David Goldsmith wrote:
On Fri, Nov 27, 2009 at 9:25 PM, Wayne Watson <sierra_mtnview@sbcglobal.net <mailto:sierra_mtnview@sbcglobal.net>> wrote:
I actually wrote my own several days ago. When I began getting myself more familiar with numpy, I was hoping there would be an easy to use version in it for this frequency approach. If not, then I'll just stick with what I have. It seems something like this should be common.
...
> If you need more stats with weights, then the attachment in > http://projects.scipy.org/scipy/ticket/604 is a good start. > > Josef
Wayne:
There is no need to "unwind": If Y(X) is the (unnormalized) freq. distr. of random variable/data X, start by computing y = Y/(Y.sum()) (if Y is already normalized, skip this step). Then:
av(X) = np.dot(X, y), sd(X) = np.sqrt(np.dot((X*X), y) - (av(X))^2), and higher moment statistics can be calculated utilizing similar formulae.
DG I was only illustrating a way that I would not consider, since the hardware has already created the pdf. I've already coded it pretty much as you have suggested. As I think I mention ed above, I'm a bit surprised numpy doesn't provide the code you suggest as part of some function. CalcSimplefromPDF(xvalues=mydatarray, avg=ture, minmax=true, ...).
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