Merge branch 'master' into FixElapsedRuntimeFormat

.github/workflows/pythonpackage.yml

@@ -23,7 +23,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
+        python-version: ['3.9', '3.10', '3.11', '3.12']
 
     steps:
     - uses: actions/checkout@v4

docs/source/install.rst

@@ -16,7 +16,7 @@ If, for some reason, you really need a custom installation,
 First, please make sure you have the execution system dependencies
 installed (see below).
 Second, the latest development version of MRIQC can be installed from
-github using ``pip`` on a Python 3 environment:
+github using ``pip`` on a Python 3 environment::
 
   python -m pip install -U mriqc
 

mriqc/__init__.py

@@ -28,6 +28,6 @@
 
 from mriqc._version import __version__
 
-__copyright__ = 'Copyright 2022, The NiPreps Developers'
+__copyright__ = 'Copyright 2016-2024, The NiPreps Developers'
 __download__ = f'https://github.com/nipreps/mriqc/archive/{__version__}.tar.gz'
 __all__ = ['__version__', '__copyright__', '__download__']

mriqc/bin/labeler.py

@@ -54,7 +54,7 @@ def main():
                 finished[j - 1] = finished[j - 1] + 1
                 hold[j - 1, i - 1] = int(file[i][j])
     finished = np.divide(np.round(np.divide(finished, total) * 1000), 10)
-    print(f"Completed: {' '.join(['%g%%' % f for f in finished])}")
+    print(f'Completed: {" ".join(["%g%%" % f for f in finished])}')
     print(f'Total: {np.round(np.divide(np.sum(finished), 3))}%')
     input('Waiting: [enter]')
 

mriqc/cli/parser.py

@@ -603,8 +603,8 @@ def parse_args(args=None, namespace=None):
         selected_label = set(config.execution.participant_label)
         if missing_subjects := selected_label - set(participant_label):
             parser.error(
-                "One or more participant labels were not found in the BIDS directory: "
-                f"{', '.join(missing_subjects)}."
+                'One or more participant labels were not found in the BIDS directory: '
+                f'{", ".join(missing_subjects)}.'
             )
         participant_label = selected_label
 

mriqc/instrumentation/resources.py

@@ -175,8 +175,8 @@ def run(self, *args, **kwargs):
 
         # Write headers (comment trace + header row)
         _header = [
-            f"# MRIQC Resource recorder started tracking PID {self._pid} "
-            f"{datetime.now(tz=UTC).strftime('(%Y/%m/%d; %H:%M:%S)')}",
+            f'# MRIQC Resource recorder started tracking PID {self._pid} '
+            f'{datetime.now(tz=UTC).strftime("(%Y/%m/%d; %H:%M:%S)")}',
             '\t'.join(('timestamp', *SAMPLE_ATTRS)).replace(
                 'memory_info', 'mem_rss_mb\tmem_vsm_mb'
             ),
@@ -198,8 +198,8 @@ def run(self, *args, **kwargs):
                 sample2file(self._pid, fd=_logfile, timestamp=wait_til)
             except psutil.NoSuchProcess:
                 print(
-                    f"# MRIQC Resource recorder killed "
-                    f"{datetime.now(tz=UTC).strftime('(%Y/%m/%d; %H:%M:%S)')}",
+                    f'# MRIQC Resource recorder finished '
+                    f'{datetime.now(tz=UTC).strftime("(%Y/%m/%d; %H:%M:%S)")}',
                     file=_logfile,
                 )
                 _logfile.flush()
@@ -216,6 +216,6 @@ def stop(self, *args):
         self._done.set()
         with Path(self._logfile).open('a') as f:
             f.write(
-                f"# MRIQC Resource recorder finished "
-                f"{datetime.now(tz=UTC).strftime('(%Y/%m/%d; %H:%M:%S)')}",
+                f'# MRIQC Resource recorder finished '
+                f'{datetime.now(tz=UTC).strftime("(%Y/%m/%d; %H:%M:%S)")}',
             )

mriqc/instrumentation/viz.py

@@ -45,7 +45,7 @@ def plot(filename, param='mem_vsm_mb', mask_processes=(), out_file=None):
     for pid in pids:
         pid_info = data[data['pid'] == pid]
         try:
-            label = f"{pid_info['name'].values[0]}"
+            label = f'{pid_info["name"].values[0]}'
         except KeyError:
             label = f'{pid}'
 

mriqc/interfaces/anatomical.py

@@ -124,8 +124,7 @@ def _run_interface(self, runtime):  # pylint: disable=R0914,E1101
 
         if np.sum(segdata > 0) < 1e3:
             raise RuntimeError(
-                'Input segmentation data is likely corrupt. '
-                'MRIQC failed to process this dataset.'
+                'Input segmentation data is likely corrupt. MRIQC failed to process this dataset.'
             )
 
         # Load air, artifacts and head masks

mriqc/interfaces/diffusion.py

@@ -27,6 +27,8 @@
 import nibabel as nb
 import numpy as np
 import scipy.ndimage as nd
+from dipy.core.gradients import gradient_table
+from dipy.stats.qc import find_qspace_neighbors
 from nipype.interfaces.base import (
     BaseInterfaceInputSpec as _BaseInterfaceInputSpec,
 )
@@ -339,7 +341,9 @@ def _run_interface(self, runtime):
         bvecs = np.loadtxt(self._results['out_bvec_file']).T
         bvals = np.loadtxt(self._results['out_bval_file'])
 
-        self._results['qspace_neighbors'] = _find_qspace_neighbors(bvals, bvecs)
+        gtab = gradient_table(bvals, bvecs=bvecs)
+
+        self._results['qspace_neighbors'] = find_qspace_neighbors(gtab)
         self._results['out_bmatrix'] = np.hstack((bvecs, bvals[:, np.newaxis])).tolist()
 
         return runtime
@@ -1386,80 +1390,6 @@ def get_spike_mask(
     return spike_mask
 
 
-def _find_qspace_neighbors(bvals: np.ndarray, bvecs: np.ndarray) -> list[tuple[int, int]]:
-    """
-    Create a mapping of dwi volume index to its nearest neighbor in q-space.
-
-    This function implements an approximate nearest neighbor search in q-space
-    (excluding delta encoding). It calculates the Cartesian distance between
-    q-space representations of each diffusion-weighted imaging (DWI) volume
-    (represented by b-values and b-vectors) and identifies the closest one
-    (excluding the volume itself and b=0 volumes).
-
-    Parameters
-    ----------
-    bvals : :obj:`~numpy.ndarray`
-        List of b-values.
-    bvecs : :obj:`~numpy.ndarray`
-        Table of b-vectors.
-
-    Returns
-    -------
-    :obj:`list` of :obj:`tuple`
-        A list of 2-tuples indicating the nearest q-space neighbor
-        of each dwi volume.
-
-    Examples
-    --------
-    >>> _find_qspace_neighbors(
-    ...     np.array([0, 1000, 1000, 2000]),
-    ...     np.array([
-    ...         [1, 0, 0],
-    ...         [1, 0, 0],
-    ...         [0.99, 0.0001, 0.0001],
-    ...         [1, 0, 0]
-    ...     ]),
-    ... )
-    [(1, 2), (2, 1), (3, 1)]
-
-    Notes
-    -----
-    This is a copy of DIPY's code to be removed (and just imported) as soon as
-    a new release of DIPY is cut including
-    `dipy/dipy#3156 <https://github.com/dipy/dipy/pull/3156>`__.
-
-    """
-    from dipy.core.geometry import cart_distance
-    from dipy.core.gradients import gradient_table
-
-    gtab = gradient_table(bvals, bvecs)
-
-    dwi_neighbors: list[tuple[int, int]] = []
-
-    # Only correlate the b>0 images
-    dwi_indices = np.flatnonzero(~gtab.b0s_mask)
-
-    # Get a pseudo-qspace value for b>0s
-    qvecs = np.sqrt(gtab.bvals)[:, np.newaxis] * gtab.bvecs
-
-    for dwi_index in dwi_indices:
-        qvec = qvecs[dwi_index]
-
-        # Calculate distance in q-space, accounting for symmetry
-        pos_dist = cart_distance(qvec[np.newaxis, :], qvecs)
-        neg_dist = cart_distance(qvec[np.newaxis, :], -qvecs)
-        distances = np.min(np.column_stack([pos_dist, neg_dist]), axis=1)
-
-        # Be sure we don't select the image as its own neighbor
-        distances[dwi_index] = np.inf
-        # Or a b=0
-        distances[gtab.b0s_mask] = np.inf
-        neighbor_index = np.argmin(distances)
-        dwi_neighbors.append((dwi_index, neighbor_index))
-
-    return dwi_neighbors
-
-
 def noise_piesno(data: np.ndarray, n_channels: int = 4) -> (np.ndarray, np.ndarray):
     """
     Estimates noise in raw diffusion MRI (dMRI) data using the PIESNO algorithm.

mriqc/utils/bids.py

@@ -68,7 +68,7 @@ def write_derivative_description(bids_dir, deriv_dir):
     if 'MRIQC_DOCKER_TAG' in os.environ:
         desc['GeneratedBy'][0]['Container'] = {
             'Type': 'docker',
-            'Tag': f"nipreps/mriqc:{os.environ['MRIQC_DOCKER_TAG']}",
+            'Tag': f'nipreps/mriqc:{os.environ["MRIQC_DOCKER_TAG"]}',
         }
     if 'MRIQC_SINGULARITY_URL' in os.environ:
         desc['GeneratedBy'][0]['Container'] = {
@@ -83,7 +83,7 @@ def write_derivative_description(bids_dir, deriv_dir):
         orig_desc = json.loads(fname.read_text())
 
     if 'Name' in orig_desc:
-        desc['Name'] = f"MRIQC - {orig_desc['Name']}"
+        desc['Name'] = f'MRIQC - {orig_desc["Name"]}'
     else:
         desc['Name'] = 'MRIQC - MRI Quality Control'
 
@@ -191,6 +191,6 @@ def derive_bids_fname(
         else:
             bidts.insert(position, entity.strip('_'))
 
-    retval = newpath / f"{'_'.join(bidts)}_{newsuffix}.{newext.strip('.')}"
+    retval = newpath / f'{"_".join(bidts)}_{newsuffix}.{newext.strip(".")}'
 
     return retval.absolute() if absolute else retval

mriqc/utils/misc.py

@@ -501,7 +501,7 @@ def initialize_meta_and_data(
 
         config.loggers.cli.log(
             25,
-            f"File size ('{mod}'): {_max_size:.2f}|{np.mean(size):.2f} " 'GB [maximum|average].',
+            f"File size ('{mod}'): {_max_size:.2f}|{np.mean(size):.2f} GB [maximum|average].",
         )
 
 

pyproject.toml

@@ -18,7 +18,7 @@ classifiers = [
 ]
 dependencies = [
   "acres",
-  "dipy",
+  "dipy >= 1.10.0",
   'importlib_resources; python_version < "3.9"', # jinja2 imports deprecated function removed in 2.1
   "markupsafe ~= 2.0.1",
   "matplotlib",
@@ -48,7 +48,7 @@ dynamic = ["version"]
 license = "Apache-2.0"
 name = "mriqc"
 readme = "README.rst"
-requires-python = ">=3.8"
+requires-python = ">=3.9"
 
 [project.urls]
 "Docker Images" = "https://hub.docker.com/r/nipreps/mriqc/tags/"