FastSurferCNN.utils.lta

class FastSurferCNN.utils.lta.LTADict

Typed dictionary containing all the information from an LTA transform file.

Attributes

type: int
nxforms: int
mean: list[float]
sigma: float
lta: AffineMatrix4x4
src_valid: int
src_filename: str
src_volume: list[int]
src_voxelsize: list[float]
src_xras: list[float]
src_yras: list[float]
src_zras: list[float]
src_cras: list[float]
dst_valid: int
dst_filename: str
dst_volume: list[int]
dst_voxelsize: list[float]
dst_xras: list[float]
dst_yras: list[float]
dst_zras: list[float]
dst_cras: list[float]
src: AffineMatrix4x4
dst: AffineMatrix4x4

Methods

clear()
copy()
fromkeys(iterable[, value])	Create a new dictionary with keys from iterable and values set to value.
get(key[, default])	Return the value for key if key is in the dictionary, else default.
items()
keys()
pop(key[, default])	If the key is not found, return the default if given; otherwise, raise a KeyError.
popitem(/)	Remove and return a (key, value) pair as a 2-tuple.
setdefault(key[, default])	Insert key with a value of default if key is not in the dictionary.
update([E, ]**F)	If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
values()

FastSurferCNN.utils.lta.read_lta(file)

Read the LTA info.

FastSurferCNN.utils.lta.write_lta(filename, affine, src_fname, src_header, dst_fname, dst_header)

Write linear transform array info to an .lta file.

Parameters:

filenamePath, str

File to write on.

affinenpt.ArrayLike

Linear transform array to be saved.

src_fnamePath, str

Source filename.

src_headerDict

Source header.

dst_fnamePath, str

Destination filename.

dst_headerDict

Destination header.

Raises:

ValueError

Header format missing field (Source or Destination).