SNR

Signal-to-Noise Ratio (SNR)

Inputs

  • Data: input dataset

Outputs

  • Signal-to-noise ratio: signal-to-noise ratio dataset
    • *SNR = \(\frac{\overline{Spectra_{x, y}}}{\sigma _{x, y}}\)*
  • Averages: averaged dataset
    • *Averages = \(\overline{Spectra_{x, y}}\)*
  • Standard Deviation: standard deviation dataset
    • Standard Deviation = \(\sigma _{x, y}\)

The SNR widget computes the SNR, average, or standard deviation of spectra. It can output the results of an entire dataset or by coordinates (x, y).

Use Select axis: x to select an axis that will act as the first element for your coordinate system defined by a numeric meta.

Use Select axis: y to select an axis that will act as the second element for your coordinate system defined by a numeric meta.

In the example above, the result will be:

output = Signal-to-noise ratio(column, row)

*SNR = \(\frac{\overline{Spectra_{column, row}}}{\sigma _{column, row}}\)*

If you want to select only one axis:

output = Average(x)

*Average = \(\overline{Spectra_{column}}\)*

or

output = Standard Deviation(x)

Standard Deviation = \(\sigma _{column}\)

If you want the result of the complete data set, you can just leave both as None.