format

Author: ArnoStrouwen

docs/src/examples/modelingtoolkitize_index_reduction.md

@@ -115,7 +115,7 @@ But that's not a satisfying answer, so what do you do about it?
 
 It turns out that higher order DAEs can be transformed into lower order DAEs.
 [If you differentiate the last equation two times and perform a substitution,
-you can arrive at the following set of equations](https://people.math.wisc.edu/~chr/am205/g_act/DAE_slides.pdf):
+you can arrive at the following set of equations](https://people.math.wisc.edu/%7Echr/am205/g_act/DAE_slides.pdf):
 
 ```math
 \begin{aligned}

src/clock.jl

@@ -14,6 +14,7 @@ Symbolics.option_to_metadata_type(::Val{:timedomain}) = TimeDomain
 
 """
     is_continuous_domain(x)
+
 true if `x` contains only continuous-domain signals.
 See also [`has_continuous_domain`](@ref)
 """
@@ -33,6 +34,7 @@ get_time_domain(x::Num) = get_time_domain(value(x))
 
 """
     has_time_domain(x)
+
 Determine if variable `x` has a time-domain attributed to it.
 """
 function has_time_domain(x::Symbolic)

src/structural_transformation/pantelides.jl

@@ -76,18 +76,18 @@ Computes which variables are the "highest-differentiated" for purposes of
 pantelides. Ordinarily this is relatively straightforward. However, in our
 case, there are two complicating  conditions:
 
-  1. We allow variables in the structure graph that don't appear in the
-     system at all. What we are interested in is the highest-differentiated
-     variable that actually appears in the system.
+ 1. We allow variables in the structure graph that don't appear in the
+    system at all. What we are interested in is the highest-differentiated
+    variable that actually appears in the system.
 
-  2. We have an alias graph. The alias graph implicitly contributes an
-     alias equation, so it doesn't actually whitelist any additional variables,
-     but it may change which variable is considered the highest differentiated one.
-     Consider the following situation:
+ 2. We have an alias graph. The alias graph implicitly contributes an
+    alias equation, so it doesn't actually whitelist any additional variables,
+    but it may change which variable is considered the highest differentiated one.
+    Consider the following situation:
 
-       Vars: x, y
-       Eqs: 0 = f(x)
-       Alias: ẋ = ẏ
+    Vars: x, y
+    Eqs: 0 = f(x)
+    Alias: ẋ = ẏ
 
     In the absence of the alias, we would consider `x` to be the highest
     differentiated variable. However, because of the alias (and because there

src/systems/discrete_system/discrete_system.jl

@@ -302,9 +302,9 @@ end
 
 """
 ```julia
-SciMLBase.DiscreteFunction{iip}(sys::DiscreteSystem, dvs=states(sys),
-                                ps=parameters(sys);
-                                version=nothing,
+SciMLBase.DiscreteFunction{iip}(sys::DiscreteSystem, dvs = states(sys),
+                                ps = parameters(sys);
+                                version = nothing,
                                 kwargs...) where {iip}
 ```
 
@@ -370,10 +370,10 @@ end
 
 """
 ```julia
-    DiscreteFunctionExpr{iip}(sys::DiscreteSystem, dvs = states(sys),
-                                     ps = parameters(sys);
-                                     version = nothing,
-                                     kwargs...) where {iip}
+DiscreteFunctionExpr{iip}(sys::DiscreteSystem, dvs = states(sys),
+                          ps = parameters(sys);
+                          version = nothing,
+                          kwargs...) where {iip}
 ```
 
 Create a Julia expression for an `DiscreteFunction` from the [`DiscreteSystem`](@ref).