def plotFilters(invert=False, log=False, lens_only=True,
macula_only=False, lens_age=[20, 40, 60, 80],
spectrum=spectrum, stiles=True):
'''
'''
if macula_only:
filters, spectrum = filt.stockman(minLambda=400,
maxLambda=700,
RETURN_SPECTRUM=True,
ONLY_MACULA=True,
resolution=1)
if lens_only and lens_age is None:
filters, spectrum = filt.stockman(minLambda=400,
maxLambda=700,
RETURN_SPECTRUM=True,
ONLY_LENS=True,
resolution=1)
if lens_only and lens_age is not None:
spectrum = np.arange(400, 700)
filters = np.zeros((len(spectrum), len(lens_age)))
for i, age in enumerate(lens_age):
filters[:, i] = filt.lens_age_correction(age, spectrum,
stiles=stiles)
fig = plt.figure()
fig.set_tight_layout(True)
ax = fig.add_subplot(111)
pf.AxisFormat()
pf.TufteAxis(ax, ['left', 'bottom'], Nticks=[5, 5])
if log:
ax.semilogy(spectrum, filters, 'k', linewidth=2)
else:
ax.plot(spectrum, filters, 'k', linewidth=2)
ax.set_xlabel('wavelength (nm)')
ax.set_xlim([400, 700])
if log:
ax.set_ylim([-10, max(filters)])
ax.set_ylabel('log density')
else:
ax.set_ylabel('density')
if invert:
pf.invert(ax, fig, bk_color='k')
plt.show()
#! /usr/bin/env python
import matplotlib.pylab as plt
import numpy as np
from base.optics import filters
from base import spectsens as ss
from base import plot as pf
from genLMS import genLMS
maxLambda = 770
filters, spectrum = filters.stockman(minLambda=390,
maxLambda=maxLambda, RETURN_SPECTRUM=True,
resolution=1)
def plotCompare(compare=['stockman', 'stockSpecSens', 'neitz']):
'''
'''
fig = plt.figure()
fig.set_tight_layout(True)
ax = fig.add_subplot(111)
pf.AxisFormat()
pf.TufteAxis(ax, ['left', 'bottom'], Nticks=[5, 5])
style = ['-', '--', '-.']
for i, condition in enumerate(compare):
Lnorm, Mnorm, Snorm = genLMS(spectrum, filters,
fundamental=condition, LMSpeaks=[559, 530, 419])
ax.plot(spectrum, Lnorm, 'r' + style[i], linewidth=2)
ax.plot(spectrum, Mnorm, 'g' + style[i], linewidth=2)
