From ffd8a6d404e23008725bf9e162ec4549bf12d465 Mon Sep 17 00:00:00 2001 From: Oscar Esteban Date: Fri, 5 Apr 2024 10:35:24 +0200 Subject: [PATCH] fix: update many apply() calls --- nitransforms/cli.py | 4 ++- nitransforms/tests/test_base.py | 7 +++--- nitransforms/tests/test_io.py | 41 ++++++++++++++++++++----------- nitransforms/tests/test_linear.py | 16 ++++++------ 4 files changed, 43 insertions(+), 25 deletions(-) diff --git a/nitransforms/cli.py b/nitransforms/cli.py index 63b8bed4..8f8f5ce0 100644 --- a/nitransforms/cli.py +++ b/nitransforms/cli.py @@ -5,6 +5,7 @@ from .linear import load as linload from .nonlinear import load as nlinload +from .resampling import apply def cli_apply(pargs): @@ -38,7 +39,8 @@ def cli_apply(pargs): # ensure a reference is set xfm.reference = pargs.ref or pargs.moving - moved = xfm.apply( + moved = apply( + xfm, pargs.moving, order=pargs.order, mode=pargs.mode, diff --git a/nitransforms/tests/test_base.py b/nitransforms/tests/test_base.py index 8422ca10..d09096f7 100644 --- a/nitransforms/tests/test_base.py +++ b/nitransforms/tests/test_base.py @@ -6,6 +6,7 @@ from ..base import SpatialReference, SampledSpatialData, ImageGrid, TransformBase from .. import linear as nitl +from ..resampling import apply def test_SpatialReference(testdata_path): @@ -95,7 +96,7 @@ def _to_hdf5(klass, x5_root): xfm = TransformBase() xfm.reference = fname assert xfm.ndim == 3 - moved = xfm.apply(fname, order=0) + moved = apply(xfm, fname, order=0) assert np.all( imgdata == np.asanyarray(moved.dataobj, dtype=moved.get_data_dtype()) ) @@ -104,7 +105,7 @@ def _to_hdf5(klass, x5_root): xfm = TransformBase() xfm.reference = fname assert xfm.ndim == 3 - moved = xfm.apply(str(fname), reference=fname, order=0) + moved = apply(xfm, str(fname), reference=fname, order=0) assert np.all( imgdata == np.asanyarray(moved.dataobj, dtype=moved.get_data_dtype()) ) @@ -118,7 +119,7 @@ def _to_hdf5(klass, x5_root): ) ] ) - giimoved = xfm.apply(fname, reference=gii, order=0) + giimoved = apply(xfm, fname, reference=gii, order=0) assert np.allclose(giimoved.reshape(xfm.reference.shape), moved.get_fdata()) # Test to_filename diff --git a/nitransforms/tests/test_io.py b/nitransforms/tests/test_io.py index bcee9198..0cc79d15 100644 --- a/nitransforms/tests/test_io.py +++ b/nitransforms/tests/test_io.py @@ -28,6 +28,8 @@ ) from nitransforms.io.base import LinearParameters, TransformIOError, TransformFileError from nitransforms.conftest import _datadir, _testdir +from nitransforms.resampling import apply + LPS = np.diag([-1, -1, 1, 1]) ITK_MAT = LPS.dot(np.ones((4, 4)).dot(LPS)) @@ -497,10 +499,13 @@ def test_afni_oblique(tmpdir, parameters, swapaxes, testdata_path, dir_x, dir_y, assert np.allclose(card_aff, nb.load("deob_3drefit.nii.gz").affine) # Check that nitransforms can emulate 3drefit -deoblique - nt3drefit = Affine( - afni._cardinal_rotation(img.affine, False), - reference="deob_3drefit.nii.gz", - ).apply("orig.nii.gz") + nt3drefit = apply( + Affine( + afni._cardinal_rotation(img.affine, False), + reference="deob_3drefit.nii.gz", + ), + "orig.nii.gz", + ) diff = ( np.asanyarray(img.dataobj, dtype="uint8") @@ -509,10 +514,13 @@ def test_afni_oblique(tmpdir, parameters, swapaxes, testdata_path, dir_x, dir_y, assert np.sqrt((diff[10:-10, 10:-10, 10:-10] ** 2).mean()) < 0.1 # Check that nitransforms can revert 3drefit -deoblique - nt_undo3drefit = Affine( - afni._cardinal_rotation(img.affine, True), - reference="orig.nii.gz", - ).apply("deob_3drefit.nii.gz") + nt_undo3drefit = apply( + Affine( + afni._cardinal_rotation(img.affine, True), + reference="orig.nii.gz", + ), + "deob_3drefit.nii.gz", + ) diff = ( np.asanyarray(img.dataobj, dtype="uint8") @@ -531,16 +539,21 @@ def test_afni_oblique(tmpdir, parameters, swapaxes, testdata_path, dir_x, dir_y, assert np.allclose(deobaff, deobnii.affine) # Check resampling in deobliqued grid - ntdeobnii = Affine(np.eye(4), reference=deobnii.__class__( - np.zeros(deobshape, dtype="uint8"), - deobaff, - deobnii.header - )).apply(img, order=0) + ntdeobnii = apply( + Affine(np.eye(4), reference=deobnii.__class__( + np.zeros(deobshape, dtype="uint8"), + deobaff, + deobnii.header + )), + img, + order=0, + ) # Generate an internal box to exclude border effects box = np.zeros(img.shape, dtype="uint8") box[10:-10, 10:-10, 10:-10] = 1 - ntdeobmask = Affine(np.eye(4), reference=ntdeobnii).apply( + ntdeobmask = apply( + Affine(np.eye(4), reference=ntdeobnii), nb.Nifti1Image(box, img.affine, img.header), order=0, ) diff --git a/nitransforms/tests/test_linear.py b/nitransforms/tests/test_linear.py index 2957f59c..9a06fe32 100644 --- a/nitransforms/tests/test_linear.py +++ b/nitransforms/tests/test_linear.py @@ -13,6 +13,7 @@ from nibabel.affines import from_matvec from nitransforms import linear as nitl from nitransforms import io +from nitransforms.resampling import apply from .utils import assert_affines_by_filename RMSE_TOL = 0.1 @@ -285,7 +286,7 @@ def test_apply_linear_transform(tmpdir, get_testdata, get_testmask, image_orient assert exit_code == 0 sw_moved_mask = nb.load("resampled_brainmask.nii.gz") - nt_moved_mask = xfm.apply(msk, order=0) + nt_moved_mask = apply(xfm, msk, order=0) nt_moved_mask.set_data_dtype(msk.get_data_dtype()) nt_moved_mask.to_filename("ntmask.nii.gz") diff = np.asanyarray(sw_moved_mask.dataobj) - np.asanyarray(nt_moved_mask.dataobj) @@ -305,7 +306,7 @@ def test_apply_linear_transform(tmpdir, get_testdata, get_testmask, image_orient sw_moved = nb.load("resampled.nii.gz") sw_moved.set_data_dtype(img.get_data_dtype()) - nt_moved = xfm.apply(img, order=0) + nt_moved = apply(xfm, img, order=0) diff = ( np.asanyarray(sw_moved.dataobj, dtype=sw_moved.get_data_dtype()) - np.asanyarray(nt_moved.dataobj, dtype=nt_moved.get_data_dtype()) @@ -314,7 +315,7 @@ def test_apply_linear_transform(tmpdir, get_testdata, get_testmask, image_orient # A certain tolerance is necessary because of resampling at borders assert np.sqrt((diff[brainmask] ** 2).mean()) < RMSE_TOL - nt_moved = xfm.apply("img.nii.gz", order=0) + nt_moved = apply(xfm, "img.nii.gz", order=0) diff = ( np.asanyarray(sw_moved.dataobj, dtype=sw_moved.get_data_dtype()) - np.asanyarray(nt_moved.dataobj, dtype=nt_moved.get_data_dtype()) @@ -343,8 +344,8 @@ def test_LinearTransformsMapping_apply(tmp_path, data_path, testdata_path): assert isinstance(hmc, nitl.LinearTransformsMapping) # Test-case: realign functional data on to sbref - nii = hmc.apply( - testdata_path / "func.nii.gz", order=1, reference=testdata_path / "sbref.nii.gz" + nii = apply( + hmc, testdata_path / "func.nii.gz", order=1, reference=testdata_path / "sbref.nii.gz" ) assert nii.dataobj.shape[-1] == len(hmc) @@ -352,13 +353,14 @@ def test_LinearTransformsMapping_apply(tmp_path, data_path, testdata_path): hmcinv = nitl.LinearTransformsMapping( np.linalg.inv(hmc.matrix), reference=testdata_path / "func.nii.gz" ) - nii = hmcinv.apply(testdata_path / "fmap.nii.gz", order=1) + nii = apply(hmcinv, testdata_path / "fmap.nii.gz", order=1) assert nii.dataobj.shape[-1] == len(hmc) # Ensure a ValueError is issued when trying to do weird stuff hmc = nitl.LinearTransformsMapping(hmc.matrix[:1, ...]) with pytest.raises(ValueError): - hmc.apply( + apply( + hmc, testdata_path / "func.nii.gz", order=1, reference=testdata_path / "sbref.nii.gz",