megengine.random.poisson¶
- poisson(lam, size=None)¶
Random variable with poisson distribution \(\operatorname{Poisson}(\lambda)\).
The corresponding probability density function is
\[f(k ; \lambda)=\frac{\lambda^{k} e^{-\lambda}}{k !},\]where k is the number of occurrences \(({\displaystyle k=0,1,2...})\).
- 参数
lam (
Union[float,Tensor]) – the lambda parameter of the distribution. Must be non-negative.size (
Optional[Iterable[int]]) – the size of output tensor. If lam is a scalar and given size is, e.g., (m, n), then the output shape is (m, n). If lam is a Tensor with shape (k, v) and given size is, e.g., (m, n), then the output shape is (m, n, k, v). Default: None.
- 返回
the output tensor.
实际案例
import megengine as mge import megengine.random as rand x = rand.poisson(lam=2., size=(1, 3)) print(x.numpy()) lam = mge.Tensor([[1.,1.], [10,10]], dtype="float32") x = rand.poisson(lam=lam) print(x.numpy()) x = rand.poisson(lam=lam, size=(1,3)) print(x.numpy())
Outputs:
[[3. 1. 3.]] [[ 2. 2.] [12. 11.]] [[[[ 1. 1.] [11. 4.]] [[ 0. 0.] [ 9. 13.]] [[ 0. 1.] [ 7. 12.]]]]