Source code for trackintel.model.locations

import trackintel as ti
from trackintel.model.util import (

_required_columns = ["user_id", "center"]

[docs] @_register_trackintel_accessor("as_locations") class Locations(TrackintelBase, TrackintelGeoDataFrame): """Trackintel class to treat a GeoDataFrames as a collections of locations. Requires at least the following columns: ['user_id', 'center'] For several usecases, the following additional columns are required: ['elevation', 'extent'] Notes ----- `Locations` are spatially aggregated `Staypoints` where a user frequently visits. Examples -------- >>> locations.to_csv("filename.csv") """ def __init__(self, *args, validate=True, **kwargs): super().__init__(*args, **kwargs) if validate: self.validate(self) @property def as_locations(self): return self @staticmethod def validate(obj): if any([c not in obj.columns for c in _required_columns]): raise AttributeError( "To process a DataFrame as a collection of locations, it must have the properties" f" {_required_columns}, but it has [{', '.join(obj.columns)}]." ) if obj.shape[0] <= 0: raise ValueError(f"GeoDataFrame is empty with shape: {obj.shape}") if obj["center"].iloc[0].geom_type != "Point": # todo: We could think about allowing both geometry types for locations (point and polygon) # One for extend and one for the center raise TypeError("The center geometry must be a Point (only first checked).")
[docs] @doc(_shared_docs["write_csv"], first_arg="", long="locations", short="locs") def to_csv(self, filename, *args, **kwargs):, filename, *args, **kwargs)
[docs] @doc(_shared_docs["write_postgis"], first_arg="", long="locations", short="locs") def to_postgis( self, name, con, schema=None, if_exists="fail", index=True, index_label=None, chunksize=None, dtype=None ):, name, con, schema, if_exists, index, index_label, chunksize, dtype)
[docs] def spatial_filter(self, areas, method="within", re_project=False): """ Filter Locations on a geo extent. See :func:`trackintel.geogr.spatial_filter` for full documentation. """ return ti.geogr.spatial_filter(self, areas, method=method, re_project=re_project)