Resolve merge conflict in test_genetics.py - keep uncommented test

Author: zihuaihuai

.github/ISSUE_TEMPLATE/feature_request.md

@@ -1,6 +1,6 @@
 ---
 name: Feature request
-about: Suggest an idea for BrainSpace
+about: Suggest an idea for BrainStat
 title: ''
 labels: ''
 assignees: ''

.github/ISSUE_TEMPLATE/support-request.md

@@ -1,6 +1,6 @@
 ---
 name: Support request
-about: Ask for help running BrainSpace
+about: Ask for help running BrainStat
 title: ''
 labels: ''
 assignees: ''
@@ -9,7 +9,7 @@ assignees: ''
 
 * **What are you trying to do?**
 
-* **If you've tried running this with BrainSpace code already, how did you do so and what went wrong?**
+* **If you've tried running this with BrainStat code already, how did you do so and what went wrong?**
 
 * **Please tell us about your computing environment:**
 

.github/workflows/development_release.yml

@@ -13,10 +13,10 @@ jobs:
     steps:
     - uses: actions/checkout@v2
 
-    - name: Set up Python 3.8.
+    - name: Set up Python 3.10.
       uses: actions/setup-python@v2
       with:
-        python-version: 3.8
+        python-version: "3.10"
 
     - name: Install Python BrainStat.
       run: |

.github/workflows/python_unittests.yml

@@ -11,7 +11,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.9, '3.10', '3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12']
         os: [ubuntu-latest, windows-latest, macos-latest]
 
     runs-on: ${{ matrix.os }}

.github/workflows/tagged_release.yml

@@ -13,10 +13,10 @@ jobs:
     steps:
     - uses: actions/checkout@v2
 
-    - name: Set up Python 3.8.
+    - name: Set up Python 3.10.
       uses: actions/setup-python@v2
       with:
-        python-version: 3.8
+        python-version: "3.10"
 
     - name: Install MATLAB
       uses: matlab-actions/setup-matlab@v0

brainstat/_utils.py

@@ -150,7 +150,7 @@ def deprecated_func(*args, **kwargs):
 def _download_file(
     url: str, output_file: Path, overwrite: bool = False, verbose=True
 ) -> None:
-    """Downloads a file.
+    """Downloads a file with retry logic for network failures.
 
     Parameters
     ----------
@@ -163,14 +163,39 @@ def _download_file(
     verbose : bool
         If true, print a download message, defaults to True.
     """
+    import time
+    from http.client import RemoteDisconnected
+    from urllib.error import URLError
 
     if output_file.exists() and not overwrite:
         return
 
     if verbose:
         logger.info("Downloading " + str(output_file) + " from " + url + ".")
-    with urllib.request.urlopen(url) as response, open(output_file, "wb") as out_file:
-        shutil.copyfileobj(response, out_file)
+    
+    # Retry logic for intermittent network failures
+    max_retries = 3
+    retry_delay = 2  # seconds
+    
+    for attempt in range(max_retries):
+        try:
+            with urllib.request.urlopen(url, timeout=30) as response, open(output_file, "wb") as out_file:
+                shutil.copyfileobj(response, out_file)
+            return  # Success, exit function
+        except (RemoteDisconnected, URLError, TimeoutError) as e:
+            if attempt < max_retries - 1:
+                logger.warning(
+                    f"Download attempt {attempt + 1}/{max_retries} failed: {e}. "
+                    f"Retrying in {retry_delay} seconds..."
+                )
+                time.sleep(retry_delay)
+                retry_delay *= 2  # Exponential backoff
+            else:
+                logger.error(f"Download failed after {max_retries} attempts.")
+                raise  # Re-raise the exception after all retries fail
+
+
+
 
 
 if __name__ == "__main__":

brainstat/context/genetics.py

@@ -127,7 +127,7 @@ def surface_genetic_expression(
                 with tempfile.NamedTemporaryFile(suffix=".gii", delete=False) as f:
                     name = f.name
                     write_surface(surface, name, otype="gii")
-                surfaces_gii.append(nib.load(name))
+                    surfaces_gii.append(nib.load(name))
             finally:
                 Path(name).unlink()
         else:

brainstat/context/histology.py

@@ -157,6 +157,15 @@ def read_histology_profile(
 
     with h5py.File(histology_file, "r") as h5_file:
         if template == "fslr32k":
+            # Known issue #369: The fslr32k data file on the server actually contains
+            # fs_LR_64k resolution data (64984 vertices) instead of fs_LR_32k (32492 vertices).
+            # This is a data hosting issue. Users expecting 32k resolution data should be aware
+            # that they will receive 64k resolution data until this is fixed on the server.
+            logger.warning(
+                "Known issue: The fslr32k histology profile data currently contains "
+                "fs_LR_64k resolution (64984 vertices) instead of fs_LR_32k (32492 vertices). "
+                "See https://github.com/MICA-MNI/BrainStat/issues/369 for details."
+            )
             profiles = h5_file.get("fs_LR_64k")[...]
         else:
             profiles = h5_file.get(template)[...]
@@ -196,6 +205,12 @@ def download_histology_profiles(
     data_dir.mkdir(parents=True, exist_ok=True)
     if template == "fslr32k":
         output_file = data_dir / "histology_fslr32k.h5"
+        # Known issue #369: warn users about data resolution mismatch
+        logger.warning(
+            "Note: The fslr32k histology profile data currently contains "
+            "fs_LR_64k resolution (64984 vertices) instead of fs_LR_32k. "
+            "See https://github.com/MICA-MNI/BrainStat/issues/369 for details."
+        )
     else:
         output_file = data_dir / ("histology_" + template + ".h5")
 

brainstat/datasets/base.py

@@ -1,6 +1,8 @@
 """ Load external datasets. """
+import json
 import tempfile
 import zipfile
+from collections import namedtuple
 from pathlib import Path
 from typing import List, Optional, Tuple, Union
 
@@ -11,9 +13,19 @@
 from brainspace.mesh.mesh_operations import combine_surfaces
 from brainspace.vtk_interface.wrappers.data_object import BSPolyData
 from netneurotools import datasets as nnt_datasets
-from netneurotools.civet import read_civet
 from nibabel import load as nib_load
 from nibabel.freesurfer.io import read_annot, read_geometry
+from sklearn.utils import Bunch
+
+try:
+    from netneurotools.datasets.utils import _get_data_dir, _get_dataset_info
+except ImportError:
+    from netneurotools.datasets.datasets_utils import _get_data_dir, _get_dataset_info
+
+try:
+    from nilearn.datasets._utils import fetch_files as _fetch_files
+except ImportError:
+    from nilearn.datasets.utils import fetch_files as _fetch_files
 
 from brainstat._utils import (
     _download_file,
@@ -24,6 +36,65 @@
 from brainstat.mesh.interpolate import _surf2surf
 
 
+def read_civet(fname: Union[str, Path]) -> Tuple[np.ndarray, np.ndarray]:
+    """
+    Reads a CIVET surface file (MNI OBJ format).
+
+    Parameters
+    ----------
+    fname : str or Path
+        Path to the CIVET surface file.
+
+    Returns
+    -------
+    vertices : numpy.ndarray
+        (N, 3) array of vertex coordinates.
+    faces : numpy.ndarray
+        (M, 3) array of face indices.
+    """
+    fname = str(fname)
+    with open(fname, "rb") as f:
+        first_char = f.read(1)
+
+    if first_char == b"P":
+        with open(fname, "r") as f:
+            content = f.read().split()
+
+        n_vertices = int(content[6])
+
+        idx = 7
+        # Vertices
+        vertices = np.array(content[idx : idx + n_vertices * 3], dtype=float).reshape(
+            -1, 3
+        )
+        idx += n_vertices * 3
+
+        # Normals
+        idx += n_vertices * 3
+
+        n_triangles = int(content[idx])
+        idx += 1
+
+        color_flag = int(content[idx])
+        idx += 1
+
+        if color_flag == 0:
+            idx += 4
+        else:
+            idx += n_vertices * 4
+
+        # Check remaining items to decide if we need to skip
+        remaining = len(content) - idx
+        if remaining == n_triangles * 3 + n_triangles:
+            idx += n_triangles
+
+        triangles = np.array(content[idx:], dtype=int).reshape(-1, 3)
+
+        return vertices, triangles
+    else:
+        raise NotImplementedError("Binary CIVET files are not supported yet.")
+
+
 def fetch_parcellation(
     template: str,
     atlas: str,
@@ -147,7 +218,7 @@ def fetch_template_surface(
         surfaces_fs = [read_geometry(file) for file in surface_files]
         surfaces = [build_polydata(surface[0], surface[1]) for surface in surfaces_fs]
     elif template == "fslr32k":
-        surfaces = [read_surface(file) for file in surface_files]
+        surfaces = [read_surface(str(file)) for file in surface_files]
     else:
         surfaces_obj = [read_civet(file) for file in surface_files]
         surfaces = [build_polydata(surface[0], surface[1]) for surface in surfaces_obj]
@@ -384,7 +455,7 @@ def _fetch_template_surface_files(
 
     if template == "fslr32k":
         layer = layer if layer else "midthickness"
-        bunch = nnt_datasets.fetch_conte69(data_dir=str(data_dir))
+        bunch = _fetch_conte69_fixed(data_dir=str(data_dir))
     elif template == "civet41k" or template == "civet164k":
         layer = layer if layer else "mid"
         if layer == "sphere":
@@ -515,3 +586,43 @@ def _fetch_civet_spheres(template: str, data_dir: Path) -> Tuple[str, str]:
 
     # Return two filenames to conform to other left/right hemisphere functions.
     return (str(filename), str(filename))
+
+
+SURFACE = namedtuple('Surface', ('lh', 'rh'))
+
+
+def _fetch_conte69_fixed(data_dir=None, url=None, resume=True, verbose=1):
+    """
+    Download files for Van Essen et al., 2012 Conte69 template.
+    Fixed version to handle encoding on Windows.
+    """
+    dataset_name = 'tpl-conte69'
+    keys = ['midthickness', 'inflated', 'vinflated']
+
+    data_dir = _get_data_dir(data_dir=data_dir)
+    info = _get_dataset_info(dataset_name)
+    if url is None:
+        url = info['url']
+
+    opts = {
+        'uncompress': True,
+        'md5sum': info['md5'],
+        'move': '{}.tar.gz'.format(dataset_name)
+    }
+
+    filenames = [
+        'tpl-conte69/tpl-conte69_space-MNI305_variant-fsLR32k_{}.{}.surf.gii'
+        .format(res, hemi) for res in keys for hemi in ['L', 'R']
+    ] + ['tpl-conte69/template_description.json']
+
+    data = _fetch_files(data_dir, files=[(f, url, opts) for f in filenames],
+                        resume=resume, verbose=verbose)
+
+    # Fix: Specify encoding='utf-8'
+    with open(data[-1], 'r', encoding='utf-8') as src:
+        data[-1] = json.load(src)
+
+    # bundle hemispheres together
+    data = [SURFACE(*data[:-1][i:i + 2]) for i in range(0, 6, 2)] + [data[-1]]
+
+    return Bunch(**dict(zip(keys + ['info'], data)))

brainstat/stats/_linear_model.py

@@ -442,7 +442,9 @@ def _compute_resls(self, Y: np.ndarray) -> Tuple[np.ndarray, dict]:
     for j in range(Y.shape[2]):
         normr = np.sqrt(self.SSE[((j + 1) * (j + 2) // 2) - 1])
         for i in range(Y.shape[0]):
-            u = Y[i, :, j] / normr
+            u = np.divide(
+                Y[i, :, j], normr, out=np.zeros_like(Y[i, :, j]), where=normr != 0
+            )
             resl[:, j] += np.diff(u[edges], axis=1).ravel() ** 2
 
     return resl, mesh_connections