chore: format

Author: Sathvik Bhagavan

README.md

@@ -4,7 +4,7 @@
 [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://SciML.github.io/UDEComponents.jl/dev/)
 [![Build Status](https://github.com/SciML/UDEComponents.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/SciML/UDEComponents.jl/actions/workflows/CI.yml?query=branch%3Amain)
 [![Coverage](https://codecov.io/gh/SciML/UDEComponents.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/SciML/UDEComponents.jl)
-[![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://github.com/SciML/ColPrac)
+[![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor%27s%20Guide-blueviolet)](https://github.com/SciML/ColPrac)
 [![Aqua](https://raw.githubusercontent.com/JuliaTesting/Aqua.jl/master/badge.svg)](https://github.com/JuliaTesting/Aqua.jl)
 
 ## Build UDEs with ModelingToolkit

src/UDEComponents.jl

@@ -22,7 +22,7 @@ Create an `ODESystem` with a neural network inside.
 function NeuralNetworkBlock(n_input = 1,
         n_output = 1;
         chain = multi_layer_feed_forward(n_input, n_output),
-        rng = Xoshiro(0), eltype=Float64)
+        rng = Xoshiro(0), eltype = Float64)
     lux_p = Lux.initialparameters(rng, chain)
     ca = ComponentArray{eltype}(lux_p)
 

test/lotka_volterra.jl

@@ -14,7 +14,7 @@ using StableRNGs
 
 function lotka_ude()
     @variables t x(t)=3.1 y(t)=1.5
-    @parameters α=1.3 [tunable=false] δ=1.8 [tunable=false]
+    @parameters α=1.3 [tunable = false] δ=1.8 [tunable = false]
     Dt = ModelingToolkit.D_nounits
     @named nn_in = RealInput(nin = 2)
     @named nn_out = RealOutput(nout = 2)
@@ -115,7 +115,7 @@ res = solve(op, Adam(), maxiters = 5000)#, callback = plot_cb)
 
 res_p = SciMLStructures.replace(Tunable(), prob.p, res)
 res_prob = remake(prob, p = res_p)
-res_sol = solve(res_prob, Rodas4(), saveat=sol_ref.t)
+res_sol = solve(res_prob, Rodas4(), saveat = sol_ref.t)
 
 # using Plots
 # plot(sol_ref, idxs = [model_true.x, model_true.y])