fix dead sciml links

JuliaDynamics · Mar 27, 2024 · 600e01b · 600e01b
1 parent e6ccdba
commit 600e01b
Show file tree

Hide file tree

Showing 2 changed files with 3 additions and 3 deletions.
diff --git a/dev/RateSys1.jl b/dev/RateSys1.jl
@@ -138,7 +138,7 @@ end
     gauss(sys::RateSystem)
 Returns a Wiener process with dimension `length(sys.u)` and covariance matrix `sys.Σ`.
 
-This function is based on the [`CorrelatedWienerProcess`](https://noise.sciml.ai/stable/noise_processes/#DiffEqNoiseProcess.CorrelatedWienerProcess) of [`DiffEqNoiseProcess.jl`](https://noise.sciml.ai/stable/), a component of `DifferentialEquations.jl`. The initial condition of the process is set to the zero vector at `t=0`.
+This function is based on the [`CorrelatedWienerProcess`](https://docs.sciml.ai/DiffEqNoiseProcess/stable/noise_processes/#DiffEqNoiseProcess.CorrelatedWienerProcess) of [`DiffEqNoiseProcess.jl`](https://docs.sciml.ai/DiffEqNoiseProcess/stable/), a component of `DifferentialEquations.jl`. The initial condition of the process is set to the zero vector at `t=0`.
 """
 function gauss(sys::RateSystem)
     Σ₂ = zeros(sum(sys.td_inds),sum(sys.td_inds)); # the covariance matrix of the time-dependent parameters, fixed to zero for now

diff --git a/src/noiseprocesses/gaussian.jl b/src/noiseprocesses/gaussian.jl
@@ -5,7 +5,7 @@
     gauss(sys::StochSystem)
 Returns a Wiener process with dimension `length(sys.u)` and covariance matrix `sys.Σ`.
 
-This function is based on the [`CorrelatedWienerProcess`](https://noise.sciml.ai/stable/noise_processes/#DiffEqNoiseProcess.CorrelatedWienerProcess) of [`DiffEqNoiseProcess.jl`](https://noise.sciml.ai/stable/), a component of `DifferentialEquations.jl`. The initial condition of the process is set to the zero vector at `t=0`.
+This function is based on the [`CorrelatedWienerProcess`](https://docs.sciml.ai/DiffEqNoiseProcess/stable/noise_processes/#DiffEqNoiseProcess.CorrelatedWienerProcess) of [`DiffEqNoiseProcess.jl`](https://docs.sciml.ai/DiffEqNoiseProcess/stable/), a component of `DifferentialEquations.jl`. The initial condition of the process is set to the zero vector at `t=0`.
 """
 function gauss(sys::StochSystem)
     # Returns a Wiener process for given covariance matrix and dimension of a StochSystem
@@ -15,4 +15,4 @@ function gauss(sys::StochSystem)
         W = CorrelatedWienerProcess(sys.Σ, 0.0, zeros(length(sys.u)))
     end
     W
-end;
+end;