z_cell+=[ztemp]
c_cell+=[ctemp]
cell_cell+=[celltemp]
c=numpy.array(c)
y=numpy.array(y)
x=numpy.array(x)
z=numpy.array(z)
pylab.figure(figsize=(10, 6))
ax=pylab.subplot(111)
stp = TernaryPlot(ax, ellabels=['Au', 'Si', 'Cu'])
celllist=[1, 2]+range(4, 21)+[22]+[24, 25]
minlist=[c.min() for c in comp[numpy.array(celllist)-1, :].T]
rangelist=numpy.float32([[m, 1.-numpy.concatenate([minlist[:i], minlist[i+1:]]).sum()] for i, m in enumerate(minlist)])
colors=stp.color_comp_calc(comp[numpy.array(celllist)-1, :], rangelist=rangelist)
pylab.clf()
for cell, xv, yv, zv in zip(cell_cell, x_cell, y_cell, z_cell):
xv=numpy.array(xv)
yv=numpy.array(yv)
zv=numpy.array(zv)
sortarr=numpy.argsort(xv)
#pylab.plot(xv[sortarr], yv[sortarr], '.', color=colors[celllist.index(cell)], markersize=16)
#pylab.plot(xv[sortarr], yv[sortarr], '-', color=colors[celllist.index(cell)], linewidth=1, alpha=.5)
a=yv[sortarr]
#a=yv[sortarr]/(yv[sortarr]+zv[sortarr])
pylab.plot(xv[sortarr], a, '.', color=colors[celllist.index(cell)], markersize=16)
pylab.plot(xv[sortarr], a, '-', color=colors[celllist.index(cell)], linewidth=1, alpha=.5)
#xplot=numpy.array(map(operator.itemgetter(1), data))
#yplot=numpy.array(map(operator.itemgetter(2), data))
#garb=numpy.array(map(operator.itemgetter(3), data))
#garb=numpy.array(map(operator.itemgetter(4), data))
#ca=numpy.array(map(operator.itemgetter(5), data))
#xlab='heat rate (K/s)'
#ylab='Tg weighted mean (K)'
##****
#start common plotting routine
pylab.figure(figsize=(10, 6))
ax=pylab.subplot(111)
stp = TernaryPlot(ax, ellabels=['Au', 'Si', 'Cu'])
minlist=[c.min() for c in ca.T]
rangelist=numpy.float32([[m, 1.-numpy.concatenate([minlist[:i], minlist[i+1:]]).sum()] for i, m in enumerate(minlist)])
colors=stp.color_comp_calc(ca, rangelist=rangelist)
pylab.clf()
for cell in set(cells):
i=numpy.where(cells==cell)
x_cell=numpy.array(xplot[i])
y_cell=numpy.array(yplot[i])
sortarr=numpy.argsort(x_cell)
x_cell=x_cell[sortarr]
y_cell=y_cell[sortarr]
col=colors[i][0]#should all be the same color so take the 1st
pylab.plot(x_cell, y_cell, '.', color=col, markersize=16)
# for xx, yy in zip(x_cell, y_cell):
# pylab.text(xx, yy, `cell`, ha='center', va='center', color=col, fontsize=12)
pylab.plot(x_cell, y_cell, '-', color=col, linewidth=1, alpha=.5)
si=numpy.float32([16.2,18.4,14.2,13.2,11.7,10.6,16.7,14.9,12.4,10.9,9.2,16.3,14.7,12.7,15.7,13.9,12.9,11.5,10.7,15.2,14.7,11.9,10.5,8.4,12.8,12.1,10,9,9.3,13.3,10.1,9.1,16.8,14.7,11.9,10.5,19.7,16.3,13.2,11.5,10.2,21,19.6,16.4,13,12.6,10.2,8.3,14.3,11.4,10.5,9.5,8.9,12.9,11.1,10,9.3,12.9,11,9.9,13.7,12.2,23,21,14.8,13.5,12.7,23.4,21.3,17,13.6,25,21,17.4,9.5,8.1,11.7,11.4,9.9,8.2,11,10.4,8.4,8.3,12.7,9.8,9.2,8.5,6.6,9.3,14.6,26.9,22.9,18.3,16.6,26.5,24.8,18.8,27,23.9,27.2,24.3,30.9,9.6,10,8,10.1,8.6,8.3,10.9,8.4,8.5,8.2,9.1,8.7,7.3,8.5,7.7,16.9,19.3,21.5,23.2,24.7,17,19.2,20.7,22.6,23.9,16.6,19.2,21.2,21.9,23.1,14.6,19.7,22.9,25.3,27.5,29,18.3,21.5,24.7,26.9,29.3,20.3,23.7,26.7,29.1,16.6,19.1,19.9,20.8,14.4,16.4,18.4,20,20.3,14.4,15.5,17,18.9,12.2,14.2,15.9,31.2,22.9,25.8,28.5,30.7,19.9,24.9,28.2,30.4,32.6,23.8,26.6,29.5,31.8,16.7,17.3,12.9,14.1,15.3,16.3,12.8,14.3,14.4,15.6,11.8,12.9,14,14.7,15.5,11.7,33.9,25.6,29.4,31.6,33.5,24.3,28.1,31.1,33.6,26.3,29.8,32.2,35.6,29.1,12.9,13.9,14.3,11.3,12.5,12.2,9.7,11,11.7,12.2,9.7,10.5,11.6,9.7,11.5,9.3,31.8,34.4,28.2,29.9,33.9,36.3,30.5,33.3,35.8,31.2,35.6,34.9])
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', fontsize=12, color='g', ha='center', va='top')
pylab.text(-0.5*rlab, 0.5*3.**.5*rlab, 'Si', fontsize=12, color='b', ha='center', va='top')
pylab.xlim(-18, 20)
pylab.ylim(-18, 18)
pylab.show()
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',
fontsize=12,
color='g',
ha='center',
