Morlet wavelet not supportd by wavCWTPeaks

aa <- (structure(list(X.0.85 = c(-1.02, -1.17, -1.29, -1.39, -1.46,
-1.5, -1.52, -1.5, -1.46, -1.39, -1.3, -1.19, -1.07, -0.93, -0.79,
-0.65, -0.5, -0.36, -0.22, -0.08, 0.05, 0.18, 0.3, 0.41, 0.52,
0.62, 0.72, 0.81, 0.89, 0.98, 1.05, 1.13, 1.19, 1.25, 1.29, 1.31,
1.31, 1.29, 1.24, 1.16, 1.06, 0.93, 0.77, 0.58, 0.38, 0.16, -0.07,
-0.31, -0.89, -1.05, -1.19, -1.31, -1.41, -1.47, -1.51, -1.51,
-1.49, -1.44, -1.37, -1.28, -1.17, -1.04, -0.91, -0.76, -0.62,
-0.47, -0.33, -0.19, -0.06, 0.08, 0.2, 0.32, 0.43, 0.54, 0.64,
0.73, 0.82, 0.91, 0.99, 1.07, 1.14, 1.2, 1.25, 1.29, 1.31, 1.31,
1.28, 1.23, 1.15, 1.04, 0.9, 0.73, 0.55, 0.34, 0.11, -0.12, -0.92,
-1.08, -1.22, -1.33, -1.42, -1.48, -1.51, -1.51, -1.48, -1.43,
-1.35, -1.26, -1.14, -1.01, -0.88, -0.74, -0.59, -0.45, -0.3,
-0.16, -0.03, 0.1, 0.22, 0.34, 0.45, 0.56, 0.66, 0.75, 0.84,
0.93, 1.01, 1.08, 1.15, 1.21, 1.26, 1.3, 1.31, 1.3, 1.27, 1.21,
1.13, 1.01, 0.87, 0.7, 0.5, 0.29, 0.07, -0.17, -0.95, -1.11,
-1.24, -1.35, -1.44, -1.49, -1.51, -1.51, -1.48, -1.42, -1.33,
-1.23, -1.12, -0.99, -0.85, -0.71, -0.56, -0.42, -0.27, -0.14,
0, 0.13, 0.25, 0.36, 0.47, 0.58, 0.68, 0.77, 0.86, 0.94, 1.02,
1.1, 1.17, 1.23, 1.27, 1.3, 1.31, 1.3, 1.26, 1.2, 1.11, 0.98,
0.83, 0.66, 0.46, 0.25, 0.02, -0.22, -0.99, -1.14, -1.27, -1.37,
-1.45, -1.5, -1.52, -1.5, -1.47, -1.4, -1.32, -1.21, -1.09, -0.96,
-0.82, -0.68, -0.53, -0.39, -0.25, -0.11, 0.02, 0.15, 0.27, 0.39,
0.5, 0.6, 0.7, 0.79, 0.87, 0.96, 1.04, 1.11, 1.18, 1.24, 1.28,
1.31, 1.31, 1.29, 1.25, 1.18, 1.08, 0.96, 0.8, 0.62, 0.42, 0.2,
-0.03, -0.27)), .Names = "X.0.85", class = "data.frame", row.names = c(NA,
-240L)))
library(wmtsa)
library(fields)
aats <- ts (aa, deltat =1/30, start = 0.0)
aa.cwt <-  wavCWT(aats)
aa.tree <- wavCWTTree (aa.cwt)
aa.peak <- wavCWTPeaks(aa.tree)

sorry I didn't realize that only the mexican hat wavelet could be used
for the peak function.  This should work fine.  and Use the tim.colors
argument in the plot() function.  I hope this helps....  This reason I
suggested the morlet wavelet is that it is compactly suppoted

aa.cwt <-  wavCWT(aats,wavelet="morlet")

aa.cwt

Continuous Wavelet Transform of aats
------------------------------------
Wavelet                 : Morlet
Wavelet frequency shift : 5 (rad/sec)
Length of series        : 241
Sampling interval       : 0.03333333
Number of scales        : 65
Range of scales         : 0.0333333333333333 to 8.03333333333333

 aa.cwt.coef <- as.matrix (aa.cwt)
   plot (aa.cwt, series=TRUE)
plot (aa.cwt, type="persp")

  aa.tree <- wavCWTTree (aa.cwt)
 aa.peak <- wavCWTPeaks (aa.tree)

Error in wavCWTPeaks(aa.tree) :
  Only CWT developed using the Mexican hat (gaussian2) filter are supported

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