geovalidate.PointSampler¶

class geovalidate.PointSampler(n_samples=100, quasi_random=None, random_state=None)[source]¶

Sample points uniformly at random inside a Shapely geometry.

Mimics the sklearn model-selection estimator API: hyperparameters are set in __init__ and sample() acts as the primary callable.

Parameters:¶

n_samples : int, default 100¶: Number of points to generate.
random_state : int, RandomState instance, or None, default None¶: Seed / random state passed to sklearn.utils.check_random_state.

Examples

>>> from shapely.geometry import box
>>> from geovalidate import PointSampler
>>> pts = PointSampler(n_samples=200, random_state=0).sample(box(0, 0, 1, 1))
>>> len(pts)
200

__init__(n_samples=100, quasi_random=None, random_state=None)[source]¶

Methods

`__init__`([n_samples, quasi_random, random_state])
`get_metadata_routing`()	Get metadata routing of this object.
`get_params`([deep])	Get parameters for this estimator.
`sample`(geometry[, n_samples])	Sample n_samples points uniformly inside geometry.
`set_params`(**params)	Set the parameters of this estimator.

get_metadata_routing()[source]¶

Get metadata routing of this object.

Please check User Guide on how the routing mechanism works.

Returns:¶: routing – A MetadataRequest encapsulating routing information.
Return type:¶: MetadataRequest

get_params(deep=True)[source]¶

Get parameters for this estimator.

Parameters:¶

deep : bool, default=True¶: If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns:¶

params – Parameter names mapped to their values.

Return type:¶

dict

sample(geometry, n_samples=None)[source]¶

Sample n_samples points uniformly inside geometry.

Parameters:¶

geometry : shapely.Geometry | geopandas.GeoSeries | geopandas.GeoDataFrame¶: Region to sample from. A GeoSeries / GeoDataFrame is dissolved into a single union before sampling. CRS is inferred automatically.
n_samples : int, optional¶: Overrides self.n_samples for this call.

Returns:¶

Single-column geometry GeoDataFrame of sampled Points.

Return type:¶

geopandas.GeoDataFrame

set_params(**params)[source]¶

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Parameters:¶

**params : dict¶: Estimator parameters.

Returns:¶

self – Estimator instance.

Return type:¶

estimator instance