#Tg avergaed over multiple scans data=[(cell, xv, yv, zv,0., cv) for cell, xv, yv, zv, cv in zip(range(1,26),x, y, z, comp) if len(zv)>0] cells=numpy.array(map(operator.itemgetter(0), data)) enth=map(operator.itemgetter(1), data) coolrate=map(operator.itemgetter(2), data) za=numpy.array(map(operator.itemgetter(3), data)) garb=numpy.float32(map(operator.itemgetter(4), data)) ca=numpy.array(map(operator.itemgetter(5), data)) title=r'Film thickness (nm)' #********start ternary plotting pylab.figure(figsize=(10, 6)) ax=pylab.subplot(111) ##stp = TernaryPlot(ax, ellabels=['Au', 'Si', 'Cu']) stp = TernaryPlot(ax, ellabels=['Au', 'Si', 'Cu'], minlist=[0.47, 0.12, .2]) stp.grid(nintervals=3) stp.label(fontsize=14) #plot za value from above by color stp.scatter(ca, s=80, c=za, label='_', cmap=cm.jet, alpha=1., marker='o') #scatter doesn't work well with legend, so label="_" (hides it); cmap chooses the color scheme; alpha allows some transparency to see overlapping data stp.colorbar(title, fontsize=14) #stp.ax.set_title(title, fontsize=14) #**** ##plot cellnumbers #celllist=[1, 2]+range(4, 21)+[22]+[24, 25] #for selectcell in celllist: # stp.text(comp[selectcell-1], `selectcell`, ha='center', va='center', color='r', fontsize=12)
from myternaryutility import TernaryPlot import matplotlib.cm as cm import numpy import pylab, copy from colorsys import rgb_to_hsv from colorsys import hsv_to_rgb pylab.figure(figsize=(6, 3)) ax=pylab.gca() #stp = TernaryPlot(ax, ellabels=['Au', 'Cu', 'Si']) stp = TernaryPlot(ax, ellabels=['A', 'B', 'C']) stp.grid(nintervals=10, printticklabels=[4]) stp.label(fontsize=12) comps=numpy.random.rand(50, 3) comps/=comps.sum(axis=1)[:, numpy.newaxis] #compdist=(numpy.random.rand(len(comps), 3)-0.5)/5 comps2=copy.copy(comps) comps2[:, 2]+=.5 comps2/=comps2.sum(axis=1)[:, numpy.newaxis] #compsdiff=comps2-comps # #terncoord=numpy.float64(comps) #terncoord2=numpy.float64(comps2) # # # #sat = ((compsdiff**2).sum(axis=1)/2.)**.5 #
35.6, 34.9
])
comps = numpy.array([au, cu, si]).T
comps = numpy.array([c / c.sum() for c in comps])
aumin = comps[:, 0].min()
cumin = comps[:, 1].min()
simin = comps[:, 2].min()
pylab.figure(figsize=(6, 3))
ax = pylab.gca()
#stp = TernaryPlot(ax, ellabels=['Au', 'Cu', 'Si'])
stp = TernaryPlot(ax,
ellabels=['Au', 'Cu', 'Si'],
minlist=[aumin, cumin, simin])
stp.grid(nintervals=10, printticklabels=[4])
stp.label(fontsize=12)
stp.colorcompplot(comps, '.', markersize=9)
colors = stp.color_comp_calc(comps)
pylab.figure(figsize=(4, 4))
#pylab.scatter(x, y, c=colors, s=40)
for xv, yv, c in zip(x, y, colors):
pylab.plot([xv], [yv], '.', color=c, ms=12)
pylab.gca().set_aspect(1)
rmax = numpy.max(x**2 + y**2)**.5
rlab = rmax + 1.5
pylab.text(rlab, 0., 'Au', fontsize=12, color='r', ha='center', va='center')
pylab.text(-0.5 * rlab,
-0.5 * 3.**.5 * rlab,
'Cu',
