PyPlot and IJulia have been having trouble over the last few days. I think it's because PyCall tagged a new version that broke a few things. I actually haven't gotten PyPlot working since they tagged the new version (missing wPython or something?). Plotly should be bundled by default with Plots and should work out of the box with IJulia. But note that this is all up in the air for a little bit as plotting packages are changing wildly with the v0.5-rc updates. In something like a week these should all be compatible with each other again, at least that seems to be the plan for the release candidate.
Also, note that the first time you plot something on a backend, it has to initialize the backend so it's slower. That's a Plots.jl thing. The second plot should be pretty fast (PyPlot's a little low). DifferentialEquations.jl should be fine speed-wise, with the first time you use a function having some compilation time (since it's not pre-compiling all of the functions). This is a known issue that will be fixed once I can get SnoopCompile to generate a precompile hinting file. So right now the first runs have all the compilations and setup, but the next runs should be instant for most simple problems. Is that the case of is it just plain slow on IJulia? On Saturday, August 6, 2016 at 6:50:00 AM UTC-7, Henri Girard wrote: > > With console version 0.5 and pyplot works, in ijulia is terribly slow and > can't initialize backend pyplot() > > 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>. >> >
