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Improve README documentation
- Update badges: Replace outdated Gitter badge with Zulip chat link and add CI status badge - Fix documentation links: Update JuliaDiffEq URLs to current SciML docs (docs.sciml.ai) - Remove outdated ParameterizedFunctions.jl requirement (package works with regular functions) - Add "Available Solvers" section documenting all 8 MATLAB solver bindings - Fix typos: "timeseries_error" -> "timeseries_errors", "overhead of over" -> "overhead of" - Add missing comma in option list 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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README.md

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# MATLABDiffEq.jl
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MATLABDiffEq.jl is a common interface binding for the [MATLAB](https://www.mathworks.com/products/matlab.html) ordinary differential equation solvers. It uses the [MATLAB.jl](https://github.com/JuliaInterop/MATLAB.jl) interop in order to
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send the differential equation over to MATLAB and solve it. Note that this
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package requires the differential equation function to be defined using
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[ParameterizedFunctions.jl](https://github.com/JuliaDiffEq/ParameterizedFunctions.jl).
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send the differential equation over to MATLAB and solve it.
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Note that this package isn't for production use and is mostly just for benchmarking
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and helping new users migrate models over to Julia.
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For more efficient solvers, see the
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[DifferentialEquations.jl documentation](https://github.com/JuliaDiffEq/DifferentialEquations.jl).
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[DifferentialEquations.jl documentation](https://docs.sciml.ai/DiffEqDocs/stable/).
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## Installation
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## Using MATLABDiffEq.jl
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MATLABDiffEq.jl is simply a solver on the DiffEq common interface, so for details see the [DifferentialEquations.jl documentation](https://juliadiffeq.github.io/DiffEqDocs.jl/dev/).
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MATLABDiffEq.jl is simply a solver on the DiffEq common interface, so for details see the [DifferentialEquations.jl documentation](https://docs.sciml.ai/DiffEqDocs/stable/).
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However, the only options implemented are those for error calculations
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(`timeseries_error`), `saveat` and tolerances.
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(`timeseries_errors`), `saveat`, and tolerances.
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Note that the algorithms are defined to have the same name as the MATLAB algorithms,
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but are not exported. Thus to use `ode45`, you would specify the algorithm as
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`MATLABDiffEq.ode45()`.
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### Available Solvers
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**Non-stiff solvers:**
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- `MATLABDiffEq.ode23()` - Low-order solver
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- `MATLABDiffEq.ode45()` - Medium-order solver (most commonly used)
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- `MATLABDiffEq.ode113()` - Variable-order Adams-Bashforth-Moulton solver
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**Stiff solvers:**
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- `MATLABDiffEq.ode15s()` - Variable-order BDF/NDF solver
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- `MATLABDiffEq.ode23s()` - Low-order Rosenbrock solver
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- `MATLABDiffEq.ode23t()` - Trapezoidal rule solver
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- `MATLABDiffEq.ode23tb()` - TR-BDF2 solver
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**DAE solver:**
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- `MATLABDiffEq.ode15i()` - For fully implicit differential equations
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## Example
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```julia
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## Measuring Overhead
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To measure the overhead of over the wrapper, note that the variables
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To measure the overhead of the wrapper, note that the variables
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from the session will be still stored in MATLAB after the computation
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is done. Thus you can simply call the same ODE function and time it
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directly. This is done by:

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