FitSinglePeak | R Documentation |
FitSinglePeak
performs a peak fit. Gaussian, Lorentzian and
Pseudo-Voigt peak shapes are supported.
FitSinglePeak(
yVals,
xVals,
peakType = 0L,
blOffset = 0,
blSlope = 0,
amplitude = 0,
fwhmLo = 0,
fwhmHi = 0,
peakPos = 0,
mu = 0
)
yVals |
y axis data. |
xVals |
x axis data. |
peakType |
peak model to use. |
blOffset |
Initial value of baseline offset at first data point. |
blSlope |
Initial value of slope of baseline. |
amplitude |
Initial value of peak amplitude. |
fwhmLo |
Initial value of left peak width (full width at half maximum). |
fwhmHi |
Initial value of right peak width (full width at half maximum). |
peakPos |
Initial value of peak position. |
mu |
Initial value of Gaussian/Lorentzian contribution. |
Peak parameters are optimized using a Levenberg-Marquardt algorithm as
implemented by the library lmfit
. The following peak types are available:
peak type index | peak function | symmetric | baseline |
-1 | Gaussian through highest point and its neighbours | yes | no |
0 | Gaussian | yes | no |
1 | Lorentzian | yes | no |
2 | Pseudo-Voigt | yes | no |
3 | Gaussian | yes | yes |
4 | Lorentzian | yes | yes |
5 | Pseudo-Voigt | yes | yes |
6 | Gaussian | no | no |
7 | Lorentzian | no | no |
8 | Pseudo-Voigt | no | no |
9 | Gaussian | no | yes |
10 | Lorentzian | no | yes |
11 | Pseudo-Voigt | no | yes |
The function for peakType = -1 is not an actual peak fit but rather the Gaussian function (symmetric, no baseline) defined by the maximum intensity point and its neighbors. It is used to automatically generate guess values for position, width and amplitude if all peak parameters are set to 0.
List with peak parameters.
Other Peak fitting functions:
EvalMultiPeak()
,
EvalSinglePeak()
,
FitSinglePeak2()
,
MultiPeakFit()
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