> Double check that
> import sympy
> sympy.__version__
> gives '1.0'.
Yes, this was the issue. Solved and thanks.
Peter
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> I'm not sure why this definition is made. It seems like a bad one,
> since there are two different ways to interpret rf(a, b) if a is a
> polynomial.
> For the other two, I get the same thing as the docstring in SymPy 1.0
> These seem mathematically correct.
Thank you very much.
I agree with yo
>
> We still haven't updated SymPy Live to SymPy 1.0, so the output of
> some examples may be different.
>
Thanks! Maybe I expressed myself misleading. Also the output in my
yupyter notebook did not correspond to what is in the documentation.
I have difficulty to understand the output of the
http://docs.sympy.org/latest/modules/functions/combinatorial.html#risingfactorial
I executed the examples in SymPy-Live but got different
outputs from what the docs say. For example for
>>> rf(x, k).rewrite(ff)
gives nothing instead of: FallingFactorial(k + x - 1, k)
>>> rf(x, k).rewrite(bino
>
> are consistent with the definitions from the previous link. For instance,
> I have the feeling that I don't understand l.g.f. (logarithmic generating
> function) exactly the same way as some contributors in the OEIS
>
The definitive guide for these definitions is Bruno Salvy's gefun packag
>> In fact they developed around the discussion of
>> Albert Rich's Rubi (RUle-Based Integration). It is worth to look this up:
>> http://www.apmaths.uwo.ca/~arich/
> if their claim to outperform Wolfram
> Mathematica is correct, that could become the strongest integrator ever.
It was one of the
AM> Yes, the fallback algorithm in SymPy, heurisch, is very slow. What's
AM> the longest time an integral took that still gave an answer from your
AM> tests?
Most of the time I used a time-out of one minute, so I cannot tell. But see
this comment by Waldek Hebisch:
https://groups.google.com/d/msg/
Two integration test suites
For some history of the two integration test suites see [1].
An implementation for SymPy can be found at github [2].
The results are listed at [3].
Running the test suites I found some examples which seem
to need special attention by the developers:
[161] Timofeev
i
Consider
(F1) sqrt(1+x^3)/x
(F2) sqrt(1+1/x^3)*sqrt(x)
According to Mathematica's online integrator
(I1) integral F1 dx = (2/3)*(sqrt(x^3+1)-arctanh(sqrt(x^3+1)))
(I2) integral F2 dx =
(2*sqrt(1/x^3+1)*x^(3/2)*(sqrt(x^3+1)-arctanh(sqrt(x^3+1/(3*sqrt(x^3+1))
SymPy Live computes (I1) as
(
> Are there improvements that can be made to SymPy's
> factorial or not?
It depends how you explain the difference between the behaviour
in Sage and SymPy.
If my speculation is right the basic product prod_i=0^n a[i]
is implemented suboptimal in SymPy. Otherwise this product
would (for large n) b
I looked today another time into the factorial function.
Unfortunately the observed gain only works with the Sage
implementation of 'prime_range' (which I used) but not
with the SymPy implementation.
First of all Sage's 'prime_range' returns a list whereas SymPy's
'primerange' is an iterator. T
Hi all,
looking yesterday at some SymPy code I observed that the
factorial function can be tuned by a simple in place
substitution of the function "swing".
timeit("sympy_factorial(100)", number=10)
timeit("factorialPS(100)", number=10)
10 loops, best of 3: 2.02 s per loop
10 loops, best
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