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 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 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')
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
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 '
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 "