Visualizing daylight data using matplotlib with radiance

It is possible to output daylight data from radiance using the following command line: 

rtrace [ options ] [ $EVAR ] [ @file ] octree]

Then, using numpy.filetxt() function, you can read the output rsult file for predefined points as an ndArray. After that, it will be easy to plot them either using matplotlib.pcolor() or matplotlib.contourf().
I prefer this method because it gives more flexibility in reading and reporting data. 

Genetic Algorithms Optimization Using Python .

Genetic algorithms have a lot of potentials for building performance, I look forward to using them in my upcoming research. This attempt was conducted using Python 2.7, Numpy and Matplotlib. You can download the IPython notebook via this link on GoogleDrive:


GhPlotLib, a Scientific Plotting Plugin for Grasshopper

[GhPlotLib], another project on the queue. 


This project aims to bring scientific plotting facilities to grasshopper. From its name, one can guess that it is based on Python\matplotlib module. 
Matplotlib is a python based plotting package developed by John D. Hunter during his final stages of preparing Ph.D. dissertation mainly to overcome problems of implementing complex code structures in MatLab. 
It is important for scientists and engineers to have such tools in their practice to express their discourse. On the other hand, a large community of designers and architects have moved towards quantitatively modeling their designs and expressing them computationally in a form of algorithms. this raised the need to having scientific computing facilities handy to architects and designers, in addition to having plotting facilities to express their mathematical modeling and computational expressions of the built environment. 

You can follow the project on GitHub via the following link: 



ANT a Machine Learning Plugin for Rhino-Grasshopper

During the last few weeks, I've been developing a new plugin for grasshopper called ANT, this plugin is meant to facilitate using Machine Learning techniques in Architecture and design. ANT is derived from the very well-known Python-based module scikit-learn.

Why depending on these techniques? 

Why Python ? 
Python is a powerful programming language. During the last few years, it has dramatically attracted the interest of scientists and engineers due to its power, interactive, efficiency, and consistent ecosystem of growing number of modules that cover major areas of science, technology, engineering and mathematics such as SciPy, NumPy, matplotlib. I have prepared a list of some topics about python importance for science and engineering I recommend them to anyone who is interested: 

Why Scikit-learn? 
There is a dramatic growing interest in applying machine learning in different disciplines, that is why it was important that machine learning algorithms become handy to non specialist users as stated by the developers of scikit-learn: "Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings. Source code, binaries, and documentation can be downloaded from http://scikit-learn.sourceforge.net."

Why Grasshopper? 
Grasshopper is a visual programming language based on algorithmic design for Rhino3D. It has gained high interest by designers and architects due to its ease of use, robustness, plugin ecosystem and other features that make it widely used by computational designers and architects.

These reasons are the main driving force to develop a machine learning plugin for grasshopper by making use of the advantage of each tool. ANT is supposed to be released under BSD simplified licence on this GitHub Repository: 

To follow the updates on ResearchGate via this link: 

And, to join our team you can fill the following form: