freesurfer

FreeSurfer data.

Classes:

• FreeSurfer –

  Base class for FreeSurfer data.

Functions:

• get_freesurfer_colormap –

  Generate matplotlib colormap from FreeSurfer LUT.

FreeSurfer

FreeSurfer(freesurfer_home: str | Path | None = None, subjects_dir: str | Path | None = None, log_level: str = 'INFO')

Base class for FreeSurfer data.

Parameters:

• freesurfer_home

  (str or ``Path`` representing a path to a directory, default: None ) –

  Path corresponding to FREESURFER_HOME env var.

• subjects_dir

  (str or ``Path`` representing a path to a directory, default: None ) –

  Path corresponding to SUBJECTS_DIR env var.

• log_level

  (str, default: 'INFO' ) –

  Logging level (e.g., "INFO", "DEBUG", "WARNING"). Default is "INFO".

Returns:

• None –

Methods:

• check_recon_all –

  Verify that the subject's FreeSurfer recon finished successfully.

• gen_aparcaseg_plots –

  Generate parcellation images (aparc & aseg) and return the path to the aparcaseg.png file.

• gen_batch_reports –

  Generate HTML reports with images for multiple subjects.

• gen_group_report –

  Generate a group report with outlier information for multiple subjects.

• gen_html_report –

  Generate html report with FreeSurfer images.

• gen_surf_plots –

  Generate pial, inflated, and sulcal images from various viewpoints.

• gen_tlrc_data –

  Generate inverse talairach data for report generation.

• gen_tlrc_report –

  Generate a before and after report of Talairach registration. (Will also run file generation if needed).

• get_colormap –

  Return the colormap for the FreeSurfer data.

• get_subjects –

  Return FreeSurfer subjects found in a directory.

• resolve_groups –

  Resolve group definitions to subject ID lists from FreeSurfer directories.

• subject_summary –

  Collect a compact individual-report summary from the subject tree.

Attributes:

• freesurfer_home –

  Path to the FreeSurfer home directory.

• logger –

  Logger for the FreeSurfer class.

• subjects_dir –

  Path to the subjects directory.

Source code in src/pyfsviz/freesurfer.py

def __init__(
    self,
    freesurfer_home: str | Path | None = None,
    subjects_dir: str | Path | None = None,
    log_level: str = "INFO",
):
    """Initialize the FreeSurfer data.

    Parameters
    ----------
    freesurfer_home : str or ``Path`` representing a path to a directory
        Path corresponding to FREESURFER_HOME env var.
    subjects_dir : str or ``Path`` representing a path to a directory
        Path corresponding to SUBJECTS_DIR env var.
    log_level : str
        Logging level (e.g., "INFO", "DEBUG", "WARNING").
        Default is "INFO".

    Returns
    -------
    None

    """
    # Set up logger
    logging.basicConfig(level=getattr(logging, log_level.upper()))
    self.logger = logging.getLogger(f"{__name__}.{self.__class__.__name__}")
    """Logger for the FreeSurfer class."""

    if freesurfer_home is None:
        self.freesurfer_home = Path(os.environ.get("FREESURFER_HOME") or "")
        """Path to the FreeSurfer home directory."""
    else:
        self.freesurfer_home = Path(freesurfer_home)

    if not self.freesurfer_home.exists():
        raise FileNotFoundError(
            f"FREESURFER_HOME not found: {self.freesurfer_home}",
        )
    if self.freesurfer_home is None:
        raise ValueError("FREESURFER_HOME must be set")

    if subjects_dir is None:
        self.subjects_dir = Path(os.environ.get("SUBJECTS_DIR") or "")
        """Path to the subjects directory."""
    elif isinstance(subjects_dir, Path):
        self.subjects_dir = subjects_dir
        if not self.subjects_dir.exists():
            raise FileNotFoundError(f"SUBJECTS_DIR not found: {self.subjects_dir}")
        os.environ["SUBJECTS_DIR"] = str(subjects_dir)
        """Path to the subjects directory."""
    else:
        self.subjects_dir = Path(subjects_dir)
        if not self.subjects_dir.exists():
            raise FileNotFoundError(f"SUBJECTS_DIR not found: {self.subjects_dir}")
        os.environ["SUBJECTS_DIR"] = subjects_dir
        """Path to the subjects directory."""

    self._mni_nii = files("pyfsviz._internal") / "mni305.cor.nii.gz"
    """Path to the MNI template NIfTI file."""
    self._mni_mgz = files("pyfsviz._internal") / "mni305.cor.mgz"
    """Path to the MNI template MGH file."""

freesurfer_home instance-attribute

freesurfer_home = Path(os.environ.get('FREESURFER_HOME') or '')

Path to the FreeSurfer home directory.

logger instance-attribute

logger = logging.getLogger(f'{__name__}.{self.__class__.__name__}')

Logger for the FreeSurfer class.

subjects_dir instance-attribute

subjects_dir = Path(os.environ.get('SUBJECTS_DIR') or '')

Path to the subjects directory.

check_recon_all

check_recon_all(subject: str) -> bool

Verify that the subject's FreeSurfer recon finished successfully.

Source code in src/pyfsviz/freesurfer.py

def check_recon_all(self, subject: str) -> bool:
    """Verify that the subject's FreeSurfer recon finished successfully."""
    recon_file = self.subjects_dir / subject / "scripts" / "recon-all.log"

    if not recon_file:
        return False

    with open(recon_file, encoding="utf-8") as f:
        line = f.readlines()[-1]
        return "finished without error" in line

gen_aparcaseg_plots

gen_aparcaseg_plots(subject: str, output_dir: str) -> Path

Generate parcellation images (aparc & aseg) and return the path to the aparcaseg.png file.

Parameters:

• subject

  (str) –

  Subject ID.

• output_dir

  (str) –

  Path to output directory.

Returns:

• Path ( Path ) –

  Path to the aparcaseg.png file.

Examples:

>>> from pyfsviz.freesurfer import FreeSurfer
>>> fs_dir = FreeSurfer(
...     freesurfer_home="/opt/freesurfer",
...     subjects_dir="/opt/data",
... )
>>> images = fs_dir.gen_aparcaseg_plots("sub-001", "/opt/data/reports/sub-001")

Source code in src/pyfsviz/freesurfer.py

def gen_aparcaseg_plots(self, subject: str, output_dir: str) -> Path:
    """Generate parcellation images (aparc & aseg) and return the path to the aparcaseg.png file.

    Parameters
    ----------
    subject : str
        Subject ID.
    output_dir : str
        Path to output directory.

    Returns
    -------
    Path:
        Path to the aparcaseg.png file.

    Examples
    --------
    >>> from pyfsviz.freesurfer import FreeSurfer
    >>> fs_dir = FreeSurfer(
    ...     freesurfer_home="/opt/freesurfer",
    ...     subjects_dir="/opt/data",
    ... )
    >>> images = fs_dir.gen_aparcaseg_plots("sub-001", "/opt/data/reports/sub-001")
    """
    fsqc.run_fsqc(
        subjects_dir=str(self.subjects_dir),
        output_dir=output_dir,
        subjects=[subject],
        screenshots=True,
        screenshots_overlay="aparc+aseg.mgz",
        screenshots_views=[
            "x=-40",
            "x=-30",
            "x=-20",
            "x=-10",
            "x=0",
            "x=10",
            "x=20",
            "x=30",
            "x=40",
            "y=-40",
            "y=-30",
            "y=-20",
            "y=-10",
            "y=0",
            "y=10",
            "y=20",
            "y=30",
            "y=40",
            "z=-40",
            "z=-30",
            "z=-20",
            "z=-10",
            "z=0",
            "z=10",
            "z=20",
            "z=30",
            "z=40",
        ],
        screenshots_layout=["3", "9"],
        no_group=True,
    )

    # Clean up/move files
    shutil.move(
        f"{output_dir}/screenshots/{subject}/{subject}.png",
        f"{output_dir}/aparcaseg.png",
    )
    shutil.rmtree(f"{output_dir}/screenshots")
    shutil.rmtree(f"{output_dir}/status")
    shutil.rmtree(f"{output_dir}/metrics")

    return Path(f"{output_dir}/aparcaseg.png")

gen_batch_reports

gen_batch_reports(output_dir: str | Path, subjects: list[str] | None = None, template: str | None = None, *, gen_images: bool = True, skip_failed: bool = True, skip_existing: bool = False) -> dict[str, Path | Exception]

Generate HTML reports with images for multiple subjects.

This method first generates all required images (TLRC, aparc+aseg, surfaces) and then creates HTML reports for each subject.

Parameters:

• output_dir

  (str or Path) –

  Directory where HTML reports will be saved.

• subjects

  (list[str] or None, default: None ) –

  List of subject IDs to process. If None, processes all subjects in the subjects directory.

• template

  (str or None, default: None ) –

  HTML template to use. Default is local individual.html.

• gen_images

  (bool, default: True ) –

  Generate images for each subject. Default is True.

• skip_failed

  (bool, default: True ) –

  If True, continues processing other subjects if one fails. If False, raises exception on first failure.

• skip_existing

  (bool, default: False ) –

  If True, skip subjects that already have an HTML report at {output_dir}/{subject}/{subject}.html. Incomplete subjects (images but no report) are still processed. Default is False.

Returns:

• dict[str, Path | Exception] –

  Dictionary mapping subject IDs to either the generated (or existing) HTML file path or the exception that occurred during processing.

Examples:

>>> from pyfsviz.freesurfer import FreeSurfer
>>> fs = FreeSurfer()
>>> results = fs.gen_batch_reports("reports/")
>>> for subject, result in results.items():
...     if isinstance(result, Path):
...         print(f"Generated report for {subject}: {result}")
...     else:
...         print(f"Failed to generate report for {subject}: {result}")

Source code in src/pyfsviz/freesurfer.py

def gen_batch_reports(
    self,
    output_dir: str | Path,
    subjects: list[str] | None = None,
    template: str | None = None,
    *,
    gen_images: bool = True,
    skip_failed: bool = True,
    skip_existing: bool = False,
) -> dict[str, Path | Exception]:
    """Generate HTML reports with images for multiple subjects.

    This method first generates all required images (TLRC, aparc+aseg, surfaces)
    and then creates HTML reports for each subject.

    Parameters
    ----------
    output_dir : str or Path
        Directory where HTML reports will be saved.
    subjects : list[str] or None
        List of subject IDs to process. If None, processes all subjects
        in the subjects directory.
    template : str or None
        HTML template to use. Default is local individual.html.
    gen_images : bool
        Generate images for each subject. Default is True.
    skip_failed : bool
        If True, continues processing other subjects if one fails.
        If False, raises exception on first failure.
    skip_existing : bool
        If True, skip subjects that already have an HTML report at
        ``{output_dir}/{subject}/{subject}.html``. Incomplete subjects
        (images but no report) are still processed. Default is False.

    Returns
    -------
    dict[str, Path | Exception]
        Dictionary mapping subject IDs to either the generated (or existing)
        HTML file path or the exception that occurred during processing.

    Examples
    --------
    >>> from pyfsviz.freesurfer import FreeSurfer
    >>> fs = FreeSurfer()
    >>> results = fs.gen_batch_reports("reports/")
    >>> for subject, result in results.items():
    ...     if isinstance(result, Path):
    ...         print(f"Generated report for {subject}: {result}")
    ...     else:
    ...         print(f"Failed to generate report for {subject}: {result}")
    """
    output_dir = Path(output_dir)
    output_dir.mkdir(parents=True, exist_ok=True)

    if subjects is None:
        subjects = self.get_subjects()

    self.logger.info(
        f"Generating reports with images for {len(subjects)} subjects...",
    )
    self.logger.info(f"Output directory: {output_dir}")

    results: dict[str, Path | Exception] = {}
    skipped = 0

    for i, subject in enumerate(subjects, 1):
        existing_html = output_dir / subject / f"{subject}.html"
        if skip_existing and existing_html.is_file():
            self.logger.info(
                f"[{i}/{len(subjects)}] Skipping {subject}: report already exists",
            )
            results[subject] = existing_html
            skipped += 1
            continue

        self.logger.info(f"[{i}/{len(subjects)}] Processing subject: {subject}")

        try:
            # Check if recon-all completed successfully
            if not self.check_recon_all(subject):
                self.logger.warning(
                    f"Subject {subject} recon-all did not complete successfully",
                )

            # Create subject-specific output directory for images
            subject_output_dir = output_dir / subject
            subject_output_dir.mkdir(parents=True, exist_ok=True)

            # Generate images
            self.logger.info(f"  Generating images for {subject}...")

            img_list = []
            if gen_images:
                # Generate TLRC data and report
                # Use a temporary subdirectory for intermediate files
                temp_tlrc_dir = subject_output_dir / "tlrc_temp"
                temp_tlrc_dir.mkdir(exist_ok=True)

                self.gen_tlrc_data(subject, str(temp_tlrc_dir))
                tlrc = Path(self.gen_tlrc_report(subject, str(temp_tlrc_dir)))

                # Move tlrc.svg to subject directory
                if tlrc.exists():
                    new_tlrc_path = subject_output_dir / "tlrc.svg"
                    tlrc.rename(new_tlrc_path)
                    img_list.append(new_tlrc_path)
                else:
                    img_list.append(tlrc)

                # Clean up intermediate files
                shutil.rmtree(temp_tlrc_dir, ignore_errors=True)

                # Generate aparc+aseg plots - save directly to subject directory
                aparcaseg = self.gen_aparcaseg_plots(
                    subject,
                    str(subject_output_dir),
                )
                img_list.append(aparcaseg)

                # Generate surface plots - save directly to subject directory
                surf = self.gen_surf_plots(subject, str(subject_output_dir))
                img_list.extend(surf)
            else:
                img_list = _report_image_files(subject_output_dir)

            # Generate HTML report using all generated images
            html_file = self.gen_html_report(
                subject=subject,
                output_dir=str(output_dir),
                img_list=img_list,
                template=template,
            )

            results[subject] = html_file

            self.logger.info(f"  ✓ Generated report with images: {html_file}")

        except Exception as e:
            error_msg = f"Failed to generate report with images for {subject}: {e!s}"
            results[subject] = e

            self.logger.error(f"  ✗ {error_msg}")  # noqa: TRY400

            if not skip_failed:
                raise e  # noqa: TRY201 # pylint: disable=try-except-raise

    successful = sum(1 for result in results.values() if isinstance(result, Path)) - skipped
    failed = len(results) - successful - skipped
    self.logger.info("\nBatch report generation with images completed:")
    self.logger.info(f"  Successful: {successful}")
    self.logger.info(f"  Skipped: {skipped}")
    self.logger.info(f"  Failed: {failed}")

    return results

gen_group_report

gen_group_report(output_dir: str | Path, subjects: list[str] | None = None, groups: _GroupDefinition | None = None, template: str | None = None, *, sd_threshold: float = 3.0) -> Path

Generate a group report with outlier information for multiple subjects.

Parameters:

• output_dir

  (str or Path) –

  Directory where HTML report will be saved.

• subjects

  (list[str] | None, default: None ) –

  List of subject IDs to process. If None, processes all subjects in the subjects directory.

• groups

  (_GroupDefinition | None, default: None ) –

  Optional group definitions for between-group box plots. Each group can be a list of subject IDs or a FreeSurfer directory to scan:

  • ["control", "patient"] scans subjects_dir/control and subjects_dir/patient
  • {"control": None, "patient": None} same as above
  • {"control": "/path/to/control_cohort"} scans an explicit path
  • {"control": ["sub-001"]} uses explicit subject IDs

• template

  (str | None, default: None ) –

  HTML template to use. Default is local group.html.

• sd_threshold

  (float, default: 3.0 ) –

  Standard deviation threshold for outlier detection. Default is 3.0.

Returns:

• Path ( Path ) –

  Path to html file.

Source code in src/pyfsviz/freesurfer.py

def gen_group_report(
    self,
    output_dir: str | Path,
    subjects: list[str] | None = None,
    groups: _GroupDefinition | None = None,
    template: str | None = None,
    *,
    sd_threshold: float = 3.0,
) -> Path:
    """Generate a group report with outlier information for multiple subjects.

    Parameters
    ----------
    output_dir : str or Path
        Directory where HTML report will be saved.
    subjects : list[str] | None
        List of subject IDs to process. If None, processes all subjects
        in the subjects directory.
    groups : _GroupDefinition | None
        Optional group definitions for between-group box plots. Each group
        can be a list of subject IDs or a FreeSurfer directory to scan:

        - ``["control", "patient"]`` scans ``subjects_dir/control`` and
          ``subjects_dir/patient``
        - ``{"control": None, "patient": None}`` same as above
        - ``{"control": "/path/to/control_cohort"}`` scans an explicit path
        - ``{"control": ["sub-001"]}`` uses explicit subject IDs
    template : str | None
        HTML template to use. Default is local group.html.
    sd_threshold : float
        Standard deviation threshold for outlier detection. Default is 3.0.

    Returns
    -------
    Path:
        Path to html file.
    """
    output_dir = Path(output_dir)
    output_dir.mkdir(parents=True, exist_ok=True)

    group_search_dirs: dict[str, Path] | None = None
    resolved_groups: dict[str, list[str]] | None = None
    if groups is not None:
        if subjects is not None:
            self.logger.warning(
                "Both subjects and groups were provided; using subjects from groups",
            )
        group_search_dirs = self._group_search_dirs(groups)
        resolved_groups = self.resolve_groups(groups)
        subjects = [subject for group_subjects in resolved_groups.values() for subject in group_subjects]
    elif subjects is None or len(subjects) < 1:
        subjects = self.get_subjects()

    self.logger.info(f"Generating group report for {len(subjects)} subjects...")
    if resolved_groups:
        for group_name, group_subjects in resolved_groups.items():
            self.logger.info(
                f"  Group {group_name}: {len(group_subjects)} subject(s)",
            )
    self.logger.info(f"Output directory: {output_dir}")

    stats_files = self._collect_group_stats_files(
        output_dir,
        subjects,
        resolved_groups,
        group_search_dirs,
    )

    # Generate plots
    metric_figures = gen_metric_plots(stats_files)
    comparison_figures = gen_group_comparison_plots(stats_files, resolved_groups) if resolved_groups else []
    comparison_plots = _plot_sections(
        comparison_figures,
        prefix="cmp",
        include_plotlyjs_first=bool(comparison_figures),
    )
    plot_sections = _plot_sections(
        metric_figures,
        prefix="plots",
        include_plotlyjs_first=not comparison_figures,
    )
    plot_htmls = [html for section in plot_sections for html in section["plots"]]

    quality_summary = check_metrics(stats_files, sd_threshold=sd_threshold)
    quality_sections = _quality_summary_sections(quality_summary)
    outlier_subjects = summarize_outlier_subjects(quality_summary)

    # Prepare template config
    if template is None:
        template = str(files("pyfsviz._internal.html") / "group.html")

    _config = {
        "timestamp": datetime.datetime.now(tz=datetime.timezone.utc).strftime(
            "%Y-%m-%d, %H:%M",
        ),
        "subjects": subjects,
        "num_subjects": len(subjects),
        "groups": resolved_groups,
        "quality_summary": quality_summary,
        "quality_sections": quality_sections,
        "outlier_subjects": outlier_subjects,
        "plots": plot_htmls,
        "plot_sections": plot_sections,
        "comparison_plots": comparison_plots,
        "sd_threshold": sd_threshold,
    }

    # Generate HTML file
    html_file = output_dir / "group_report.html"
    tpl = Template(str(template))
    tpl.generate_conf(_config, str(html_file))

    self.logger.info(f"✓ Generated group report: {html_file}")
    return html_file

gen_html_report

gen_html_report(subject: str, output_dir: str, img_list: list[Path] | None = None, template: str | None = None) -> Path

Generate html report with FreeSurfer images.

Parameters:

• subject

  (str) –

  Subject ID.

• output_dir

  (str) –

  HTML file name

• img_list

  (list[Path] | None, default: None ) –

  List of image paths (PNG format).

• template

  (str | None, default: None ) –

  HTML template to use. Default is local freesurfer.html.

Returns:

• Path ( Path ) –

  Path to html file.

Examples:

>>> from pyfsviz.freesurfer import FreeSurfer
>>> fs_dir = FreeSurfer(
...     freesurfer_home="/opt/freesurfer",
...     subjects_dir="/opt/data",
... )
>>> report = fs_dir.gen_html_report("sub-001", "/opt/data/reports")

Source code in src/pyfsviz/freesurfer.py

def gen_html_report(
    self,
    subject: str,
    output_dir: str,
    img_list: list[Path] | None = None,
    template: str | None = None,
) -> Path:
    """Generate html report with FreeSurfer images.

    Parameters
    ----------
    subject : str
        Subject ID.
    output_dir : str
        HTML file name
    img_list : list[Path] | None
        List of image paths (PNG format).
    template : str | None
        HTML template to use. Default is local freesurfer.html.

    Returns
    -------
    Path:
        Path to html file.

    Examples
    --------
    >>> from pyfsviz.freesurfer import FreeSurfer
    >>> fs_dir = FreeSurfer(
    ...     freesurfer_home="/opt/freesurfer",
    ...     subjects_dir="/opt/data",
    ... )
    >>> report = fs_dir.gen_html_report("sub-001", "/opt/data/reports")
    """
    if template is None:
        template = str(files("pyfsviz._internal.html") / "individual.html")
    if img_list is None:
        img_list = _report_image_files(self.subjects_dir / subject)

    tlrc = []
    aseg = []
    surf = []

    output_path = Path(output_dir)
    output_path.mkdir(parents=True, exist_ok=True)

    # Subject-specific directory
    subject_dir = output_path / subject
    subject_dir.mkdir(parents=True, exist_ok=True)

    for img in img_list:
        if "tlrc" in img.name and img.suffix == ".svg":
            # Read SVG content directly for embedding
            with open(img, encoding="utf-8") as f:
                svg_content = f.read()
            tlrc.append(svg_content)
        # Images are already in the subject directory, just reference by filename
        elif "aparcaseg" in img.name:
            aseg.append(img.name)
        elif "aparc_legend" in img.stem:
            continue
        else:
            labels = {
                "lh_pial": "LH Pial",
                "rh_pial": "RH Pial",
                "lh_infl": "LH Inflated",
                "rh_infl": "RH Inflated",
                "lh_white": "LH White Matter",
                "rh_white": "RH White Matter",
            }
            surface_type = img.stem
            surf_tuple = (labels.get(surface_type, surface_type), img.name)
            surf.append(surf_tuple)

    summary = self.subject_summary(subject)
    summary["generated_at"] = datetime.datetime.now(tz=datetime.timezone.utc).strftime(
        "%Y-%m-%d, %H:%M",
    )

    _config = {
        "timestamp": summary["generated_at"],
        "subject": subject,
        "summary": summary,
        "tlrc": tlrc,
        "aseg": aseg,
        "surf": surf,
    }

    # Save HTML file in subject directory
    html_file = subject_dir / f"{subject}.html"
    tpl = Template(str(template))
    tpl.generate_conf(_config, str(html_file))

    return html_file

gen_surf_plots

gen_surf_plots(subject: str, output_dir: str) -> list[Path]

Generate pial, inflated, and sulcal images from various viewpoints.

Parameters:

• output_dir

  (str) –

  Surface plot output directory.

Returns:

• list[Path]: –

  List of generated PNG images

Examples:

>>> from pyfsviz.freesurfer import FreeSurfer
>>> fs_dir = FreeSurfer(
...     freesurfer_home="/opt/freesurfer",
...     subjects_dir="/opt/data",
... )
>>> images = fs_dir.gen_surf_plots("sub-001", "/opt/data/reports/sub-001")

Source code in src/pyfsviz/freesurfer.py

def gen_surf_plots(self, subject: str, output_dir: str) -> list[Path]:
    """Generate pial, inflated, and sulcal images from various viewpoints.

    Parameters
    ----------
    output_dir : str
        Surface plot output directory.

    Returns
    -------
    list[Path]:
        List of generated PNG images

    Examples
    --------
    >>> from pyfsviz.freesurfer import FreeSurfer
    >>> fs_dir = FreeSurfer(
    ...     freesurfer_home="/opt/freesurfer",
    ...     subjects_dir="/opt/data",
    ... )
    >>> images = fs_dir.gen_surf_plots("sub-001", "/opt/data/reports/sub-001")
    """
    surf_dir = f"{self.subjects_dir}/{subject}/surf"
    label_dir = f"{self.subjects_dir}/{subject}/label"
    generated: list[Path] = []

    hemis = {"lh": "left", "rh": "right"}
    for key, val in hemis.items():
        pial = f"{surf_dir}/{key}.pial"
        inflated = f"{surf_dir}/{key}.inflated"
        sulc = f"{surf_dir}/{key}.sulc"
        white = f"{surf_dir}/{key}.white"
        annot = f"{label_dir}/{key}.aparc.annot"
        cmap_info = _aparc_surf_cmap(Path(annot))
        if cmap_info is None:
            cmap: colors.Colormap = self.get_colormap()
            vmin: float | None = None
            vmax: float | None = None
        else:
            cmap, n_colors = cmap_info
            vmin, vmax = 0.0, float(n_colors)

        label_files = {pial: "pial", inflated: "infl", white: "white"}

        for surf, label in label_files.items():
            fig, axs = plt.subplots(2, 3, subplot_kw={"projection": "3d"})
            for view, row, col in _SURF_VIEWS:
                plotting.plot_surf_roi(
                    surf,
                    annot,
                    hemi=val,
                    view=view,
                    bg_map=sulc,
                    bg_on_data=True,
                    darkness=1,
                    cmap=cmap,
                    vmin=vmin,
                    vmax=vmax,
                    axes=axs[row, col],
                    figure=fig,
                    colorbar=False,
                )

            out_file = Path(output_dir) / f"{key}_{label}.png"
            plt.savefig(out_file, dpi=300, format="png")
            plt.close()
            generated.append(out_file)

    return sorted(generated)

gen_tlrc_data

gen_tlrc_data(subject: str, output_dir: str) -> None

Generate inverse talairach data for report generation.

Parameters:

• output_dir

  (str) –

  Path for intermediate file output.

Examples:

>>> from pyfsviz.freesurfer import FreeSurfer
>>> fs_dir = FreeSurfer(
...     freesurfer_home="/opt/freesurfer",
...     subjects_dir="/opt/data",
... )
>>> fs_dir.gen_tlrc_data("sub-001", "/opt/data/sub-001/mri/transforms")

Source code in src/pyfsviz/freesurfer.py

def gen_tlrc_data(self, subject: str, output_dir: str) -> None:
    """Generate inverse talairach data for report generation.

    Parameters
    ----------
    output_dir : str
        Path for intermediate file output.

    Examples
    --------
    >>> from pyfsviz.freesurfer import FreeSurfer
    >>> fs_dir = FreeSurfer(
    ...     freesurfer_home="/opt/freesurfer",
    ...     subjects_dir="/opt/data",
    ... )
    >>> fs_dir.gen_tlrc_data("sub-001", "/opt/data/sub-001/mri/transforms")
    """
    # get inverse transform
    lta_file = self.subjects_dir / subject / "mri" / "transforms" / "talairach.xfm.lta"
    xfm = np.genfromtxt(lta_file, skip_header=5, max_rows=4)
    inverse_xfm = np.linalg.inv(xfm)
    np.savetxt(
        f"{output_dir}/inv.xfm",
        inverse_xfm,
        fmt="%0.8f",
        delimiter=" ",
        newline="\n",
        encoding="utf-8",
    )

    # convert subject original T1 to nifti (for FSL)
    convert = MRIConvert(
        in_file=self.subjects_dir / subject / "mri" / "orig.mgz",
        out_file=f"{output_dir}/orig.nii.gz",
        out_type="niigz",
    )
    convert.run()

    # use FSL to convert template file to subject original space
    flirt = FLIRT(
        in_file=self._mni_nii,
        reference=f"{output_dir}/orig.nii.gz",
        out_file=f"{output_dir}/mni2orig.nii.gz",
        in_matrix_file=f"{output_dir}/inv.xfm",
        apply_xfm=True,
        out_matrix_file=f"{output_dir}/out.mat",
    )
    flirt.run()

gen_tlrc_report

gen_tlrc_report(subject: str, output_dir: str, tlrc_dir: str | None = None, *, gen_data: bool = True) -> Path

Generate a before and after report of Talairach registration. (Will also run file generation if needed).

Parameters:

• subject

  (str) –

  Subject ID.

• output_dir

  (str) –

  Path to SVG output.

• gen_data

  (bool, default: True ) –

  Generate inverse Talairach data, by default True

• tlrc_dir

  (str | None, default: None ) –

  Path to output of gen_tlrc_data. Default is the subject's mri/transforms directory.

Returns:

• Path ( Path ) –

  SVG file generated from the niworkflows SimpleBeforeAfterRPT

Examples:

>>> from pyfsviz.freesurfer import FreeSurfer
>>> fs_dir = FreeSurfer(
...     freesurfer_home="/opt/freesurfer",
...     subjects_dir="/opt/data",
... )
>>> report = fs_dir.gen_tlrc_report("sub-001", "/opt/data/reports/sub-001")

Source code in src/pyfsviz/freesurfer.py

def gen_tlrc_report(
    self,
    subject: str,
    output_dir: str,
    tlrc_dir: str | None = None,
    *,
    gen_data: bool = True,
) -> Path:
    """Generate a before and after report of Talairach registration. (Will also run file generation if needed).

    Parameters
    ----------
    subject : str
        Subject ID.
    output_dir : str
        Path to SVG output.
    gen_data : bool
        Generate inverse Talairach data, by default True
    tlrc_dir : str | None
        Path to output of `gen_tlrc_data`. Default is the subject's mri/transforms directory.

    Returns
    -------
    Path:
        SVG file generated from the niworkflows SimpleBeforeAfterRPT

    Examples
    --------
    >>> from pyfsviz.freesurfer import FreeSurfer
    >>> fs_dir = FreeSurfer(
    ...     freesurfer_home="/opt/freesurfer",
    ...     subjects_dir="/opt/data",
    ... )
    >>> report = fs_dir.gen_tlrc_report("sub-001", "/opt/data/reports/sub-001")
    """
    if tlrc_dir is None:
        tlrc_dir = f"{self.subjects_dir}/{subject}/mri/transforms"

    mri_dir = f"{self.subjects_dir}/{subject}/mri"

    if gen_data:
        self.gen_tlrc_data(subject, tlrc_dir)

    # use white matter segmentation to compare registrations
    report = SimpleBeforeAfterRPT(
        before=f"{mri_dir}/orig.mgz",
        after=f"{tlrc_dir}/mni2orig.nii.gz",
        wm_seg=f"{mri_dir}/wm.mgz",
        before_label="Subject Orig",
        after_label="Template",
        out_report=f"{output_dir}/tlrc.svg",
    )
    result = report.run()
    return result.outputs.out_report

get_colormap

get_colormap() -> ListedColormap

Return the colormap for the FreeSurfer data.

Source code in src/pyfsviz/freesurfer.py

def get_colormap(self) -> colors.ListedColormap:
    """Return the colormap for the FreeSurfer data."""
    return get_freesurfer_colormap(self.freesurfer_home)

get_subjects

get_subjects(search_dir: str | Path | None = None) -> list[str]

Return FreeSurfer subjects found in a directory.

Parameters:

• search_dir

  (str | Path | None, default: None ) –

  Directory to scan for subject folders. Defaults to self.subjects_dir.

Returns:

• list[str] –

  Subject IDs with a completed talairach transform.

Source code in src/pyfsviz/freesurfer.py

def get_subjects(self, search_dir: str | Path | None = None) -> list[str]:
    """Return FreeSurfer subjects found in a directory.

    Parameters
    ----------
    search_dir
        Directory to scan for subject folders. Defaults to ``self.subjects_dir``.

    Returns
    -------
    list[str]
        Subject IDs with a completed talairach transform.
    """
    base = self.subjects_dir if search_dir is None else Path(search_dir)
    if not base.exists():
        msg = f"Subject search directory not found: {base}"
        raise FileNotFoundError(msg)

    return sorted(
        subject.name
        for subject in base.iterdir()
        if subject.is_dir() and (subject / "mri" / "transforms" / "talairach.lta").exists()
    )

resolve_groups

resolve_groups(groups: _GroupDefinition) -> dict[str, list[str]]

Resolve group definitions to subject ID lists from FreeSurfer directories.

Each group can be defined as:

• A list of subject IDs (explicit membership)
• None or omitted value: scan subjects_dir / group_name
• A path string or Path: scan that directory for subject folders

Parameters:

• groups

  (_GroupDefinition) –

  Group names mapped to subject lists or directories, or a list of subdirectory names under subjects_dir.

Returns:

• dict[str, list[str]] –

  Mapping of group names to discovered subject IDs.

Source code in src/pyfsviz/freesurfer.py

def resolve_groups(self, groups: _GroupDefinition) -> dict[str, list[str]]:
    """Resolve group definitions to subject ID lists from FreeSurfer directories.

    Each group can be defined as:

    - A list of subject IDs (explicit membership)
    - ``None`` or omitted value: scan ``subjects_dir / group_name``
    - A path string or ``Path``: scan that directory for subject folders

    Parameters
    ----------
    groups
        Group names mapped to subject lists or directories, or a list of
        subdirectory names under ``subjects_dir``.

    Returns
    -------
    dict[str, list[str]]
        Mapping of group names to discovered subject IDs.
    """
    resolved: dict[str, list[str]] = {}
    group_items: list[tuple[str, _GroupSpec]] = (
        [(name, None) for name in groups] if isinstance(groups, list) else list(groups.items())
    )

    for group_name, group_spec in group_items:
        if isinstance(group_spec, list):
            resolved[group_name] = group_spec
            continue

        if group_spec is None or group_spec == "":
            search_dir = self.subjects_dir / group_name
        else:
            search_path = Path(group_spec)
            search_dir = search_path if search_path.is_absolute() else self.subjects_dir / search_path

        subjects = self.get_subjects(search_dir)
        if not subjects:
            self.logger.warning(
                f"No FreeSurfer subjects found for group '{group_name}' in {search_dir}",
            )
        resolved[group_name] = subjects

    return resolved

subject_summary

subject_summary(subject: str) -> dict[str, Any]

Collect a compact individual-report summary from the subject tree.

Parameters:

• subject

  (str) –

  Subject ID.

Returns:

• dict[str, Any] –

  Fields for the individual HTML summary card.

Source code in src/pyfsviz/freesurfer.py

def subject_summary(
    self,
    subject: str,
) -> dict[str, Any]:
    """Collect a compact individual-report summary from the subject tree.

    Parameters
    ----------
    subject : str
        Subject ID.

    Returns
    -------
    dict[str, Any]
        Fields for the individual HTML summary card.
    """
    recon_info = self._get_recon_info(subject)
    tlrc_info = self._check_talairach(subject)

    return {
        "subject": subject,
        "recon_status": "finished without error" if self.check_recon_all(subject) else "recon failed",
        "runtime": _format_runtime(float(recon_info["runtime"])),
        "fs_version": recon_info["version"],
        "command": recon_info["command"],
        "talairach_afd": tlrc_info["afd"],
        "talairach_qa": tlrc_info["qa"],
        "talairach_zscore": tlrc_info["z-score"],
    }

get_freesurfer_colormap

get_freesurfer_colormap(freesurfer_home: Path | str) -> ListedColormap

Generate matplotlib colormap from FreeSurfer LUT.

Code from: https://github.com/Deep-MI/fsqc/blob/stable/fsqc/createScreenshots.py

Parameters:

• freesurfer_home

  (path or str representing a path to a directory) –

  Path corresponding to FREESURFER_HOME env var.

Returns:

• colormap ( ListedColormap ) –

  A matplotlib compatible FreeSurfer colormap.

Source code in src/pyfsviz/freesurfer.py

def get_freesurfer_colormap(freesurfer_home: Path | str) -> colors.ListedColormap:
    """Generate matplotlib colormap from FreeSurfer LUT.

    Code from:
    https://github.com/Deep-MI/fsqc/blob/stable/fsqc/createScreenshots.py

    Parameters
    ----------
    freesurfer_home : path or str representing a path to a directory
        Path corresponding to FREESURFER_HOME env var.

    Returns
    -------
    colormap : matplotlib.colors.ListedColormap
        A matplotlib compatible FreeSurfer colormap.

    """
    freesurfer_home = Path(freesurfer_home) if isinstance(freesurfer_home, str) else freesurfer_home
    lut = pd.read_csv(
        freesurfer_home / "FreeSurferColorLUT.txt",
        sep=r"\s+",
        comment="#",
        header=None,
        names=range(8),  # FS8+ adds col for tissue class, so allow extra cols when reading in
        skipinitialspace=True,
        skip_blank_lines=True,
    )
    lut = lut.iloc[:, :6].dropna(subset=[0, 2, 3, 4, 5])
    lut = np.array(lut)

    lut_tab = np.array(lut[:, (2, 3, 4, 5)].astype(float) / 255, dtype="float32")
    lut_tab[:, 3] = 1

    return colors.ListedColormap(lut_tab)

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