wavCWT (wmtsa) iterations?
Hi Stephen, How large is your dataset? I routinely do wavelet analysis on series of ~10000 observations on a computer with 1 gigabyte of ram. You are aware that if you divide your data you are limiting the temporal scales that you can look at, right? If you divide your data into one week pieces then you won't be able to obtain information on the variability at larger scales. The larger scale you will be able to analyze will be even shorter than a week after you remove boundary coefficients. This may be good enough if you are interested in processes occurring at small temporal scales, but clearly not adequate if your interest is in larger temporal scales (or if you are doing exploratory analyzes). Getting wavelet coefficients in chunks of data and then plotting them together is not kosher either because the coefficients obtained near the edges between chunks will be biased. Julian
stephen sefick wrote:
I have hit the max memory for my poor little computer. I there a way to just section the sections that I would like to look at instead of doing the transform on the whole dataset? scale.range only works when I specify deltat(x.ts). It would be nice to start this at say a day to a week. my data is in 15min. intervals so this could correspond to 96 to 672 readings. The other thing that I was wondering if I could do is do this on subsets of the data and then combine them into one big plot for the CWT of the entire data set- iterate through "chunks" and then combine them at the end? thanks Error: cannot allocate vector of size 98.2 Mb In addition: Warning messages: 1: In wavCWT(x.ts) : Reached total allocation of 502Mb: see help(memory.size) 2: In wavCWT(x.ts) : Reached total allocation of 502Mb: see help(memory.size) 3: In wavCWT(x.ts) : Reached total allocation of 502Mb: see help(memory.size) 4: In wavCWT(x.ts) : Reached total allocation of 502Mb: see help(memory.size)