beta#
- ivy.beta(a, b, /, *, shape=None, device=None, dtype=None, seed=None, out=None)[source]#
Return an array filled with random values sampled from a beta distribution.
- Parameters:
a (
Union[float,NativeArray,Array]) – Alpha parameter of the beta distribution.b (
Union[float,NativeArray,Array]) – Beta parameter of the beta distribution.shape (
Optional[Union[Shape,NativeShape]], default:None) – If the given shape is, e.g(m, n, k), thenm * n * ksamples are drawn Can only be specified whenmeanandstdare numeric values, else exception will be raised. Default isNone, where a single value is returned.device (
Optional[Union[Device,NativeDevice]], default:None) – device on which to create the array. ‘cuda:0’, ‘cuda:1’, ‘cpu’ etc. (Default value = None).dtype (
Optional[Union[Dtype,NativeDtype]], default:None) – output array data type. IfdtypeisNone, the output array data type will be the default floating point data type. DefaultNoneseed (
Optional[int], default:None) – A python integer. Used to create a random seed distributionout (
Optional[Array], default:None) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.
- Return type:
- Returns:
ret – Returns an array with the given shape filled with random values sampled from a beta distribution.
- Array.beta(self, beta, /, *, shape=None, device=None, dtype=None, seed=None, out=None)[source]#
ivy.Array instance method variant of ivy.beta. This method simply wraps the function, and so the docstring for ivy.beta also applies to this method with minimal changes.
- Parameters:
self (
Array) – Input Array.alpha – The first parameter of the beta distribution.
beta (
Union[int,Array,NativeArray]) – The second parameter of the beta distribution.device (
Optional[Union[Device,NativeDevice]], default:None) – device on which to create the array.dtype (
Optional[Union[Dtype,NativeDtype]], default:None) – output array data type. IfdtypeisNone, the output array data type will be the default data type. DefaultNoneseed (
Optional[int], default:None) – A python integer. Used to create a random seed distributionout (
Optional[Array], default:None) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.
- Return type:
Array- Returns:
ret – Drawn samples from the parameterized beta distribution with the shape of the array.
- Container.beta(self, beta, /, *, shape=None, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, device=None, dtype=None, seed=None, out=None)[source]#
ivy.Container instance method variant of ivy.beta. This method simply wraps the function, and so the docstring for ivy.beta also applies to this method with minimal changes.
- Parameters:
self (
Container) – Input container. Should have a numeric data type.alpha – The alpha parameter of the distribution.
beta (
Union[int,float,Container,Array,NativeArray]) – The beta parameter of the distribution.shape (
Optional[Union[Shape,NativeShape,Container]], default:None) – The shape of the output array. Default isNone.key_chains (
Optional[Union[List[str],Dict[str,str],Container]], default:None) – The key-chains to apply or not apply the method to. Default isNone.to_apply (
Union[bool,Container], default:True) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default isTrue.prune_unapplied (
Union[bool,Container], default:False) – Whether to prune key_chains for which the function was not applied. Default isFalse.map_sequences (
Union[bool,Container], default:False) – Whether to also map method to sequences (lists, tuples). Default isFalse.device (
Optional[Union[str,Container]], default:None) – The device to place the output array on. Default isNone.dtype (
Optional[Union[str,Container]], default:None) – The data type of the output array. Default isNone.seed (
Optional[Union[int,Container]], default:None) – A python integer. Used to create a random seed distributionout (
Optional[Container], default:None) – optional output container, for writing the result to. It must have a shape that the inputs broadcast to.
- Return type:
Container- Returns:
ret – A container object, with values drawn from the beta distribution.