PyDSTool.jl

A wrapper for the Python PyDSTool library for the SciML Scientific Machine Learning organization
Author SciML
Popularity
7 Stars
Updated Last
1 Year Ago
Started In
October 2016

PyDSTool.jl

PyDSTool.jl is a wrapper for the PyDSTool Python library for analysis of dynamical systems. This wrapper includes three parts:

1. Installation and direct access to PyDSTool
2. A low-level development API and provides some functionality to make directly dealing with the library a little bit easier, but still requires knowledge of PyDSTool itself.
3. A high-level API for usage with DifferentialEquations

The tests show how to use the functionality. It is used as an addon in the DifferentialEquations.jl ecosystem. It is recommended that users use this functionality through DifferentialEquations.jl.

Bifurcation analysis is provided by the wrapper package PyDSTool.jl, which wraps the functionality of PyDSTool. The the package has an interface for directly using PyDSTool itself, included is a higher level interface that makes these tools compatible with more standard JuliaDiffEq types.

Installation

This functionality does not come standard with DifferentialEquations.jl. To use this functionality, you must install PyDSTool.jl:

```]add PyDSTool
using PyDSTool```

Calcium Bifurcation Tutorial

In this tutorial we will show how to do some simple bifurcation plots. We will follow the PyDSTool tutorial for the calcium channel model and re-create the results using the wrapped functionality.

Specification of a Model

We will specify the model using a ParameterizedFunction:

```using ParameterizedFunctions
f = @ode_def begin
dv = ( i + gl * (vl - v) - gca * 0.5 * (1 + tanh( (v-v1)/v2 )) * (v-vca) )/c
dw = v-w
end vl vca i gl gca c v1 v2```

(Note that using PyDSTool requires use of the `@ode_def` macro). Next to build the ODE we need an initial condition and a starting timepoint.

```u0 = [0;0]
tspan = [0;30]
p = [-60,120,0.0,2,4,20,-1.2,18]```

Then we use the following command to build the PyDSTool ODE:

`dsargs = build_ode(f,u0,tspan,p)`

Now we need to build the continuation type. Following the setup of PyDSTool's tutorial, we need to start near the steady state. The commands translate as:

```ode = ds[:Generator][:Vode_ODEsystem](dsargs)
ode[:set](pars = Dict("i"=>-220))
ode[:set](ics  = Dict("v"=>-170))
PC = ds[:ContClass](ode)```

Once we have the continuation type, we can call the `bifurcation_curve` function. Instead of building the args into some object one-by-one, we simply make a function call with keyword arguments. Using the same arguments as the PyDSTool tutorial:

```bif = bifurcation_curve(PC,"EP-C",["i"],
max_num_points=450,
max_stepsize=2,min_stepsize=1e-5,
stepsize=2e-2,loc_bif_points="all",
save_eigen=true,name="EQ1",
print_info=true,calc_stab=true)```

This returns a `BifurcationCurve` type. Important fields of this type are:

• `points`: the values along the curve
• `special_points`: the values for the bifurcation points
• `stab`: an array which gives the stability of each point along the curve. `"S"` is for stable, `N` is for neutral, and `U` is for unstable.

Instead of using the fields directly, we will use the plot recipe. The plot recipe requires you give the `x,y` coordinates to plot. Here we will plot it in the `(i,v)` plane:

```using Plots
plot(bif,(:i,:v))```

Bifucation Curve Function Definition

```function bifurcation_curve(PC,bif_type,freepars;max_num_points=450,
max_stepsize=2,min_stepsize=1e-5,
stepsize=2e-2,loc_bif_points="all",
save_eigen=true,name="DefaultName",
print_info=true,calc_stab=true,
var_tol = 1e-6, func_tol = 1e-6,
test_tol = 1e-4,
initpoint=nothing,solver_sequence=[:forward])```

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