Bumping posts by adding tags

[ChrisRackauckas]

Upcoming API Changes in DifferentialEquations.jl

There have been a few looming API change proposals, and with JuliaCon 2017 coming up, I would like all of the API change proposals to be settled. We are asking for user input for what they feel about these changes. For more details, see our post on the latest ecosystem update. http://juliadiffeq.org/2017/04/07/features.html Unlike previous API changes (way back in pre-1.0 land), these changes are not “core” and are mostly user-focused to try and clear up what seem to be common issues new users…

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DifferentialEquations.jl 2.0 Release: Blog Post and Breaking Changes

Hello everyone, I am pleased to announce the release of DifferentialEquations.jl 2.0. The release notes are at the JuliaDiffEq blog: This post details breaking changes. These were some lasting issues in the API that have been gathered over the last year and all of these changes were made in the same release. We hope by getting all of these done now (and closing all of the API related issues!), we can have a much more stable ride post-2.0. Indeed, my main goal here was to make sure that the A…

got bumped by adding the diffeq tag.

Call for bikeshedding: Updated ParameterizedFunction Syntax

I know people like bikeshedding syntax . I am looking to update the syntax for the macros in DifferentialEquations.jl (ParameterizedFunctions.jl) for “easily defining diffeqs”. I am looking for a syntax that can capture a lot of different types of diffeqs, looks natural (i.e. looks like a math or science paper), but also must be easy to parse. I opened an issue here to write down what my proposal is and start working it into something that’s doable (I’m not sure the current proposa…

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ODE.jl not efficient for Monte Carlo problem?

My code solves the Monte Carlo problem of a large ensemble of particles interacting with field. I use the Newton’s Equations to evolve the system. Numerically, ordinary equation is needed. Some pieces of my code are as follows: function Eq1(t, y) (x, y, px, py) = y r = sqrt( x^2 + y^2 + s1 ) x_prime = px y_prime = py px_prime = -2x/r^3 py_prime = -2y/r^3 [x_prime; y_prime; px_prime; py_prime] end function Init2() x = Array(Float64, ne) y = similar(x) …

are two of many that did not get bumped