Skip to main content

Street geometry processing toolkit

Project description

neatnet: Street Geometry Processing Toolkit

Continuous Integration codecov

Introduction

neatnet offers a set of tools pre-processing of street network geometry aimed at its simplification. This typically means removal of dual carrieageways, roundabouts and similar transportation-focused geometries and their replacement with a new geometry representing the street space via its centerline. The resulting geometry shall be closer to a morphological representation of space than the original source, that is typically drawn with transportation in mind (e.g. OpenStreetMap).

Examples

import neatnet

simplified = neatnet.neatify(gdf)

Installing

You can install neatnet from PyPI or from conda-forge using the tool of your choice:

pip install neatnet

Or (recommended):

conda install neatnet -c conda-forge

Contribution

While we consider the API stable, the project is young and may be evolving fast. All contributions are very welcome, see our guidelines in CONTRIBUTING.md.

Recommended Citations

The package is a result of a scientific collaboration between The Research Team on Urban Structure of Charles University (USCUNI), NEtwoRks, Data, and Society research group of IT University Copenhagen (NERDS) and Oak Ridge National Laboratory.

If you use neatnet for a research purpose, please consider citing the original paper introducing it.

Canonical Citation (primary)

forthcoming

Repository Citation (secondary)

DOI

Funding

The development has been supported by the Charles University’s Primus program through the project "Influence of Socioeconomic and Cultural Factors on Urban Structure in Central Europe", project reference PRIMUS/24/SCI/023.


This package developed & and maintained by:

Copyright (c) 2024-, neatnet Developers

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

neatnet-0.1.4.tar.gz (25.2 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

neatnet-0.1.4-py3-none-any.whl (145.5 kB view details)

Uploaded Python 3

File details

Details for the file neatnet-0.1.4.tar.gz.

File metadata

  • Download URL: neatnet-0.1.4.tar.gz
  • Upload date:
  • Size: 25.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for neatnet-0.1.4.tar.gz
Algorithm Hash digest
SHA256 1cc391ecfd6e2d880664b2e9a258ee19e26605ec5fefbb55a63d9b244c3638c6
MD5 da13aec6fa2c221b816920c37072b7ed
BLAKE2b-256 d22145ab48ec9920879fc1556f4d9bcd1d60574444943936827b16ddb5bd187b

See more details on using hashes here.

Provenance

The following attestation bundles were made for neatnet-0.1.4.tar.gz:

Publisher: release_to_pypi.yml on uscuni/neatnet

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file neatnet-0.1.4-py3-none-any.whl.

File metadata

  • Download URL: neatnet-0.1.4-py3-none-any.whl
  • Upload date:
  • Size: 145.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for neatnet-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 b77991c383005782093846d9bf0863df0f112e93d2f3ade08bb308d29bf8122b
MD5 0988cfa63bafe99a5cbe1e555cfa8643
BLAKE2b-256 de315f186dbc0e5eb3cdcbbb3210c4c0b4f17fb06a3478dada4b93c7a973dd04

See more details on using hashes here.

Provenance

The following attestation bundles were made for neatnet-0.1.4-py3-none-any.whl:

Publisher: release_to_pypi.yml on uscuni/neatnet

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page