cmtk

navis.transforms.cmtk.cmtk_version

Get CMTK version.

Source code in navis/transforms/cmtk.py

@requires_cmtk
def cmtk_version(as_string=False):
    """Get CMTK version."""
    p = subprocess.run([_cmtkbin / "streamxform", "--version"], capture_output=True)
    version = p.stdout.decode("utf-8").rstrip()

    if as_string:
        return version
    else:
        return tuple(int(v) for v in version.split("."))

navis.transforms.cmtk.find_cmtkbin

Find directory with CMTK binaries.

Source code in navis/transforms/cmtk.py

def find_cmtkbin(tool: str = "streamxform") -> str:
    """Find directory with CMTK binaries."""
    for path in _search_path:
        path = pathlib.Path(path).absolute()
        if not path.is_dir():
            continue

        try:
            return next(path.glob(tool)).resolve().parent
        except StopIteration:
            continue
        except BaseException:
            raise

navis.transforms.cmtk.parse_target_specs

Parse target specs into argument that can be passed to CMTK.

Source code in navis/transforms/cmtk.py

def parse_target_specs(target):
    """Parse target specs into argument that can be passed to CMTK."""
    # Note to self: this function should also deal with VoxelNeurons and NRRD filepaths
    # For NRRD filepaths: we need to add an empty "--" before the filepath (I think)

    from .templates import TemplateBrain  # avoid circular import

    assert isinstance(target, (str, TemplateBrain, np.ndarray, list, tuple))

    if isinstance(target, str):
        from . import registry

        target = registry.find_template(target)

    if isinstance(target, TemplateBrain):
        specs = list(target.dims) + list(target.voxdims)
        # Note to self: need to check TemplateBrain (and flybrains) consistent definition of
        # dims, voxdims and origin (maybe even add origin)

    # At this point we expect specs to be an iterable
    specs = np.asarray(target)
    assert len(specs) in (
        6,
        9,
    ), f"Target specs must be of length 6 or 9, got {len(specs)}"
    target = "--target-grid "
    target += ",".join(
        map(str, specs[:3].astype(int))
    )  # Number of voxels (must be integer)
    target += ":"
    target += ",".join(map(str, specs[3:].astype(float)))  # Voxel size (can be float)
    if len(specs) == 9:
        target += ":"
        target += ",".join(map(str, specs[6:].astype(float)))  # Origin (can be float)

    return target

navis.transforms.cmtk.requires_cmtk

Check if CMTK is available.

Source code in navis/transforms/cmtk.py

def requires_cmtk(func):
    """Check if CMTK is available."""

    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        if not _cmtkbin:
            raise ValueError(
                "Cannot find CMTK. Please install from "
                "http://www.nitrc.org/projects/cmtk and "
                "make sure that it is your path!"
            )
        return func(*args, **kwargs)

    return wrapper

navis.transforms.cmtk.xform_cmtk

Xform 3d coordinates.

PARAMETER	DESCRIPTION
points	Points to transform. DataFrame must have x/y/z columns. TYPE: (N, 3) array | pandas.DataFrame
transforms	Either filepath to CMTK transform or `CMTKtransform`. Multiple regs must be given as list and will be applied sequentially in the order provided. TYPE: filepath(s) | CMTKtransform(s)
inverse	Whether to invert transforms. If single boolean will apply to all transforms. Can also provide `inverse` as list of booleans. TYPE: bool | list thereof DEFAULT: False
affine_fallback	If True, points that failed to transform during warping transform will be transformed using only the affine transform. TYPE: bool DEFAULT: False

RETURNS	DESCRIPTION
pointsxf	Transformed points. Will contain np.nan for points that did not transform. TYPE: (N, 3) numpy.ndarray

Source code in navis/transforms/cmtk.py

@requires_cmtk
def xform_cmtk(
    points: np.ndarray,
    transforms,
    inverse: bool = False,
    affine_fallback: bool = False,
    **kwargs,
) -> np.ndarray:
    """Xform 3d coordinates.

    Parameters
    ----------
    points :            (N, 3) array | pandas.DataFrame
                        Points to transform. DataFrame must have x/y/z columns.
    transforms :        filepath(s) | CMTKtransform(s)
                        Either filepath to CMTK transform or `CMTKtransform`.
                        Multiple regs must be given as list and will be applied
                        sequentially in the order provided.
    inverse :           bool | list thereof
                        Whether to invert transforms. If single boolean will
                        apply to all transforms. Can also provide `inverse` as
                        list of booleans.
    affine_fallback :   bool
                        If True, points that failed to transform during warping
                        transform will be transformed using only the affine
                        transform.

    Returns
    -------
    pointsxf :          (N, 3) numpy.ndarray
                        Transformed points. Will contain `np.nan` for points
                        that did not transform.

    """
    transforms = list(utils.make_iterable(transforms))

    if isinstance(inverse, bool):
        inverse = [inverse] * len(transforms)

    directions = ["forward" if not i else "inverse" for i in inverse]

    for i, r in enumerate(transforms):
        if not isinstance(r, CMTKtransform):
            if not isinstance(r, (str, pathlib.Path)):
                raise TypeError("`reg` must be filepath or CMTKtransform")
            transforms[i] = CMTKtransform(r, directions=directions[i])

    # Combine all transforms into a sequence of transforms
    seq = TransformSequence(*transforms)

    # Transform points
    xf = seq.xform(points)

    # If requested, try again with affine only for points that failed to xform
    if affine_fallback:
        isnan = np.any(np.isnan(xf), axis=1)
        if np.any(isnan):
            xf[isnan] = seq.xform(points[isnan], affine_only=True)

    return xf