Comment #9 on issue 1598 by ondrej.certik: New polynomials manipulation
module
http://code.google.com/p/sympy/issues/detail?id=1598
ok, first expand=False only speeds things up a bit for me (from 3.16s to
2.84s),
however, this:
$ SYMPY_GROUND_TYPES=gmpy bin/isympy
Python 2.6.2 console for SymPy 0.7.0-git
These commands were executed:
>>> from __future__ import division
>>> from sympy import *
>>> x, y, z = symbols('xyz')
>>> k, m, n = symbols('kmn', integer=True)
>>> f, g, h = map(Function, 'fgh')
Documentation can be found at http://sympy.org/
In [1]: a = (x+y+sin(z))**20
In [2]: b = a.expand()
In [3]: %time c = factor(b, expand=False)
CPU times: user 0.44 s, sys: 0.00 s, total: 0.44 s
Wall time: 0.45 s
makes it faster than sage!
sage: var("x y z")
(x, y, z)
sage: a = (x+y+sin(z))**20
sage: b = a.expand()
sage: %time c = factor(b)
CPU times: user 0.15 s, sys: 0.01 s, total: 0.16 s
Wall time: 0.59 s
but that's because sage is using maxima if there is sin(x) in the
expression. So
that's really awesome.
So let's rather compare this:
$ SYMPY_GROUND_TYPES=gmpy bin/isympy
Python 2.6.2 console for SymPy 0.7.0-git
These commands were executed:
>>> from __future__ import division
>>> from sympy import *
>>> x, y, z = symbols('xyz')
>>> k, m, n = symbols('kmn', integer=True)
>>> f, g, h = map(Function, 'fgh')
Documentation can be found at http://sympy.org/
In [1]: a = (x+y+z)**20
In [2]: b = a.expand()
In [3]: %time c = factor(b, expand=False)
CPU times: user 0.40 s, sys: 0.00 s, total: 0.40 s
Wall time: 0.40 s
to this:
sage: var("x y z")
(x, y, z)
sage: a = (x+y+z)**20
sage: b = a.expand()
sage: %time c = factor(b)
CPU times: user 0.14 s, sys: 0.00 s, total: 0.15 s
Wall time: 0.15 s
E.g. Sage (pari) is only about 2.6x faster. My lecture is on Thursday at
4pm, so if
you can make it 3x faster with gmpy + Cython, then we can beat Sage.
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