Merge pull request #489 from dPys/enh/nibabel_splitmerge_interfaces

oesteban · web-flow · commit 7b28b4fe2384 · 2020-04-16T11:24:08.000-07:00
ENH: Add nibabel-based split and merge interfaces
diff --git a/niworkflows/interfaces/nibabel.py b/niworkflows/interfaces/nibabel.py
@@ -1,27 +1,34 @@
 # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
 # vi: set ft=python sts=4 ts=4 sw=4 et:
 """Nibabel-based interfaces."""
+from pathlib import Path
 import numpy as np
 import nibabel as nb
 from nipype import logging
 from nipype.utils.filemanip import fname_presuffix
 from nipype.interfaces.base import (
-    traits, TraitedSpec, BaseInterfaceInputSpec, File,
-    SimpleInterface
+    traits,
+    TraitedSpec,
+    BaseInterfaceInputSpec,
+    File,
+    SimpleInterface,
+    OutputMultiObject,
+    InputMultiObject,
 )
 
-IFLOGGER = logging.getLogger('nipype.interface')
+IFLOGGER = logging.getLogger("nipype.interface")
 
 
 class _ApplyMaskInputSpec(BaseInterfaceInputSpec):
-    in_file = File(exists=True, mandatory=True, desc='an image')
-    in_mask = File(exists=True, mandatory=True, desc='a mask')
-    threshold = traits.Float(0.5, usedefault=True,
-                             desc='a threshold to the mask, if it is nonbinary')
+    in_file = File(exists=True, mandatory=True, desc="an image")
+    in_mask = File(exists=True, mandatory=True, desc="a mask")
+    threshold = traits.Float(
+        0.5, usedefault=True, desc="a threshold to the mask, if it is nonbinary"
+    )
 
 
 class _ApplyMaskOutputSpec(TraitedSpec):
-    out_file = File(exists=True, desc='masked file')
+    out_file = File(exists=True, desc="masked file")
 
 
 class ApplyMask(SimpleInterface):
@@ -35,8 +42,9 @@ def _run_interface(self, runtime):
         msknii = nb.load(self.inputs.in_mask)
         msk = msknii.get_fdata() > self.inputs.threshold
 
-        self._results['out_file'] = fname_presuffix(
-            self.inputs.in_file, suffix='_masked', newpath=runtime.cwd)
+        self._results["out_file"] = fname_presuffix(
+            self.inputs.in_file, suffix="_masked", newpath=runtime.cwd
+        )
 
         if img.dataobj.shape[:3] != msk.shape:
             raise ValueError("Image and mask sizes do not match.")
@@ -48,19 +56,18 @@ def _run_interface(self, runtime):
             msk = msk[..., np.newaxis]
 
         masked = img.__class__(img.dataobj * msk, None, img.header)
-        masked.to_filename(self._results['out_file'])
+        masked.to_filename(self._results["out_file"])
         return runtime
 
 
 class _BinarizeInputSpec(BaseInterfaceInputSpec):
-    in_file = File(exists=True, mandatory=True, desc='input image')
-    thresh_low = traits.Float(mandatory=True,
-                              desc='non-inclusive lower threshold')
+    in_file = File(exists=True, mandatory=True, desc="input image")
+    thresh_low = traits.Float(mandatory=True, desc="non-inclusive lower threshold")
 
 
 class _BinarizeOutputSpec(TraitedSpec):
-    out_file = File(exists=True, desc='masked file')
-    out_mask = File(exists=True, desc='output mask')
+    out_file = File(exists=True, desc="masked file")
+    out_mask = File(exists=True, desc="output mask")
 
 
 class Binarize(SimpleInterface):
@@ -72,20 +79,98 @@ class Binarize(SimpleInterface):
     def _run_interface(self, runtime):
         img = nb.load(self.inputs.in_file)
 
-        self._results['out_file'] = fname_presuffix(
-            self.inputs.in_file, suffix='_masked', newpath=runtime.cwd)
-        self._results['out_mask'] = fname_presuffix(
-            self.inputs.in_file, suffix='_mask', newpath=runtime.cwd)
+        self._results["out_file"] = fname_presuffix(
+            self.inputs.in_file, suffix="_masked", newpath=runtime.cwd
+        )
+        self._results["out_mask"] = fname_presuffix(
+            self.inputs.in_file, suffix="_mask", newpath=runtime.cwd
+        )
 
         data = img.get_fdata()
         mask = data > self.inputs.thresh_low
         data[~mask] = 0.0
         masked = img.__class__(data, img.affine, img.header)
-        masked.to_filename(self._results['out_file'])
+        masked.to_filename(self._results["out_file"])
 
-        img.header.set_data_dtype('uint8')
-        maskimg = img.__class__(mask.astype('uint8'), img.affine,
-                                img.header)
-        maskimg.to_filename(self._results['out_mask'])
+        img.header.set_data_dtype("uint8")
+        maskimg = img.__class__(mask.astype("uint8"), img.affine, img.header)
+        maskimg.to_filename(self._results["out_mask"])
 
         return runtime
+
+
+class _SplitSeriesInputSpec(BaseInterfaceInputSpec):
+    in_file = File(exists=True, mandatory=True, desc="input 4d image")
+
+
+class _SplitSeriesOutputSpec(TraitedSpec):
+    out_files = OutputMultiObject(File(exists=True), desc="output list of 3d images")
+
+
+class SplitSeries(SimpleInterface):
+    """Split a 4D dataset along the last dimension into a series of 3D volumes."""
+
+    input_spec = _SplitSeriesInputSpec
+    output_spec = _SplitSeriesOutputSpec
+
+    def _run_interface(self, runtime):
+        in_file = self.inputs.in_file
+        img = nb.load(in_file)
+        extra_dims = tuple(dim for dim in img.shape[3:] if dim > 1) or (1,)
+        if len(extra_dims) != 1:
+            raise ValueError(f"Invalid shape {'x'.join(str(s) for s in img.shape)}")
+        img = img.__class__(img.dataobj.reshape(img.shape[:3] + extra_dims),
+                            img.affine, img.header)
+
+        self._results["out_files"] = []
+        for i, img_3d in enumerate(nb.four_to_three(img)):
+            out_file = str(
+                Path(fname_presuffix(in_file, suffix=f"_idx-{i:03}")).absolute()
+            )
+            img_3d.to_filename(out_file)
+            self._results["out_files"].append(out_file)
+
+        return runtime
+
+
+class _MergeSeriesInputSpec(BaseInterfaceInputSpec):
+    in_files = InputMultiObject(
+        File(exists=True, mandatory=True, desc="input list of 3d images")
+    )
+    allow_4D = traits.Bool(
+        True, usedefault=True, desc="whether 4D images are allowed to be concatenated"
+    )
+
+
+class _MergeSeriesOutputSpec(TraitedSpec):
+    out_file = File(exists=True, desc="output 4d image")
+
+
+class MergeSeries(SimpleInterface):
+    """Merge a series of 3D volumes along the last dimension into a single 4D image."""
+
+    input_spec = _MergeSeriesInputSpec
+    output_spec = _MergeSeriesOutputSpec
+
+    def _run_interface(self, runtime):
+        nii_list = []
+        for f in self.inputs.in_files:
+            filenii = nb.squeeze_image(nb.load(f))
+            ndim = filenii.dataobj.ndim
+            if ndim == 3:
+                nii_list.append(filenii)
+                continue
+            elif self.inputs.allow_4D and ndim == 4:
+                nii_list += nb.four_to_three(filenii)
+                continue
+            else:
+                raise ValueError(
+                    "Input image has an incorrect number of dimensions" f" ({ndim})."
+                )
+
+        img_4d = nb.concat_images(nii_list)
+        out_file = fname_presuffix(self.inputs.in_files[0], suffix="_merged")
+        img_4d.to_filename(out_file)
+
+        self._results["out_file"] = out_file
+        return runtime
diff --git a/niworkflows/interfaces/tests/test_nibabel.py b/niworkflows/interfaces/tests/test_nibabel.py
@@ -4,7 +4,7 @@
 import nibabel as nb
 import pytest
 
-from ..nibabel import Binarize, ApplyMask
+from ..nibabel import Binarize, ApplyMask, SplitSeries, MergeSeries
 
 
 def test_Binarize(tmp_path):
@@ -14,10 +14,10 @@ def test_Binarize(tmp_path):
     mask = np.zeros((20, 20, 20), dtype=bool)
     mask[5:15, 5:15, 5:15] = bool
 
-    data = np.zeros_like(mask, dtype='float32')
+    data = np.zeros_like(mask, dtype="float32")
     data[mask] = np.random.gamma(2, size=mask.sum())
 
-    in_file = tmp_path / 'input.nii.gz'
+    in_file = tmp_path / "input.nii.gz"
     nb.Nifti1Image(data, np.eye(4), None).to_filename(str(in_file))
 
     binif = Binarize(thresh_low=0.0, in_file=str(in_file)).run()
@@ -36,28 +36,32 @@ def test_ApplyMask(tmp_path):
     mask[8:11, 8:11, 8:11] = 1.0
 
     # Test the 3D
-    in_file = tmp_path / 'input3D.nii.gz'
+    in_file = tmp_path / "input3D.nii.gz"
     nb.Nifti1Image(data, np.eye(4), None).to_filename(str(in_file))
 
-    in_mask = tmp_path / 'mask.nii.gz'
+    in_mask = tmp_path / "mask.nii.gz"
     nb.Nifti1Image(mask, np.eye(4), None).to_filename(str(in_mask))
 
     masked1 = ApplyMask(in_file=str(in_file), in_mask=str(in_mask), threshold=0.4).run()
-    assert nb.load(masked1.outputs.out_file).get_fdata().sum() == 5**3
+    assert nb.load(masked1.outputs.out_file).get_fdata().sum() == 5 ** 3
 
     masked1 = ApplyMask(in_file=str(in_file), in_mask=str(in_mask), threshold=0.6).run()
-    assert nb.load(masked1.outputs.out_file).get_fdata().sum() == 3**3
+    assert nb.load(masked1.outputs.out_file).get_fdata().sum() == 3 ** 3
 
     data4d = np.stack((data, 2 * data, 3 * data), axis=-1)
     # Test the 4D case
-    in_file4d = tmp_path / 'input4D.nii.gz'
+    in_file4d = tmp_path / "input4D.nii.gz"
     nb.Nifti1Image(data4d, np.eye(4), None).to_filename(str(in_file4d))
 
-    masked1 = ApplyMask(in_file=str(in_file4d), in_mask=str(in_mask), threshold=0.4).run()
-    assert nb.load(masked1.outputs.out_file).get_fdata().sum() == 5**3 * 6
+    masked1 = ApplyMask(
+        in_file=str(in_file4d), in_mask=str(in_mask), threshold=0.4
+    ).run()
+    assert nb.load(masked1.outputs.out_file).get_fdata().sum() == 5 ** 3 * 6
 
-    masked1 = ApplyMask(in_file=str(in_file4d), in_mask=str(in_mask), threshold=0.6).run()
-    assert nb.load(masked1.outputs.out_file).get_fdata().sum() == 3**3 * 6
+    masked1 = ApplyMask(
+        in_file=str(in_file4d), in_mask=str(in_mask), threshold=0.6
+    ).run()
+    assert nb.load(masked1.outputs.out_file).get_fdata().sum() == 3 ** 3 * 6
 
     # Test errors
     nb.Nifti1Image(mask, 2 * np.eye(4), None).to_filename(str(in_mask))
@@ -69,3 +73,58 @@ def test_ApplyMask(tmp_path):
         ApplyMask(in_file=str(in_file), in_mask=str(in_mask), threshold=0.4).run()
     with pytest.raises(ValueError):
         ApplyMask(in_file=str(in_file4d), in_mask=str(in_mask), threshold=0.4).run()
+
+
+@pytest.mark.parametrize("shape,exp_n", [
+    ((20, 20, 20, 15), 15),
+    ((20, 20, 20), 1),
+    ((20, 20, 20, 1), 1),
+    ((20, 20, 20, 1, 3), 3),
+    ((20, 20, 20, 3, 1), 3),
+    ((20, 20, 20, 1, 3, 3), -1),
+    ((20, 1, 20, 15), 15),
+    ((20, 1, 20), 1),
+    ((20, 1, 20, 1), 1),
+    ((20, 1, 20, 1, 3), 3),
+    ((20, 1, 20, 3, 1), 3),
+    ((20, 1, 20, 1, 3, 3), -1),
+])
+def test_SplitSeries(tmp_path, shape, exp_n):
+    """Test 4-to-3 NIfTI split interface."""
+    os.chdir(tmp_path)
+
+    in_file = str(tmp_path / "input.nii.gz")
+    nb.Nifti1Image(np.ones(shape, dtype=float), np.eye(4), None).to_filename(in_file)
+
+    _interface = SplitSeries(in_file=in_file)
+    if exp_n > 0:
+        split = _interface.run()
+        n = int(isinstance(split.outputs.out_files, str)) or len(split.outputs.out_files)
+        assert n == exp_n
+    else:
+        with pytest.raises(ValueError):
+            _interface.run()
+
+
+def test_MergeSeries(tmp_path):
+    """Test 3-to-4 NIfTI concatenation interface."""
+    os.chdir(str(tmp_path))
+
+    in_file = tmp_path / "input3D.nii.gz"
+    nb.Nifti1Image(np.ones((20, 20, 20), dtype=float), np.eye(4), None).to_filename(
+        str(in_file)
+    )
+
+    merge = MergeSeries(in_files=[str(in_file)] * 5).run()
+    assert nb.load(merge.outputs.out_file).dataobj.shape == (20, 20, 20, 5)
+
+    in_4D = tmp_path / "input4D.nii.gz"
+    nb.Nifti1Image(np.ones((20, 20, 20, 4), dtype=float), np.eye(4), None).to_filename(
+        str(in_4D)
+    )
+
+    merge = MergeSeries(in_files=[str(in_file)] + [str(in_4D)]).run()
+    assert nb.load(merge.outputs.out_file).dataobj.shape == (20, 20, 20, 5)
+
+    with pytest.raises(ValueError):
+        MergeSeries(in_files=[str(in_file)] + [str(in_4D)], allow_4D=False).run()
