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TODO: 1. Modularize the code (break into the following classes and sort dependencies) * LSeries (Is already in there. Have to free it from the other 3 modules) * GammaFactor (Done and documented) * IncompleteGeneralizedGammaFactor (To be done) * InverseMellinGammaFactor (To be done) 2. Stuff still computed using gp: * Delta polynomials in _recursions_at_infinity (search for comment below) * _without_gp (gamma_series) has this line sinser = sage_eval(rs(gp_eval('Vec(sin(Pi*(%s)))'%(z0+x)))) * init_Ginf: still uses pari (see below) * Ginf: still uses pari to evaluate continued fraction 3. Doctest everything, making sure it all works 100% and fix issues with coercion, complex inputs, etc., as they are systematically uncovered. 4. Possibly maybe change from digits to bits prec. 5. Optimize. ----------------------------------------------------- |
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Dokchiter's Paper: attachment:dokchitser.pdf |
Dokchitser Project for Sage Days 11
TODO:
- Modularize the code (break into the following classes and sort dependencies)
- LSeries (Is already in there. Have to free it from the other 3 modules)
GammaFactor (Done and documented)
IncompleteGeneralizedGammaFactor (To be done)
InverseMellinGammaFactor (To be done)
- Stuff still computed using gp:
- Delta polynomials in _recursions_at_infinity (search for comment below)
- _without_gp (gamma_series) has this line
- sinser = sage_eval(rs(gp_eval('Vec(sin(Pi*(%s)))'%(z0+x))))
- init_Ginf: still uses pari (see below)
- Ginf: still uses pari to evaluate continued fraction
- Doctest everything, making sure it all works 100% and fix issues with coercion, complex inputs, etc., as they are systematically uncovered.
- Possibly maybe change from digits to bits prec.
- Optimize.
From Jen:
Here's the version (closest to Dokchitser's original pari code) that still uses continued fraction approximation:
http://sage.math.washington.edu/home/jen/sage-3.0.5-x86_64-Linux/l4.py
(needs gamma_series.py to run:
http://sage.math.washington.edu/home/jen/sage-3.0.5-x86_64-Linux/gamma_series.py)
The version with Pade approximation (l5.py) has a negligible speedup but only really works for low precision. I'm not sure if Pade gives us a means of computing bounds (I think Mike Rubinstein said that continued fractions won't). Also, l4.py doesn't work for imaginary inputs yet - some coercion with SymbolicRing that I didn't try.
Dokchiter's Paper: attachment:dokchitser.pdf