Format

Author: hersle

docs/src/basics/FAQ.md

@@ -197,13 +197,13 @@ eqs = [x1 + x2 + 1 ~ 0
        2 * D(D(x1)) + D(D(x2)) + D(D(x3)) + D(x4) + 4 ~ 0]
 @named sys = ODESystem(eqs, t)
 sys = structural_simplify(sys)
-prob = ODEProblem(sys, [], (0,1))
+prob = ODEProblem(sys, [], (0, 1))
 ```
 
 We can solve this problem by using the `missing_variable_defaults()` function
 
 ```julia
-prob = ODEProblem(sys, ModelingToolkit.missing_variable_defaults(sys), (0,1))
+prob = ODEProblem(sys, ModelingToolkit.missing_variable_defaults(sys), (0, 1))
 ```
 
 This function provides 0 for the default values, which is a safe assumption for dummy derivatives of most models.  However, the 2nd argument allows for a different default value or values to be used if needed.
@@ -225,10 +225,10 @@ container type. For example:
 using ModelingToolkit, StaticArrays
 using ModelingToolkit: t_nounits as t, D_nounits as D
 
-sts = @variables x1(t)=0.0
+sts = @variables x1(t) = 0.0
 eqs = [D(x1) ~ 1.1 * x1]
 @mtkbuild sys = ODESystem(eqs, t)
-prob = ODEProblem{false}(sys, [], (0,1); u0_constructor = x->SVector(x...))
+prob = ODEProblem{false}(sys, [], (0, 1); u0_constructor = x->SVector(x...))
 ```
 
 ## Using a custom independent variable