josiann.moves.sequential.Metropolis1D
- class josiann.moves.sequential.Metropolis1D(*, variance, bounds=None, repr_attributes=(), **kwargs)[source]
Metropolis step obtained from a uni-variate normal distribution with mean <x> and variance <variance>
Instantiate a Move.
- Parameters:
variance (
float
) – the variance for the normal distribution.bounds (
Optional
[ndarray
[Any
,dtype
[Union
[float64
,int64
]]]] (default:None
)) – optional sequence of (min, max) bounds for values to propose in each dimension.repr_attributes (
tuple
[str
,...
] (default:()
)) – list of attribute names to include in the string representation of this Move.kwargs (Any) –
Methods
Instantiate a Move.
Generate a new proposed vector x.
Set bounds for the move.
Methods
- Metropolis1D.__init__(*, variance, bounds=None, repr_attributes=(), **kwargs)[source]
Instantiate a Move.
- Parameters:
variance (
float
) – the variance for the normal distribution.bounds (
Optional
[ndarray
[Any
,dtype
[Union
[float64
,int64
]]]] (default:None
)) – optional sequence of (min, max) bounds for values to propose in each dimension.repr_attributes (
tuple
[str
,...
] (default:()
)) – list of attribute names to include in the string representation of this Move.kwargs (Any) –
- Metropolis1D.get_proposal(x, state)
Generate a new proposed vector x.