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 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 '
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')
p._send('altxaxis ticklabel type spec')
p._send('altxaxis tick place opposite')
p._send('altxaxis tick spec %d' % (len(labels)-1))
for i in range(len(labels)-1):
p._send('altxaxis tick major %d,%f' % (i,ed[i]))
p._send('altxaxis ticklabel %d, "%s"' % (i,labels[i]))
p._send('altxaxis label place opposite')
p._send('altxaxis label char size 1.2')
p._send('altxaxis label font 2')
p._send('altxaxis label "Subsurface Metal"')
p._send('altxaxis bar linewidth 4')
p.save('figure3_dissertation.png')
#p.redraw()
##hold on
##p1=plot(ed,dissH_H,'ko','MarkerFaceColor',[.4 .4 .4],'MarkerSize',8)
##%p2=plot(ed,dissH_O,'ks','MarkerFaceColor',[.8 .8 .8],'MarkerSize',8)
##p3=plot(ed,dissH_O_450,'ks','MarkerFaceColor',[0.8 0.8 0.8],'MarkerSize',8)
##axis([-3.2 -2.4 -1.6 1])
##hold off
##l=legend('H_2','O_2');
##xlabel('d-band center (eV)')
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)')
p.text(x=-3.1,y=7,string='(b.)',charsize=1.4,font=2)
p.legend(x=-2.85,y=7.25,font=2,charsize=1.2)
p.save('figure2b.eps')
p.save('figure2b.pdf')
p.save('figure2b.agr')
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 '
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 "
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)
p.save('figure2a_talk.png')
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)
p.xlabel('Pt-X Matrix Element (eV)')
p.ylabel('Pt rms d-band width (eV)')
p.save('figure3.eps')
p.save('figure3.pdf')
p.save('figure3.agr')
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],
line=Line(linestyle=1,color=black,linewidth=4))
hline=Data([-2.9,-3.0],[3.5,3.5],
line=Line(linestyle=1,color=black,linewidth=4))
#p.plot(d1,model_fit,vline,hline)
p.plot(d1)
p.xaxis(-3.3,-2.5)
p.yaxis(3,3.7)
p.xlabel('d-band center (eV)')
p.ylabel("""rms d-band width (eV)""")
#
#p.legend(x=-2.8,y=3.6,charsize=1.2,font=2)
p.text(x=-2.6,y=3.65,string='(a.)',charsize=1.4,font=2)
#p.text(x=-2.87,y=3.5,string='slope=-1',charsize=1.4,font=2)
p.save('figure2a.eps')
p.save('figure2a.pdf')
p.save('figure2a.agr')
