def plothist(base, value, x, y, mean, median, std, stdAbs):
ax= plt.subplot2grid((4,3),(1,1),colspan=1)
font=20
plt.plot(base[:-1],value,c='blue')
plt.plot(x,y,'--',c='red')
plt.xlabel(r'$\mathtt{Contagens \; (adu)}$',size=font)
plt.ylabel(r'$\mathtt{Frequ\^encia\;}$'+'(%)',size=font)
plt.title(r'$\mathtt{Histograma \quad da \quad imagem \quad combinada}$',size=font)
f = interp1d(base[:-1], value, kind='cubic')
x16 = mean-std
x50 = mean
x84 = mean+std
index16 = returnIndex(x,x16)
index84 = returnIndex(x,x84)
plt.ylim(ymax=1.1*f(x50))
plt.plot(mean, f(mean),'o')
drawLine(x16,0,f(x16),'1', pos='left')
drawLine(x84,0,f(x84),'3')
plt.annotate('2',xy=(mean*1.0001,f(mean)*1.001),xycoords='data',size=17)
plt.annotate('',xy=(x16,f(x16)/2), xycoords='data',xytext=(x84,f(x16)/2), textcoords='data',arrowprops=dict(arrowstyle="<->"),)
plt.annotate(r'$\mathtt{\sigma^+_-}$', xy=(x50*0.9999,1.08*f(x16)/2), xycoords='data',fontsize=14)
# Informacões dos intervalor da media +/- sigma
num = algarismoSig(std)
mean = str(round(mean,num))
std = str(round(std,num))
num = algarismoSig(stdAbs)
median = str(round(median,num))
stdAbs = str(round(stdAbs,num))
textstr0 = ''
textstr1 = ''
textstr2 = r'$\mathtt{Histograma: }$'
textstr3 = r'$\mathtt{Media= \; %s_-^+ \; %s \quad adu}$' %(mean, std)
textstr4 = r'$\mathtt{Mediana= \; %s_-^+ \; %s \quad adu}$'%(median,stdAbs)
textstr5 = r'$\mathtt{1 \; - \;(%.2f \; adu,%.2f}$'%(x16,f(x16)) +' %' + r'$\mathtt{)}$'
textstr6 = r'$\mathtt{2 \; - \;(%.2f \; adu,%.2f}$'%(x50,f(x50)) +' %' + r'$\mathtt{)}$'
textstr7 = r'$\mathtt{3 \; - \;(%.2f \; adu,%.2f}$'%(x84,f(x84)) +' %' + r'$\mathtt{)}$'
textstr = [textstr0,textstr1,textstr2,textstr3,textstr4,textstr5, textstr6, textstr7]
return textstr
def dadosMeanTemp(vetor, vetorstd):
mean = np.mean(vetor)
std = np.std(vetor)
meanStd = np.mean(vetorstd)
num = algarismoSig(std)
mean = round(mean, num)
std = round(std, num)
meanFrame = vetor[0]
stdFrame = vetorstd[0]
num = algarismoSig(stdFrame)
meanFrame = round(meanFrame, num)
stdFrame = round(stdFrame, num)
ratio = stdFrame / std
mean = str(mean)
std = str(std)
meanFrame = str(meanFrame)
stdFrame = str(stdFrame)
sinal = None
textstr0 = ''
textstr1 = r'$\mathtt{\barM_{temp} = \; %s_-^+ \; %s \;\; adu}$' % (mean,
std)
textstr2 = r'$\mathtt{\barM_{frame} = \; %s_-^+ \; %s \;\; adu}$' % (
meanFrame, stdFrame)
textstr3 = r'$\mathtt{\bar\sigma_{frame} = \; %.1f \; \sigma_{temp}}$' % (
ratio)
if ratio > 1.1:
sinal = r'$\mathtt{\gg}$'
if 0.9 < ratio < 1.1:
sinal = r'$\mathtt{\approx}$'
if ratio < 0.9:
sinal = r'$\mathtt{\ll}$'
textstr4 = r'$\mathtt{\bar\sigma_{frame}}$' + sinal + r'$\mathtt{ \sigma_{temp} \;\; (>10}$' + '%' + r'$\mathtt{)}$'
textstr = [textstr0, textstr1, textstr2, textstr3, textstr4]
caixa(textstr, 4, 3, 2, 2, font=26, space=0.15)
return stdFrame
def linhaReferencia(y): lenY = len(y) mean = np.mean(y) std = np.std(y) num = algarismoSig(std) mean = round(mean, num) std = round(std,num) linhaR = [] lisStd = [] i=0 while i < lenY: linhaR.append(mean) i+=1 x = np.linspace(0,lenY, lenY) linhaR = np.asarray(linhaR) plt.plot(x,linhaR, '-', c='red', linewidth=1.5) plt.plot(x,linhaR - std, '--', c='red', linewidth=1.5) plt.plot(x,linhaR + std, '--', c='red', linewidth=1.5)
def plotTempDC(temperatura, DC, std, ganho):
ax = plt.subplot2grid((3, 2), (0, 1))
DC = np.asarray(DC) / ganho
std = np.asarray(std) / ganho
font = 15
i = 0
#arredonda para a casa decimal com o primeiro algarismo significativo
while i < len(DC):
num = algarismoSig(std[i])
DC[i] = round(DC[i], num)
std[i] = round(std[i], num)
i += 1
plt.plot(temperatura, DC)
plt.errorbar(temperatura, DC, std, c='blue', fmt='o')
plt.xlabel(r'$\mathtt{Temperatura \quad (^oC)}$', size=font)
plt.ylabel(r'$\mathtt{Corrente \quad de \quad escuro \quad (e-/pix/s)}$',
size=font)
plt.title(r'$\mathtt{Corrente \quad de \quad escuro \quad em \quad fun}$' +
u'ç' + r'$\mathtt{\~ao \quad da \quad temperatura}$',
size=font + 2)
plt.xlim(xmax=temperatura[0] * 0.9)
i = 0
while i < len(DC):
DC[i] = str(DC[i])
std[i] = str(std[i])
textstr = r'$\mathtt{DC(%i^oC) \; = \quad %s^+_- \; %s \; e-/pix/s}$' % (
temperatura[i], DC[i], std[i])
plt.text(0.05,
0.90 - i * 0.07,
textstr,
ha='left',
va='center',
size=font + 1,
transform=ax.transAxes)
i += 1
return (DC[-1], std[-1])
def plotGradiente(posx, posy, Vetormean, eixo='x'):
font = 20
nDados = len(Vetormean)
mean = np.mean(Vetormean)
std = np.std(Vetormean)
ax = plt.subplot2grid((4, 3), (posx, posy), colspan=1)
x = np.linspace(0, nDados, nDados)
num = algarismoSig(std)
mean = str(round(mean, num))
std = str(round(std, num))
if eixo == 'x':
textstr = r'$\mathtt{\barF_y = %s_-^+ \; %s \quad adu}$' % (mean, std)
strX = r'$\mathtt{x (pixel)}$'
strY = r'$\mathtt{M \acutee dia \; das \; contagens \; em \; Y}$'
else:
textstr = r'$\mathtt{\barF_x = %s_-^+ \; %s \quad adu }$' % (mean, std)
strX = r'$\mathtt{y (pixel)}$'
strY = r'$\mathtt{M \acutee dia \; das \; contagens \; em \; X}$'
plt.plot(x, Vetormean, color='gray', alpha=0.8)
plt.xlim(0, nDados)
plt.xlabel(strX, size=font)
plt.ylabel(strY, size=font)
plt.gca().get_yaxis().get_major_formatter().set_useOffset(False)
plt.text(0.05,
0.90,
textstr,
va='center',
ha='left',
size=20,
transform=ax.transAxes)
linhaReferencia(Vetormean)
meanBin, meanStdBin = binagem(x, Vetormean)
return meanBin, meanStdBin
def Graph_residuos(x, y, std, image_path):
i, font, residuo, err = 0, 17, [], []
for dado in y:
residuo.append(dado - coefAng * x[i] - intercept)
i += 1
for dado in std:
err.append(sqrt(dado**2 + stdLinAjust**2))
ax = plt.subplot(122)
plt.plot(x, residuo, c='blue')
plt.errorbar(x, residuo, err, c='blue', fmt='o')
plt.xlabel(r'$\mathtt{Vari\^ancia \quad (adu)}$', size=font)
plt.ylabel(r'$\mathtt{Intensidade \quad do \quad sinal \quad (e-)}$',
size=font)
plt.title(
r'$\mathtt{Curva: \quad res \acute\iota duos \quad = \quad sinal \quad - \quad ajuste \quad linear}$'
+ '\n',
size=font)
plt.xlim(xmin=0.99 * x[0], xmax=1.01 * x[-1])
linhaReferencia(x, residuo)
num = algarismoSig(np.std(residuo))
mean = str(round(np.mean(residuo), num))
std = str(round(np.std(residuo), num))
if '-0.0' == mean:
mean = mean[1:]
plt.text(
0.05,
0.9,
r'$\mathtt{M\acuteedia \; = \; %s^+_- \; %s \quad el\acuteetrons}$' %
(mean, std),
va='center',
ha='left',
size=font + 3,
transform=ax.transAxes)
plt.savefig(image_path + '\\' + 'Relatório Ganho.pdf', format='pdf')
def caixaInfo(vetorx, vetory, meanBinX, stdBinX, meanBinY, stdBinY):
stdx = np.std(vetorx)
num = algarismoSig(stdx)
stdx = round(stdx, num)
num = algarismoSig(stdBinX)
meanBinX = round(meanBinX, num)
stdBinX = round(stdBinX, num)
stdRelativeX = stdx / stdBinX
stdy = np.std(vetory)
num = algarismoSig(stdy)
stdy = round(stdy, num)
num = algarismoSig(stdBinY)
meanBinY = round(meanBinY, num)
stdBinY = round(stdBinY, num)
stdRelativeY = stdy / stdBinY
meanBinX = str(meanBinX)
stdBinX = str(stdBinX)
meanBinY = str(meanBinY)
stdBinY = str(stdBinY)
fonte = 24
sinal = None
textstr0 = r'$\mathtt{Gradiente:}$'
textstr1 = r'$\mathtt{Eixo \quad Y \; ---------}$'
textstr2 = r'$\mathtt{\barF_{bin}= \; %s_-^+ \; %s \;\; adu} }$' % (
meanBinX, stdBinX)
textstr3 = r'$\mathtt{\sigma_x = \; %.1f \;\; \bar\sigma_{bin}}$' % (
stdRelativeX)
if 0.9 < stdRelativeX < 1.1:
sinal = [r'$\mathtt{\approx}$', '']
if stdRelativeX > 1.1:
sinal = [
r'$\mathtt{\gg}$', r'$\mathtt{(> \; 10}$' + ' %' + r'$\mathtt{)}$'
]
if stdRelativeX < 0.9:
sinal = [
r'$\mathtt{\ll}$', r'$\mathtt{(< \; 10}$' + ' %' + r'$\mathtt{)}$'
]
textstr4 = r'$\mathtt{\sigma_x \;}$' + sinal[
0] + r'$\mathtt{\; \sigma_{bin} \; }$' + sinal[1]
textstr5 = r'$\mathtt{Eixo \quad X \; ---------}$'
textstr6 = r'$\mathtt{\barF_{bin}= \; %s_-^+ \; %s \;\; adu} }$' % (
meanBinY, stdBinY)
textstr7 = r'$\mathtt{\sigma_y = \; %.1f \;\; \bar\sigma_{bin}}$' % (
stdRelativeY)
if 0.9 < stdRelativeY < 1.1:
sinal = [r'$\mathtt{\approx}$', '']
if stdRelativeY > 1.1:
sinal = [
r'$\mathtt{\gg}$', r'$\mathtt{(> \; 10}$' + ' %' + r'$\mathtt{)}$'
]
if stdRelativeY < 0.9:
sinal = [
r'$\mathtt{\ll}$', r'$\mathtt{(< \; 10}$' + ' %' + r'$\mathtt{)}$'
]
textstr8 = r'$\mathtt{\sigma_y \;}$' + sinal[
0] + r'$\mathtt{\; \sigma_{bin} \; }$' + sinal[1]
textstr = [
textstr0, textstr1, textstr2, textstr3, textstr4, textstr5, textstr6,
textstr7, textstr8
]
return textstr