[R] Help with wavCWTPeaks
stephen sefick
ssefick at gmail.com
Fri Dec 5 20:07:11 CET 2008
#my suggestion would be to use the morlet wavelet as opposed to the
mexican hat wavelet (default).
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, wavelet="morlet", col=tim.colors(100))
aa.tree <- wavCWTTree (aa.cwt)
On Fri, Dec 5, 2008 at 12:15 PM, <mauede at alice.it> wrote:
> I cannot understand the following error printed out when I try to get the
> extrema of my time series.
> I would appreciate some suggestion as I really cannot interpret the error. I
> might not be using a proper
> set of parameters in calling such functions. I am learning by doing ...
>
>> aa.peak <- wavCWTPeaks (aa.tree)
> Error in `row.names<-.data.frame`(`*tmp*`, value = c("1", "0")) :
> invalid 'row.names' length
>
> My data vector is as follows:
>> aa
> [1] -0.852625404 -0.886941142 -0.920699269 -0.953858240 -0.986377090
> [6] -1.018215725 -1.049335086 -1.079697274 -1.109265628 -1.138004782
> [11] -1.165880733 -1.192860894 -1.218914146 -1.244010899 -1.268123116
> [16] -1.291224432 -1.313290096 -1.334297111 -1.354224193 -1.373051833
> [21] -1.390762317 -1.407339716 -1.422769965 -1.437040775 -1.450141701
> [26] -1.462064157 -1.472801336 -1.482348272 -1.490701780 -1.497860461
> [31] -1.503824640 -1.508596384 -1.512179425 -1.514579128 -1.515802478
> [36] -1.515858035 -1.514755845 -1.512507449 -1.509125815 -1.504625250
> [41] -1.499021421 -1.492331231 -1.484572809 -1.475765432 -1.465929450
> [46] -1.455086269 -1.443258266 -1.430468724 -1.416741774 -1.402102340
> [51] -1.386576077 -1.370189287 -1.352968891 -1.334942359 -1.316137624
> [56] -1.296583049 -1.276307350 -1.255339556 -1.233708931 -1.211444912
> [61] -1.188577082 -1.165135088 -1.141148591 -1.116647219 -1.091660532
> [66] -1.066217945 -1.040348675 -1.014081694 -0.987445689 -0.960469010
> [71] -0.933179631 -0.905605109 -0.877772541 -0.849708278 -0.821438088
> [76] -0.792987122 -0.764379898 -0.735640266 -0.706791393 -0.677855738
> [81] -0.648855033 -0.619810274 -0.590741693 -0.561668758 -0.532610156
> [86] -0.503583784 -0.474606745 -0.445695338 -0.416865062 -0.388130609
> [91] -0.359505865 -0.331003918 -0.302637056 -0.274416782 -0.246353810
> [96] -0.218458088 -0.190738802 -0.163204394 -0.135862573 -0.108720337
> [101] -0.081783987 -0.055059152 -0.028550808 -0.002263304 0.023799613
> [106] 0.049634774 0.075239551 0.100611836 0.125750005 0.150652886
> [111] 0.175319722 0.199750141 0.223944116 0.247901927 0.271624125
> [116] 0.295111492 0.318365000 0.341385774 0.364175049 0.386734130
> [121] 0.409064353 0.431167045 0.453043480 0.474694850 0.496122212
> [126] 0.517326465 0.538308303 0.559068185 0.579606300 0.599922532
> [131] 0.620016432 0.639887183 0.659533578 0.678953988 0.698146340
> [136] 0.716367156 0.734459833 0.752428741 0.770277372 0.788008310
> [141] 0.805623188 0.823122667 0.840506396 0.857773019 0.874920094
> [146] 0.891944162 0.908840641 0.925603903 0.942227205 0.958702728
> [151] 0.975021541 0.991173645 1.007147946 1.022932278 1.038513449
> [156] 1.053877190 1.069008243 1.083890313 1.098506181 1.112837647
> [161] 1.126865608 1.140570088 1.153930270 1.166924526 1.179530477
> [166] 1.191725035 1.203484451 1.214784382 1.225599912 1.235905642
> [171] 1.245675755 1.254884072 1.263504095 1.271509107 1.278872248
> [176] 1.285566555 1.291565077 1.296840902 1.301367293 1.305117743
> [181] 1.308066011 1.310186290 1.311453212 1.311841963 1.311328350
> [186] 1.309888930 1.307500999 1.304142758 1.299793348 1.294432925
> [191] 1.288042752 1.280605267 1.272104143 1.262524364 1.251852272
> [196] 1.240075658 1.227183764 1.213167403 1.198018950 1.181732402
> [201] 1.164303440 1.145729407 1.126009401 1.105144212 1.083136426
> [206] 1.059990384 1.035712188 1.010309729 0.983792617 0.956172242
> [211] 0.927461713 0.897675875 0.866831225 0.834945955 0.802039881
> [216] 0.768134393 0.733252445 0.697418506 0.660658502 0.622999781
> [221] 0.584471057 0.545102363 0.504924994 0.463971453 0.422275398
> [226] 0.379871580 0.336795792 0.293084805 0.248776314 0.203908880
> [231] 0.158521870 0.112655403 0.066350293 0.019647991 -0.027409468
> [236] -0.074779520 -0.122419124 -0.170284817 -0.218332766 -0.266518818
> [241] -0.314798550
>
> I convert it into a time series and then I get the CWT coefficients. Then I
> build the tree
> that exhibits only 3 branches (see attached plot)
>
> aats <- ts (aa, deltat =1/30, start = 0.0)
> aa.cwt <- wavCWT(aats)
> aa.tree <- wavCWTTree (aa.cwt)
>
> I can get the data for each of the 3 branches:
>> aa.tree[[1]]
> $itime
> [1] 135 135 134 133 132 130 128 126 123 122 122 122 122 123 126
>
> $iscale
> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
>
> $time
> [1] 4.466667 4.466667 4.433333 4.400000 4.366667 4.300000 4.233333 4.166667
> [9] 4.066667 4.033333 4.033333 4.033333 4.033333 4.066667 4.166667
>
> $scale
> [1] 0.03333333 0.06666667 0.10000000 0.13333333 0.16666667 0.20000000
> [7] 0.23333333 0.26666667 0.30000000 0.33333333 0.36666667 0.40000000
> [13] 0.43333333 0.46666667 0.50000000
>
> $extrema
> [1] 0.001143350 0.004153357 0.009778222 0.018315375 0.030294895 0.046225772
> [7] 0.066645451 0.092064228 0.122788334 0.158757578 0.199797960 0.245925327
> [13] 0.297235272 0.354056031 0.417519487
>
>> aa.tree[[2]]
> $itime
> [1] 202 202 202 202 202 202 202 202 202 202 205
>
> $iscale
> [1] 1 2 3 4 5 6 7 8 9 10 11
>
> $time
> [1] 6.7 6.7 6.7 6.7 6.7 6.7 6.7 6.7 6.7 6.7 6.8
>
> $scale
> [1] 0.03333333 0.06666667 0.10000000 0.13333333 0.16666667 0.20000000
> [7] 0.23333333 0.26666667 0.30000000 0.33333333 0.36666667
>
> $extrema
> [1] 0.002490402 0.014052846 0.038579099 0.078779561 0.136699962 0.213884238
> [7] 0.311455206 0.430189008 0.570761962 0.734351009 0.924577986
>
>> aa.tree[[3]]
> $itime
> [1] 240 239 238 237 236 235 233 232 230 228 225 222 219 216 212 210 208 206
> [19] 205 204 202 201 199 198 197 195 194 191 189 187 185 182 180 178 176 175
> [37] 173 172 171 170 169 169 169 169 168 168 168 168 168 168 168 168 168 168
> [55] 168 168 168 168 168 168 168 168 168 168 168
>
> $iscale
> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
> [25] 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
> [49] 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
>
> $time
> [1] 7.966667 7.933333 7.900000 7.866667 7.833333 7.800000 7.733333 7.700000
> [9] 7.633333 7.566667 7.466667 7.366667 7.266667 7.166667 7.033333 6.966667
> [17] 6.900000 6.833333 6.800000 6.766667 6.700000 6.666667 6.600000 6.566667
> [25] 6.533333 6.466667 6.433333 6.333333 6.266667 6.200000 6.133333 6.033333
> [33] 5.966667 5.900000 5.833333 5.800000 5.733333 5.700000 5.666667 5.633333
> [41] 5.600000 5.600000 5.600000 5.600000 5.566667 5.566667 5.566667 5.566667
> [49] 5.566667 5.566667 5.566667 5.566667 5.566667 5.566667 5.566667 5.566667
> [57] 5.566667 5.566667 5.566667 5.566667 5.566667 5.566667 5.566667 5.566667
> [65] 5.566667
>
> $scale
> [1] 0.03333333 0.06666667 0.10000000 0.13333333 0.16666667 0.20000000
> [7] 0.23333333 0.26666667 0.30000000 0.33333333 0.36666667 0.40000000
> [13] 0.43333333 0.46666667 0.50000000 0.53333333 0.56666667 0.60000000
> [19] 0.63333333 0.66666667 0.70000000 0.73333333 0.80000000 0.83333333
> [25] 0.86666667 0.93333333 0.96666667 1.00000000 1.10000000 1.16666667
> [31] 1.23333333 1.30000000 1.36666667 1.43333333 1.53333333 1.60000000
> [37] 1.70000000 1.80000000 1.90000000 2.00000000 2.13333333 2.23333333
> [43] 2.36666667 2.50000000 2.66666667 2.80000000 2.96666667 3.13333333
> [49] 3.30000000 3.50000000 3.70000000 3.90000000 4.10000000 4.36666667
> [55] 4.60000000 4.86666667 5.16666667 5.46666667 5.76666667 6.10000000
> [61] 6.43333333 6.80000000 7.20000000 7.60000000 8.03333333
>
> $extrema
> [1] 2.112717e-01 3.394113e-01 4.169413e-01 4.778086e-01 5.320947e-01
> [6] 5.855642e-01 6.505954e-01 7.254532e-01 8.219651e-01 9.412408e-01
> [11] 1.091710e+00 1.275782e+00 1.497830e+00 1.756278e+00 2.045967e+00
> [16] 2.359591e+00 2.690719e+00 3.035522e+00 3.392502e+00 3.757973e+00
> [21] 4.130551e+00 4.509703e+00 5.280292e+00 5.670084e+00 6.062074e+00
> [26] 6.851106e+00 7.247628e+00 8.045326e+00 8.846766e+00 9.649727e+00
> [31] 1.045085e+01 1.124541e+01 1.202478e+01 1.277755e+01 1.383239e+01
> [36] 1.446487e+01 1.528176e+01 1.590892e+01 1.632802e+01 1.653015e+01
> [41] 1.646514e+01 1.618348e+01 1.553216e+01 1.461983e+01 1.320993e+01
> [46] 1.194458e+01 1.028845e+01 8.643199e+00 7.088004e+00 5.416952e+00
> [51] 4.006859e+00 2.871097e+00 1.871285e+00 1.170313e+00 7.029019e-01
> [56] 3.738840e-01 1.729185e-01 7.505307e-02 3.059919e-02 1.050205e-02
> [61] 3.342503e-03 8.703506e-04 1.810757e-04 3.389703e-05 4.903014e-06
>
>
> Best regards,
> --
> Maura
>
> Alice Messenger ;-) chatti anche con gli amici di Windows Live Messenger e
> tutti i telefonini TIM!
> Vai su http://maileservizi.alice.it/alice_messenger/index.html?pmk=footer
--
Stephen Sefick
Let's not spend our time and resources thinking about things that are
so little or so large that all they really do for us is puff us up and
make us feel like gods. We are mammals, and have not exhausted the
annoying little problems of being mammals.
-K. Mullis
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