geochron 0.6.0

A companion package to geostructures enabling geo-spatial-temporal data structures.

Geochron

A companion package to geostructures (https://github.com/ccbest/geostructures) enabling geo-spatial-temporal data structures

Installation

Geochron is available on PYPI

$ pip install geochron 

Optional Dependencies

Geochron does not require any of the below dependencies to function, however some functionality uses:

• networkx (chron-nets/geosynchnet)
• timehash (geotimehash)

Overview

Geochron enables various ways of displaying and structuring geospatial-temporal data

The methods currently supported are:

• time hexes H3 Geohashes with second dimension time (Original Niemeyer can also be used)
• chron-net (https://www.nature.com/articles/s41467-020-17634-2)
• geotimehash (https://isprs-annals.copernicus.org/articles/IV-4-W2/31/2017/isprs-annals-IV-4-W2-31-2017.pdf)
• geosynchnet (geographic synchronous networks)

Basic Functionality

The primary and simplest use case is converting a geostructures FeatureCollection to another datastructure. Geostructures FeatureCollections can take most major geospatial standards like shapefiles and geopandas. See geostructures documentation.

import datetime as dt
from geochron import convert_timehex, convert_chronnet, convert_geotimehash
from geostructures.geohash import H3Hasher

hasher = H3Hasher(resolution=11)

timehex_output = convert_timehex(fcol=Feature_Collection_of_time_shapes,
time_delta= dt.timedelta(hours=1), hash_func= hasher.hash_collection)

chronnet_output = convert_chronnet(fcol=Feature_Collection_of_time_shapes,
time_delta= dt.timedelta(hours=1), hash_func= hasher.hash_collection, self_loops = True, mode = "directed")

geotimehash_output = convert_geotimehash(fcol=Feature_Collection_of_time_shapes, precision = 8,
hash_func= hasher.hash_collection)

geosynchnet_output = convert_geosynchnet(fcol=Feature_Collection_of_time_shapes, 
time_delta= dt.timedelta(hours=1), hash_func= hasher.hash_collection)

timegrid_output = convert_time_grid(fcol=Feature_Collection_of_time_shapes, 
time_interval: dt.timedelta(days=1), time_subinterval dt.timedelta(hours=1), 
hash_func= hasher.hash_coordinates, integerize=False)

Geochron also provides helper functions for visualization using popular libraries like Folium and Pydeck. These helpers arlocated in geochron.visualizations

More Information

For an more in-depth introduction, please review our collection of Jupyter notebooks.

Reporting Issues / Requesting Features

The Geochron team uses Github issues to track development goals. Please include as much detail as possible so we can effectively triage your request.

Contributing

We welcome all contributors! Please review CONTRIBUTING.md for more information.

Developers

Eli Talbert (Sr. Data Scientist/PhD/Project Owner)
https://github.com/etalbert102

Carl Best (Sr. Data Scientist)
https://github.com/ccbest/