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Here is a simple ODE system (from some perturbation theory toy problem; the real problem is bigger):
```julia
using ModelingToolkit, DifferentialEquations
using ModelingToolkit: t_nounits as t, D_n…
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Maybe a short introduction in which you list what is necessary to understand the text would be good; it starts right off with differential equations and such, for example, and so it might be good to w…
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An analogue of [scipy.signal.convolve2d](https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.convolve2d.html) would be extremely useful to simulate the following classes of models for ex…
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To compare GPyOpt with other contributions in uncertainty quantification, do you have examples or tutorials for the following models: Lorenz63 (dim=3), Lorenz96(dim=9) and JAK-STAT as used by Campbell…
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See http://en.wikipedia.org/wiki/Cauchy_euler_ode . The ODE is of the form `a_n*x**n*f(x).diff(x, n) + … + a_1*x*f(x).diff(x) + a_0 = 0`. These can be solved in a general way, either by making the s…
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```py
def f(u, h, p, t):
du1 = 1.1/(1 + 3.16227*(h(p, t-20)[0])**(1.25)) - 10*u[0]/(1 + 40*u[1])
du2 = 100*u[0]/(1 + 40*u[1]) - 2.43*u[1]
return[du1,du2]
u0 = [1.05767027/3, 1.030713491/3…
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This question is out of a curiosity,
As the documentation says , `odesys = convert(ODESystem, repressilator)` will convert a reaction network called repressilator to a system of ODEs.
Is it possib…
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There are three major ways of calculating the time-dependent sensitivity of a system of differential equations:
- Automatic Differentiation
- Finite Differences
- Sensitivity Equations
Unlike FD or A…
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## 50 / 00 Intro to ODE
Certainly! Here are a few suggestions to enhance the text:
1. **Introduction**: Consider adding a brief introduction to differential equations, highlighting their importa…
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**Missing book link**
The section "Ordinary Differential Equations" has this description of the {rODE} package,
Package r pkg("rODE") (inspired **by** the book of Gould, Tobochnik and
…