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StaticArrays.jl is great, but not useful for large arrays that are associated with high-dimensional systems, Maybe one could use StaticArrays only for low dimensional systems (say up to 10 variables) …
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Running lyapunovs.jl at:
```
using DynamicalSystems
lor = Systems.lorenz(ρ = 32.0) #this is not the original parameter!
issubtype(typeof(ds), ContinuousDynamicalSystem) # true
λλ = lyapunovs(…
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Just trying to run the nlts example for continuous time. The command:
using DynamicalSystems, PyPlot
ds = Systems.lorenz() # Max lyapunov is around 0.90
dt = 0.05
x = timeseries(ds, 1000.0; dt…
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The Smaller and Generalized Alignment Indices methods are robust techniques that can distinguish chaotic behavior from regular, or stable periodic orbits from unstable ones, efficiently.
These effi…
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Reading how [`ContinuousDS(prob::ODEProblem)` w/o Jacobian](https://github.com/JuliaDynamics/DynamicalSystemsBase.jl/blob/6a2698981f621b28ba4be0fe4aa4fa08e669ceb5/src/continuous.jl#L110):
```julia
#…
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Currently has the readme but not the license. Need to investigate.
For reference, here are the current contents of the `v0.4.0-beta` tarball:
```
nengolib-0.4.0b0/
nengolib-0.4.0b0/nengolib/
…
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There are two ways to create an e.g. `ContinuousDS`. One is to use closures, like it is done for almost all systems:
```julia
function roessler(u0=rand(3); a = 0.2, b = 0.2, c = 5.7)
@inline …
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Lyapunov analysis is not a part of ode solver/
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I tried the Lorenz example:
```
using DynamicalSystems, StaticArrays
ds = Systems.lorenz()
lyapunovs(ds,10^4;dt=1.0, Ttr=10.0)
3-element Array{Float64,1}:
0.922575
-1.25806
-13.3176
``…
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Related to #84 and #356, but open a separate issue.
The claim in the [docstring](https://github.com/QuantEcon/QuantEcon.py/blob/9ff0b7e9200aa8b83bd14fe86c7f227ecf2a9c8d/quantecon/matrix_eqn.py#L109…