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fix docstrings and formatting
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@dkuegler
dkuegler committed Mar 21, 2024
1 parent ae8ae5a commit 3783a80
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Showing 2 changed files with 57 additions and 53 deletions.
106 changes: 55 additions & 51 deletions FastSurferCNN/segstats.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -470,22 +470,28 @@ def add_measure_parser(subparser_callback: SubparserCallback) -> None:
def add_two_help_messages(parser: argparse.ArgumentParser) -> None:
"""
Adds separate help flags -h and --help to the parser for simple and detailed help.
Both trigger the help action.
Both trigger the help action. The respective help texts will have "(this message)"
added to the help message associated with the currently shown help message.
Parameters
----------
parser: argparse.ArgumentParser
parser to add the flags to
The parser object to add the two help flags to.
"""
def this_msg(msg: str, flag: str) -> str:
import sys
return f"{msg} (this message)" if flag in sys.argv else msg
parser.add_argument(
"-h", action="help",
help=this_msg("show a short help message and exit", "-h"))
"-h",
action="help",
help=this_msg("show a short help message and exit", "-h"),
)
parser.add_argument(
"--help", action="help",
help=this_msg("show a long, detailed help message and exit", "--help"))
"--help",
action="help",
help=this_msg("show a long, detailed help message and exit", "--help"),
)


def _check_arg_path(
Expand Down Expand Up @@ -557,33 +563,29 @@ def _check_arg_defined(attr: str, /, args: argparse.Namespace) -> bool:
return not (value is None or empty(value))


def check_shape_affine(
def assert_same_shape_affine(
img1: "nib.analyze.SpatialImage",
img2: "nib.analyze.SpatialImage",
name1: str,
name2: str,
) -> None:
"""
Check whether the shape and affine of
Check whether the shape and affine of `img1` and `img2` are the same.
Parameters
----------
img1 : nibabel.SpatialImage
Image 1.
img2 : nibabel.SpatialImage
Image 2.
name1 : str
Name of image 1.
name2 : str
Name of image 2.
img1, img2 : nibabel.SpatialImage
The image whose shape and affine must be the same.
name1, name2 : str
The name of the image
Raises
-------
RuntimeError
------
AssertionError
If shapes or affines are not the same.
"""
if img1.shape != img2.shape or not np.allclose(img1.affine, img2.affine):
raise RuntimeError(
raise AssertionError(
f"The shapes or affines of the {name1} and the {name2} image are not "
f"similar, both must be the same!"
)
Expand All @@ -606,21 +608,22 @@ def parse_files(
Path to SUBJECTS_DIR, where subject directories are.
subject_id : str, optional
The subject_id string.
require_measurefile: bool, default=False
require_measurefile : bool, default=False
require the measurefile to exist.
Returns
-------
segfile : Path
Path to the segmentation file, most likely an absolute path.
The path to the segmentation file, most likely an absolute path.
pvfile : Path, None
Path to the pvfile file, most likely an absolute path.
The path to the pvfile file, most likely an absolute path.
normfile : Path, None
Path to the norm file, most likely an absolute path, or None if not passed.
The path to the norm file, most likely an absolute path, or None if not passed.
segstatsfile : Path
Path to the output segstats file, most likely an absolute path.
The path to the output segstats file, most likely an absolute path.
measurefile : Path, None
Path to the measure file, most likely an absolute path, not None is not passed.
The path to the measure file, most likely an absolute path, not None is not
passed.
Raises
------
Expand Down Expand Up @@ -721,12 +724,12 @@ def main(args: argparse.Namespace) -> Literal[0] | str:
Parameters
----------
args : object
Parameter object as defined by `make_arguments().parse_args()`
Parameter object as defined by `make_arguments().parse_args()`.
Returns
-------
Literal[0], str
Either as a successful return code or a string with an error message
Either 0 (successful return code) or a string with an error message.
"""
from time import perf_counter_ns
from FastSurferCNN.utils.common import assert_no_root
Expand Down Expand Up @@ -800,13 +803,13 @@ def main(args: argparse.Namespace) -> Literal[0] | str:
preproc_image, pvfile_preproc, pv_data
)

check_shape_affine(seg, pv_img, "segmentation", "pv_guide")
assert_same_shape_affine(seg, pv_img, "segmentation", "pv_guide")
if normfile is not None:
_norm: ImageTuple = load_image(normfile, blocking=True)
norm, norm_data = _norm
check_shape_affine(seg, norm, "segmentation", "norm")
assert_same_shape_affine(seg, norm, "segmentation", "norm")

except (IOError, RuntimeError, FileNotFoundError) as e:
except (IOError, RuntimeError, FileNotFoundError, AssertionError) as e:
return e.args[0]

lut: Optional[pd.DataFrame] = None
Expand Down Expand Up @@ -1340,6 +1343,7 @@ def preproc_image(
data = np.sqrt(data)
return data


def seg_borders(
_array: _ArrayType,
label: np.integer | bool,
Expand All @@ -1351,13 +1355,13 @@ def seg_borders(
Parameters
----------
_array: numpy.ndarray
_array : numpy.ndarray
Image to compute borders from, typically either a label image or a binary mask.
label: int, bool
label : int, bool
Which classes to consider for border computation (True/False for binary mask).
out: nt.NDArray[bool], optional
out : nt.NDArray[bool], optional
The array for inplace computation.
cmp_dtype: npt.DTypeLike, default=int8
cmp_dtype : npt.DTypeLike, default=int8
The data type to use for border laplace computation.
Returns
Expand Down Expand Up @@ -1401,10 +1405,10 @@ def borders(
----------
_array : _ArrayType
Label array to compute borders from (can also be a binary mask).
labels : Iterable[np.integer], bool
labels : Iterable[int], bool
List/array of labels to consider for borders, may also be bool, if _array is
already a binary mask.
max_label : np.integer, optional
max_label : int, optional
Maximum label number in the lookup table.
six_connected : bool, optional
Whether to use 6-connected (face-neighbor) or 27-connected (vertex-neighbor) to
Expand Down Expand Up @@ -1668,14 +1672,14 @@ def pv_calc(
maps : dict[str, np.ndarray], optional
Only returned, if return_maps is True:
A dictionary with the 5 meta-information pv-maps:
nbr: An image of alternative labels that were considered instead of the voxel's
label.
nbr_means: The local mean intensity of the label nbr at the specific voxel.
seg_means: The local mean intensity of the primary label at the specific voxel.
mixing_coeff: The partial volume of the primary label at the location.
nbr_mixing_coeff: The partial volume of the alternative (nbr) label at the
location.
- `nbr`: An image of alternative labels that were considered instead of the
voxel's label.
- `nbr_means`: The local mean intensity of the label nbr at the specific voxel.
- `seg_means`: The local mean intensity of the primary label at the specific
voxel.
- `mixing_coeff`: The partial volume of the primary label at the location.
- `nbr_mixing_coeff`: The partial volume of the alternative (nbr) label at the
location.
"""
input_checker = {
"seg": (seg, np.integer),
Expand All @@ -1693,9 +1697,10 @@ def pv_calc(
raise TypeError("The labels list is not an arraylike of ints.")

if seg.shape != pv_guide.shape:
raise RuntimeError(f"The shapes of the segmentation and the pv_guide must "
f"be identical, but shapes are {seg.shape} and "
f"{pv_guide.shape}!")
raise RuntimeError(
f"The shapes of the segmentation and the pv_guide must be identical, but "
f"shapes are {seg.shape} and {pv_guide.shape}!"
)
if seg.shape != norm.shape:
raise RuntimeError(
f"The shape of the segmentation and the norm must be identical, but shapes "
Expand Down Expand Up @@ -1937,7 +1942,7 @@ def global_stats(
Parameters
----------
lab : _IntType
The label to get the stats for
The label to get the stats for.
norm : np.ndarray, optional
The intensity image (default: None, do not compute intensity stats such as
normMin, normMax, etc.).
Expand Down Expand Up @@ -2126,7 +2131,7 @@ def pv_calc_patch(
the image.
borders : dict[int, npt.NDArray[bool]]
Dictionary containing the borders for each label.
seg : numpy.typing.NDArray[numpy.integer]
seg : numpy.typing.NDArray[int]
The segmentation (full image) defining the labels.
pv_guide : numpy.ndarray
The (full) image with intensities to guide the PV calculation.
Expand All @@ -2153,7 +2158,6 @@ def pv_calc_patch(
-------
dict[int, float]
Dictionary of per-label PV-corrected volume of affected voxels in the patch.
"""

# Variable conventions:
Expand Down Expand Up @@ -2328,7 +2332,7 @@ def patch_neighbors(
A sequence of all labels that we want to compute the PV for.
pv_guide : numpy.ndarray
The (full) image with intensities to guide the PV calculation.
seg : numpy.typing.NDArray[numpy.integer]
seg : numpy.typing.NDArray[int]
The segmentation (full image) defining the labels.
border_patch : npt.NDArray[bool]
Binary mask for the current patch, True, where a voxel is considered to be a
Expand Down
4 changes: 2 additions & 2 deletions FastSurferCNN/utils/run_tools.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -145,8 +145,8 @@ def finish(self, timeout: float = None) -> MessageBuffer:
if i > 0:
self.kill()
raise RuntimeError(
"The process {} did not stop properly in Popen.finish, "
"abandoning.".format(self)
f"The process {self} did not stop properly in Popen.finish, "
"abandoning."
)
i += 1
if i == 0:
Expand Down

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