Opened 11 years ago
Last modified 7 years ago
#9794 new enhancement
Make easy wrapper for symbolic lagrange interpolation
Reported by: | kcrisman | Owned by: | burcin |
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Priority: | major | Milestone: | sage-6.4 |
Component: | symbolics | Keywords: | |
Cc: | jason | Merged in: | |
Authors: | Reviewers: | ||
Report Upstream: | N/A | Work issues: | |
Branch: | Commit: | ||
Dependencies: | Stopgaps: |
Description
Currently, one has to do something like one of these.
> 1. There is no way to get a symbolic interpolated polynomial de novo > without going through polynomial rings, e.g. all these steps: > > pts = [(1,2),(2,3),(3,2),(4,3),(5,2),(6,3)] > R.<x>=QQ[] > f = R.lagrange_polynomial(pts) > SR(f) > Yes. You could define your own function :) (see http://sage.cs.drake.edu/home/pub/2/, for example). Also, mpmath and numpy/scipy can get numerical values for the coefficients, I believe. Maxima also can construct a lagrange polynomial (load the 'interpol' package) sage: maxima.load('interpol') "/home/jason/sage-4.4.2/local/share/maxima/5.20.1/share/numeric/interpol.ma c" sage: maxima.lagrange([[1,2],[3,4]]) -x+2*(x-1)+3
That's too bad; we need to wrap this to make it very easy to get the interpolation from a list of points with one command from SR.
One thing to discuss would be whether one would want an approximate one if the coefficients were floats/RR, or always to try for an exact one.
Change History (4)
comment:1 Changed 8 years ago by
- Milestone changed from sage-5.11 to sage-5.12
comment:2 Changed 7 years ago by
- Milestone changed from sage-6.1 to sage-6.2
comment:3 Changed 7 years ago by
- Milestone changed from sage-6.2 to sage-6.3
comment:4 Changed 7 years ago by
- Milestone changed from sage-6.3 to sage-6.4
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