citydpc

CityDPC: A Python Library for 3D City Model Processing

https://github.com/rwth-e3d/citydpc

Science Score: 52.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
    Organization rwth-e3d has institutional domain (www.e3d.rwth-aachen.de)
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (18.0%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

CityDPC: A Python Library for 3D City Model Processing

Basic Info
  • Host: GitHub
  • Owner: RWTH-E3D
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 871 KB
Statistics
  • Stars: 7
  • Watchers: 5
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed 6 months ago
Metadata Files
Readme License Citation

README.md

CityDPC

CityDPC: A Python Library for 3D City Model Processing

CityDPC is an open-source Python library designed for handling and analyzing 3D city models in CityGML and CityJSON formats. It provides tools for geometric computations, including identifying shared walls between buildings—critical for urban energy simulations. The library enables the loading, validation, and manipulation of city datasets, supporting applications like Urban Building Energy Modeling (UBEM). CityDPC integrates with UBEM tools like TEASER+, streamlining urban-scale energy assessments by efficiently processing and analyzing large building datasets.

Getting started

If you want to use CityDPC in your workflow you can install it using bash pip install git+https://github.com/RWTH-E3D/CityDPC.git

If you want to run the examples, start by cloning the repo. Continue by installing the package, while in the root director, using: bash pip install . If you are developing we highly recommend using the Development Mode using: bash pip install -e .

Also take a look at the examples!

Support

If you ran into any problems feel free to open a new issue or reach out to one of the developers.

Roadmap

Take a look at the issues any planned features will be listed there.

Contributing

If you want to contribute have a look over at the issues. Either open a new one for a feature you would like to work on and add your comments or find an issue missing an assignee and start working. Feel also free to reach out to one of the developers!

Fromatting & Linting

The code is formatted using Python Black and linted using flake8.

Acknowledgment

We gratefully acknowledge the financial support by BMWK, promotional reference 03EWR010B.

License

Available under the Apache 2.0 License. See the Cite this repository function or the CITATION.cff for citation of this repository.

Project status

Currently under active development.

Latest Changes

  • 0.1.20 CityGML - read all surfaceMember elements
  • 0.1.19 fix measuredHeight assignment on CityJSON import
  • 0.1.18 more warning options
  • 0.1.17 fix datasetToDataframe mismatch
  • 0.1.16 update License
  • 0.1.15 (un-)allowedIDs parameter for imports
  • 0.1.14 support for generic attributes on surfaces
  • 0.1.13 support for gen:doubleAttributes on buildings
  • 0.1.12 add reduce function to dataset for bulk deletions
  • 0.1.11 better namespace creation for output
  • 0.1.10 suppress warnings by type
  • 0.1.9 more config options, fixed typo, minor address change
  • 0.1.8 address handling improvements
  • 0.1.7 fix empty geometrie creation/output
  • 0.1.6 fix type of surface properties
  • 0.1.5 fix index issue in collinear point detection
  • 0.1.4 option for fixing single outliers in GroundSurfaces using input flags
  • 0.1.3 warning for non planar surfaces
  • 0.1.2 fixes for loading CityGML files
  • 0.1.1 add more user config options

Owner

  • Name: RWTH Aachen University - E3D Institute of Energy Efficiency and Sustainable Building
  • Login: RWTH-E3D
  • Kind: organization
  • Email: e3d@e3d.rwth-aachen.de
  • Location: Aachen

RWTH E3D

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
type: conference-paper
title: "CityDPC: A Python Library for handling 3D City Model Datasets"
authors:
  - family-names: Shamovich
    given-names: Maxim
  - family-names: Raming
    given-names: Simon
  - family-names: Malhotra
    given-names: Avichal
  - family-names: Frisch
    given-names: Jérôme
  - family-names: Van Treeck
    given-names: Christoph
year: 2024
doi: 10.1002/bapi.202400038
conference:
  name: "BauSim Conference 2024"
languages:
  - en
preferred-citation:
  type: conference-paper
  authors:
    - family-names: Shamovich
      given-names: Maxim
    - family-names: Raming
      given-names: Simon
    - family-names: Malhotra
      given-names: Avichal
    - family-names: Frisch
      given-names: Jérôme
    - family-names: Van Treeck
      given-names: Christoph
  title: "CityDPC: A Python Library for handling 3D City Model Datasets"
  year: 2024
  conference:
    name: "BauSim Conference 2024"
  doi: 10.1002/bapi.202400038
  languages:
    - en

GitHub Events

Total
  • Issues event: 5
  • Watch event: 6
  • Issue comment event: 6
  • Member event: 1
  • Push event: 14
  • Fork event: 2
Last Year
  • Issues event: 5
  • Watch event: 6
  • Issue comment event: 6
  • Member event: 1
  • Push event: 14
  • Fork event: 2

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 3
  • Total pull requests: 0
  • Average time to close issues: 5 days
  • Average time to close pull requests: N/A
  • Total issue authors: 2
  • Total pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 3
  • Pull requests: 0
  • Average time to close issues: 5 days
  • Average time to close pull requests: N/A
  • Issue authors: 2
  • Pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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  • c0nb4 (2)
  • swifmaneum (1)
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