Source code for trackintel.model.staypoints

import pandas as pd

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

_required_columns = ["user_id", "started_at", "finished_at"]

[docs] @_register_trackintel_accessor("as_staypoints") class Staypoints(TrackintelBase, TrackintelGeoDataFrame): """Trackintel class to treat a GeoDataFrame as collections of `Staypoints`. Requires at least the following columns: ['user_id', 'started_at', 'finished_at'] Requires valid point geometries; the 'index' of the GeoDataFrame will be treated as unique identifier of the `Staypoints`. For several usecases, the following additional columns are required: ['elevation', 'purpose', 'is_activity', 'next_trip_id', 'prev_trip_id', 'trip_id', location_id] Notes ----- `Staypoints` are defined as location were a person did not move for a while. Under consideration of location uncertainty this means that a person stays within a close proximity for a certain amount of time. The exact definition is use-case dependent. 'started_at' and 'finished_at' are timezone aware pandas datetime objects. Examples -------- >>> staypoints.generate_locations() """ def __init__(self, *args, validate=True, **kwargs): super().__init__(*args, **kwargs) if validate: self.validate(self) # create circular reference directly -> avoid second call of init via accessor @property def as_staypoints(self): return self @staticmethod def validate(obj): # check columns if any([c not in obj.columns for c in _required_columns]): raise AttributeError( "To process a DataFrame as a collection of staypoints, it must have the properties" f" {_required_columns}, but it has {', '.join(obj.columns)}." ) # check timestamp dtypes assert isinstance( obj["started_at"].dtype, pd.DatetimeTZDtype ), f"dtype of started_at is {obj['started_at'].dtype} but has to be tz aware datetime64" assert isinstance( obj["finished_at"].dtype, pd.DatetimeTZDtype ), f"dtype of finished_at is {obj['finished_at'].dtype} but has to be tz aware datetime64" # check geometry assert ( obj.geometry.is_valid.all() ), "Not all geometries are valid. Try x[~ x.geometry.is_valid] where x is you GeoDataFrame" if obj.geometry.iloc[0].geom_type != "Point": raise TypeError("The geometry must be a Point (only first checked).") @property def center(self): """Return the center coordinate of this collection of staypoints.""" lat = self.geometry.y lon = self.geometry.x return (float(lon.mean()), float(lat.mean()))
[docs] def generate_locations( self, method="dbscan", epsilon=100, num_samples=1, distance_metric="haversine", agg_level="user", activities_only=False, print_progress=False, n_jobs=1, ): """ Generate locations from the staypoints. See :func:`trackintel.preprocessing.generate_locations` for full documentation. """ return ti.preprocessing.generate_locations( self, method=method, epsilon=epsilon, num_samples=num_samples, distance_metric=distance_metric, agg_level=agg_level, activities_only=activities_only, print_progress=print_progress, n_jobs=n_jobs, )
[docs] def merge_staypoints(self, triplegs, max_time_gap="10min", agg={}): """ Aggregate staypoints horizontally via time threshold. See :func:`trackintel.preprocessing.merge_staypoints` for full documentation. """ return ti.preprocessing.merge_staypoints(self, triplegs, max_time_gap=max_time_gap, agg=agg)
[docs] def create_activity_flag(self, method="time_threshold", time_threshold=15.0, activity_column_name="is_activity"): """ Add a flag whether or not a staypoint is considered an activity based on a time threshold. See :func:`trackintel.analysis.create_activity_flag` for full documentation. """ return ti.analysis.create_activity_flag( self, method=method, time_threshold=time_threshold, activity_column_name=activity_column_name )
[docs] def spatial_filter(self, areas, method="within", re_project=False): """ Filter Staypoints 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)
[docs] @doc(_shared_docs["write_csv"], first_arg="", long="staypoints", short="sp") def to_csv(self, filename, *args, **kwargs):, filename, *args, **kwargs)
[docs] @doc(_shared_docs["write_postgis"], first_arg="", long="staypoints", short="sp") 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 temporal_tracking_quality(self, granularity="all"): """ Calculate per-user temporal tracking quality (temporal coverage). See :func:`trackintel.analysis.temporal_tracking_quality` for full documentation. """ return ti.analysis.temporal_tracking_quality(self, granularity=granularity)
[docs] def generate_trips(self, triplegs, gap_threshold=15, add_geometry=True): """ Generate trips based on staypoints and triplegs. See :func:`trackintel.preprocessing.generate_trips` for full documentation. """ return ti.preprocessing.generate_trips(self, triplegs, gap_threshold=gap_threshold, add_geometry=add_geometry)
[docs] def radius_gyration(self, method="count", print_progress=False): """ Calculate radius for gyration for Staypoints See :func:`trackintel.analysis.radius_gyration` for full documentation. """ return ti.analysis.radius_gyration(self, method, print_progress)
[docs] def jump_length(self): """ Calculate jump length per user between consecutive staypoints. See :func:`trackintel.analysis.jump_length` for full documentation. """ return ti.analysis.jump_length(self)