On Mon, Sep 28, 2009 at 8:45 PM, jah <jah.mailingl...@gmail.com> wrote:
> On Mon, Sep 28, 2009 at 4:48 PM, <josef.p...@gmail.com> wrote: > >> On Mon, Sep 28, 2009 at 7:19 PM, jah <jah.mailingl...@gmail.com> wrote: >> > Hi, >> > >> > Suppose I have a set of x,y,c data (something useful for >> > matplotlib.pyplot.plot() ). Generally, this data is not rectangular at >> > all. Does there exist a numpy function (or set of functions) which will >> > take this data and construct the smallest two-dimensional arrays X,Y,C ( >> > suitable for matplotlib.pyplot.contour() ). >> > >> > Essentially, I want to pass in the data and a grid step size in the x- >> and >> > y-directions. The function would average the c-values for all points >> which >> > land in any particular square. Optionally, I'd like to be able to >> specify a >> > value to use when there are no points in x,y which are in the square. >> > >> > Hope this makes sense. >> >> If I understand correctly numpy.histogram2d(x, y, ..., weights=c) might >> do >> what you want. >> >> There was a recent thread on its usage. >> > > It is very close, but it normed=True, will first normalize the weights > (undesirably) and then it will normalize the normalized weights by dividing > by the cell area. Instead, what I want is the cell value to be the average > off all the points that were placed in the cell. This seems like a common > use case, so I'm guessing this functionality is present already. So if 3 > points with weights [10,20,30] were placed in cell (i,j), then the cell > should have value 20 (the arithmetic mean of the points placed in the cell). > > Would this work for you ? >>> s = histogram2d(x,y,weights=c) # Not normalized, so you get the sum of the weights >>> n = histogram2d(x,y) # Now you have the number of elements in each bin >>> mean = s/n David > Here is the desired use case: I have a set of x,y,c values that I could > pass into matplotlib's scatter() or hexbin(). I'd like to take this same > set of points and transform them so that I can pass them into matplotlib's > contour() function. Perhaps matplotlib has a function which does this. > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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