Comment #1 on issue 3545 by asmeu...@gmail.com: solving a complicated
expression with square roots
http://code.google.com/p/sympy/issues/detail?id=3545
So the issue here is
1. Can we get solve() to return something simpler?
2. solve() just hangs unless you call it with simplify=False and
Comment #2 on issue 3545 by asmeu...@gmail.com: solving a complicated
expression with square roots
http://code.google.com/p/sympy/issues/detail?id=3545
I missed the last part of the pastebin:
The reflection of f over g is then given in parameterized form as
x(m) = q
y(m) =
Status: Valid
Owner:
Labels: Type-Defect Priority-Medium
New issue 3546 by smi...@gmail.com: 0*x
http://code.google.com/p/sympy/issues/detail?id=3546
0*x
0
0*oo
nan
The x and all factors for which is_finite is not True should be retained in
a product so that a proper determination
Comment #1 on issue 3546 by asmeu...@gmail.com: 0*x
http://code.google.com/p/sympy/issues/detail?id=3546
I think this was discussed before. If 0*x remained unevaluated, then
nothing would work like you want it to. x - x would not go to 0. Try
making the change in the core and seeing how
Status: Valid
Owner:
Labels: Type-Defect Priority-Medium
New issue 3547 by smi...@gmail.com: Undefined functions with number
arguments should have is_number be False
http://code.google.com/p/sympy/issues/detail?id=3547
Function('f')(1).is_number
True
Perhaps it would be better to
What about this?
class Syms(object):
Return an Indexed object with name given at instantiation.
Indexing can be done using matrix or function notation.
Examples
from sympy.future import Syms
a=Syms('a')
a[1]
a[1]
a(1)
a[1]
a(i,k)
On Sun, Dec 2, 2012 at 9:46 AM, Chris Smith smi...@gmail.com wrote:
I don't follow you...if the function or Indexed has a different name then
it's different from others, and if the argument(s) of any function or
Indexed are different they represent different objects.
On Sat, Dec 1, 2012 at 5:07 PM, Chris Smith smi...@gmail.com wrote:
eqs=Tuple(*[A(0) + 5*A(1) - 2, -3*A(0) + 6*A(1) - 15])
solve(eqs, eqs.atoms(Function))
{A(0): -3, A(1): 1}
On Sun, Dec 2, 2012 at 6:59 AM, Chris Smith smi...@gmail.com wrote:
eqs=Tuple(*([A[0] + 5*A[1] - 2, -3*A[0]+ 6*A[1] -
Sorry for the extra mail!
On Sun, Dec 2, 2012 at 10:04 PM, Shriramana Sharma samj...@gmail.com wrote:
Hi can you clarify why you have used a * inside the Tuple constructor
in both the above cases and why the additional () around the []
containing the list in the second case? The Tuple
On 02/12/12 16:07, Stefan Krastanov wrote:
I do not think that the sympy's lambdify function is a good fit here.
It is mainly used for translating sympy expressions to something
faster but not as precise (python math or numpy). It is strange to use
it to translate something from sympy back to
I'm trying to plot a statistical expression using the following code
from sympy.stats import *
X = StudentT(X, 50)
t = Symbol('t', positive=True)
plot(simplify(E(exp(I*t*X))), (t, 1e-6, 1e-2))
and I get this error
-- 455 elif p[1] is None or q[1] is None or not flat(p,
presumably just surrounding your expression with re() should do the job.
The error seems to be a bug in the adaptive sampling so switching off
(with a kwarg) should solve the problem.
Concerning the complex numbers, originally whenever a complex number
was encountered we plotted only the real
Just confirmed: the error is within the adaptive sampling routine:
plot(re(E(exp(I*t*X))), (t, 1e-6, 1e-2), adaptive=False) results in
the attached file
On 2 December 2012 19:15, Stefan Krastanov krastanov.ste...@gmail.com wrote:
presumably just surrounding your expression with re() should do
Awesome.
How about for very small numbers?
plot(re(simplify(E(exp(I*t*X, (t, 1e-30, 1e-26))
On Sun, Dec 2, 2012 at 12:29 PM, Stefan Krastanov
krastanov.ste...@gmail.com wrote:
Just confirmed: the error is within the adaptive sampling routine:
plot(re(E(exp(I*t*X))), (t, 1e-6, 1e-2),
On Dec 2, 2012, at 10:21 AM, Freddie Witherden fred...@witherden.org wrote:
On 02/12/12 16:07, Stefan Krastanov wrote:
I do not think that the sympy's lambdify function is a good fit here.
It is mainly used for translating sympy expressions to something
faster but not as precise (python math
Of you have a tuple literal, it's redundant. Tuple(*(1,2)) is the same
as Tuple(1,2). But if you have a variable, you have to use Tuple(*a).
Aaron Meurer
On Dec 2, 2012, at 9:34 AM, Shriramana Sharma samj...@gmail.com wrote:
On Sat, Dec 1, 2012 at 5:07 PM, Chris Smith smi...@gmail.com wrote:
On Dec 2, 2012, at 12:37 PM, Stefan Krastanov
krastanov.ste...@gmail.com wrote:
The plotting module uses numpy floats so it will fail on very small
number or on small intervals.
Even worse, the main plotting backend, namely matplotlib, also uses
machine precision, so even if we do the
I found out from the Python documentation that * unpacks lists, but my
question about the extra () in the second example still stands...
It unpacks tuples, too.
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Great.
I first had to install setuptools, but then this worked fine. (At least
on Linux. I haven't tried Windows or Mac.)
I was going to put in a change to the doc, but I see someone has already
beaten me to it -- thanks.
Just so I am clear on the concept -
After doing this you can just
On Sun, Dec 2, 2012 at 5:47 PM, Rathmann pkrathma...@gmail.com wrote:
Great.
I first had to install setuptools, but then this worked fine. (At least on
Linux. I haven't tried Windows or Mac.)
I was going to put in a change to the doc, but I see someone has already
beaten me to it --
Hello. I have the following equations (all equal to zero) which I am
able to solve using SymPy for the Ep,De and La subscripted variables
after supplying the DeltaP() DeltaQ() and mu values:
2*Ep(0)/7 + Ep(1)/7 + 2*Ep(2)/35 + Ep(3)/70 - La(3)
Ep(0)/7 + 6*Ep(1)/35 + 9*Ep(2)/70 + 2*Ep(3)/35 +
I don't think there is a way to get back the matrices for the input
equations, but I think the following will give you what you want. It can be
streamlined, but you can see the steps below:
eqs=Tuple(*eqs)
eqs.atoms(Function)
set([La(3), Ep(0), DeltaQ(1, 0), DeltaQ(0, 0), Ep(2), Ep(3), De(2),
If you could take a moment to look over
https://github.com/sympy/sympy/pull/1682 you can solve for indexed
quantities without having to do the dummy substitution yourself.
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