Command

Description

Examples

+

Addition of  the y values of spectra, or addition of constants to the x and y values.

Add together the y values in s1, s2, and s3:
<tt>>>stot=s1+s2+s3;</tt>
Add 10 to the y values in s8:
<tt>>>s9=s8+10;</tt>
Add 10 to the y values, and 2 to the x values:
<tt>>>s9=s8+[2 10;];</tt>

Note: The spectra to be added must have identical x axes; otherwise use combine.

-

Subtraction of the y values of two spectra, or subtraction of constants from the x and y values.

Subtract the y values in s2 from those in:
<tt>>>s3=s2-s1;</tt>
Subract 10 from the y value in s1:
<tt>>>s2=s1-10;</tt>
Subtract 20 from the x vaue in s10:
<tt>>>s11=s10-[20 0];</tt>

Note: Can only subtract spectra if they have identical x axes.

*

Multiplication of the y values of two  spectra,  or multiply the x or y values by a constant

Multiply the y values of  s2 and s1:
<tt>>>s3=s2*s1;</tt>
Multiply the y value in s1 by 10:
<tt>>>s2=s1*10;</tt>
Multiply the x value in s5 by 2 and the y value by 3.5: 
<tt>>>s7=s5*[2 3.5];</tt>

Note: When multiplying spectra, they must have identical x axes.

/

Division of  the spectra of the y values of two spectra, or divide the x or y values by a constant

Divide  the y values of  s2 by those in s1:
<tt>>>s3=s2/s1;</tt>
Divide the y values in s1 by 10:
<tt>>>s2=s1/10;</tt>
Divide the x values in s5 by 2 and the y value by 3.5: 
<tt>>>s7=s5/[2 3.5];</tt>

Note: When dividing two spectra, they must have identical x axes.

combine

Combine avearges the y values in  two or more spectra. The x tolerance and combination method are optional. The default method assumes that errors are determined by counting statistics. 

Average s1, s2 and s3 if the x points are closer than 0.01:
<tt>>>s4=combine(0.01,s1,s2,s3);</tt>
Average all of the spectra in the array of spec1d objects stotal. No tolerance is specified; the default value is eps:
<tt>>>sc=combine(stotal);</tt>

cut

Remove data over specified range(s) in x

Cut s1 outside of the range 101 to 102  in x
<tt>>>r=cut(s1,[101 102]);</tt>
Cut s1 in the x range 101-102 and 109-110 
<tt>>>r=cut(s1,[102 101],[110 109]);</tt>

display

Display the x, y and error values in a spectra

Print the x, y and error values of s2 in the Matlab command window
<tt>>>disp(s2);</tt>

dxdy

Differentiate a spectra

Differentiate spectra s4:
<tt>>>sd=dxdy(s4);</tt>

extract

Extract the x, y, and error values to arrays 

Extract the data from s10 to arrays x, y, error:
<tt>>>[x,y,e]=extract(s10);</tt>

fits

Perform a non-linear least-squares fit on of a specified model to the data in a spectra

Fit a Gaussian to s1, with automatic estimation of start values of parameters. All parameters are allowed to vary, and the default values for the fit control parameters are used:
<tt>>>[sfit,fitpars]=fits(s1,'gauss');</tt>
Same as above, but with initial parameters specified and background (parameter 4) fixed:
<tt>>>[sfit,fitpars]=fits(s1,'gauss',[0.9 0.1 0.2 0.1],[1 1 1 0]);</tt>
As above, but with the fit control parameters specified:
<tt>>>[sfit,fitpars]=fits(s1,'gauss',[0.9 0.1 0.2 0.1],[1 1 1 0],[0.001 20 0.01]);</tt>

getfield

Get the values of  specified fields

Obtain the x values from d24:
<tt>>>x=getfield(d24,'x');</tt>
Obtain the x and y  values from d24:
<tt>>>[x,y]=getfield(d24,'x');</tt>
Obtain the x values and the x_label from d24:
<tt>>>[x,xlab]=getfield(d24,'x','x_label');</tt>

Note: the number of output variables must equal the number of fields requested.

horzcat

Create an array of spectra

Form an array of the spec1d the objects s4, s5, s6:
<tt>>>sout=[s4 s5 s6];</tt>

interpolate

Interpolate a spectrum to new x vales

Interpolate s10 to the x values specified in the array xnew:
<tt>>>snew=interpolate(s10,xnew);</tt>

loads

Load data from a file into a spectra

Load scan number 14 from the SPEC file ce2.dat:
<tt>>>s1=loads('specbatch', 'ce2.dat, X=Theta,Y=Exp_Hutch,M=Mon,S=14');</tt>
Load and combine scans 14 to 20:
<tt>>>s1=loads('specbatch', 'ce2.dat, X=Theta,Y=Exp_Hutch,M=Mon,S=[14++20]');</tt>
Load scans 14 to 20 into  an array:
<tt>>>s1=loads('specbatch', 'ce2.dat, X=Theta,Y=Exp_Hutch,M=Mon,S=[14:20]');</tt>

Load data from the ILL file ho001.dat:
<tt>>>s1=loads('illbatch', 'ho001.dat, X=OM,Y=I1,M=Mon');</tt>
Load  and combine ho001.dat to ho009.dat:
<tt>>>s1=loads('illbatch', 'ho00[1++9].dat, X=OM,Y=I1,M=Mon');</tt>
Load ho001.dat to ho009.dat into an array:
<tt>>>s1=loads('illbatch', 'ho00[1:9].dat, X=OM,Y=I1,M=Mon');</tt>

mapplot

Make a 2D plot of the data in an array of spectra.
Note: this is a visualisation tool, and not for data analysis.

Plot  array stot  (21 spectra):
<tt>>>mapplot(stot);</tt>
Plot and smooth using a Gaussian convolution of width 0.1;
<tt>>>mapplot(stot,[1:21],0.1);</tt>

normalise

Normalise the y data in a spectra to a specified value

Normalise y data in s2 to 10.5
<tt>>>s5=normalise(s2,10.5);</tt>

peakm

Calculate peak properties using the method of moments

Perform a peak analysis on s2:
<tt>>>stats=peakm(s2);</tt>
Perform peak analysis on array sall:
<tt>>>stats=peakm(sall);</tt>

peakt

Calculate the integrated intensity (and its error) using trapezoidal integration

Trapezoidal integration of peak in s3:
<tt>>>stats=peakt(s3);</tt>
Trapezoidal integration of array stot:
<tt>>>stats=peakt(stot);</tt>

plot

Basic plotting routine for displaying the contents of one or several spectra

Plot s3:
<tt>>>plot(s3);</tt>
Overlay s1, s2 and s3:
<tt>>>plot(s1 s2 s3);</tt>
Overlay s1, s2 and s3 on a loglog plot:
<tt>>>plot(s1 s2 s3,'loglog');</tt>
Overlay s1, s2 and s3 on a semilogy plot:
<tt>>>plot(s1 s2 s3,'loglog');</tt>

Overlay spectra in array st:
<tt>>>plot(st);</tt>
 

rebin

Rebin the data in a spectra to a new x axis

setfield

Set the values of specific fields

Set the x values in d24 to array xn:
<tt>>>d24=setfield(d24,'x',xn);</tt>
Set the datafile variable (i.e. title of graph)
<tt>>>d24=setfield(d24,'datafile','Great data');</tt>
 

smooth

Smooth the data using a 1D Gaussian convolution

Convolute s with a Gaussian of variance 0.2:
<tt>>>s=smooth(s,0.2)</tt>
 

spec1d

Create a new spec1d object

For a structure r 
<tt>>>r=spec1d(r)</tt>
converts r to a spec1d object

vertcat

Append the data from several spectra into one

Create a single spec1d object from s1, s2 and s3:
<tt>>>snew=[s1; s2; s3];</tt>