dtd = tdm[1:] - tdm[:-1]
ax2 = fig.add_subplot(2, 1, 2)
bins = np.linspace(min(min(dtp), min(dtd)), max(max(dtp), max(dtd)), 50)
bc, be, _ = ax2.hist([dtp, dtd],
bins,
stacked=True,
color=['r', 'm'],
label=['peaks', 'edges'],
alpha=0.5)
ax2.set_xlabel(r'$Zeitdifferenz\,der\,peaks / dips$ (ms)', size='large')
ax2.legend(loc='best', numpoints=1, prop={'size': 10})
ax2.set_ylabel(r'$H\"aufigkeit$', size='large')
ax2.grid()
print("** Histogram statistics:")
m_dtp, s_dtp, sm_dtp = ppk.histstat(bc[0], be, pr=False)
m_dtd, s_dtd, sm_dtd = ppk.histstat(bc[1], be, pr=False)
print(" --> mean time differnce of peaks: (%.5g +/- %.2g) ms" %
(m_dtp, sm_dtp))
print(" dips: (%.5g +/- %.2g) ms" %
(m_dtd, sm_dtp))
ax2.text(0.1,
0.85,
"peaks: (%.5g$\pm$%.2g) ms" % (m_dtp, sm_dtp),
transform=ax2.transAxes)
ax2.text(0.1,
0.75,
" edges: (%.5g$\pm$%.2g) ms" % (m_dtd, sm_dtd),
transform=ax2.transAxes)
plt.show()
ax3.set_ylabel('$Autocorrelation$ ' + units[1], size='large')
ax3.legend(loc='best', numpoints=1, prop={'size': 10})
ax3.grid()
# statistische Auswertung
# plot distribution of time differences between peaks/dips
dtp = tpm[1:] - tpm[:-1]
ax4 = fig.add_subplot(2, 2, 4)
bins = np.linspace(min(dtp), max(dtp), 50)
bc, be, _ = ax4.hist(dtp,
bins,
stacked=True,
color='r',
label='peaks',
alpha=0.5)
ax4.set_xlabel(r'$Zeitdifferenz\,der\,peaks$ (ms)', size='large')
# ax4.legend(loc='best', numpoints=1, prop={'size':10})
ax4.set_ylabel(r'$H\"aufigkeit$', size='large')
ax4.grid()
print("** Histogram statistics:")
m_dtp, s_dtp, sm_dtp = ppk.histstat(bc, be, pr=False)
print(" --> mean time differnce of peaks: (%.5g +/- %.2g) ms" %
(m_dtp, sm_dtp))
ax4.text(0.05,
0.9,
"mean=(%.5g$\pm$%.2g) ms" %
(m_dtp, max(sm_dtp, (be[1] - be[0]) / np.sqrt(12))),
transform=ax4.transAxes)
plt.show()
#Create Array of differences of Maximums
deltaMax = deltaArray(maxac)
deltaMin = deltaArray(minac)
print(deltaMax)
print(deltaMin)
deltaMin = (-1)*deltaMin
deltaNew = deltaMin + deltaMax
# plot data as histogram
nbin = 10
binc, bine, patches = plt.hist(deltaNew, nbin,facecolor='g', log=False, alpha=1)
plt.title("Histogramm of MaxDifferences")
plt.show()
#Calculate Period and Uncertainity from Histogram data
Perioddata = PhyPraKit.histstat(binc, bine, patches)
print("Period by amplitude alone = " + str(Perioddata[0]))
print("?? = " + str(Perioddata[1]))
print("Uncertainity = " + str(Perioddata[2]))
print("True Period in s = " + str(Perioddata[0]/0.05555555555))
print("True Uncertantiy = " + str(Perioddata[2]/0.05555555555))
#Stelle Frequenz Spektrum dar
fourierspec = PhyPraKit.FourierSpectrum(time,smoothamplitude)
plt.plot(fourierspec[0],fourierspec[1])
plt.title("Frequenz Spektrum des Signals")
print('Frequency by Fourier Analysis = ' +str(findMaximumxPos(*fourierspec)))
plt.show()