def plotUniqueGreenSeries():
'''
'''
# Unique green series plot
fig1 = plt.figure()
fig2 = plt.figure()
fig1.set_tight_layout(True)
fig2.set_tight_layout(True)
ax1 = fig1.add_subplot(111)
ax2 = fig2.add_subplot(111)
pf.AxisFormat()
pf.TufteAxis(ax1, ['left', 'bottom'], Nticks=[5, 5])
pf.TufteAxis(ax2, ['left', 'bottom'], Nticks=[5, 5])
for j in [0.04, 0.34, 0.94, 2, 4, 6]:
stage2, stage3 = genStockmanAnalysis(spectrum, filters, Lnorm,
Mnorm, Snorm, j)
ax1.plot(spectrum, stage3['blue'], c='b', alpha=0.7)
for j in np.arange(0.1, 5, 0.75):
ax2.plot(spectrum, Snorm - (j / 10 * (Lnorm + (0.5 * Mnorm))),
c='b', alpha=0.7)
ax1.plot(spectrum, np.zeros(len(spectrum)), 'k',
linewidth=1)
ax2.plot(spectrum, np.zeros(len(spectrum)), 'k',
linewidth=1)
ax1.set_xlim([spectrum[0], 650])
ax1.set_ylim([-0.7, 1.4])
ax1.set_xlabel('wavelength (nm)')
ax1.set_ylabel('sensitivity')
ax2.set_xlim([spectrum[0], 700])
ax2.set_ylim([-0.9, 1.2])
ax2.set_xlabel('wavelength (nm)')
ax2.set_ylabel('sensitivity')
plt.show()
import numpy as np
from base import optics as op
from base import plot as pf
from stockmanModel import genStockmanAnalysis
from genLMS import genLMS
maxLambda = 770
filters, spectrum = op.filters.stockman(minLambda=390,
maxLambda=maxLambda, RETURN_SPECTRUM=True,
resolution=1)
Lnorm, Mnorm, Snorm = genLMS(spectrum, filters,
fundamental='stockspecsens', LMSpeaks=[559, 530, 421])
stage2, stage3 = genStockmanAnalysis(spectrum, filters, Lnorm,
Mnorm, Snorm)
def plotStage2Stockman():
'''
'''
fig = plt.figure()
fig.set_tight_layout(True)
ax = fig.add_subplot(111)
pf.AxisFormat()
pf.TufteAxis(ax, ['left', 'bottom'], Nticks=[5, 5])
for key in stage2:
ax.plot(spectrum, stage2[key])
ax.set_xlim([spectrum[0], spectrum[-1]])
ax.set_xlabel('wavelength (nm)')
ax.set_ylabel('sensitivity')