# calibrate_harmonicpower: Quantitative calibration, through harmonic power, for Out and...

### Description

Estimates the number of harmonics required for the four Fourier methods implemented in Momocs: elliptical Fourier analysis (see efourier), radii variation analysis (see rfourier) and tangent angle analysis (see tfourier) and discrete Fourier transform (see dfourier). It returns and can plot cumulated harmonic power whether dropping the first harmonic or not, and based and the maximum possible number of harmonics on the Coo object.

### Usage

 1 calibrate_harmonicpower(x, method, id, nb.h, drop, thresh, plot, verbose) 

### Arguments

 x a Coo of Opn object method any method from c('efourier', 'rfourier', 'sfourier', 'tfourier') for Outs and dfourier for Outs. id the shapes on which to perform calibrate_harmonicpower. All of them by default nb.h numeric the maximum number of harmonic, on which to base the cumsum drop numeric the number of harmonics to drop for the cumulative sum thresh vector of numeric for drawing horizontal lines, and also used for minh below plot logical whether to plot the result or simply return the matrix verbose whether to print results

### Details

The power of a given harmonic n is calculated as follows for elliptical Fourier analysis and the n-th harmonic: HarmonicPower_n \frac{A^2_n+B^2_n+C^2_n+D^2_n}{2} and as follows for radii variation and tangent angle: HarmonicPower_n= \frac{A^2_n+B^2_n+C^2_n+D^2_n}{2}

### Value

returns a list with component:

• gg a ggplot object, q the quantile matrix

• minh a quick summary that returns the number of harmonics required to achieve a certain proportion of the total harmonic power.

Other calibration: calibrate_deviations, calibrate_r2, calibrate_reconstructions

### Examples

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 data(bot) cal <- calibrate_harmonicpower(bot) ## Not run: # for Opn objects data(olea) calibrate_harmonicpower(olea, "dfourier") # let customize the ggplot library(ggplot2) cal$gg + theme_minimal() + coord_cartesian(xlim=c(3.5, 12.5), ylim=c(90, 100)) + ggtitle("Harmonic power calibration") ## End(Not run) # if you want to do efourier with 99% calibrate_harmonicpower in one step # efourier(bot, nb.h=calibrate_harmonicpower(bot, "efourier", plot=FALSE)$minh["99%"]) 

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