Describe the bug
nf_avg = polyval(nf_fit_coeff, -dg)
The minus sign seems not correct.
According to the definition of the polynomial NF under
https://gnpy.readthedocs.io/en/master/extending.html
NF = f(G_max - G)
I did a regression based on my NF vs Gain data and got the following coef:
nf_fit_coeff = [0.0016, 0.036, 0.094, 5.0352] and when G_max-G = 4.
I shall expecting polyval(nf_fit_coeff, 4) = 6.1 dB
But what I got is actually polyval(nf_fit_coeff, 4) = 5.14 dB
NF is underestimated.
Describe the bug nf_avg = polyval(nf_fit_coeff, -dg) The minus sign seems not correct.
According to the definition of the polynomial NF under https://gnpy.readthedocs.io/en/master/extending.html NF = f(G_max - G) I did a regression based on my NF vs Gain data and got the following coef: nf_fit_coeff = [0.0016, 0.036, 0.094, 5.0352] and when G_max-G = 4. I shall expecting polyval(nf_fit_coeff, 4) = 6.1 dB
But what I got is actually polyval(nf_fit_coeff, 4) = 5.14 dB NF is underestimated.