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. Josef > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion