#!/usr/bin/env python
# coding: utf-8

# # Light Sources

# A light source is a surface or object emitting light by a transformation of energy. <a name="back_reference_1"></a><a href="#reference_1">[1]</a>
# 
# An important difference exists between a light source and an illuminant. The former is an actual physical light and can be use to illuminate a surface while the later is usually mathematically defined, reproducible and may not be physically created.
# 
# > At present no artificial source is recommended to realise CIE standard illuminant D65 or any other illuminant D of different correlated colour temperature. It is hoped that new developments in light sources and filters will eventually offer sufficient basis for a CIE recommendation. <a name="back_reference_2"></a><a href="#reference_2">[2]</a>
# 
# [Colour](https://github.com/colour-science/colour/) provides the following light sources spectral distributions:

# In[1]:


from pprint import pprint

import colour

pprint(sorted(colour.LIGHT_SOURCES_SDS.keys()))


# ## RIT Light Sources

# The *RIT* light sources have been extracted from the [PointerData.xls](http://www.cis.rit.edu/research/mcsl2/online/PointerData.xls) spreadsheet. <a name="back_reference_3"></a><a href="#reference_3">[3]</a>
# 
# Unfortunately references for the data are not indicated thus the light source names cannot be accurately verified.
# 
# The *RIT* light sources have the following range and increments:

# In[2]:


from colour.colorimetry.datasets.light_sources.sds import LIGHT_SOURCES_RIT_SDS
for key, value in sorted(LIGHT_SOURCES_RIT_SDS.items()):
    print('{0}: {1}'.format(key, value.shape))


# In[3]:


from colour.plotting import *


# In[4]:


colour_style();


# In[5]:


from colour.utilities import batch

# Plotting the *RIT* light sources.
for light_sources in batch(list(LIGHT_SOURCES_RIT_SDS.values()), 4):
    plot_multi_sds(light_sources);


# ## NIST Light Sources

# The *NIST* light sources have been extracted from the [NIST CQS simulation 7.4.xls](http://cie2.nist.gov/TC1-69/NIST CQS simulation 7.4.xls) spreadsheet. <a name="back_reference_4"></a><a href="#reference_4">[4]</a>
# 
# They have been divided into 3 categories:
# 
# * Traditional light sources from *NIST*.
# * LED light sources from *NIST*.
# * Philips light sources from *NIST*.
# 
# The *NIST* light sources have the following range and increments:

# In[6]:


from colour.colorimetry.datasets.light_sources.sds import (
    LIGHT_SOURCES_NIST_TRADITIONAL_SDS,
    LIGHT_SOURCES_NIST_LED_SDS,
    LIGHT_SOURCES_NIST_PHILIPS_SDS)

for name, categorie in (('Traditional', LIGHT_SOURCES_NIST_TRADITIONAL_SDS),
                        ('LED', LIGHT_SOURCES_NIST_LED_SDS),
                        ('Philips', LIGHT_SOURCES_NIST_PHILIPS_SDS)):
    print('"{0}" Light Sources:'.format(name))
    for key, value in sorted(categorie.items()):
        print('\t{0}: {1}'.format(key, value.shape))
    print('\n')


# In[7]:


# Plotting the *NIST* *Traditional* light sources.
traditional_light_sources = [v for k, v in sorted(LIGHT_SOURCES_NIST_TRADITIONAL_SDS.items())] 
for light_sources in batch(traditional_light_sources, 4):
    plot_multi_sds(light_sources);


# In[8]:


# Plotting the *NIST* *LED* light sources.
LED_light_sources = [v for k, v in sorted(
        LIGHT_SOURCES_NIST_LED_SDS.items())] 
for light_sources in batch(LED_light_sources, 4):
    plot_multi_sds(light_sources);


# In[9]:


# Plotting the *NIST* *Philips* light sources.
philips_light_sources = [v for k, v in sorted(LIGHT_SOURCES_NIST_PHILIPS_SDS.items())] 
for light_sources in batch(philips_light_sources, 4):
    plot_multi_sds(light_sources);


# ## Chromaticity Coordinates

# For convenience purpose the chromaticity coordinates of the provided light sources are given for the *CIE 1931 2° Standard Observer* and *CIE 1964 10° Standard Observer*:

# In[10]:


sorted(colour.LIGHT_SOURCES['CIE 1931 2 Degree Standard Observer'].items())


# > Note: `'cie_2_1931'` is defined as a convenient alias for `'CIE 1931 2 Degree Standard Observer'`:

# In[11]:


sorted(colour.LIGHT_SOURCES['cie_2_1931'])


# In[12]:


sorted(colour.LIGHT_SOURCES['CIE 1964 10 Degree Standard Observer'].items())


# > Note: `'cie_10_1964'` is defined as a convenient alias for `'CIE 1964 10 Degree Standard Observer'`:

# In[13]:


sorted(colour.ILLUMINANTS['cie_10_1964'])


# ## Bibliography

# 1. <a href="#back_reference_1">^<a> <a name="reference_1"></a>CIE. (n.d.). 17-982 primary light source. Retrieved October 02, 2014, from http://eilv.cie.co.at/term/982
# 2. <a href="#back_reference_2">^<a> <a name="reference_2"></a>CIE TC 1-48. (2004). CIE 015:2004 Colorimetry, 3rd Edition. CIE 015:2004 Colorimetry, 3rd Edition (pp. 1–82). ISBN:978-3-901-90633-6
# 3. <a href="#back_reference_3">^<a> <a name="reference_3"></a>Pointer, M. R. (1980). Pointer’s Gamut Data. Retrieved from http://www.cis.rit.edu/research/mcsl2/online/PointerData.xls
# 4. <a href="#back_reference_4">^<a> <a name="reference_4"></a>Ohno, Y., & Davis, W. (2008). NIST CQS simulation 7.4. Retrieved from http://cie2.nist.gov/TC1-69/NIST%20CQS%20simulation%207.4.xls

# ## Dataset

# 1. *RIT* Light Sources: Pointer, M. R. (1980). Pointer’s Gamut Data. Retrieved from http://www.cis.rit.edu/research/mcsl2/online/PointerData.xls
# 2. *NIST* Light Sources: Ohno, Y., & Davis, W. (2008). NIST CQS simulation 7.4. Retrieved from http://cie2.nist.gov/TC1-69/NIST%20CQS%20simulation%207.4.xls