| array index summations [message #69201] |
Fri, 18 December 2009 03:07 |
H. Evans
Messages: 18
Registered: December 2009
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Junior Member |
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Hi,
I have a time-series data set, effectively a 3-vector (x,y,z), where
the Z values are to be binned into a 2D array along X/Y.
Currently, I'm using the following, which loops over all of the data
points (which could be numbered in the millions):
; calculate the X & Y indices into the 2D array
ix = FLOOR((x - self.xfit[0]) / self.xfit[1])
iy = FLOOR((y - self.yfit[0]) / self.yfit[1])
; Range check the index calculations
ii = WHERE( (ix ge 0) AND (ix LT self.nx) AND $
(iy ge 0) AND (iy LT self.ny) )
IF ii[0] GE 0 THEN BEGIN
ix = ix[ii]
iy = iy[ii]
zz = z[ii]
FOR i=0L,N_ELEMENTS(ix)-1 do BEGIN
(*self.zsum) [ ix[i], iy[i]] += zz[i]
(*self.zsum2)[ ix[i], iy[i]] += zz[i]^2
(*self.nmap) [ ix[i], iy[i]]++
ENDFOR
ENDIF
I want to get rid of the FOR loop. So I was thinking initially of
something analogous to:
x = INDGEN(10)
y = INTARR(5)
i = [0,0,0,0,0, 1,1, 2,3,4] ; one for every element of X
y[i] += x
where y would then become:
y = [ 10, 11, 7, 8, 9]
with the assumption that IDL would do a "loop" over the indices
accumulating the results in y at the appropriate indices, or rewritten
in C:
for (j=0; j<10; j++) {
y[i[j]] =+ x[j]
}
This, of course, doesn't happen. Another option is to use the
histogram with the TOTAL function to solve the binning, but this then
still implies looping over the nX*nY bins, which could also be large
(~100*600). Or:
h = HISTOGRAM( i, reverse_ind=ri)
for j=0L,N_ELEMENTS(h)-1 DO $
IF (h[j] GT 0) THEN $
y[j] = TOTAL( x[ ri[ri[j]] : ri[ri[j+1]-1] ])
But this still yields a FOR loop.
Also, is it possible to provide weights for the entries to the
histogram, rather than just counting the number of entries in the
bins. So for each bin it would return SUM(weights[i]) rather than
N_ELEMENTS(i), where I is the list of indices of the data points that
went into the bin (or i[j] = ri[ri[j]] : ri[ri[j+1]-1] in the above
example)
Ideas?
Thanks,
Hugh
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