wavCWT (wmtsa) iterations?

Stephen,

I should have pointed out that both bits of sample code I sent should work 
just fine with plotting functions that require a matrix [e.g., image()], 
rather than a vector, of colors.

Like Julian, I often try the built-in palette functions first... and they 
are simpler... but they often are not flexible enough to achieve desired 
effects (the sample shading from blue to tan and back to blue is an 
example).

Glen

*************************************************
Glen A. Sargeant, Ph.D.
Research Wildlife Biologist/Statistician
Northern Prairie Wildlife Research Center
8711 37th Street SE
Jamestown, ND  58401

Phone: (701) 253-5528
E-mail:  glen_sargeant at usgs.gov
FAX:     (701) 253-5553
*************************************************



"stephen sefick" <ssefick at gmail.com> 
Sent by: r-sig-ecology-bounces at r-project.org
05/19/2008 01:39 PM

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Subject
[R-sig-eco] wavCWT (wmtsa) iterations?






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)

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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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

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)