pypho v1

Basic Setup Data signal and noise representation pypho_setup pypho_bits pypho_signalsrc pypho_lasmod pypho_cwlaser pypho_oamp (new) pypho_osnr (new) pypho_fiber pypho_cfiber (new) pypho_optfi (improved) pypho_eye pypho_poincare pypho_arbmod (new) pypho_sample (new) pypho_functions
 Examples

Data signal and noise representation

The optical data signals and the noise vectors are defined in a list, which can contain more than one signal. If an optical signal E is defined as done in the basic setup above, the optical signal itself is represented by two numpay arrays which contains the complex sample values of the X- and the Y-polarisation plane. E[0]['E'][0] is the X-polarisation and E[0]['E'][1] is the Y-polarisation:

>>> E[0]['E']
array([[  4.42838749e-003 -6.11669972e-004j,
          4.44132200e-003 -4.55343696e-004j, ...,
          4.40185784e-003 -7.45482750e-004j,
          4.41682653e-003 -6.81389659e-004j],
       [ -4.94065646e-003 +0.00000000e+000j,         
         -4.94065646e-003 +0.00000000e+000j, ...,
         -4.94065646e-003 +0.00000000e+000j,
         -4.94065646e-003 +0.00000000e+000j]])

Each array contains $SPS * NOS$ samples. The unit is $\sqrt{W}$.

Noise is represented as a noise vector in the frequency domain. The number of noise bins is $SPS * NOS$. The bins have a frequency resolution of $f_S / SPS$ and the unit is $W/Hz$.

array([  6.15149232e-11,   6.15149232e-11,   6.15149232e-11, ...,
         6.15149232e-11,   6.15149232e-11,   6.15149232e-11])