RSEIS (version 3.5-2)

wlet.do: Return Wavelet transform

Description

Wavelet transform

Usage

wlet.do(why, dt, noctave = 6, nvoice = 20,
flip = TRUE, ploty = TRUE, zscale = 1,
col = terrain.colors(100), STAMP = STAMP, units="", scaleloc=c(0.4,0.95))

Arguments

why

signal

dt

sample rate (s)

noctave

number of octives

nvoice

number of voices

flip

logical, whether to flip the orientation

ploty

logical, whether to plot y

zscale

scale of the image

col

color palette

STAMP

cahracter stamp for identification

units

character, units to put on plot

scaleloc

2-vector, percentatge of bottom margin for the color scale

Value

baha

list: wavelet transform image, noctave = number of octaves, nvoice = number of voices, flip = logical, whether image is flipped (default=TRUE)

PE

plotting information list: why=y-axis, dt=time series sample, interval, zscale=(1,2,3) image scaling, col=color map, ygrid = logical(default=FALSE), STAMP = character string

Details

This function uses the cwt (package:Rwave) code to calculate the continuous wavelet transform, but plots it differently. Morelet wavelet is used by default. The cwt produces an image, the modulus of the transform, which is passed on to wlet.do along with the number of octaves and the number of voices. Plotting parameters are passed to the function so that replotting can be accomplished (use plotwlet) without having to recalculate the transform.

Plotting parameters are passed on to the plotting function, plotwlet.

See Also

Rwave, cwt , plotwlet, contwlet , pwlet2freqs, wlet.drive

Examples

## Not run: 
# data(CE1)
# 
# plot(CE1$x, CE1$y, type='l')
# 
# require(Rwave)
# 
# out <- wlet.do(CE1$y, CE1$dt, flip = FALSE, ploty = TRUE)
# 
# 
# ####  show with different scalings:
# plotwlet(out$baha, CE1$y, CE1$dt , zscale=3,
# col=rainbow(100) ,  ygrid=FALSE)
# 
# plotwlet(out$baha, CE1$y, CE1$dt , zscale=1,  col=terrain.colors(100) ,
# ygrid=TRUE)
# 
# ##############  add frequency scale on the right hand side of image
# pfreqs <- c(0.5, 1, 2,3,4,5, 10, 14)
# 
#  zp <- pwlet2freqs(noctave=out$baha$noctave , nvoice=out$baha$nvoice,
#      CE1$dt,
#      flip = TRUE, pfreqs, plot = TRUE,
#      perc = 0.85)
# 
# 
# 
# 
# ## End(Not run)