locan.simulation.simulate_locdata.simulate_NeymanScott#
- locan.simulation.simulate_locdata.simulate_NeymanScott(parent_intensity=100, region=(0, 1.0), expansion_distance=0, offspring=None, clip=True, shuffle=True, seed=None)[source]#
Generate clustered point data following a Neyman-Scott random point process. Parent positions are distributed according to a homogeneous Poisson process with parent_intensity within the boundaries given by region expanded by the expansion_distance. Each parent position is then replaced by offspring points as passed or generated by a given function. Offspring from parent events that are located outside the region are included.
- Parameters:
parent_intensity (
int
|float
) – The intensity (points per unit region measure) of the Poisson point process for parent events.region (
Union
[Region
,_SupportsArray
[dtype
[Any
]],_NestedSequence
[_SupportsArray
[dtype
[Any
]]],bool
,int
,float
,complex
,str
,bytes
,_NestedSequence
[Union
[bool
,int
,float
,complex
,str
,bytes
]]]) – The region (or support) for each feature. If array-like it must provide upper and lower bounds for each feature.expansion_distance (
float
) – The distance by which region is expanded on all boundaries.offspring (
Union
[_SupportsArray
[dtype
[Any
]],_NestedSequence
[_SupportsArray
[dtype
[Any
]]],bool
,int
,float
,complex
,str
,bytes
,_NestedSequence
[Union
[bool
,int
,float
,complex
,str
,bytes
]],Callable
[...
,Any
],None
]) – Points or function for point process to provide offspring points. Callable must take single parent point as parameter. If array-like it must have enough elements to fit the randomly generated number of parent events.clip (
bool
) – If True the result will be clipped to ‘region’. If False the extended region will be kept.shuffle (
bool
) – If True shuffle the samples.seed (
Union
[None
,int
,Sequence
[int
],SeedSequence
,BitGenerator
,Generator
]) – random number generation seed
- Returns:
The generated samples.
- Return type: