harm.quant(Coo, id = 1:Coo@coo.nb, smooth.it = 0, harm.range= seq(8, 32, 6),
scale = FALSE, center = TRUE, align = FALSE,
plot = TRUE, legend = TRUE, palette = col.summer, lineat.y=c(1, 5, 10))
harm.qual(Coo, id = 1, smooth.it = 0, harm.range= c(1, 2, 4, 8, 16, 32),
scale = FALSE, center = TRUE, align = FALSE, method = c("stack", "panel")[1],
legend = TRUE,
palette = col.summer, shp.col="#70809033", shp.border="#708090EE")
harm.pow(Coo, id=1:Coo@coo.nb, probs=c(0, 0.5, 1), nb.h = 24,
drop = 1, smooth.it = 0, plot = TRUE,
legend = TRUE, title="Fourier power spectrum",
lineat.x=seq(0, nb.h, by=6), lineat.y=c(0.9, 0.99), bw=0.1)
Coo
objectinteger
. The id
of the shape to display. A range of id
s can be passed to harm.pow
vector
of numeric
, to define quantiles to calculate ; see quantileinteger
. The number of smoothing iteration to perform.vector
of integer
giving the harmonic range to calculate. See nb.h
for harm.pow
.integer
. The maximal number of harmonics to calculate.logical
. Whether to scale or not the shape.logical
. Whether to center or not the shape.logical
. Whether to align or not the shape.logical
. Whether to plot or not the shape. If FALSE
, only the results are returned.harm.qual
. If "stack"
outlines are plotted on the same same, if "panel"
, separate reconstructions are plotted.logical
. Whether to display a legend box.character
. The title to add.logical
. Whether to drop the first harmonic for plotting and power calculation.vector
of numeric
to specify where to plot dashed lines on the x-axis.vector
of numeric
to specify where to plot dashed lines on the y-axis.numeric
. The width of horizontal segments drawn for each harmonic.harm.quant
returns a matrix containing deviations for each harmonic and corresponding quantiles.
harm.pow
returns a matrix containing cumulated harmonic power for each harmonic.harm.quant
is based on euclidean distance between original and reconstructed outlines harm.pow returns and plot cumulated harmonic power. The power of a given harmonic $n$ is calculated as follows:
$$HarmonicPower_n= \frac{A^2_n+B^2_n+C^2_n+D^2_n}{2}$$data(bot)
harm.quant(bot)
harm.qual(bot)
harm.pow(bot)
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