(sw-res)=

# sw_res

## Syntax
  
`p = sw_res(source,poldeg)`
  
`p = sw_res(source,poldeg,true)`
 
## Description
  
`p = sw_res(fid,poldeg)` reads tabulated resolution data from the
`source` file which contains the FWHM energy resolution values as a
function of energy transfer in two columns. First  column is the energy
transfer values (positive is energy loss), while the second is the FWHM
of the Gaussian resolution at the given energy transfer.
  
`p = sw_res(fid,poldeg,plot)` the polynomial fit will be shown in a
figure if `plot` is true.
 
## Examples
  
This example shows how to fit a tabulated resolution data (MERLIN energy
resolution for $E_i=50$ meV and 300 Hz chopper frequency). Using the
fitted polynomial, the energy resolution can be calculated at an
arbitrary energy transfer value.
 
```matlab
resDat = [0 2.31;10 1.80;20 1.37;30 1.02;40 0.78;49 0.67]
```
*Output*
```
resDat =
         0    2.3100
   10.0000    1.8000
   20.0000    1.3700
   30.0000    1.0200
   40.0000    0.7800
   49.0000    0.6700
```
 
```matlab
polyRes = sw_res(resDat,3)
```
 
```{image} /_static/img/generated/s_1.png
:alt: polyRes = sw_res(resDat,3)
```
```matlab
EN = 13
dE = polyval(polyRes,EN)
```
*Output*
```
dE =
    1.6635
```
 
  
## Input Arguments
  
`source`
: String, path to the resolution file or a matrix with two columns, where
  the first column gives the energy transfer value and second column
  gives the resolution FWHM.
  
`polDeg`
: Degree of the fitted polynomial, default value is 5.
  
`plot`
: If `true` the resolution will be plotted, default value
  is `true`.
  
## Output Arguments
  
`p`
: The coefficients for a polynomial $p(x)$ of degree $n$
  that is a best fit (in a least-squares sense) for the resolution data.
  The coefficients in $p$  are in descending powers, and
  the length of $p$ is $n+1$:
 
  $$p(x)=p_1\cdot x^n+p_2\cdot x^{n-1}+...+p_n\cdot x+p_{n+1}$$
  
## See Also
  
[polyfit] \| [sw_instrument](#sw-instrument)
 
*[FWHM]: Full Width at Half Maximum