bugfix: frozen_system and docs update

Project.toml

@@ -2,7 +2,7 @@ name = "CriticalTransitions"
 uuid = "251e6cd3-3112-48a5-99dd-66efcfd18334"
 authors = ["Reyk Börner, Orjan Ameye, Ryan Deeley, Raphael Römer", "George Datseris"]
 repo = "https://github.com/juliadynamics/CriticalTransitions.jl.git"
-version = "0.7.0"
+version = "0.7.1"
 
 [deps]
 ConstructionBase = "187b0558-2788-49d3-abe0-74a17ed4e7c9"

README.md

@@ -12,6 +12,20 @@
 A Julia package for the numerical investigation of **noise- and rate-induced transitions in dynamical systems**.
 
 Building on [DynamicalSystems.jl](https://juliadynamics.github.io/DynamicalSystems.jl/stable/) and [DifferentialEquations.jl](https://diffeq.sciml.ai/stable/), this package aims to provide a toolbox for dynamical systems under time-dependent forcing, with a focus on tipping phenomena and metastability.
+
+## Installation
+`CriticalTransitions` is a registered Julia package.
+
+```console
+julia> ] add CriticalTransitions
+```
+
+or
+
+```julia
+using Pkg; Pkg.add("CriticalTransitions")
+```
+
 ## Usage
 See [package documentation](https://juliadynamics.github.io/CriticalTransitions.jl/stable/).
 

docs/pages.jl

@@ -4,12 +4,14 @@ pages = [
     "Getting started" => "quickstart.md",
     "Tutorial" => "examples/tutorial.md",
     "Examples" => Any[
-        "Defining stochastic systems" => "examples/stochastic-dynamics.md",
-        "Large deviations: Maier-Stein system" => "examples/gMAM_Maierstein.md",
-        "Simple gMAM: Kerr Parametric Oscillator" => "examples/sgMAM_KPO.md",
-        "Transition Path Theory: Finite element method" => "examples/transition_path_theory_double_well.md",
-        "Minimal action method: Optimal Control problem" => "examples/OC_mam.md",
-        "Constructing rate system" => "examples/RateSystem.md",
+        "Defining a system" => Any[
+            "Defining stochastic systems" => "examples/stochastic-dynamics.md",
+            "Constructing a rate system" => "examples/RateSystem.md",],
+        "System analysis" => Any[  
+            "Large deviations: Maier-Stein system" => "examples/gMAM_Maierstein.md",
+            "Simple gMAM: Kerr Parametric Oscillator" => "examples/sgMAM_KPO.md",
+            "Minimal action method: Optimal Control problem" => "examples/OC_mam.md",
+            "Transition path theory: Finite element method" => "examples/transition_path_theory_double_well.md",],
     ],
     "Manual" => Any[
         "Define your system" => "man/system_construction.md",

docs/src/quickstart.md

@@ -1,35 +1,41 @@
 # Getting started
 
 ## Installation
-To install the Julia language, we recommend [juliaup](https://github.com/JuliaLang/juliaup).
+> To install the Julia language, we recommend [juliaup](https://github.com/JuliaLang/juliaup).
+
+`CriticalTransitions` is a registered Julia package (as of `v0.7`) and can be installed with the Julia package manager:
+
+```console
+julia> ]
+Pkg>   add CriticalTransitions
+```
+or 
 
-The `CriticalTransitions.jl` package can be installed from Github via the Julia package manager:
 ```julia
-using Pkg; Pkg.add(url="https://github.com/juliadynamics/CriticalTransitions.jl.git")
+using Pkg; Pkg.add("CriticalTransitions")
 ```
-You can then load the package with `using CriticalTransitions`.
 
-The package is currently tested to be compatible with Julia versions `1.10` and `1.11`.
+The package is currently tested to be compatible with Julia versions `1.10-1.12`.
 
 ## Basic usage
-The general workflow of `CriticalTransitions.jl` essentially follows two steps, similar to `DynamicalSystems.jl`:
+The general workflow of CriticalTransitions.jl consists of two steps, similar to DynamicalSystems.jl:
 
 1. Define your dynamical system (see [Defining a forced dynamical system](@ref))
-2. Investigate the system by calling functions (see [Index](@ref))
+2. Investigate the system by calling methods (see [Index](@ref))
 
-Some functions are only loaded as extensions when loading other dependency packages (see [Extensions](@ref)).
+Some methods are only loaded as extensions when loading other dependency packages (see [Extensions](@ref)).
 
 ## Documentation
-The [Tutorial](@ref) and code examples in the *Examples* section illustrate some use cases of the package. All available functions and types are documented in the *Manual* section (see [Index](@ref) for an overview).
+The [Tutorial](@ref) and code examples in the *Examples* section illustrate some use cases of the package. All available methods and types are documented in the *Manual* section (see [Index](@ref) for an overview).
 
 ## Index
 A quick overview of available features:
 
 **Defining a system and its forcing**
 - [`DynamicalSystemsBase.CoupledODEs`](@ref)
 - [`DynamicalSystemsBase.CoupledSDEs`](@ref) (alias for `StochSystem`)
-- [`RateSystem`](@ref)
-- [`ForcingProfile`](@ref)
+- [`CriticalTransitions.RateSystem`](@ref)
+- [`CriticalTransitions.ForcingProfile`](@ref)
 
 **System analysis and simulation**
 ```@index

src/r_tipping/RateSystem.jl

@@ -192,7 +192,7 @@ corresponding to the frozen system of the non-autonomous [`RateSystem`](@ref) `r
 time `t`.
 """
 function frozen_system(rs::RateSystem, t)
-    ds = CoupledODEs(rs.forcing.unforced_rule, current_state(ds), get_forcing(rs, t))
+    ds = CoupledODEs(rs.forcing.unforced_rule, current_state(rs), parameters(rs, t))
     return ds
 end
 

test/Project.toml

@@ -26,7 +26,7 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
 Aqua = "0.8.7"
-Attractors = "1.19.12"
+Attractors = "1.27"
 ChaosTools = "3.2.1"
 DiffEqNoiseProcess = "5.24"
 ExplicitImports = "1.9"
@@ -38,4 +38,4 @@ OptimizationOptimisers = "0.3"
 OrdinaryDiffEq = "6.90"
 Statistics = ">=1.9"
 StochasticDiffEq = "6.71"
-julia = "1.10"
+julia = "1.10"

test/r_tipping/RateSystem.jl

@@ -34,6 +34,19 @@ fp = ForcingProfile(profile, (-5.0, 5.0))
 
 rs = RateSystem(ds, fp, pidx; forcing_start_time, forcing_duration, forcing_scale)
 
+@testset "frozen_system" begin
+    frozen = frozen_system(rs, rs.forcing.t0)
+    unforced = rs.forcing.unforced_rule
+    u = [2.0];
+    t = 10.0
+    du_frozen = dynamic_rule(frozen)(u, current_parameters(frozen), t)
+    du_orig = dynamic_rule(ds)(u, current_parameters(ds), t)
+    du_unforced = unforced(u, [rs.forcing.p0], t)
+
+    @test du_frozen == du_orig
+    @test du_frozen == du_unforced
+end
+
 @testset "RateSystem" begin
     @testset "DynamicalSystems API" begin
         @test current_state(rs) == x0