ENH: Added Anisotropic Power interface to Dipy

.zenodo.json

@@ -81,6 +81,12 @@
         "name": "Keshavan, Anisha",
         "orcid": "0000-0003-3554-043X"
       },
+      {
+        "affiliation": "University of California, San Francisco",
+        "name": "Jordan, Kesshi",
+        "orcid": "0000-0001-6313-0580"
+      },
+
       {
         "affiliation": "Developer",
         "name": "Clark, Daniel",

doc/about.rst

@@ -13,13 +13,13 @@ Citation
    Gorgolewski, Krzysztof J.; Esteban, Oscar; Burns, Christopher; Ziegler, Erik; Pinsard, Basile; Madison, Cindee; Waskom, Michael;
    Ellis, David Gage; Clark, Dav; Wong, Jason; Dayan, Michael; Manhães-Savio, Alexandre; Notter, Michael Philipp; Johnson, Hans;
    Dewey, Blake E; Halchenko, Yaroslav O.; Hamalainen, Carlo; Keshavan, Anisha; Clark, Daniel; Huntenburg, Julia M.; Hanke, Michael;
-   Nichols, B. Nolan; Wassermann , Demian; Eshaghi, Arman; Markiewicz, Christopher J.; Varoquaux, Gael; Acland, Benjamin; 
+   Nichols, B. Nolan; Wassermann , Demian; Eshaghi, Arman; Markiewicz, Christopher J.; Varoquaux, Gael; Acland, Benjamin;
    Forbes, Jessica; Rokem, Ariel; Kong, Xiang-Zhen; Gramfort, Alexandre; Kleesiek, Jens; Schaefer, Alexander; Sikka, Sharad;
    Perez-Guevara, Martin Felipe; Glatard, Tristan; Iqbal, Shariq; Liu, Siqi; Welch, David; Sharp, Paul; Warner, Joshua; Kastman, Erik;
    Lampe, Leonie; Perkins, L. Nathan; Craddock, R. Cameron; Küttner, René; Bielievtsov, Dmytro; Geisler, Daniel; Gerhard, Stephan;
    Liem, Franziskus; Linkersdörfer, Janosch; Margulies, Daniel S.; Andberg, Sami Kristian; Stadler, Jörg; Steele, Christopher John;
    Broderick, William; Cipollini, Ben; Cooper, Gavin; Floren, Andrew; Huang, Lijie; Gonzalez, Ivan; McNamee, Daniel;
-   Papadopoulos Orfanos, Dimitri; Pellman, John; Triplett, William; Goncalves, Mathias; Durnez, Joke; Ghosh, Satrajit (2017). Nipype: 
+   Papadopoulos Orfanos, Dimitri; Pellman, John; Triplett, William; Goncalves, Mathias; Durnez, Joke; Ghosh, Satrajit (2017). Nipype:
    a flexible, lightweight and extensible neuroimaging data processing framework in Python.
    0.13.0 Zenodo. `10.5281/zenodo.50186 <http://dx.doi.org/10.5281/zenodo.575897>`_
 
@@ -94,7 +94,7 @@ Citation
 			  Goncalves, Mathias and
 			  Durnez, Joke and
 			  Ghosh, Satrajit},
-	  title        = {{Nipype: a flexible, lightweight and extensible 
+	  title        = {{Nipype: a flexible, lightweight and extensible
 			   neuroimaging data processing framework in Python.
 			   0.13.0}},
 	  month        = may,

nipype/interfaces/dipy/__init__.py

@@ -4,3 +4,4 @@
 from .preprocess import Resample, Denoise
 from .reconstruction import RESTORE, EstimateResponseSH, CSD
 from .simulate import SimulateMultiTensor
+from .anisotropic_power import APMQball

nipype/interfaces/dipy/anisotropic_power.py

@@ -0,0 +1,78 @@
+# -*- coding: utf-8 -*-
+"""Change directory to provide relative paths for doctests
+   >>> import os
+   >>> filepath = os.path.dirname( os.path.realpath( __file__ ) )
+   >>> datadir = os.path.realpath(os.path.join(filepath, '../../testing/data'))
+   >>> os.chdir(datadir)
+"""
+
+from __future__ import print_function, division, unicode_literals, absolute_import
+
+import nibabel as nb
+
+from ... import logging
+from ..base import TraitedSpec, File, isdefined
+from .base import DipyDiffusionInterface, DipyBaseInterfaceInputSpec
+
+IFLOGGER = logging.getLogger('interface')
+
+
+class APMQballInputSpec(DipyBaseInterfaceInputSpec):
+    mask_file = File(exists=True,
+                     desc='An optional brain mask')
+
+
+class APMQballOutputSpec(TraitedSpec):
+    out_file = File(exists=True)
+
+
+class APMQball(DipyDiffusionInterface):
+    """
+    Calculates the anisotropic power map
+
+    Example
+    -------
+
+    >>> import nipype.interfaces.dipy as dipy
+    >>> apm = dipy.APMQball()
+    >>> apm.inputs.in_file = 'diffusion.nii'
+    >>> apm.inputs.in_bvec = 'bvecs'
+    >>> apm.inputs.in_bval = 'bvals'
+    >>> apm.run()                                   # doctest: +SKIP
+    """
+    input_spec = APMQballInputSpec
+    output_spec = APMQballOutputSpec
+
+    def _run_interface(self, runtime):
+        from dipy.reconst import shm
+        from dipy.data import get_sphere
+        from dipy.reconst.peaks import peaks_from_model
+
+        gtab = self._get_gradient_table()
+
+        img = nb.load(self.inputs.in_file)
+        data = img.get_data()
+        affine = img.affine
+        mask = None
+        if isdefined(self.inputs.mask_file):
+            mask = nb.load(self.inputs.mask_file).get_data()
+
+        # Fit it
+        model = shm.QballModel(gtab,8)
+        sphere = get_sphere('symmetric724')
+        peaks = peaks_from_model(model=model, data=data,
+                                 relative_peak_threshold=.5,
+                                 min_separation_angle=25,
+                                 sphere=sphere, mask=mask)
+        apm = shm.anisotropic_power(peaks.shm_coeff)
+        out_file = self._gen_filename('apm')
+        nb.Nifti1Image(apm.astype("float32"), affine).to_filename(out_file)
+        IFLOGGER.info('APM qball image saved as {i}'.format(i=out_file))
+
+        return runtime
+
+    def _list_outputs(self):
+        outputs = self._outputs().get()
+        outputs['out_file'] = self._gen_filename('apm')
+
+        return outputs

nipype/interfaces/dipy/tests/test_auto_APMQball.py

@@ -0,0 +1,35 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from __future__ import unicode_literals
+from ..anisotropic_power import APMQball
+
+
+def test_APMQball_inputs():
+    input_map = dict(b0_thres=dict(usedefault=True,
+    ),
+    ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    in_bval=dict(mandatory=True,
+    ),
+    in_bvec=dict(mandatory=True,
+    ),
+    in_file=dict(mandatory=True,
+    ),
+    mask_file=dict(),
+    out_prefix=dict(),
+    )
+    inputs = APMQball.input_spec()
+
+    for key, metadata in list(input_map.items()):
+        for metakey, value in list(metadata.items()):
+            assert getattr(inputs.traits()[key], metakey) == value
+
+
+def test_APMQball_outputs():
+    output_map = dict(out_file=dict(),
+    )
+    outputs = APMQball.output_spec()
+
+    for key, metadata in list(output_map.items()):
+        for metakey, value in list(metadata.items()):
+            assert getattr(outputs.traits()[key], metakey) == value