File:Haitz-law.svg
Summary
| Description |
English: Plot of Haitz's law of the luminosity per package of LEDs increasing exponentially over time, while the cost per lumen drops exponentially.
Feel free to add new data points and upload updated versions using the provided Matplotlib code. New data points must be the best values (highest luminosity per package or lowest price per luminosity) at their given time of publication. |
| Date | |
| Source | Own work |
| Author | Geek3 |
| Other versions |
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| SVG development | |
| SVG development | |
| Source code | Python code#! /usr/bin/env python
# -*- coding:utf8 -*-
import matplotlib.pyplot as plt
import numpy as np
import scipy.optimize as op
from math import *
# data: "The case for a national research program on semiconductor lighting" Sandia Report (2000), "Solid-state lighting", Optik & Photonik 2 (2011), and others
# flux in lm/W
flux = zip(
(1968, 0.001, 'GaAsP'),
(1970, 0.0027, 'GaAsP'),
(1972, 0.0041, 'GaAsP'),
(1974, 0.035, 'GaAsPN'),
(1980, 0.062, 'GaAsPN'),
(1983, 0.12, 'GaAlAs'),
(1987, 0.41, 'GaAlAs'),
(1989, 0.78, 'GaAlAs'),
(1992, 1.2, 'GaAlInP'),
(1995, 2.6, 'GaAlInP'),
(1996, 3.9, 'GaAlInP'),
(1998, 11., 'GaAlInP'),
(1999, 17., 'GaAlInP'),
(2000, 46., 'GaAlInP'),
(2005, 170., 'GaAlInP'),
(2003, 110., 'GaInN'),
(2006, 310., 'GaInN'),
(2007, 460., 'GaInN'),
(2009, 1.7e3, 'GaInN'),
(2010, 5.3e3, 'GaInN')
)
# cost in $/lm
cost = zip(
(1973, 53., 'GaAsP'),
(1976, 9.2, 'GaAsPN'),
(1979, 6.2, 'GaAsPN'),
(1981, 3.6, 'GaAsPN'),
(1983, 2.1, 'GaAlAs'),
(1987, 0.64, 'GaAlAs'),
(1989, 0.32, 'GaAlAs'),
(1994, 0.28, 'GaAlInP'),
(1996, 0.14, 'GaAlInP'),
(1997, 0.10, 'GaAlInP'),
(1999, 0.099, 'GaAlInP'),
(2000, 0.077, 'GaAlInP'),
(2001, 0.059, 'GaAlInP'),
(2003, 0.022, 'GaAlInP'),
(2005, 0.017, 'GaAlInP'),
(2007, 0.0096, 'GaInN'),
(2009, 0.0076, 'GaInN'),
(2010, 0.0038, 'GaInN')
)
fig = plt.figure(figsize=(520 / 90.0, 340 / 90.0), dpi=72)
plt.plot(flux[0], flux[1], 'ro', mew=0.8, label='flux / package [lm]')
plt.plot(cost[0], cost[1], 'bD', mew=0.8, label='cost / lumen [$/lm]')
def line(p, x):
return p[0] * (x - p[1])
flux_line = op.minimize(lambda p, x, y: sum((line(p, x) - np.log10(y))**2), x0=(0.1, 2000), args=(np.array(flux[0]), np.array(flux[1])))
trange = np.linspace(1967.5, 2016, 100)
plt.plot(trange, 10**line(flux_line.x, np.array(trange)), 'r-')
cost_line = op.minimize(lambda p, x, y: sum((line(p, x) - np.log10(y))**2), x0=(0.1, 2000), args=(np.array(cost[0]), np.array(cost[1])))
plt.plot(trange, 10**line(cost_line.x, np.array(trange)), 'b-')
plt.gca().tick_params(axis='both', which='major', labelsize=14.4)
plt.gca().set_yscale('log')
plt.grid(True)
plt.xlim(1966, 2017)
plt.ylim(0.6e-3, 1e4)
plt.legend(loc='upper left')
plt.tight_layout()
plt.savefig('Haitz-law.svg')
|
.svg)
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