probly.representation.conformal_set.array.ArrayOneHotConformalSet¶
- class probly.representation.conformal_set.array.ArrayOneHotConformalSet(array: ndarray)[source]¶
Bases:
ArrayAxisProtected[ArraySample],OneHotConformalSetOne-hot conformal set backed by a NumPy array.
- array: np.ndarray¶
- astype(dtype: DTypeLike, order: Order = 'K', casting: Literal['no', 'equiv', 'safe', 'same_kind', 'unsafe'] = 'unsafe', subok: bool = True, copy: bool = True) Self[source]¶
Copy of the array, cast to a specified type.
- property flags: ArrayFlagsLike¶
The flags of the array.
- classmethod from_array_sample(sample: ndarray) Self[source]¶
Create a one-hot conformal set from a raw NumPy array.
- Parameters:
sample – A one-hot encoded boolean or integer array.
- Returns:
The created conformal set.
- classmethod from_sample(sample: Sample[np.ndarray]) Self[source]¶
Create a one-hot conformal set from a sample.
- Parameters:
sample – A sample containing a one-hot encoded array.
- Returns:
The created conformal set.
- permitted_functions = {}¶
- permitted_ufuncs = {}¶
- protected_values(func: Callable | None = None, method: str | None = None) dict[str, ArrayProtectedValue] | None[source]¶
Return all protected field values.
The values are preserved as-is and are not coerced to
np.ndarray. Optionally takes the function that triggered the call for context. This can be used to conditionally modify the returned values or prevent them from being accessed.
- reshape(*shape: int | tuple[int, ...], order: str = 'C', copy: bool | None = None) Self[source]¶
Return a copy with reshaped protected values.
- transpose(*axes: int | None) Self[source]¶
Return a transposed version of the ArraySample.
This method implicitly also provides full axis tracking support for - np.moveaxis - np.rollaxis Those functions call out to transpose methods for custom array types.
- Parameters:
axes – The axes to transpose.
- Returns:
A transposed version of the ArraySample.
- type = 'one_hot'¶