On Wed, Aug 12, 2009 at 6:28 AM, John Hunter<jdh2358@gmail.com> wrote:
We would like to add function plotting to mpl, but to do this right we need to be able to adaptively sample a function evaluated over an interval so that some tolerance condition is satisfied, perhaps with both a relative and absolute error tolerance condition. I am a bit out of my area of competency here, eg I do not know exactly how the tolerance condition should be specified, but I suspect some of you here may be experts on this. Does anyone have some code compatible with the BSD license, preferably based on numpy but we would consider an extension code or scipy solution, for doing this?
The functionality we have in mind is provided in matlab with fplot
http://www.mathworks.com/access/helpdesk/help/techdoc/index.html?/access/hel...
We would like 1D and 2D versions of this ideally. If anyone has some suggestions, let me know.
Denis Bzowy has replied to me off list with some code adaptive spline approximation code he is working on. He has documentation and code for the 1D case, and is preparing for the 2D case, and is seeking feedback. He's having trouble posting to the list, and asked me to forward this, so please make sure his email, included in this post, is in any replies http://drop.io/denis_adaspline1