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).

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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.

![](images/snr_print.png)

In the example above, the result will be:

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

*SNR = \\(\frac{\overline{Spectra_{column, row}}}{\sigma _{column, row}}\\)*
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If you want to select only one axis:


![](images/snr_average_x.png)

**output = Average(x)**

*Average = \\(\overline{Spectra_{column}}\\)*
 
 or
 
 
![](images/snr_std_y.png)

**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.