Merge remote-tracking branch 'nipy/master'

Author: tsalo

.travis.yml

@@ -31,7 +31,7 @@ install:
 - conda update --all -y python=$TRAVIS_PYTHON_VERSION
 # - if [[ "${INSTALL_DEB_DEPENDECIES}" == "true" && ${TRAVIS_PYTHON_VERSION:0:1} == "2" ]]; then
 #   conda install -y vtk mayavi; fi
-- conda install -y nipype
+- conda install -y nipype matplotlib nitime
 - pip install python-coveralls coverage doctest-ignore-unicode
 - if [ ! -z "$DUECREDIT_ENABLE"]; then pip install duecredit; fi
 - rm -r /home/travis/miniconda/lib/python${TRAVIS_PYTHON_VERSION}/site-packages/nipype*
@@ -43,7 +43,7 @@ install:
 script:
 - python -W once:FSL:UserWarning:nipype `which nosetests` --with-doctest --with-doctest-ignore-unicode --with-cov --cover-package nipype --logging-level=DEBUG --verbosity=3
 after_success:
-- coveralls --config_file ${COVERAGE_PROCESS_START}
+- bash <(curl -s https://codecov.io/bash) -t ac172a50-8e66-42e5-8822-5373fcf54686 -cF unittests
 deploy:
   provider: pypi
   user: satra

CHANGES

@@ -1,6 +1,9 @@
 Upcoming release 0.13
 =====================
 
+* ENH: Add a DVARS calculation interface (https://github.com/nipy/nipype/pull/1606)
+* ENH: Convenient load/save of interface inputs (https://github.com/nipy/nipype/pull/1591)
+* ENH: Add a Framewise Displacement calculation interface (https://github.com/nipy/nipype/pull/1604)
 * FIX: Use builtins open and unicode literals for py3 compatibility (https://github.com/nipy/nipype/pull/1572)
 * TST: reduce the size of docker images & use tags for images (https://github.com/nipy/nipype/pull/1564)
 * ENH: Implement missing inputs/outputs in FSL AvScale (https://github.com/nipy/nipype/pull/1563)

README.rst

@@ -8,8 +8,8 @@ NIPYPE: Neuroimaging in Python: Pipelines and Interfaces
 .. image:: https://circleci.com/gh/nipy/nipype/tree/master.svg?style=svg
   :target: https://circleci.com/gh/nipy/nipype/tree/master
 
-.. image:: https://coveralls.io/repos/nipy/nipype/badge.png
-  :target: https://coveralls.io/r/nipy/nipype
+.. image:: https://codecov.io/gh/nipy/nipype/branch/master/graph/badge.svg
+  :target: https://codecov.io/gh/nipy/nipype
 
 .. image:: https://www.codacy.com/project/badge/182f27944c51474490b369d0a23e2f32
   :target: https://www.codacy.com/app/krzysztof-gorgolewski/nipy_nipype

circle.yml

@@ -25,7 +25,6 @@ dependencies:
         timeout: 1600
     - mkdir -p ~/docker; docker save nipype/nipype_test:py27 > ~/docker/image.tar :
         timeout: 1600
-    - pip install xunitmerge
 
 test:
   override:
@@ -50,13 +49,10 @@ test:
 
   post:
     - bash docker/circleci/teardown.sh
+    - for xml_f in ${CIRCLE_TEST_REPORTS}/nose/coverage*.xml; do bash <(curl -s https://codecov.io/bash) -f $xml_f -t ac172a50-8e66-42e5-8822-5373fcf54686 -F unittests; done
+    - for xml_f in ${CIRCLE_TEST_REPORTS}/nose/smoketest*.xml; do bash <(curl -s https://codecov.io/bash) -f $xml_f -t ac172a50-8e66-42e5-8822-5373fcf54686 -F smoketests; done
 
 general:
   artifacts:
     - "~/docs"
     - "~/logs"
-    - "~/coverage_py27.xml"
-    - "~/coverage_py35.xml"
-    - "~/nosetests_py27.xml"
-    - "~/nosetests_py35.xml"
-    - "~/scratch"

codecov.yml

@@ -0,0 +1,20 @@
+coverage:
+  range: "0...100"
+  status:
+    project:
+      default:
+        target: 0
+        threshold: 100
+      patch:
+        target: 0
+        threshold: 100
+      unittests:
+        target: 0
+        threshold: 100
+        flags:
+          - "unittests"
+      smoketests:
+        target: 0
+        threshold: 100
+        flags:
+          - "smoketests"

doc/users/interface_tutorial.rst

@@ -4,27 +4,27 @@
  Tutorial : Interfaces
 =======================
 
-Specifying options
-------------------
+Specifying input settings
+-------------------------
 
 The nipype interface modules provide a Python interface to external
 packages like FSL_ and SPM_.  Within the module are a series of Python
 classes which wrap specific package functionality.  For example, in
 the fsl module, the class :class:`nipype.interfaces.fsl.Bet` wraps the
 ``bet`` command-line tool.  Using the command-line tool, one would
-specify options using flags like ``-o``, ``-m``, ``-f <f>``, etc...
+specify input settings using flags like ``-o``, ``-m``, ``-f <f>``, etc...
 However, in nipype, options are assigned to Python attributes and can
 be specified in the following ways:
 
-Options can be assigned when you first create an interface object:
+Settings can be assigned when you first create an interface object:
 
 .. testcode::
 
    import nipype.interfaces.fsl as fsl
    mybet = fsl.BET(in_file='foo.nii', out_file='bar.nii')
    result = mybet.run()
 
-Options can be assigned through the ``inputs`` attribute:
+Settings can be assigned through the ``inputs`` attribute:
 
 .. testcode::
 
@@ -34,14 +34,53 @@ Options can be assigned through the ``inputs`` attribute:
    mybet.inputs.out_file = 'bar.nii'
    result = mybet.run()
 
-Options can be assigned when calling the ``run`` method:
+Settings can be assigned when calling the ``run`` method:
 
 .. testcode::
 
    import nipype.interfaces.fsl as fsl
    mybet = fsl.BET()
    result = mybet.run(in_file='foo.nii', out_file='bar.nii', frac=0.5)
 
+Settings can be saved to a json file:
+
+.. testcode::
+
+   import nipype.interfaces.fsl as fsl
+   mybet = fsl.BET(in_file='foo.nii', out_file='bar.nii', frac=0.5)
+   mybet.save_inputs_to_json('bet-settings.json')
+
+Once saved, the three inputs set for ``mybet`` will be stored in a JSON
+file. These settings can also be loaded from a json file:
+
+.. testcode::
+
+   import nipype.interfaces.fsl as fsl
+   mybet = fsl.BET()
+   mybet.load_inputs_from_json('bet-settings.json', overwrite=False)
+
+
+Loading settings will overwrite previously set inputs by default, unless
+the ``overwrite`` argument is ``False``. Conveniently, the settings can be
+also read during the interface instantiation:
+
+.. testcode::
+
+   import nipype.interfaces.fsl as fsl
+   mybet = fsl.BET(from_file='bet-settings.json')
+
+If the user provides settings during interface creation, they will take
+precedence over those loaded using ``from_file``:
+
+.. testcode::
+
+   import nipype.interfaces.fsl as fsl
+   mybet = fsl.BET(from_file='bet-settings.json', frac=0.7)
+
+In this case, ``mybet.inputs.frac`` will contain the value ``0.7`` regardless
+the value that could be stored in the ``bet-settings.json`` file.
+
+
 Getting Help
 ------------
 

docker/circleci/run_examples.sh

@@ -11,6 +11,9 @@ echo 'filemanip_level = DEBUG' >> /root/.nipype/nipype.cfg
 echo 'log_to_file = true' >> /root/.nipype/nipype.cfg
 echo 'log_directory = /scratch/logs/' >> /root/.nipype/nipype.cfg
 
-python /root/src/nipype/tools/run_examples.py $@
+coverage run /root/src/nipype/tools/run_examples.py $@
+arr=$@
+tmp_var=$( IFS=$' '; echo "${arr[*]}" )
+coverage xml -o "/scratch/smoketest_${tmp_var//[^A-Za-z0-9_-]/_}.xml"
 
-chmod 777 -R /scratch/logs
+chmod 777 -R /scratch/logs

docker/circleci/teardown.sh

@@ -7,10 +7,9 @@ set -u
 set -e
 
 mkdir -p ${CIRCLE_TEST_REPORTS}/nose
-xunitmerge ~/scratch/nosetests*.xml ${CIRCLE_TEST_REPORTS}/nose/${CIRCLE_PROJECT_REPONAME}.xml
-sudo mv ~/scratch/coverage*.xml ~/
+sudo mv ~/scratch/*.xml ${CIRCLE_TEST_REPORTS}/nose
 mkdir -p ~/docs
 sudo mv ~/scratch/docs/* ~/docs/
 mkdir -p ~/logs
 sudo mv ~/scratch/builddocs.log ~/logs/builddocs.log
-sudo mv ~/scratch/logs/* ~/logs/
+sudo mv ~/scratch/logs/* ~/logs/

examples/README

@@ -1,4 +1,4 @@
 A dataset for use with these scripts can be downloaded from the nipype
 website. At the time of writing, it's at:
 
-http://nipy.org/nipype/users/pipeline_tutorial.html
+http://nipype.readthedocs.io/en/0.12.0/users/pipeline_tutorial.html

examples/rsfmri_vol_surface_preprocessing_nipy.py

@@ -52,7 +52,9 @@
 from nipype.interfaces.base import CommandLine
 CommandLine.set_default_terminal_output('allatonce')
 
+# https://github.com/moloney/dcmstack
 from dcmstack.extract import default_extractor
+# pip install pydicom
 from dicom import read_file
 
 from nipype.interfaces import (fsl, Function, ants, freesurfer, nipy)
@@ -64,6 +66,7 @@
 
 from nipype.algorithms.rapidart import ArtifactDetect
 from nipype.algorithms.misc import TSNR
+from nipype.algorithms.compcor import ACompCor
 from nipype.interfaces.utility import Rename, Merge, IdentityInterface
 from nipype.utils.filemanip import filename_to_list
 from nipype.interfaces.io import DataSink, FreeSurferSource
@@ -228,51 +231,6 @@ def build_filter1(motion_params, comp_norm, outliers, detrend_poly=None):
         out_files.append(filename)
     return out_files
 
-
-def extract_noise_components(realigned_file, mask_file, num_components=5,
-                             extra_regressors=None):
-    """Derive components most reflective of physiological noise
-
-    Parameters
-    ----------
-    realigned_file: a 4D Nifti file containing realigned volumes
-    mask_file: a 3D Nifti file containing white matter + ventricular masks
-    num_components: number of components to use for noise decomposition
-    extra_regressors: additional regressors to add
-
-    Returns
-    -------
-    components_file: a text file containing the noise components
-    """
-    imgseries = nb.load(realigned_file)
-    components = None
-    for filename in filename_to_list(mask_file):
-        mask = nb.load(filename).get_data()
-        if len(np.nonzero(mask > 0)[0]) == 0:
-            continue
-        voxel_timecourses = imgseries.get_data()[mask > 0]
-        voxel_timecourses[np.isnan(np.sum(voxel_timecourses, axis=1)), :] = 0
-        # remove mean and normalize by variance
-        # voxel_timecourses.shape == [nvoxels, time]
-        X = voxel_timecourses.T
-        stdX = np.std(X, axis=0)
-        stdX[stdX == 0] = 1.
-        stdX[np.isnan(stdX)] = 1.
-        stdX[np.isinf(stdX)] = 1.
-        X = (X - np.mean(X, axis=0)) / stdX
-        u, _, _ = sp.linalg.svd(X, full_matrices=False)
-        if components is None:
-            components = u[:, :num_components]
-        else:
-            components = np.hstack((components, u[:, :num_components]))
-    if extra_regressors:
-        regressors = np.genfromtxt(extra_regressors)
-        components = np.hstack((components, regressors))
-    components_file = os.path.join(os.getcwd(), 'noise_components.txt')
-    np.savetxt(components_file, components, fmt=b"%.10f")
-    return components_file
-
-
 def rename(in_files, suffix=None):
     from nipype.utils.filemanip import (filename_to_list, split_filename,
                                         list_to_filename)
@@ -592,7 +550,7 @@ def create_workflow(files,
     realign.inputs.slice_info = 2
     realign.plugin_args = {'sbatch_args': '-c%d' % 4}
 
-    # Comute TSNR on realigned data regressing polynomials upto order 2
+    # Compute TSNR on realigned data regressing polynomials up to order 2
     tsnr = MapNode(TSNR(regress_poly=2), iterfield=['in_file'], name='tsnr')
     wf.connect(realign, "out_file", tsnr, "in_file")
 
@@ -694,14 +652,10 @@ def merge_files(in1, in2):
                filter1, 'out_res_name')
     wf.connect(createfilter1, 'out_files', filter1, 'design')
 
-    createfilter2 = MapNode(Function(input_names=['realigned_file', 'mask_file',
-                                                  'num_components',
-                                                  'extra_regressors'],
-                                     output_names=['out_files'],
-                                     function=extract_noise_components,
-                                     imports=imports),
+    createfilter2 = MapNode(ACompCor(),
                             iterfield=['realigned_file', 'extra_regressors'],
                             name='makecompcorrfilter')
+    createfilter2.inputs.components_file = 'noise_components.txt'
     createfilter2.inputs.num_components = num_components
 
     wf.connect(createfilter1, 'out_files', createfilter2, 'extra_regressors')
@@ -717,7 +671,7 @@ def merge_files(in1, in2):
     wf.connect(filter1, 'out_res', filter2, 'in_file')
     wf.connect(filter1, ('out_res', rename, '_cleaned'),
                filter2, 'out_res_name')
-    wf.connect(createfilter2, 'out_files', filter2, 'design')
+    wf.connect(createfilter2, 'components_file', filter2, 'design')
     wf.connect(mask, 'mask_file', filter2, 'mask')
 
     bandpass = Node(Function(input_names=['files', 'lowpass_freq',
@@ -923,7 +877,7 @@ def get_names(files, suffix):
     wf.connect(smooth, 'out_file', datasink, 'resting.timeseries.@smoothed')
     wf.connect(createfilter1, 'out_files',
                datasink, 'resting.regress.@regressors')
-    wf.connect(createfilter2, 'out_files',
+    wf.connect(createfilter2, 'components_file',
                datasink, 'resting.regress.@compcorr')
     wf.connect(maskts, 'out_file', datasink, 'resting.timeseries.target')
     wf.connect(sampleaparc, 'summary_file',