neurocarto.util.util_numpy

neurocarto.util.util_numpy.is_sorted(a, strict=False)

Is a sorted?

reference

Parameters:

  • a (ndarray[tuple[int, ...], dtype[number]]) – Array[number, N]

  • strict – strict increase

Returns:

Return type:

bool

neurocarto.util.util_numpy.same_index(a)

Get index of save value.

Parameters:

a (ndarray[tuple[int, ...], dtype[number]]) – Array[V, N] or Array[V, N, M]

Returns:

list of index Array[N, *] for particular duplicated value V.

Return type:

list[ndarray[tuple[int, …], dtype[int64]]]

neurocarto.util.util_numpy.closest_point_index(a, p, v)

Find the index of closed point in a.

Parameters:

  • a (ndarray[tuple[int, ...], dtype[float64]]) – Array[V:float, N[, D]]

  • p (float | Sequence[float] | ndarray[tuple[int, ...], dtype[float64]]) – V or Array[V:float, D]

  • v (float) – V threshold

Returns:

index of N

Return type:

int | None

neurocarto.util.util_numpy.index_of(ref, val, missing='error')

Get index of ref for each value in a.

Parameters:

  • ref (ndarray[tuple[int, ...], dtype[int64]]) – reference Array[V, A].

  • val (int | list[int] | ndarray[tuple[int, ...], dtype[int64]]) – value Array[V, B].

  • missing (int | Literal['error', 'drop']) – {‘error’, ‘drop’} or int

Returns:

index Array[A, B]

Raises:

  • TypeError – unknown ‘missing’

  • ValueError – channel not in ref

Return type:

ndarray[tuple[int, …], dtype[int64]]

neurocarto.util.util_numpy.interpolate_nan(a, kernel=1, iteration=1, f='mean', n=nan)

interpolate NaN value in a.

Parameters:

  • a (ndarray[tuple[int, ...], dtype[float64]]) – image Array[float, (N,) Y, X]

  • kernel (int | tuple[int, int]) – int or (sy:int, sx:int)

  • iteration (int)

  • f (str | Callable[[ndarray[tuple[int, ...], dtype[float64]]], float]) – interpolate function (Array[float]) -> float

  • n (float) – fill value after iteration

Returns:

image array

Return type:

ndarray[tuple[int, …], dtype[float64]]