library(knitr) opts_chunk$set(fig.width=11, fig.height=7, base64_images=F, fig.align="center", message=F, warning=F, fig.path='figure_cwt/')
library(centWaveP)
for (i in seq(1, 50, 5)) { wav = centWaveP:::return.wavelet('mexh') %>% { centWaveP:::scale.wavelet(i, .)$y } plot(wav) cat(sum(wav > 0), i, "\n") }
for (i in seq(1, 50, 5)) { wav = centWaveP:::return.wavelet('nmexh') %>% { centWaveP:::scale.wavelet(i, .)$y } plot(wav) cat(sum(wav < 0), i, "\n") }
eic = { dnorm(seq(-6, 6, by =0.1)) } %>% { ./max(.) } plot(eic) for (i in seq(1, 50, 5)) { wav = cwt(eic, i, 'mexh') print(plot(wav, main = i)) cat(sum(wav > 0), i, "\n") }
eic = { dnorm(seq(-6, 6, by =0.1)) + dnorm(seq(-6, 6, by =0.1), mean = 3) } %>% { ./max(.) } plot(eic) for (i in seq(1, 50, 5)) { wav = cwt(eic, i, 'nmexh') print(plot(wav, main = i)) cat(sum(wav < 0), i, "\n") }
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