ApproxFun package regression on 0.4 : sqrt and ^ doesn't work

[alsam]

Hello All,
There is a regression in 0.4 for
Julia package for function approximation
0.3:

   _       _ _(_)_     |  A fresh approach to technical computing
  (_)     | (_) (_)    |  Documentation: http://docs.julialang.org
   _ _   _| |_  __ _   |  Type "help()" for help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 0.3.11 (2015-07-27 06:18 UTC)
 _/ |\__'_|_|_|\__'_|  |  Official http://julialang.org/ release
|__/                   |  x86_64-unknown-linux-gnu

julia> using ApproxFun

julia> x= Fun(identity, [0,100])
Fun([50.0,50.0],Chebyshev(【0.0,100.0】))

julia> g = sqrt(x)
Fun([7.07107],(1+x)^0.5*(1-x)^0.0[Chebyshev(【0.0,100.0】)])

julia> g[2]
1.4142135623730958

ok but the same snippet for 0.4 produces

              _
   _       _ _(_)_     |  A fresh approach to technical computing
  (_)     | (_) (_)    |  Documentation: http://docs.julialang.org
   _ _   _| |_  __ _   |  Type "help()" for help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 0.4.0-dev+6402 (2015-07-30 09:54 UTC)
 _/ |\__'_|_|_|\__'_|  |  Commit a9b71c6* (0 days old master)
|__/                   |  x86_64-unknown-linux-gnu

julia> using ApproxFun

julia> x= Fun(identity, [0,100])
Fun([50.0,50.0],Chebyshev(【0.0,100.0】))

julia> g = sqrt(x)
ERROR: Override itransform(::ApproxFun.Ultraspherical{0},cfs,plan...)
 in error at ./error.jl:21
 in itransform at /home/asamoilo/.julia/v0.4/ApproxFun/src/Fun/FunctionSpace.jl:352
 in roots at /home/asamoilo/.julia/v0.4/ApproxFun/src/Extras/roots.jl:34
 in .^ at /home/asamoilo/.julia/v0.4/ApproxFun/src/Extras/specialfunctions.jl:177
 in sqrt at /home/asamoilo/.julia/v0.4/ApproxFun/src/Extras/specialfunctions.jl:209

Thanks!

[tkelman]

Please file this bug at the ApproxFun repository. The package maintainers there should be able to figure out their own code and determine whether they need to change something or if there's actually a bug in base Julia.

[tkelman]

And it seems to work fine if you do Pkg.checkout("ApproxFun"), so whatever the problem was they've fixed it on ApproxFun master but not yet tagged in METADATA. Generally if you expect packages to work in a stable way you should be using release Julia, not master.

[alsam]

Thanks a lot!

[yuyichao]

And I bet it's due to the recent DFT api change. JuliaApproximation/ApproxFun.jl#216