pyliburo
Release 0.12

Python Library for Urban Optimization

Keywords: urban, design, architecture, optimisation
License: GPL-3.0
Install: pip install pyliburo==0.12

Documentation

#========================================================
Py4design previously known as Pyliburo
#========================================================
The citation if you are using the library for your research work:

Chen, Kian Wee, and Leslie Norford. 2017. “Developing an Open Python Library for Urban Design Optimisation - Pyliburo.” In Building Simulation 2017, 486–493. San Francisco, USA.

Publications that have used Py4design:

Chen, Kian Wee, and Leslie Norford. 2017. “Evaluating Urban Forms for Comparison Studies in the Massing Design Stage.” Sustainability 9 (6). doi:10.3390/su9060987.

Chen, Kian Wee, Patrick Janssen, and Leslie Norford. 2017. “Automatic Parameterisation of Semantic 3D City Models for Urban Design Optimisation.” In Future Trajectories of Computation in Design – Proceedings of the 17th International Conference on Computer Aided Architectural Design Futures, 51–65. Istanbul, Turkey.

Chen, Kian Wee, Patrick Janssen, and Leslie Norford. 2017. “Automatic Generation of Semantic 3D City Models from Conceptual Massing Models.” In Future Trajectories of Computation in Design – Proceedings of the 17th International Conference on Computer Aided Architectural Design Futures, 84–100. Istanbul, Turkey.

Chen, Kian Wee, and Leslie K Norford. 2016. “Workflow for Generating 3D Urban Models from Open City Data for Performance-Based Urban Design.” In Asim 2016 IBPSA Asia Conference. Jeju, Korea.

API documentation available at http://chenkianwee.github.io/py4design/
Working examples are available at https://github.com/chenkianwee/py4design_examples

To run the environment:

1.) install miniconda for python2.7
(instructions on how to use anaconda: http://conda.pydata.org/docs/using/envs.html)

2.) libraries to download:

    a.) follow the conda install instruction for pythonocc from this link: http://www.pythonocc.org/download/ 

    b.) conda install scipy (BSD accepted license)
    
    c.) conda install sympy
    
    d.) pip install numpy-stl

3.) pip install py4design

4.) install Daysim from http://daysim.ning.com/ for the daylighting analysis

    a.) if c:/daysim/radiance/bin on env path, delete it
	
5.) conda install spyder (for editing the scripts)

#========================================================
list of libraries used in py4design
#========================================================

1.) lxml ((BSD) libxml2 and libxslt2 (MIT))

2.) pyshp (mit license)

3.) pythonocc (GNU LGPL3)

4.) numpy (BSD 3-clause "New" or "Revised" License)

5.) scipy (BSD 3-clause "New" or "Revised" License)

6.) sympy (BSD 3-clause "New" or "Revised" License)

7.) pycollada (BSD 3-clause "New" or "Revised" License)

8.) networkx (BSD 3-clause "New" or "Revised" License)

9.) scikit-learn (BSD 3-clause "New" or "Revised" License)

10.) pymf

11.) cvxopt (GNU General Public License v3.0)

12.) matplotlib 

13.) numpy-stl

Dependencies: 8
Dependent packages: 0
Dependent repositories: 0
Total releases: 14
Latest release: Aug 22, 2018
First release: May 2, 2017
Stars: 10
Forks: 9
Watchers: 9
Contributors: 5
Repository size: 166 MB
SourceRank: 8