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<p align="center">
<img width="800" height="100" src="https://github.com/ksmet1977/luxpy/blob/master/docs/images/LUXPY_logo3.jpg">
</p>
# Python toolbox for lighting and color science
* Author: Kevin A.G. Smet (ksmet1977 at gmail.com)
* Version: 1.9.5
* Date: January 20, 2022
* License: [GPLv3](https://github.com/ksmet1977/luxpy/blob/master/LICENSE.md)
[](https://doi.org/10.5281/zenodo.1298963)
### Cite LuxPy:
If you use the package, please cite the following **tutorial paper** published in **LEUKOS**:
[**Smet, K. A. G. (2019). Tutorial: The LuxPy Python Toolbox for Lighting and Color Science. LEUKOS, 1–23. DOI: 10.1080/15502724.2018.1518717**](https://www.tandfonline.com/doi/full/10.1080/15502724.2018.1518717)
### **NEW** luxpy basic web-app [under development]:
For some online spectral calculations (ANSI/IES TM30, CIE 13.3-1995 Ra, CIE 224:2017 Rf, alpha-opic irradiances, Equivalent Daylight Illuminance (EDI), Efficacy of Luminous Radiation (ELR), Daylight Efficacy Ratio (DER), IES/LDT Luminous Intensity Distribution plots/renders, ...) using a python web-application:
[**luxpy.herokuapp.com**](https://luxpy.herokuapp.com/) or [**share.streamlit.io/ksmet1977/luxpy_app/main/luxpy_app.py**](https://share.streamlit.io/ksmet1977/luxpy_app/main/luxpy_app.py)
-------------------------------------------------------------------------------
## What is LuxPy?
**Luxpy** is an open source package under a GPLv3 license that supports several common
**lighting**, **colorimetric**, **color appearance** and other **color science**
related calculations and models, such as:
* spectral data interpolation (conform CIE15-2018) and normalization
* calculation of daylight phase, blackbody radiator and other reference illuminant spectra
* calculation of tristimulus values
* correlated color temperature and Duv (methods: robertson1968, ohno2014, li2016, zhang2019)
* color space transformations
* chromatic adaptation transforms
* color appearance models
* color rendition indices (eg. CIE Ra, CIE 224:2017 Rf, ANSI/IES TM30 Rf, Rg, ... + IES TM30 Annex E priority levels & reports)
* calculation of photobiological quantities (eg melanopic irradiance, MEDI, CS, ...)
* multi-component spectrum creation and optimization
* hyper-spectral image simulation and rendering
* MacAdam ellipses
* color differences (cam02ucs, DE2000, ...)
* modelling of individual observer color matching functions (Asano, 2016)
* calculation of CIEOP06 (cfr. CIE TC1-97) color matching functions and cone-fundamentals
* display characterization
* reading and visualizing IES and LDT photometric files (vizualizations: 2D polar plots, 3D plots, single-bounce physical-based rendering)
* spectral mismatch (f1', correction factors) and measurement uncertainty (under development)
* ...
As of May 2019, LuxPy now also has a toolbox **spectro** for **spectral measurements** with **JETI** and **OceanOptics** spectrometers:
* spectro.jeti: easy installation (dll's are part of sub-package).
* spectro.oceanoptics: more tricky installation (requires manual install of **python-seabreeze**, ...; see [here](https://github.com/ksmet1977/luxpy/blob/master/luxpy/toolboxes/spectro/oceanoptics/oceanoptics.md) or subpackage help for more info)
**UPDATED** (May, 2021): **ANSI/IES-TM30-2018** graphical output (**Color Rendition Reports**, **Color Vector Graphics**, **Annex E priority levels**...)
-------------------------------------------------------------------------------
## How to use LuxPy (basics)?
Luxpy can be easily installed from pypi `pip install luxpy` or anaconda `conda install -c ksmet1977 luxpy`.
An overview of the *basic usage* is given in the [**luxpy basic usage.ipynb**](https://github.com/ksmet1977/luxpy/blob/master/luxpy_basic_usage.ipynb) jupyter notebook (**!! Don't right-click to save, see below for download instructions !!**),
as well as the tutorial paper published in LEUKOS: [**Smet, K. A. G. (2019). Tutorial: The LuxPy Python Toolbox for Lighting and Color Science. LEUKOS, 1–23. DOI: 10.1080/15502724.2018.1518717**](https://www.tandfonline.com/doi/full/10.1080/15502724.2018.1518717)
* !!! **To download jupyter notebook:**
1. Open the notebook in github by clicking it and then press download button at the top right; don't right-click the notebook link itself and use 'save as ...', as this apparently results in some *NotJSONError* when opening the notebook!
2. If the jupyter notebook fails to open or download or still gives an error: (*Github seems to experience some type of problem sometimes with its jupyter notebook backend, see [issue](https://github.com/iurisegtovich/PyTherm-applied-thermodynamics/issues/11)*), try opening the file using the [nbviewer.jupyter.org](https://nbviewer.jupyter.org) online viewer, (or just click this direct link: [nbviewer.jupyter.org/github/ksmet1977/luxpy/blob/master/luxpy_basic_usage.ipynb](https://nbviewer.jupyter.org/github/ksmet1977/luxpy/blob/master/luxpy_basic_usage.ipynb)) and then download it from there (use download notebook button at the top right of the page).
For more details on structure, functionality, etc., see:
1. the github pages on: [**ksmet1977.github.io/luxpy/**](http://ksmet1977.github.io/luxpy/)
2. the [**LuxPy_Documentation**](https://github.com/ksmet1977/luxpy/blob/master/LuxPy_Documentation.pdf) pdf
3. or, the **\__doc__string** of each function.
To get help on, for example the **spd_to_xyz()** function, type:
import luxpy as lx
?lx.spd_to_xyz
To get a list of functions/modules, type:
dir(lx)
-------------------------------------------------------------------------------
## Python tutorials
#### Some basic tutorials can be found at:
* [cs231n.github.io/python-numpy-tutorial/](http://cs231n.github.io/python-numpy-tutorial/)
* [docs.python.org/3/tutorial/](https://docs.python.org/3/tutorial/)
#### A list of basic and more advanced is given at:
* [wiki.python.org/moin/BeginnersGuide/Programmers](https://wiki.python.org/moin/BeginnersGuide/Programmers)
#### Matlab versus Python:
* [scipy.github.io/old-wiki/pages/NumPy_for_Matlab_Users.html](http://scipy.github.io/old-wiki/pages/NumPy_for_Matlab_Users.html)
#### Udemy.com:
* [Udemy.com](https://www.udemy.com/courses/search/?ref=home&src=ukw&q=python%20numpy) offers some great courses. Although some of these are payed, they often come at huge discounted prices.
#### Youtube.com:
* [www.youtube.com](https://www.youtube.com/results?search_query=python+numpy+tutorial) also has lots of free online tutorials.