Task is: find image/preimage, if you have n f-s, its interval(-s) (if
empty, then (-oo, +oo)) and user interval input.
Example:
2
x**4 - 16x - function
[14, 55) - func interval
2*x - 4
[0, 44]
1
[54, +oo) - user interval
I'm parsing input with regexp transforming input to sympy-understandable
The imageset function is our interface for this in the development version
>>> domain = Interval(0, sqrt(3))
>>> result = imageset(x, x**3 - 3*x, domain)
It doesn't guarantee to give you back a nice set though. It defaults to an
ImageSet object which can answer some questions like set membership
Hello,
I think that this problem is impossible to solve in general.
What are the functions you want to study ?
Christophe, a simple user
2013/10/30 Alexander Birukov
> Hello everyone.
>
> Was wondering how can I get an image of function if I have an interval for
> it (problem comes if I have
Hello everyone.
Was wondering how can I get an image of function if I have an interval for
it (problem comes if I have unioned intervals. I dont know how can I call
each interval start/end or at least split union into Nth intervals). SymPy
docs gives info about transform. but I've browsed sour
Yes, this is a defect.
I created in fact a Issue this week for it:
https://code.google.com/p/sympy/issues/detail?id=4079
On Wednesday, October 30, 2013 12:03:32 PM UTC+1, Harsh Gupta wrote:
>
> >>> from sympy.integrals import transforms
> >>> FT = fourier_transform
> >>> from sympy.abc import x,
On Oct 30, 2013, at 5:39 AM, Chris Smith wrote:
Yes, we would have to switch to conditions first.
But the issues of evaluation order would require an OrderedDict as you say.
I don't recall if we have that yet.
OrderedDict is in Python 2.7+. There's a recipe that can be added for 2.6.
I don't b
desmos, btw, also evaluates items in the order given from left to right.
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Yes, we would have to switch to conditions first.
But the issues of evaluation order would require an OrderedDict as you say.
I don't recall if we have that yet.
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>>> from sympy.integrals import transforms
>>> FT = fourier_transform
>>> from sympy.abc import x, k
>>> FT(1,x,k)
0
Sympy evaluates the fourier transform of 1 as 0 though it is dirac_delta(k).
Similarly sympy evaluates the fourier transform of powers of x as 0 as well.
http://mathworld.wolfram.c
