pychopmarg.noise
Classes
- class pychopmarg.noise.NoiseCalc(L: int, Tb: float, ts_ix: int, t: ndarray[Any, dtype[Real]], vic_pulse_resp: ndarray[Any, dtype[Real]], agg_pulse_resps: list[ndarray[Any, dtype[Real]]], f: ndarray[Any, dtype[Real]], Ht: ndarray[Any, dtype[Comp]], H21: ndarray[Any, dtype[Comp]], Hr: ndarray[Any, dtype[Comp]], Hctf: ndarray[Any, dtype[Comp]], eta0: float, Av: float, snr_tx: float, Add: float, sigma_Rj: float, eps: float = 0.001)[source]
Noise calculator for COM
- L = 4
- Tb = 9.412e-12
- ts_ix = 0
- t = array([0.])
- vic_pulse_resp = array([0.])
- agg_pulse_resps: list[ndarray[Any, dtype[Real]]] = []
- f = array([0.])
- Ht = array([0.+0.j])
- H21 = array([0.+0.j])
- Hr = array([0.+0.j])
- Hctf = array([0.+0.j])
- eta0 = 0.0
- Av = 0.6
- snr_tx = 25.0
- Add = 0.0
- sigma_Rj = 0.0
- fN = 53125000000.0
- nspui = 32
- varX = 0.0
- baud_rate_sample(x: ndarray[Any, dtype[Real]]) ndarray[Any, dtype[Real]][source]
Resample the input at fBaud., respecting the current sampling phase.
- Parameters:
x – Signal to be resampled.
- Returns:
Resampled vector.
- property Srn: ndarray[Any, dtype[Real]]
One-sided folded noise PSD at Rx sampler input, uniformly sampled over [0, PI] (rads./s norm.).
Notes
1. Re: the scaling term:
2 * self.f[-1], when combined w/ the implicit1/Nof theirfft()function, this givesdf.
- Sxn(agg_pulse_resp: ndarray[Any, dtype[Real]]) ndarray[Any, dtype[Real]][source]
Crosstalk PSD at Rx FFE input.
- Parameters:
agg_pulse_resp – Aggressor pulse response (V).
- Returns:
One-sided crosstalk PSD at Rx FFE input, uniformly sampled over [0, PI] (rads./s norm.).
- Stn(Hrx: ndarray[Any, dtype[Comp]] | None = None) ndarray[Any, dtype[Real]][source]
One-sided Tx noise PSD at Rx FFE input, uniformly sampled over [0, PI] (rads./s norm.).
- Keyword Arguments:
Hrx – Complex voltage transfer function of Rx FFE. Default: None (Use flat unity response.)
- property Sjn: ndarray[Any, dtype[Real]]
One-sided Noise PSD due to jitter at Rx FFE input, uniformly sampled over [0, PI] (rads./s norm.).