def graceHistogramaTc(nAmostras):
plo = GracePlot() # A grace session opens
s1 = Symbol(symbol=symbols.none, fillcolor=3)
l1 = Line(type=lines.none)
l2 = Line(type=lines.solid)
histogramaTc = []
histogramaSu = []
for resultado in nAmostras:
t, mag, mag2, logmag2, energia, calor, su, cumo, cumuE, p = resultado
histogramaTc.append((p, t[su.argmax()]))
histogramaSu.append((p, su.max()))
graficos = []
for p in concentracao:
dados = [x[1] for x in histogramaTc if x[0] == p]
hists, bin_edges = np.histogram(dados, 10)
d1 = DataBar(x=bin_edges[:-1], y=hists, symbol=s1, line=l1)
graficos.append(d1)
mu, std = norm.fit(dados)
x = np.linspace(min(bin_edges), max(bin_edges), 100)
y = norm.pdf(x, mu, std)
d1 = Data(x=x, y=y, symbol=s1, line=l2)
graficos.append(d1)
g = plo[0]
g.plot(graficos)
#g.text('test',.51,.51,color=2)
g.title('histograma de TC')
g.yaxis(label=Label('Tc', font=2, charsize=1.5))
g.xaxis(label=Label('p', font=5, charsize=1.5))
plo.save(dir + '/resultado/histograma.agr')
def graceDiagrama(diagrama):
p = GracePlot() # A grace session opens
s1 = Symbol(symbol=symbols.circle, fillcolor=colors.red)
l1 = Line(type=lines.none)
a, b = ([x[0] for x in diagrama], [x[1] for x in diagrama])
d1 = Data(x=a, y=b, symbol=s1, line=l1)
g = p[0]
g.plot(d1)
#g.text('test',.51,.51,color=2)
g.title('Diagrama')
g.yaxis(label=Label('Tc', font=2, charsize=1.5))
g.xaxis(label=Label('p', font=5, charsize=1.5))
p.save(dir + '/resultado/diagrama.agr')
def plotarDiagramaGausianas(diagramas):
print 'iniciando plot gaussianas'
pp = GracePlot() # A grace session opens
s1 = Symbol(symbol=symbols.circle, fillcolor=colors.red)
l1 = Line(type=lines.none)
TcP = []
diagramaM = []
for p in concentracao:
TcP = [x[1] for x in diagramas if x[0] == p]
TcMedio, std = norm.fit(TcP)
diagramaM.append((p, TcMedio))
a, b = ([x[0] for x in diagrama], [x[1] for x in diagrama])
d1 = Data(x=a, y=b, symbol=s1, line=l1)
g = pp[0]
g.plot(d1)
g.title('Diagrama')
g.yaxis(label=Label('Tc', font=2, charsize=1.5))
g.xaxis(label=Label('p', font=5, charsize=1.5))
pp.save(dir + '/resultado/diagramaMedio.agr')
def plotarMaximos(amostras):
print 'iniciando plot amostras '
pSus = GracePlot()
pCalor = GracePlot()
s1 = Symbol(symbol=symbols.circle)
l1 = Line(type=lines.none)
histogramaTcSus = []
histogramaSus = []
histogramaTcCalor = []
histogramaCalor = []
for resultado in amostras:
t, mag, mag2, logmag2, energia, calor, su, cumo, cumuE, p = resultado
histogramaTcSus.append((p, t[su.argmax()]))
histogramaSus.append((p, su.max()))
histogramaTcCalor.append((p, t[calor.argmax()]))
histogramaCalor.append((p, calor.max()))
graficosSus = []
graficosCalor = []
for p in concentracao:
dadosTcSus = [x[1] for x in histogramaTcSus if x[0] == p]
dadosSus = [x[1] for x in histogramaSus if x[0] == p]
dadosTcCalor = [x[1] for x in histogramaTcCalor if x[0] == p]
dadosCalor = [x[1] for x in histogramaCalor if x[0] == p]
dSus = Data(x=dadosTcSus, y=dadosSus, symbol=s1, line=l1)
graficosSus.append(dSus)
dCalor = Data(x=dadosTcCalor, y=dadosCalor, symbol=s1, line=l1)
graficosCalor.append(dCalor)
gSus = pSus[0]
gSus.plot(graficosSus)
gSus.title('distribuicao susceptibilidade maxima')
gSus.yaxis(label=Label('susceptibilidade', font=2, charsize=1.5))
gSus.xaxis(label=Label('Tc', font=5, charsize=1.5))
pSus.save(dir + '/resultado/distribuicaoSus.agr')
gCalor = pCalor[0]
gCalor.plot(graficosCalor)
gCalor.title('Distribuicao calor máximo')
gCalor.yaxis(label=Label('calor', font=2, charsize=1.5))
gCalor.xaxis(label=Label('tc', font=5, charsize=1.5))
pCalor.save(dir + '/resultado/distribuicaoCalor.agr')
print 'finalizando plot dos máximos '
from GracePlot import *
import math
p = GracePlot() # A grace session opens
l1 = Line(type=lines.none)
x1 = map(lambda x: x / 10., range(0, 100))
y1 = map(math.sin, x1)
y2 = map(math.cos, x1)
d2 = Data(x=x1,
y=y1,
symbol=Symbol(symbol=symbols.circle, fillcolor=colors.red),
line=l1)
d3 = Data(x=x1,
y=y2,
symbol=Symbol(symbol=symbols.circle, fillcolor=colors.blue),
line=l1)
g = p[0]
g.plot([d2, d3])
g.xaxis(label=Label('X axis', font=5, charsize=1.5),
tick=Tick(majorgrid=True,
majorlinestyle=lines.dashed,
majorcolor=colors.blue,
minorgrid=True,
minorlinestyle=lines.dotted,
minorcolor=colors.blue))
for col in args.colors:
colo[ll] = col
ll += 1
if (args.mp or args.eps != 'noeps'):
import matplotlib.font_manager as fnt
import matplotlib.pyplot as plt
xlab = args.xlabel
fig = plt.figure(1)
graf = fig.add_axes([0.13, 0.1, 0.8, 0.8])
if args.xg:
scriptpath = os.path.dirname(os.path.realpath(__file__))
sys.path.append(scriptpath + '/graceplot')
import GracePlot as xg
pgr = xg.GracePlot()
pg = pgr[0]
pg.title(args.title)
s1 = xg.Symbol(symbol=0, fillcolor=0)
l1 = xg.Line(type=1, linewidth=1)
xlabel = xg.Label(args.xlabel)
ylabel = xg.Label(args.ylabel)
pg.xaxis(label=xlabel)
pg.yaxis(label=ylabel)
if (args.scale == 'logx' or args.scale == 'logxy'):
pg.xaxis(scale='logarithmic')
if (args.scale == 'logy' or args.scale == 'logxy'):
pg.yaxis(scale='logarithmic')
colcount = 0
legcount = 0
#%[files,labels,ed,dw,fd,rho_ef]=textread('Pt_3d_electonic_structure.csv','%s%s%n%n%n%n','headerlines',1);
from GracePlot import *
from math import *
from Numeric import *
rhod_ef=[1.65, 2.04, 2.80, 3.58, 4.23, 4.78, 4.78, 5.19]
rhod_ef.reverse()
rho_ef=array([31.65, 33.14, 36.60, 33.86, 25.20, 20.37, 16.55, 16.74])*0.17
sf=6.75/8;
ed=[-2.44, -2.60, -2.74, -2.84, -3.00, -3.12, -3.18, -3.16];
dw=[9.11, 9.70, 10.47, 11.10, 12.14, 12.84, 13.21, 13.03];
p=GracePlot(3.0,4)
p.SetView(0.15,0.15,0.9,1.25)
#set(gcf,'Units','inches','Position',[1 1 6.75 4],'PaperPositionMode','auto','PaperSize',[6.75 4])
d1=Data(ed,rho_ef,
symbol=Symbol(symbol=square,fillcolor=black,size=1.4),
line=Line(linestyle=0),
legend='Density of states \\cW\C 0.17')
d2=Data(ed,rhod_ef,symbol=Symbol(symbol=circle,fillcolor=gray,size=1.4),
line=Line(linestyle=0),
legend='Density of d-states')
p.plot(d1,d2)
p.xaxis(-3.2,-2.4)
p.yaxis(1,7.5)
p.xlabel('d-band center (eV)')
p.ylabel('\\f{12}r\\f{2}\sE\sf\N (arbitrary units)')
from GracePlot import *
import math
import random
p = GracePlot(width=8, height=6) # A grace session opens
x=[1,2,3,4,5,6,7,8,9,10]
y=[1,2,3,4,5,6,7,8,9,10]
labels=['pt1','pt2','Iridium','Na','Ti','hydrogen','Mo '+format_scientific("1.23e3") ,'Ta','pokemon','digital']
dy=map(lambda x:random.random()*2.,x)
s1=Symbol(symbol=symbols.square,fillcolor=colors.cyan)
l1=Line(type=lines.none)
d1=DataXYDY(x=x,y=y,dy=dy,symbol=s1,line=l1)
g=p[0]
g.xaxis(xmin=0, xmax=12)
g.yaxis(ymin=0, ymax=12)
g.plot(d1, autoscale=False)
for i in range(len(labels)):
g.text(' '+labels[i],x[i],y[i],color=colors.violet,charsize=1.2)
g.line(x1=3, y1=1, x2=8, y2=2, linewidth=3, color=colors.green4)
def plotarMediaQuantidades(Amostras):
s1 = Symbol(symbol=symbols.none, fillcolor=colors.red)
l1 = Line(type=lines.solid)
pMag = GracePlot()
pMag2 = GracePlot()
pLogmag2 = GracePlot()
pEnergia = GracePlot()
pCalor = GracePlot()
pSus = GracePlot()
pCumu = GracePlot()
pCumuE = GracePlot()
vMag = []
vMag2 = []
vLogmag2 = []
vEnergia = []
vCalor = []
vSus = []
vCumu = []
vCumuE = []
for p in concentracao:
t = dadosMag = [x[0] for x in amostras if x[9] == p]
mag = dadosMag = [x[1] for x in amostras if x[9] == p]
mag2 = dadosMag = [x[2] for x in amostras if x[9] == p]
logmag2 = dadosMag = [x[3] for x in amostras if x[9] == p]
energia = dadosMag = [x[4] for x in amostras if x[9] == p]
calor = dadosMag = [x[5] for x in amostras if x[9] == p]
sus = dadosMag = [x[6] for x in amostras if x[9] == p]
cumu = dadosMag = [x[7] for x in amostras if x[9] == p]
cumuE = dadosMag = [x[8] for x in amostras if x[9] == p]
t = sum(t) / len(t)
mag = sum(mag) / len(mag)
mag2 = sum(mag2) / len(mag2)
logmag2 = sum(logmag2) / len(logmag2)
energia = sum(energia) / len(energia)
calor = sum(calor) / len(calor)
sus = sum(sus) / len(sus)
cumu = sum(cumu) / len(cumu)
cumuE = sum(cumuE) / len(cumuE)
dMag = Data(x=t, y=mag, symbol=s1, line=l1)
dMag2 = Data(x=t, y=mag2, symbol=s1, line=l1)
dLogmag2 = Data(x=t, y=logmag2, symbol=s1, line=l1)
dEnergia = Data(x=t, y=energia, symbol=s1, line=l1)
dCalor = Data(x=t, y=calor, symbol=s1, line=l1)
dSus = Data(x=t, y=sus, symbol=s1, line=l1)
dCumu = Data(x=t, y=cumu, symbol=s1, line=l1)
dCumuE = Data(x=t, y=cumuE, symbol=s1, line=l1)
vMag.append(dMag)
vMag2.append(dMag2)
vLogmag2.append(dLogmag2)
vEnergia.append(dEnergia)
vCalor.append(dCalor)
vSus.append(dSus)
vCumu.append(dCumu)
vCumuE.append(dCumuE)
gMag = pMag[0]
gMag.plot(vMag)
gMag.title('Magnetizacao x Temperatura')
gMag.yaxis(label=Label('magnetizacao', font=5, charsize=1.5))
gMag.xaxis(label=Label('T', font=5, charsize=1.5))
pMag.save(dir + '/resultado/mag.agr')
gMag2 = pMag2[0]
gMag2.plot(vMag2)
gMag2.title('magnetizacao2 x Temperatura')
gMag2.yaxis(label=Label('mag2', font=5, charsize=1.5))
gMag2.xaxis(label=Label('T', font=5, charsize=1.5))
pMag2.save(dir + '/resultado/mag2.agr')
gLogmag2 = pLogmag2[0]
gLogmag2.plot(vLogmag2)
gLogmag2.title('logmag2 x Temperatura')
gLogmag2.yaxis(label=Label('logmag2', font=5, charsize=1.5))
gLogmag2.xaxis(label=Label('T', font=5, charsize=1.5))
pLogmag2.save(dir + '/resultado/logmag2.agr')
gEnergia = pEnergia[0]
gEnergia.plot(vEnergia)
gEnergia.title('energia x Temperatura')
gEnergia.yaxis(label=Label('energia', font=5, charsize=1.5))
gEnergia.xaxis(label=Label('T', font=5, charsize=1.5))
pEnergia.save(dir + '/resultado/energia.agr')
gCalor = pCalor[0]
gCalor.plot(vCalor)
gCalor.title('Calor especifico x Temperatura')
gCalor.yaxis(label=Label('Calor', font=2, charsize=1.5))
gCalor.xaxis(label=Label('T', font=5, charsize=1.5))
pCalor.save(dir + '/resultado/calor.agr')
gSus = pSus[0]
gSus.plot(vSus)
gSus.title('Susceptibilidade x Temperatura')
gSus.yaxis(label=Label('Susceptibilidade', font=5, charsize=1.5))
gSus.xaxis(label=Label('T', font=5, charsize=1.5))
pSus.save(dir + '/resultado/sus.agr')
gCumu = pCumu[0]
gCumu.plot(vCumu)
gCumu.title('cumulante da magnetizacao x Temperatura')
gCumu.yaxis(label=Label('cumulante', font=5, charsize=1.5))
gCumu.xaxis(label=Label('T', font=5, charsize=1.5))
pCumu.save(dir + '/resultado/cumu.agr')
gCumuE = pCumuE[0]
gCumuE.plot(vCumuE)
gCumuE.title('cumulante da energia x Temperatura')
gCumuE.yaxis(label=Label('cumulante', font=5, charsize=1.5))
gCumuE.xaxis(label=Label('T', font=5, charsize=1.5))
pCumuE.save(dir + '/resultado/cumue.agr')
print "plot da quantidades finalizado "
def plotarGausianas(amostras):
print 'iniciando plot gaussianas '
pTcSus = GracePlot()
pSus = GracePlot()
pTcCalor = GracePlot()
pCalor = GracePlot()
s1 = Symbol(symbol=symbols.none, fillcolor=3)
l1 = Line(type=lines.solid)
histogramaTcSus = []
histogramaSus = []
histogramaTcCalor = []
histogramaCalor = []
for resultado in amostras:
t, mag, mag2, logmag2, energia, calor, su, cumo, cumuE, p = resultado
histogramaTcSus.append((p, t[su.argmax()]))
histogramaSus.append((p, su.max()))
histogramaTcCalor.append((p, t[calor.argmax()]))
histogramaCalor.append((p, calor.max()))
graficosTcSus = []
graficosSus = []
graficosTcCalor = []
graficosCalor = []
for p in concentracao:
dadosTcSus = [x[1] for x in histogramaTcSus if x[0] == p]
dadosSus = [x[1] for x in histogramaSus if x[0] == p]
dadosTcCalor = [x[1] for x in histogramaTcCalor if x[0] == p]
dadosCalor = [x[1] for x in histogramaCalor if x[0] == p]
mu, std = norm.fit(dadosTcSus)
a = mu - 2 * std
b = mu + 2 * std
x = np.linspace(a, b, 100)
y = norm.pdf(x, mu, std)
dTcSus = Data(x=x, y=y, symbol=s1, line=l1)
graficosTcSus.append(dTcSus)
mu, std = norm.fit(dadosSus)
a = mu - 2 * std
b = mu + 2 * std
x = np.linspace(a, b, 100)
y = norm.pdf(x, mu, std)
dSus = Data(x=x, y=y, symbol=s1, line=l1)
graficosSus.append(dSus)
mu, std = norm.fit(dadosTcCalor)
a = mu - 2 * std
b = mu + 2 * std
x = np.linspace(a, b, 100)
y = norm.pdf(x, mu, std)
dTcCalor = Data(x=x, y=y, symbol=s1, line=l1)
graficosTcCalor.append(dTcCalor)
mu, std = norm.fit(dadosCalor)
a = mu - 2 * std
b = mu + 2 * std
x = np.linspace(a, b, 100)
y = norm.pdf(x, mu, std)
dCalor = Data(x=x, y=y, symbol=s1, line=l1)
graficosCalor.append(dCalor)
gTcSus = pTcSus[0]
gTcSus.plot(graficosTcSus)
gTcSus.title('gausiana Tc sus')
gTcSus.yaxis(label=Label('P(Tc)', font=2, charsize=1.5))
gTcSus.xaxis(label=Label('Tc', font=5, charsize=1.5))
pTcSus.save(dir + '/resultado/gassianaTcSus.agr')
gSus = pSus[0]
gSus.plot(graficosSus)
gSus.title('Gaussiana sus')
gSus.yaxis(label=Label('P(susceptibilidade)', font=2, charsize=1.5))
gSus.xaxis(label=Label('susceptibilidade', font=5, charsize=1.5))
pSus.save(dir + '/resultado/gassianaSus.agr')
gTcCalor = pTcCalor[0]
gTcCalor.plot(graficosTcCalor)
gTcCalor.title('gausiana TC calor')
gTcCalor.yaxis(label=Label('P(Tc)', font=2, charsize=1.5))
gTcCalor.xaxis(label=Label('Tc', font=5, charsize=1.5))
pTcCalor.save(dir + '/resultado/gassianaTcCalor.agr')
gCalor = pCalor[0]
gCalor.plot(graficosCalor)
gCalor.title('Gausiana calor')
gCalor.yaxis(label=Label('Tc', font=2, charsize=1.5))
gCalor.xaxis(label=Label('p', font=5, charsize=1.5))
pCalor.save(dir + '/resultado/gassianaCalor.agr')
print 'finalizando plot gaussianas '
#%[files,labels,ed,dw,fd,rho_ef]=textread('Pt_3d_electonic_structure.csv','%s%s%n%n%n%n','headerlines',1);
from GracePlot import *
from math import *
rhod_ef=[1.65, 2.04, 2.80, 3.58, 4.23, 4.78, 4.78, 5.19].reverse()
rho_ef=[31.65, 33.14, 36.60, 33.86, 25.20, 20.37, 16.55, 16.74];
sf=6.75/8;
ed=[-2.44, -2.60, -2.74, -2.84, -3.00, -3.12, -3.18, -3.16];
dw=[9.11, 9.70, 10.47, 11.10, 12.14, 12.84, 13.21, 13.03];
p=GracePlot(3,4)
p.SetView(0.15,0.15,0.9,1.25)
#set(gcf,'Units','inches','Position',[1 1 6.75 4],'PaperPositionMode','auto','PaperSize',[6.75 4])
d1=Data(ed,map(lambda x:sqrt(x), dw),
symbol=Symbol(symbol=circle,fillcolor=black,size=1.6),
line=Line(linestyle=0),
legend='data')
fit=Data([-3.2,-2.6],[-1.*-3.2+0.5,-1.*-2.6+0.5],
line=Line(linestyle=1,color=black,linewidth=4),
legend='y=0.5-x')
def line(x):
return -1.2*(x+2.44)+sqrt(9.27)
model_fit=Data([-3.2,-2.6],[line(-3.2),line(-2.6)],
line=Line(linestyle=1,color=black,linewidth=4),
legend='y=0.5-x')
vline=Data([-2.9, -2.9],[0.5+2.9,0.5+2.9+.1],
def plotarQuantidades(Amostras):
s1 = Symbol(symbol=symbols.none, fillcolor=colors.red)
l1 = Line(type=lines.solid)
pMag = GracePlot()
pMag2 = GracePlot()
pLogmag2 = GracePlot()
pEnergia = GracePlot()
pCalor = GracePlot()
pSus = GracePlot()
pCumu = GracePlot()
pCumuE = GracePlot()
vMag = []
vMag2 = []
vLogmag2 = []
vEnergia = []
vCalor = []
vSus = []
vCumu = []
vCumuE = []
mag = []
magMedia = np.array(mag, float)
magMedia += np.array()
for resultado in Amostras:
t, mag, mag2, logmag2, energia, calor, sus, cumu, cumuE, pp = resultado
dMag = Data(x=t, y=mag, symbol=s1, line=l1)
dMag2 = Data(x=t, y=mag2, symbol=s1, line=l1)
dLogmag2 = Data(x=t, y=logmag2, symbol=s1, line=l1)
dEnergia = Data(x=t, y=energia, symbol=s1, line=l1)
dCalor = Data(x=t, y=calor, symbol=s1, line=l1)
dSus = Data(x=t, y=sus, symbol=s1, line=l1)
dCumu = Data(x=t, y=cumu, symbol=s1, line=l1)
dCumuE = Data(x=t, y=cumuE, symbol=s1, line=l1)
vMag.append(dMag)
vMag2.append(dMag2)
vLogmag2.append(dLogmag2)
vEnergia.append(dEnergia)
vCalor.append(dCalor)
vSus.append(dSus)
vCumu.append(dCumu)
vCumuE.append(dCumuE)
gMag = pMag[0]
gMag.plot(vMag)
gMag.title('Magnetizacao x Temperatura')
gMag.yaxis(label=Label('magnetizacao', font=5, charsize=1.5))
gMag.xaxis(label=Label('T', font=5, charsize=1.5))
pMag.save(dir + '/resultado/mag.agr')
gMag2 = pMag2[0]
gMag2.plot(vMag2)
gMag2.title('magnetizacao2 x Temperatura')
gMag2.yaxis(label=Label('mag2', font=5, charsize=1.5))
gMag2.xaxis(label=Label('T', font=5, charsize=1.5))
pMag2.save(dir + '/resultado/mag2.agr')
gLogmag2 = pLogmag2[0]
gLogmag2.plot(vLogmag2)
gLogmag2.title('logmag2 x Temperatura')
gLogmag2.yaxis(label=Label('logmag2', font=5, charsize=1.5))
gLogmag2.xaxis(label=Label('T', font=5, charsize=1.5))
pLogmag2.save(dir + '/resultado/logmag2.agr')
gEnergia = pEnergia[0]
gEnergia.plot(vEnergia)
gEnergia.title('energia x Temperatura')
gEnergia.yaxis(label=Label('energia', font=5, charsize=1.5))
gEnergia.xaxis(label=Label('T', font=5, charsize=1.5))
pEnergia.save(dir + '/resultado/energia.agr')
gCalor = pCalor[0]
gCalor.plot(vCalor)
gCalor.title('Calor especifico x Temperatura')
gCalor.yaxis(label=Label('Calor', font=2, charsize=1.5))
gCalor.xaxis(label=Label('T', font=5, charsize=1.5))
pCalor.save(dir + '/resultado/calor.agr')
gSus = pSus[0]
gSus.plot(vSus)
gSus.title('Susceptibilidade x Temperatura')
gSus.yaxis(label=Label('Susceptibilidade', font=5, charsize=1.5))
gSus.xaxis(label=Label('T', font=5, charsize=1.5))
pSus.save(dir + '/resultado/sus.agr')
gCumu = pCumu[0]
gCumu.plot(vCumu)
gCumu.title('cumulante da magnetizacao x Temperatura')
gCumu.yaxis(label=Label('cumulante', font=5, charsize=1.5))
gCumu.xaxis(label=Label('T', font=5, charsize=1.5))
pCumu.save(dir + '/resultado/cumu.agr')
gCumuE = pCumuE[0]
gCumuE.plot(vCumuE)
gCumuE.title('cumulante da energia x Temperatura')
gCumuE.yaxis(label=Label('cumulante', font=5, charsize=1.5))
gCumuE.xaxis(label=Label('T', font=5, charsize=1.5))
pCumuE.save(dir + '/resultado/cumue.agr')
print "plot da quantidades finalizado "
if args.colors:
for index, col in enumerate(args.colors):
colo[index] = col
if (args.mp or args.eps != 'noeps'):
import matplotlib.font_manager as fnt
import matplotlib.pyplot as plt
fig = plt.figure(1)
graf = fig.add_axes([0.13, 0.1, 0.8, 0.8])
if args.xg:
scriptpath = os.path.dirname(os.path.realpath(__file__))
sys.path.append(scriptpath + '/graceplot')
import GracePlot as xg
pgr = xg.GracePlot()
pg = pgr[0]
pg.title(args.title)
s1 = xg.Symbol(symbol=0, fillcolor=0)
l1 = xg.Line(type=1, linewidth=1)
xlabel = xg.Label(args.xlabel)
ylabel = xg.Label(args.ylabel)
pg.xaxis(label=xlabel)
pg.yaxis(label=ylabel)
if (args.scale == 'logx' or args.scale == 'logxy'):
pg.xaxis(scale='logarithmic')
if (args.scale == 'logy' or args.scale == 'logxy'):
pg.yaxis(scale='logarithmic')
fpat = re.compile(r'(?P<nom>[^/\.]+)\.')
for tiq, doc in enumerate(args.files):
#%[files,labels,ed,dw,fd,rho_ef]=textread('Pt_3d_electonic_structure.csv','%s%s%n%n%n%n','headerlines',1);
from GracePlot import *
from math import *
rhod_ef=[1.65, 2.04, 2.80, 3.58, 4.23, 4.78, 4.78, 5.19].reverse()
rho_ef=[31.65, 33.14, 36.60, 33.86, 25.20, 20.37, 16.55, 16.74];
sf=6.75/8;
ed=[-2.44, -2.60, -2.74, -2.84, -3.00, -3.12, -3.18, -3.16];
dw=[9.11, 9.70, 10.47, 11.10, 12.14, 12.84, 13.21, 13.03];
p=GracePlot()
#p.SetView(0.15,0.15,0.9,1.1)
#set(gcf,'Units','inches','Position',[1 1 6.75 4],'PaperPositionMode','auto','PaperSize',[6.75 4])
d1=Data(ed,map(lambda x:sqrt(x), dw),
symbol=Symbol(symbol=circle,fillcolor=orange,size=1.4),
line=Line(linestyle=0),
legend='data')
fit=Data([-3.2,-2.6],[-1.*-3.2+0.5,-1.*-2.6+0.5],
line=Line(linestyle=1,color=black,linewidth=4),
legend='y=0.5-x')
p.plot(d1,fit)
p.xaxis(-3.3,-2.5)
p.yaxis(3,3.7)
p.xlabel('d-band center (eV)')
#p.ylabel("""\\x\\c\\z{1.4}V\\m{1}\\z{0.9}\\v{0.75}>>>>>\\N\\C\\f{}\M{1}d-band width""")
p.ylabel("""rms d-band width""")
#
#p.text(x=-2.6,y=3.65,string='(a.)',charsize=1.4,font=2)
labels=['Pt','Ni','Co','Fe','Mn','Cr','V','Ti']
#interlayer spacing
d=array([2.34,2.04,2.04,2.05,2.01,2.04,2.10,2.14])
#matrix elements
V_pt3d=7.62*(rd*pt_rd)**1.5/d**5
#Real band data
W2=array([9.11,9.7,10.47,11.1,12.14,12.84,13.21,13.03])
W=sqrt(W2)
p=GracePlot(3.,4)
p.SetView(0.15,0.15,0.95,1.25)
d=Data(tb_Wd,W,symbol=Symbol(symbol=circle,fillcolor=red),
line=Line(type=0))
# from best fit of the data
#width=0.92*V_pt3d/min(V_pt3d)+0.92
V_data=Data(V_pt3d,W,symbol=Symbol(symbol=circle,fillcolor=black),
line=Line(type=0))
p.plot(V_data)
for i in range(len(labels)):
p.text(labels[i],x=V_pt3d[i]+0.002,y=W[i],font=2,charsize=1.4)
string loctype %(coordinates)s
string %(x)g, %(y)g
string color %(color)d
string rot %(angle)f
string font %(font)d
string just %(just)d
string char size %(size)f
string def "%(text)s"
""" % locals()
self.write(strg)
c = GracePlot.colors
stylecolors = [c.green, c.blue, c.red, c.orange, c.magenta, c.black]
s1, s2, s3, s4, s5, s6 = [
GracePlot.Symbol(symbol=GracePlot.symbols.circle,
fillcolor=sc,
size=0.3,
linestyle=GracePlot.lines.none) for sc in stylecolors
]
l1, l2, l3, l4, l5, l6 = [
GracePlot.Line(type=GracePlot.lines.solid, color=sc, linewidth=2.0)
for sc in stylecolors
]
noline = GracePlot.Line(type=GracePlot.lines.none)
graceSession = myGrace(width=11, height=8)
g = graceSession[0]
g.xlimit(-1, 16)
g.ylimit(-1, 22)
from GracePlot import *
labels=['Pt', 'Ni','Co','Fe','Mn','Cr','V','Ti']
ed=[-2.44, -2.60, -2.74, -2.84, -3.0, -3.12, -3.18, -3.16];
dissH_H=[-0.63, -0.27, -0.06, 0.05, 0.30, 0.49, 0.64, 0.75];
dissH_O=[-1.27, -0.61, -0.40,-0.29, -0.17, 0.18, 0.28, 0.78];
dissH_O_450=[-1.47, -0.82, -0.59, -0.54, -0.40, -0.07, 0.20, 0.63];
p=GracePlot(6,4)
#p.SetView(.15,.15,.9,1.1)
hdata=Data(ed,dissH_H,symbol=Symbol(symbol=circle,fillcolor=red,size=1.4),
line=Line(linestyle=0),
legend='H\s2')
odata=Data(ed,dissH_O_450,symbol=Symbol(symbol=square,fillcolor=orange,size=1.4),
line=Line(linestyle=0),
legend='O\s2')
zero=Data([-3.2,-2.4],[0,0],
symbol=Symbol(symbol=0),
line=Line(color=black))
p.plot(hdata,odata,zero)
p.xaxis(-3.2,-2.4)
p.yaxis(-2,1)
p.legend(x=-2.6,y=0.7,font=2,charsize=1.3)
sweeptime = sweeptime - 2 # synch issue
ssweeptime = "%s" % sweeptime ## prevents extra points
lockin.write("slen " + ssweeptime + "\n")
lockin.write("send 0 \n") # perform a single shot
#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!#
#####################################################################
#####################################################################
# Acquisition
#####################################################################
# Open a Grace session (leave open)
p = GracePlot()
# Labels, axes properties, line/symbol properties for Grace plot
p.title("All your resonance are belong to us")
p.xaxis(
label=Label("Frequency (Hz)", font=5, charsize=1.5),
tick=Tick(
majorgrid=on, majorlinestyle=dashed, majorcolor=blue, minorgrid=off, minorlinestyle=dotted, minorcolor=blue
),
)
p.yaxis(
label=Label("Power", font=5, charsize=1.5),
tick=Tick(
majorgrid=on, majorlinestyle=dashed, majorcolor=blue, minorgrid=off, minorlinestyle=dotted, minorcolor=blue
),
)
