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Re: Help setting up an array
Craig Markwardt wrote:
> Peter Thorne <email@example.com> writes:
> > Thanks to everyone who has replied. At nearly 11pm I'm not sure whether
> > its exactly what I'm looking for, I shall investigate further tomorrow.
> > It seems like as suggested I have been looking at it for too long so
> > have tried to explain it in far too much difficulty, sorry. So, I'll
> > give a hopefully better example:
> > 3-D (to keep everyone happy, theoretically could be expected to be 2 to
> > 5 dimensional)
> > Locations array (points within a 3-D ellipsoid)
> > x y z (coordinates)
> > (1.5,3.4,2.0) point 0
> > (3.,-0.5,6.3) point 1
> > (1.3,2,.-4.5) point 2
> > (-0.1,1.7,0.1) point 3
> > .
> > .
> > .
> > .
> > (3.1,9.2,-1.4) point npoint
> > npoint is of order (10,000)
> > From this I wish to create a say 50x50x50 grid which covers all
> > plausible values (found by min and max in each column of the locations
> > array).
> > Then I need to rebin each of these points into the 3-D grid-space, so
> > each grid-box has a value which is the number of these original points
> > which fall within that grid-box. Other considerations are peripheral,
> > the problem arises in this transformation from the locations array to a
> > finite difference grid in which the values can be rebinned and how they
> > are rebinned.
> > This may have been covered already, but as my IDL license is at work and
> > not home I can't check :(
> > Thanks again for all the pointers and comments
> Yeah, this is indeed a job for HISTOGRAM. What you need to do is
> check out how HIST_2D is implemented. This can generalize to many
> dimensions. The one thing that HIST_2D does *not* do is to pass along
> the REVERSE_INDICES array, but it is trivial to add this if you need
> it (say, if you want to "invert" the histogram and find out which
> points fall in a particular bin).
> The end result will be something like this (for 3d, but not tested):
> i = floor((x-xmin)/xstep)
> j = floor((y-ymin)/ystep)
> k = floor((z-zmin)/zstep)
> ijk = i + nx*(j + ny*k)
> h = histogram(ijk)
> h = reform(h, nx, ny, nz, /overwrite)
> If you are clever you can generalize this to multi-d. Doing
> multi-dimensional histograms, with weighting, is something I've been
> intending to do in a program called CMHISTOGRAM. Alas it is only half
OK, I took the bait, and wasted some time. It's amazing how productive
you can be when you have other things to do.
Attached you'll find HIST_ND, for n-dimensional histograms. It's well
documented, and pretty straightforward. Try it out with some random
; Perform an N-dimensional histogram, also known as the joint
; density function of N variables, ala HIST_2D.
; CALLING SEQUENCE:
; V: A NxP array representing P data points in N dimensions.
; BINSIZE: The size of the bin to use. Either a P point vector
; specifying a separate size for each dimension, or a scalar,
; which will be used for all dimensions. If BINSIZE is not
; passed, NBINS must be.
; OPTIONAL INPUTS:
; MIN: The minimum value for the histogram. Either a P point
; vector specifying a separate minimum for each dimension, or a
; scalar, which will be used for all dimensions. If omitted,
; the natural minimum within the dataset will be used.
; MAX: The maximum value for the histogram. Either a P point
; vector specifying a separate maximmum for each dimension, or a
; scalar, which will be used for all dimensions. If omitted, the
; natural maximum within the dataset will be used.
; NBINS: Rather than specifying the binsize, you can pass NBINS,
; the number of bins in each dimension, which can be a P point
; vector, or a scalar. If BINSIZE it also passed, NBINS will be
; ignored, otherwise BINSIZE will then be calculated as
; binsize=(max-min)/nbins. Note that *unlike* RSI's version of
; histogram as of IDL 5.4, this keyword actually works as
; advertised, giving you NBINS bins over the range min to max.
; KEYWORD PARAMETERS:
; MIN,MAX: See above
; REVERSE_INDICES: Set to a named variable to receive the
; reverse indices, for mapping which points occurred in a given
; The N-Dimensional histogram, of size N1xN2xN3x...xND where the
; Ni's are the number of bins implied by the data, and input
; min, max and binsize.
; OPTIONAL OUTPUTS:
; The reverse indices
; MODIFICATION HISTORY:
; Wed Mar 28 19:41:10 2001, JD Smith <firstname.lastname@example.org>
; Written, based on HIST_2D, and suggestions of CM.
if n_elements(s) ne 2 then message,'Input must be N x P'
if n_elements(mx) eq 0 then begin
need_mn=n_elements(mn) eq 0
if need_mn then mn=mx
for i=0,s-1 do begin
if need_mn then mn[i]=tmn
if n_elements(mn) eq 1 and s gt 1 then mn=replicate(mn,s)
if n_elements(mx) eq 1 and s gt 1 then mx=replicate(mx,s)
if n_elements(bs) eq 1 and s gt 1 then bs=replicate(bs,s)
if n_elements(bs) eq 0 and n_elements(nb) ne 0 then bs=float(mx-mn)/nb else $
message,'Must pass one of binsize or NBINS'
for i=s-2,0,-1 do begin
if arg_present(ri) then $