I compiled version 0.5 julia git :
Here is the result
julia> using DifferentialEquations
INFO: Precompiling module DifferentialEquations...
WARNING: Method definition cgrad(Any, Any) in module PlotUtils at
/home/pi/.julia/v0.5/PlotUtils/src/color_gradients.jl:82 overwritten at
/home/pi/.julia/v0.5/PlotUtils/src/color_gradients.jl:99.
WARNING: Method definition #cgrad(Array{Any, 1}, PlotUtils.#cgrad, Any,
Any) in module PlotUtils overwritten.
julia> using DifferentialEquations
julia> alpha = 0.5 #Setting alpha to 1/2
0.5
julia> f(y,t) = alpha*y
f (generic function with 1 method)
julia> u0 = 1.5
1.5
julia> prob = ODEProblem(f,u0)
DifferentialEquations.ODEProblem(f,1.5,DifferentialEquations.#232,false,1,(1,),false)
julia> timespan = [0,1]
2-element Array{Int64,1}:
0
1
julia> sol = solve(prob,timespan)
ERROR: MethodError: objects of type Float64 are not callable
in ode_determine_initΔt(::Float64, ::Float64, ::Rational{Int64},
::Rational{Int64}, ::Int64, ::#f, ::Int64) at
/home/pi/.julia/v0.5/DifferentialEquations/src/ode/ode_solve.jl:308
in #solve#453(::Array{Any,1}, ::Function,
::DifferentialEquations.ODEProblem, ::Array{Int64,1}) at
/home/pi/.julia/v0.5/DifferentialEquations/src/ode/ode_solve.jl:131
in solve(::DifferentialEquations.ODEProblem, ::Array{Int64,1}) at
/home/pi/.julia/v0.5/DifferentialEquations/src/ode/ode_solve.jl:81
julia> plot(sol)
ERROR: UndefVarError: sol not defined
Le lundi 1 août 2016 16:37:09 UTC+2, Chris Rackauckas a écrit :
>
> I am pleased to announce the first release of DifferentialEquations.jl
> <https://github.com/ChrisRackauckas/DifferentialEquations.jl>.
>
> An accompanying blog post explains the motivation and philosophy of the
> package in more detail.
> <http://www.stochasticlifestyle.com/introducing-differentialequations-jl/>
>
> DifferentialEquations.jl is a library of methods for solving various
> differential equations. DifferentialEquations.jl makes it easy to access
> many different methods for solving equations and plot the results. This
> v0.1 release marks that the core of DifferentialEquations.jl is complete,
> which includes:
>
>
> - The standard ODE, SDE, and PDE (Heat and Poisson) solvers
>
> <http://chrisrackauckas.github.io/DifferentialEquations.jl/latest/#implemented-solvers>
> .
> - Plot recipes for all the basic types.
> - Tests for convergence of every algorithm.
> - Extensive documentation
> <http://chrisrackauckas.github.io/DifferentialEquations.jl/latest/>and
> tutorials
>
> <https://github.com/ChrisRackauckas/DifferentialEquations.jl/tree/master/examples>
> .
>
> DifferentialEquations.jl also has many special features not seen in other
> differential equation libraries, which includes (but is not limited to):
>
>
> - A simple interface via multiple-dispatch (see the blog post
> <http://www.stochasticlifestyle.com/introducing-differentialequations-jl/>
> ).
> - Implementations of Feagin's Order 10, 12, and 14 Runge-Kutta methods
>
> <https://github.com/ChrisRackauckas/DifferentialEquations.jl/blob/master/examples/Feagin's%20Order%2010%2C%2012%2C%20and%2014%20methods.ipynb>
> .
> - Compatibility with Julia-defined number types
>
> <https://github.com/ChrisRackauckas/DifferentialEquations.jl/blob/master/examples/Solving%20Equations%20in%20With%20Julia-Defined%20Types.ipynb>.
> This
> has been tested to work with Bigs, DecFP, and ArbFloats, and is actively
> being tested with ArbReals and DoubleDouble.
> - Wrappers to ODE.jl and ODEInterface.jl
>
> <https://github.com/ChrisRackauckas/DifferentialEquations.jl/blob/master/examples/Calling%20External%20Solvers%20-%20ODEjl%20and%20ODEInterface.ipynb>,
>
> giving you instant access to tons of different solver methods just by
> changing the `alg` keyword.
> - State-of-the-art stochastic differential equation solvers
>
> <http://chrisrackauckas.github.io/DifferentialEquations.jl/latest/solvers/sde_solve/>.
> Implemented
> are results from recent papers, and many other algorithms (including fast
> adaptivity and highly-stable explicit methods) are waiting on a private
> branch until papers are published.
> - Finite element solvers for some common stochastic PDEs
>
> <http://chrisrackauckas.github.io/DifferentialEquations.jl/latest/tutorials/femstochastic_example/>
> including
> the Reaction-Diffusion equation used to describe Turing Morphogenesis
>
> <https://github.com/ChrisRackauckas/DifferentialEquations.jl/blob/master/examples/Solving%20the%20Gierer-Meinhardt%20Equations.ipynb>
> .
> - An algorithm design and testing suite
>
> <http://chrisrackauckas.github.io/DifferentialEquations.jl/latest/man/convergence/>
> .
>
> For more information, check out the documentation
> <http://chrisrackauckas.github.io/DifferentialEquations.jl/latest/>or the
> IJulia
> tutorial notebooks
> <https://github.com/ChrisRackauckas/DifferentialEquations.jl/tree/master/examples>.
> If
> you're interested in contributing, please see the Contributor's Guide
> <http://chrisrackauckas.github.io/DifferentialEquations.jl/latest/internals/contributors_guide/>
>
> and/or chat with me on the Gitter channel
> <https://gitter.im/ChrisRackauckas/DifferentialEquations.jl>.
>
