This project implements a spatiotemporal trajectory index called Grid-mapped Interval Trees (G-IT) in Python. It provides a simple trajectory access mechanism primarily designated for historical persistent spatiotemporal data. The project contains three main files: GIT.py, which implements the G-IT index, and Trajectory.py, which implements the trajectory data type and testGIT.py, which implements test cases.
The following Python libraries are required to run this project:
- Shapely
- Intervaltree
You can install them using pip:
pip install shapely
pip install intervaltree- GIT.py: Implementation of the G-IT index.
- Trajectory.py: Implementation of the trajectory data type.
- TestGIT.py: A script that inserts a toy dataset into a G-IT index instance and tests different query types.
To run the TestGIT.py script, simply execute the following command:
python TestGIT.pyThis will create a G-IT index instance, insert a toy dataset into the index, and perform various queries. The output will show the results of the queries, which include spatial window query, temporal window query, and spatio-temporal window query.
To use the G-IT index and trajectory classes in your own project, you can import them as follows:
from GIT import GIT
from Trajectory import TrajectoryCreate a G-IT index instance by specifying the parameters for the spatial grid:
git_index = GIT(sf_xmin=0, sf_xmax=100, sf_ymin=0, sf_ymax=100, delta_x=10, delta_y=10)Create a trajectory instance and insert it into the G-IT index:
from shapely.geometry import Point
traj = Trajectory(1, [(1, Point(5, 5)), (2, Point(5, 15)), (3, Point(15, 15)), (4, Point(25, 5))])
git_index.insert(traj)
Perform various queries on the G-IT index:
# Spatial window query
result = git_index.spatial_window_query(x1, y1, x2, y2)
# Temporal window query
result = git_index.temporal_window_query(t1, t2)
# Spatio-temporal window query
result = git_index.spatio_temporal_window_query(x1, y1, x2, y2, t1, t2)