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

In vbonhomme/Momocs: Morphometrics using R

Quantitative calibration, through harmonic power, for Out and Opn objects

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

calibrate_harmonicpower()

calibrate_harmonicpower_efourier(
  x,
  id = 1:length(x),
  nb.h,
  drop = 1,
  thresh = c(90, 95, 99, 99.9),
  plot = TRUE
)

calibrate_harmonicpower_rfourier(
  x,
  id = 1:length(x),
  nb.h,
  drop = 1,
  thresh = c(90, 95, 99, 99.9),
  plot = TRUE
)

calibrate_harmonicpower_tfourier(
  x,
  id = 1:length(x),
  nb.h,
  drop = 1,
  thresh = c(90, 95, 99, 99.9),
  plot = TRUE
)

calibrate_harmonicpower_sfourier(
  x,
  id = 1:length(x),
  nb.h,
  drop = 1,
  thresh = c(90, 95, 99, 99.9),
  plot = TRUE
)

calibrate_harmonicpower_dfourier(
  x,
  id = 1:length(x),
  nb.h,
  drop = 1,
  thresh = c(90, 95, 99, 99.9),
  plot = TRUE
)

Arguments

x	a Coo of Opn object
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 Silent message and progress bars (if any) with options("verbose"=FALSE).

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.

See Also

Other calibration: calibrate_deviations(), calibrate_r2(), calibrate_reconstructions

Examples

b5 <- bot %>% slice(1:5)
b5  %>% calibrate_harmonicpower_efourier(nb.h=12)
b5  %>% calibrate_harmonicpower_rfourier(nb.h=12)
b5  %>% calibrate_harmonicpower_tfourier(nb.h=12)
b5  %>% calibrate_harmonicpower_sfourier(nb.h=12)

# on Opn
olea %>% slice(1:5) %>%
    calibrate_harmonicpower_dfourier(nb.h=12)

# let customize the ggplot
library(ggplot2)
cal <- b5  %>% calibrate_harmonicpower_efourier(nb.h=12)
cal$gg + theme_minimal() +
coord_cartesian(xlim=c(3.5, 12.5), ylim=c(90, 100)) +
ggtitle("Harmonic power calibration")

vbonhomme/Momocs documentation built on Nov. 13, 2023, 8:54 p.m.