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! 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