sampler Module¶

Road sampling functionality.

class geo_sampling.sampler.RoadSampler(segments: List[RoadSegment])[source]¶

Bases: object

Class for sampling road segments with various strategies.

get_road_type_summary(road_types: str | List[str] | None = None) → Dict[str, int][source]¶

Get count summary by road type.

Parameters:: road_types – Road types to include
Returns:: Dictionary mapping road type to count

plot_sample(sample: List[RoadSegment], title: str | None = None, show_comparison: bool = True, figsize: tuple = (12, 10)) → None[source]¶

Plot sampled segments.

Parameters:

sample – Sampled road segments
title – Plot title
show_comparison – Whether to show comparison with full dataset
figsize – Figure size

random_sample(n: int, road_types: str | List[str] | None = None, seed: int | None = None) → List[RoadSegment][source]¶

Get random sample of road segments.

Parameters:

n – Number of segments to sample
road_types – Road types to include (None = all types)
seed – Random seed for reproducibility

Returns:

List of sampled RoadSegment objects

Raises:

ValueError – If sample size exceeds available segments

sample_by_length(target_length_km: float, road_types: str | List[str] | None = None, seed: int | None = None) → List[RoadSegment][source]¶

Sample segments to approximate a target total length.

Parameters:

target_length_km – Target total length in kilometers
road_types – Road types to include
seed – Random seed for reproducibility

Returns:

List of sampled RoadSegment objects

save_csv(segments: List[RoadSegment], path: str | Path) → None[source]¶

Save segments to CSV file.

Parameters:

segments – Road segments to save
path – Output file path

stratified_sample(n: int, by: str = 'osm_type', road_types: str | List[str] | None = None, seed: int | None = None) → List[RoadSegment][source]¶

Get stratified sample maintaining proportions across strata.

Parameters:

n – Total number of segments to sample
by – Field to stratify by (default: “osm_type”)
road_types – Road types to include
seed – Random seed for reproducibility

Returns:

List of sampled RoadSegment objects

to_dataframe(segments: List[RoadSegment])[source]¶

Convert segments to pandas DataFrame.

Parameters:: segments – Road segments to convert
Returns:: pandas.DataFrame with segment data

geo_sampling.sampler.load_segments_from_csv(path: str | Path) → List[RoadSegment][source]¶

Load road segments from CSV file.

Parameters:: path – Path to CSV file
Returns:: List of RoadSegment objects

geo_sampling.sampler.sample_roads(segments: List[RoadSegment], n: int, road_types: str | List[str] | None = None, strategy: str = 'random', seed: int | None = None) → List[RoadSegment][source]¶

Convenience function to sample roads.

Parameters:

segments – Road segments to sample from
n – Number of segments to sample
road_types – Road types to include
strategy – Sampling strategy (“random” or “stratified”)
seed – Random seed

Returns:

List of sampled RoadSegment objects