Re: [julia-users] ANN: ApproxFun v0.05 with support for piecewise and singular functions

[Stefan Karpinski]

Do we have a video somewhere of one of your talks about ApproxFun? This is
a really impressive package.

On Tue, Dec 30, 2014 at 10:54 PM, Sheehan Olver 
wrote:

>
> ApproxFun is a package for approximating functions and solving
> differential equations.  ApproxFun v0.05 adds support for piecewise and
> singular functions.  For example, we can sample a function with semicircle
> or other Jacobi singularities:
>
> x=Fun(identity,[-1,1])
> sample(exp(x)*sqrt(1-x^2),100)
> sample((1-x)^0.123/(1+x)^0.567,100)
>
>
> Or integrate the absolute value of sin:
>
> x=Fun(identity,[-5,5])
> sum(abs(sin(x)))
>
>
> Or even solve PDEs with discontinuous coefficients.  Other improvements
> include 2-5x faster ODE solving, so that now an ODE requiring a million
> unknowns can be solved in one second, and preliminary support for high
> precision functions.
>
> Thanks go to Gustavo Goretkin (MIT) and Mikael Slevinsky (Oxford) for many
> contributions!
>
> Note: Julia v0.4 is not supported due to issue #9378
>

[julia-users] ANN: ApproxFun v0.05 with support for piecewise and singular functions

[Sheehan Olver]

ApproxFun is a package for approximating functions and solving differential 
equations.  ApproxFun v0.05 adds support for piecewise and singular 
functions.  For example, we can sample a function with semicircle or other 
Jacobi singularities:

x=Fun(identity,[-1,1])
sample(exp(x)*sqrt(1-x^2),100)
sample((1-x)^0.123/(1+x)^0.567,100)


Or integrate the absolute value of sin:

x=Fun(identity,[-5,5])
sum(abs(sin(x)))


Or even solve PDEs with discontinuous coefficients.  Other improvements 
include 2-5x faster ODE solving, so that now an ODE requiring a million 
unknowns can be solved in one second, and preliminary support for high 
precision functions.  

Thanks go to Gustavo Goretkin (MIT) and Mikael Slevinsky (Oxford) for many 
contributions!

Note: Julia v0.4 is not supported due to issue #9378