ci_ex = ci('tests/data/seg.nii.gz', 3.0, 'SegmentationImage', 'NA', 'NA')
with pytest.raises(TypeError): # Invalid computational type
ci_ex = ci('tests/data/seg.nii.gz', ri_good, 'Segmntation', 'NA', 'NA')
with pytest.raises(TypeError): # Invalid radiologic type
ci_ex = ci('tests/data/seg.nii.gz', ri_good, 'SegmentationImage', 3.0, 'NA', computation_properties=3.0)
with pytest.raises(TypeError): # Invalid computation properties type
ci_ex = ci('tests/data/seg.nii.gz', ri_good, 'SegmentationImage', 'NA', 'NA', computation_properties=3.0)
def test_cis_good_input():
ri_ex = ri('tests/data/mri.nii.gz', 'MRI', 'T1', '20000123', ['x', 'y', 'z'], [2, 2, 2])
# Test RadiologicImage passed as reference
ci_ex1 = ci('tests/data/seg1.nii.gz', ri_ex, 'SegmentationImage', 'NA', 'NA',
command_used_to_generate='run1.sh')
ci_ex2 = ci('tests/data/seg2.nii.gz', ri_ex, 'RegistrationImage', 'MRI', 'T1',
command_used_to_generate='run2.sh')
image_set = cis([ci_ex1, ci_ex2])
# Manually create filtered set after filtering by contrast for T2 images only
filtered_set = cis(ci_ex2)
assert image_set.computed_images == [ci_ex1, ci_ex2]
assert image_set.filter_by_radiology_type('MRI').computed_images == filtered_set.computed_images
assert image_set.filter_by_computed_type('RegistrationImage').computed_images == filtered_set.computed_images
assert image_set.filter_by_contrast('T1').computed_images == filtered_set.computed_images
def test_ci_good_input():
ri_ex = ri('tests/data/mri.nii.gz', 'MRI', 'T1', '20000123', ['x', 'y', 'z'], [2, 2, 2])
# Test RadiologicImage passed as reference
ci_ex = ci('tests/data/seg.nii.gz', ri_ex, 'SegmentationImage', 'NA', 'NA',
command_used_to_generate='run.sh',
computation_properties={'notes': 'just a test case'})
assert ci_ex.computed_type == 'SegmentationImage'
assert ci_ex.reference_radiologic_image.radiologic_type == 'MRI'
assert ci_ex.reference_radiologic_image.contrast == 'T1'
assert ci_ex.reference_radiologic_image.acquisition_date == '20000123'
assert ci_ex.reference_radiologic_image.image_dimensions == ['x', 'y', 'z']
assert ci_ex.reference_radiologic_image.image_resolution == [2, 2, 2]
assert ci_ex.reference_radiologic_image.image_units == ['mm', 'mm', 'mm']
# Test without command_used_to_generate or computation_properties parameter
ci_ex = ci('tests/data/seg.nii.gz', ri_ex, 'SegmentationImage', 'NA', 'NA')