SNR is defined as the maximum signal value divided by the standard deviation of the noise.
calc_spec_snr(
mrs_data,
sig_region = c(4, 0.5),
noise_region = c(-0.5, -2.5),
p_order = 2,
interp_f = 4,
full_output = FALSE
)| mrs_data | an object of class |
|---|---|
| sig_region | a ppm region to define where the maximum signal value should be estimated. |
| noise_region | a ppm region to defined where the noise level should be estimated. |
| p_order | polynomial order to fit to the noise region before estimating the standard deviation. |
| interp_f | interpolation factor to improve detection of the highest signal value. |
| full_output | output signal, noise and SNR values separately. |
an array of SNR values.
The mean noise value is subtracted from the maximum signal value to reduce DC offset bias. A polynomial detrending fit (second order by default) is applied to the noise region before the noise standard deviation is estimated.