pypho_functions is a collection of usefull functions to make your coding live easier.
dbm2w( power_dbm )
Converts a power value from dBm to W: $P|_{W} = 10^{\frac{P|_{dBm}}{10}}$ W
| Parameter | Type | Description |
|---|---|---|
power_dbm |
float | Power value in dBm ($P|_{dBm}$). |
| Output | Type | Description |
|---|---|---|
| Power value in W | float | $P|_{W}$ |
w2dbm( power_w )
Converts a power value from W to dBm: $P|_{dBm} = 10\cdot \lg{\left(\frac{P|_{W}}{1mW}\right)}$ dBm.
| Parameter | Type | Description |
|---|---|---|
power_dbm |
float | Power value in W ($P|_{W}$). |
| Output | Type | Description |
|---|---|---|
| Power value in dBm | float | $P|_{dBm}$ |
getpower_W( E )
Calculates the mean power in W of an optical Signal $E$: $P|_{dBm} = \frac{1}{T} \int _{ \tau=0 }^{ T } \left( \left\lvert E_x(\tau) \right\rvert^{ 2 } +\left\lvert E_y(\tau) \right\rvert^{ 2 }\right) d\tau $.
| Parameter | Type | Description |
|---|---|---|
E |
numpy.ndarray | 2 dimensional array with complex values, which represents the sample points over time of the X- and Y-polarisation. For example E[0]['E'].Read here about data signal and noise representation |
| Output | Type | Description |
|---|---|---|
| Power value in W | float | $P|_{W}$ |
getpower_dBm( E )
Same as getpower_w( E ), but output is in dBm.