Main Panel¶
Clone: Clone popup window
Help: Show popup help document
Close: Close popup
Separate Merged Peaks Using Peak Models
The Peak Separator code uses a Markov Chain Monte Carlo search which, using idealised peak shapes, attempts to deconvolve overlapped peak regions into their separate constituent peaks.
This routine is also suitable for accurately fitting model shapes to single peaks in order to calculate precise intensities.
Options Peak Separator Parameters Min. Number of peaks is by default set to one, it is not possible to set this to a value less than one. Max. Number of peaks is by default set to one, increasing this value allows the search routine to fit more models. The best fit may be found with fewer than the maximum number models. Higher numbers slow the routine, and setting this value to 0 allows the routine to (effectively) fit unlimited peaks. Only pick positive peaks. If you are not interested in negative peaks, removing the possibility of fitting negative peaks can reduce search time. Peak Model fits the spectra with either a Gaussian peak model or a Lorentzian peak model.
Options Region Peak List choose which peak list newly picked peaks should be added to. Peaks picked using this method will have their details appended with ‘PeakSepartor’ so you know where they came from. Region Table shows which area of the current spectrum is about to be searched. Add Region. Once an area of spectra has been highlighted clicking this button will pass it’s details on to the Peak Separator. Reset All will reset all search parameters. Separate Peaks will run the Peak Separator code with your current settings. This may take a few minutes to run, depending on the size of the spectral region being searched, the number of peaks being fitted and the speed of your machine. Please wait while this completes.
After a successful Peak Separation run, the found peaks will be added to the selected peak list. These peaks intensties (volume) have been found using the peak model selected.
Advanced Settings Tab Rate affects the speed of the Markov Chain Monte Carlo routine. A smaller value results in longer execution, but possibly higher quality results. The default setting is deemed sensible for the majority of runs. Line Width offers a finer degree of control over maximum and minimum peak widths for each dimension. The default values are very stupid and could do with re-checking for each experiment. Re-Pick Entire Peak List if you would like to use the Peak Separator to repick every peak in your peak list, try this option - but note that this may take a very long time!
Documentation missing
Min. number of peaks: Minimum number of peaks to find (must be > 0)
Max. number of peaks: Maximum number of peaks to find (0 is unlimited - not recommended)
False: Search for both positive and negative intensity peaks
True: Limit search to only positive peaks
Gaussian: Choose a Gaussian model peak shape to fit to peaks
Lorentzian: Choose a Lorentzian model peak shape to fit to peaks
Region that search will limit itself to
Peak List: Select which peak list new peaks are to be added to
Table 1 | |
dim. | Documentation missing |
start (ppm) | Documentation missing |
end (ppm) | Documentation missing |
actual size | Documentation missing |
Add Region: Add selected specrtral region
Separate Peaks: Run peak search now
Documentation missing
Rate of MCMC step size change: Rate effects speed of run, smaller values take longer but may produce better results
*None*: Select which peak list to repick (new peaks will be put into a new peak list)
Repick Peak List: Repick selected peak list into a new peak list.
Separate Peaks: Run peak search now