poisson#
- ivy.poisson(lam, *, shape=None, device=None, dtype=None, seed=None, fill_value=0, out=None)[source]#
Draws samples from a poisson distribution.
- Parameters:
lam (
Union
[float
,Array
,NativeArray
]) – Rate parameter(s) describing the poisson distribution(s) to sample. It must have a shape that is broadcastable to the requested shape.shape (
Optional
[Union
[Shape
,NativeShape
]], default:None
) – If the given shape is, e.g ‘(m, n, k)’, then ‘m * n * k’ samples are drawn. (Default value = ‘None’, where ‘ivy.shape(lam)’ samples are drawn)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. Ifdtype
isNone
, the output array data type will be the default floating-point data type. DefaultNone
seed (
Optional
[int
], default:None
) – A python integer. Used to create a random seed distribution.fill_value (
Optional
[Union
[int
,float
]], default:0
) – if lam is negative, fill the output array with this value on that specific dimension.out (
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
Drawn samples from the poisson distribution
Examples
>>> lam = [1.0, 2.0, 3.0] >>> ivy.poisson(lam) ivy.array([1., 4., 4.])
>>> lam = [1.0, 2.0, 3.0] >>> ivy.poisson(lam, shape = (2,3)) ivy.array([[0., 2., 2.], [1., 2., 3.]])
- Array.poisson(self, *, shape=None, device=None, dtype=None, seed=None, fill_value=0, out=None)[source]#
- Parameters:
self (
Array
) – Input Array of rate parameter(s). It must have a shape that is broadcastable to the requested shapeshape (
Optional
[Union
[Shape
,NativeShape
]], default:None
) – If the given shape is, e.g ‘(m, n, k)’, then ‘m * n * k’ samples are drawn. (Default value = ‘None’, where ‘ivy.shape(lam)’ samples are drawn)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. Ifdtype
isNone
, the output array data type will be the default floating-point data type. DefaultNone
seed (
Optional
[int
], default:None
) – A python integer. Used to create a random seed distributionfill_value (
Optional
[Union
[float
,int
]], default:0
) – if lam is negative, fill the output array with this value on that specific dimension.out (
Optional
[Array
], default:None
) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.
- Returns:
ret – Drawn samples from the parameterized poisson distribution.
Examples
>>> lam = ivy.array([1.0, 2.0, 3.0]) >>> lam.poisson() ivy.array([1., 4., 4.])
>>> lam = ivy.array([1.0, 2.0, 3.0]) >>> lam.poisson(shape=(2,3)) ivy.array([[0., 2., 2.], [1., 2., 3.]])
- Container.poisson(self, /, *, shape=None, device=None, dtype=None, seed=None, fill_value=0, out=None)[source]#
ivy.Container instance method variant of ivy.poisson. This method simply wraps the function, and so the docstring for ivy.poisson also applies to this method with minimal changes.
- Parameters:
self (
Container
) – Input container with rate parameter(s) describing the poisson distribution(s) to sample.shape (
Optional
[Union
[Shape
,NativeShape
,Container
]], default:None
) – optional container including ints or tuple of ints, Output shape for the arrays in the input container.device (
Optional
[Union
[Device
,NativeDevice
,Container
]], default:None
) – device on which to create the array ‘cuda:0’, ‘cuda:1’, ‘cpu’ etc. (Default value = None).dtype (
Optional
[Union
[Dtype
,NativeDtype
,Container
]], default:None
) – output container array data type. Ifdtype
isNone
, the output data type will be the default floating-point data type. DefaultNone
seed (
Optional
[Union
[int
,Container
]], default:None
) – A python integer. Used to create a random seed distribution.fill_value (
Optional
[Union
[float
,int
,Container
]], default:0
) – if lam is negative, fill the output array with this value on that specific dimension.out (
Optional
[Container
], default:None
) – optional output container, for writing the result to.
- Return type:
Container
- Returns:
ret – container including the drawn samples.
Examples
>>> lam = ivy.Container(a=ivy.array([7,6,5]), b=ivy.array([8,9,4])) >>> shape = ivy.Container(a=(2,3), b=(1,1,3)) >>> lam.poisson(shape=shape) { a: ivy.array([[5, 4, 6], [12, 4, 5]]), b: ivy.array([[[8, 13, 3]]]) }