Merge master and fix merge conflict

Author: adelavega

.mailmap

@@ -93,7 +93,7 @@ Josh Warner <[email protected]> JDWarner <[email protected]
 Josh Warner <[email protected]> Josh Warner (Mac) <[email protected]>
 Kai Schlamp <[email protected]> medihack <[email protected]>Jessica Forbes <[email protected]> jessicaforbes <[email protected]>
 Katie Bottenhorn <[email protected]> 62442katieb <[email protected]>
-Kesshi Jordan <[email protected]> Kesshi Jordan <[email protected]> 
+Kesshi Jordan <[email protected]> Kesshi Jordan <[email protected]>
 Kesshi Jordan <[email protected]> Kesshi Jordan <[email protected]>
 Kesshi Jordan <[email protected]> Kesshi Jordan <[email protected]>
 Kesshi Jordan <[email protected]> Kesshi Jordan <[email protected]>

.travis.yml

@@ -94,9 +94,10 @@ before_install:
 
 install:
 - travis_retry pip install $EXTRA_PIP_FLAGS -e .[$NIPYPE_EXTRAS]
+- travis_retry pip install pytest-xdist
 
 script:
-- py.test -v --cov nipype --cov-config .coveragerc --cov-report xml:cov.xml -c nipype/pytest.ini --doctest-modules nipype
+- py.test -v --cov nipype --cov-config .coveragerc --cov-report xml:cov.xml -c nipype/pytest.ini --doctest-modules nipype -n auto
 
 after_script:
 - codecov --file cov.xml --flags unittests -e TRAVIS_JOB_NUMBER

.zenodo.json

@@ -589,6 +589,11 @@
       "affiliation": "MIT, HMS",
       "name": "Ghosh, Satrajit",
       "orcid": "0000-0002-5312-6729"
+    },
+    {
+      "affiliation": "University of Washington",
+      "name": "Richie-Halford, Adam",
+      "orcid": "0000-0001-9276-9084"
     }
   ],
   "keywords": [

README.rst

@@ -91,7 +91,7 @@ To participate in the Nipype development related discussions please use the foll
 
 Please add *[nipype]* to the subject line when posting on the mailing list.
 
-You can even hangout with the Nipype developers in their 
+You can even hangout with the Nipype developers in their
 `Gitter <https://gitter.im/nipy/nipype>`_ channel or in the BrainHack `Slack <https://brainhack.slack.com/messages/C1FR76RAL>`_ channel. (Click `here <https://brainhack-slack-invite.herokuapp.com>`_ to join the Slack workspace.)
 
 

doc/devel/interface_specs.rst

@@ -12,8 +12,8 @@ In case of trouble, we encourage you to post on `NeuroStars <https://neurostars.
 NeuroStars.org is a platform similar to StackOverflow but dedicated to neuroinformatics.
 You can also post on the nipype developers mailing list: http://mail.python.org/mailman/listinfo/neuroimaging.
 As we are sharing a mailing list with the nipy community, please add ``[nipype]`` to the message title.
-Alternatively, you're welcome to chat with us in the Nipype 
-`Gitter <https://gitter.im/nipy/nipype>`_ channel or in the 
+Alternatively, you're welcome to chat with us in the Nipype
+`Gitter <https://gitter.im/nipy/nipype>`_ channel or in the
 BrainHack `Slack <https://brainhack.slack.com/messages/C1FR76RAL>`_ channel.
 (Click `here <https://brainhack-slack-invite.herokuapp.com>`_ to join the Slack workspace.)
 

docker/files/run_pytests.sh

@@ -29,6 +29,7 @@ export COVERAGE_FILE=${WORKDIR}/tests/.coverage.py${PYTHON_VERSION}
 py.test -v --junitxml=${WORKDIR}/tests/pytests_py${PYTHON_VERSION}.xml \
     --cov nipype --cov-config /src/nipype/.coveragerc \
     --cov-report xml:${WORKDIR}/tests/coverage_py${PYTHON_VERSION}.xml \
+    -n auto \
     -c ${TESTPATH}/pytest.ini ${TESTPATH}
 exit_code=$?
 

docker/generate_dockerfiles.sh

@@ -92,7 +92,7 @@ function generate_main_dockerfile() {
                 conda_install='python=${PYTHON_VERSION_MAJOR}.${PYTHON_VERSION_MINOR}
                                icu=58.1 libxml2 libxslt matplotlib mkl numpy paramiko
                                pandas psutil scikit-learn scipy traits=4.6.0' \
-                pip_install="grabbit==0.2.6 https://github.com/bids-standard/pybids/tarball/0.7.0" \
+                pip_install="pytest-xdist" \
                 activate=true \
     --copy docker/files/run_builddocs.sh docker/files/run_examples.sh \
            docker/files/run_pytests.sh nipype/external/fsl_imglob.py /usr/bin/ \
@@ -107,7 +107,7 @@ function generate_main_dockerfile() {
     --user neuro \
     --miniconda use_env=neuro \
                 pip_opts="-e" \
-                pip_install="/src/nipype[all]" \
+                pip_install="/src/nipype[all] https://github.com/bids-standard/pybids/tarball/0.7.0" \
     --workdir /work \
     --label org.label-schema.build-date='$BUILD_DATE' \
             org.label-schema.name="NIPYPE" \

nipype/__init__.py

@@ -25,17 +25,22 @@
 
 
 class NipypeTester(object):
-    def __call__(self, doctests=True, parallel=True):
+    def __call__(self, doctests=True, parallel=False):
         try:
             import pytest
-        except:
+        except ImportError:
             raise RuntimeError(
                 'py.test not installed, run: pip install pytest')
         args = []
         if not doctests:
             args.extend(['-p', 'no:doctest'])
-        if not parallel:
-            args.append('-n0')
+        if parallel:
+            try:
+                import xdist
+            except ImportError:
+                raise RuntimeError(
+                    "pytest-xdist required for parallel run")
+            args.append('-n auto')
         args.append(os.path.dirname(__file__))
         pytest.main(args=args)
 

nipype/algorithms/modelgen.py

@@ -144,6 +144,61 @@ def scale_timings(timelist, input_units, output_units, time_repetition):
     timelist = [np.max([0., _scalefactor * t]) for t in timelist]
     return timelist
 
+def bids_gen_info(bids_event_files,
+                  condition_column='trial_type',
+                  amplitude_column=None,
+                  time_repetition=False,
+                  ):
+    """Generate subject_info structure from a list of BIDS .tsv event files.
+
+    Parameters
+    ----------
+
+    bids_event_files : list of str
+        Filenames of BIDS .tsv event files containing columns including:
+        'onset', 'duration', and 'trial_type' or the `condition_column` value.
+    condition_column : str
+        Column of files in `bids_event_files` based on the values of which
+        events will be sorted into different regressors
+    amplitude_column : str
+        Column of files in `bids_event_files` based on the values of which
+        to apply amplitudes to events. If unspecified, all events will be
+        represented with an amplitude of 1.
+
+    Returns
+    -------
+
+    list of Bunch
+    """
+    info = []
+    for bids_event_file in bids_event_files:
+        with open(bids_event_file) as f:
+            f_events = csv.DictReader(f, skipinitialspace=True, delimiter='\t')
+            events = [{k: v for k, v in row.items()} for row in f_events]
+        conditions = list(set([i[condition_column] for i in events]))
+        runinfo = Bunch(conditions=[], onsets=[], durations=[], amplitudes=[])
+        for condition in conditions:
+            selected_events = [i for i in events if i[condition_column]==condition]
+            onsets = [float(i['onset']) for i in selected_events]
+            durations = [float(i['duration']) for i in selected_events]
+            if time_repetition:
+                decimals = math.ceil(-math.log10(time_repetition))
+                onsets = [np.round(i, decimals) for i in onsets]
+                durations = [np.round(i ,decimals) for i in durations]
+            if condition:
+                runinfo.conditions.append(condition)
+            else:
+                runinfo.conditions.append('e0')
+            runinfo.onsets.append(onsets)
+            runinfo.durations.append(durations)
+            try:
+                amplitudes = [float(i[amplitude_column]) for i in selected_events]
+                runinfo.amplitudes.append(amplitudes)
+            except KeyError:
+                runinfo.amplitudes.append([1] * len(onsets))
+        info.append(runinfo)
+    return info
+
 
 def gen_info(run_event_files):
     """Generate subject_info structure from a list of event files
@@ -190,6 +245,23 @@ class SpecifyModelInputSpec(BaseInterfaceInputSpec):
         desc='List of event description files 1, 2 or 3 '
         'column format corresponding to onsets, '
         'durations and amplitudes')
+    bids_event_file = InputMultiPath(
+        File(exists=True),
+        mandatory=True,
+        xor=['subject_info', 'event_files', 'bids_event_file'],
+        desc='TSV event file containing common BIDS fields: `onset`,'
+        '`duration`, and categorization and amplitude columns')
+    bids_condition_column = traits.Str(exists=True,
+        mandatory=False,
+        default_value='trial_type',
+        usedefault=True,
+        desc='Column of the file passed to `bids_event_file` to the '
+        'unique values of which events will be assigned'
+        'to regressors')
+    bids_amplitude_column = traits.Str(exists=True,
+        mandatory=False,
+        desc='Column of the file passed to `bids_event_file` '
+        'according to which to assign amplitudes to events')
     realignment_parameters = InputMultiPath(
         File(exists=True),
         desc='Realignment parameters returned '
@@ -432,8 +504,15 @@ def _generate_design(self, infolist=None):
         if infolist is None:
             if isdefined(self.inputs.subject_info):
                 infolist = self.inputs.subject_info
-            else:
+            elif isdefined(self.inputs.event_files):
                 infolist = gen_info(self.inputs.event_files)
+            elif isdefined(self.inputs.bids_event_file):
+                infolist = bids_gen_info(
+                    self.inputs.bids_event_file,
+                    self.inputs.bids_condition_column,
+                    self.inputs.bids_amplitude_column,
+                    self.inputs.time_repetition,
+                    )
         self._sessinfo = self._generate_standard_design(
             infolist,
             functional_runs=self.inputs.functional_runs,

nipype/algorithms/tests/test_auto_SpecifyModel.py

@@ -5,6 +5,19 @@
 
 def test_SpecifyModel_inputs():
     input_map = dict(
+        bids_amplitude_column=dict(
+            exists=True,
+            mandatory=False,
+        ),
+        bids_condition_column=dict(
+            exists=True,
+            mandatory=False,
+            usedefault=True,
+        ),
+        bids_event_file=dict(
+            mandatory=True,
+            xor=['subject_info', 'event_files', 'bids_event_file'],
+        ),
         event_files=dict(
             mandatory=True,
             xor=['subject_info', 'event_files'],