#!/usr/bin/python3
import ephys as ep
t = ep.Quantity(0, 0.0001, 's').name(label='Time', latex='t')
U = ep.Quantity(0, 0.02, 'V').name(label='Photo Diode Voltage', latex='U_{PD}')
ep.daq('data.csv', t, U, skip=2)
t.prefunit('ms')
p = ep.Plot()
p.error(t, U, ecolor='0.3')
A = ep.Quantity('V').name(latex='U_0')
mu = ep.Quantity('s').name(latex='\\mu')
gamma = ep.Quantity('s').name(latex='\\Gamma')
mf = ep.LorentzFit(A, mu, gamma)
mf.fit(t, U)
p.fit(mf)
p.save('tut.png')
#!/usr/bin/python3
import ephys as ep
t = ep.Quantity(0, 0.0001, 's').name(label='Time', latex='t')
U = ep.Quantity(0, 0.02, 'V').name(label='Photo Diode Voltage', latex='U_{PD}')
ep.daq('data.csv', t, U, skip=2)
t.prefunit('ms')
p = ep.Plot()
p.error(t, U, ecolor='0.3')
A = ep.Quantity('V').name(latex='U_0')
mu = ep.Quantity('s').name(latex='\\mu')
gamma = ep.Quantity('s').name(latex='\\Gamma')
mf = ep.LorentzFit(A, mu, gamma)
mf.fit(t, U)
p.fit(mf)
p.save('tut.png')
#!/usr/bin/python3
import ephys as ep
x = ep.Quantity('mm').name(label='Positon', latex='x_0')
U = ep.Quantity('mV').name(label='Voltage under Neadle', latex='U_N')
ep.daq('small.csv', x, U, ep.StdDev(U), skip=1)
x.variance = 0.00001**2
p = ep.Plot()
p.error(x, U)
offset = ep.Quantity('V').name(symbol='U_0')
m = ep.Quantity('V/m').name(symbol='m')
lin = ep.PolynomFit(offset, m)
lin.fit(x, U)
p.fit(lin)
p.save('small.png')
#!/usr/bin/python3
import ephys as ep
x = ep.Quantity('mm').name(label='Positon', latex='x_0')
U = ep.Quantity('mV').name(label='Voltage under Neadle', latex='U_N')
ep.daq('small.csv', x, U, ep.StdDev(U), skip=1)
x.variance = 0.00001**2
p = ep.Plot()
p.error(x, U)
offset = ep.Quantity('V').name(symbol='U_0')
m = ep.Quantity('V/m').name(symbol='m')
lin = ep.PolynomFit(offset, m)
lin.fit(x, U)
p.fit(lin)
p.save('small.png')