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')