Remove unnecessary capitalization

Fixes #100.

Author: HarrisonGrodin

README.md

@@ -28,9 +28,9 @@ and parameters. Therefore we label them as follows:
 using ModelingToolkit
 
 # Define some variables
-@Param t σ ρ β
-@Variable x(t) y(t) z(t)
-@Deriv D'~t
+@param t σ ρ β
+@variable x(t) y(t) z(t)
+@deriv D'~t
 ```
 
 Then we build the system:
@@ -81,8 +81,8 @@ state of the previous ODE. This is the nonlinear system defined by where the
 derivatives are zero. We use (unknown) variables for our nonlinear system.
 
 ```julia
-@Variable x y z
-@Param σ ρ β
+@variable x y z
+@param σ ρ β
 
 # Define a nonlinear system
 eqs = [0 ~ σ*(y-x),
@@ -223,7 +223,7 @@ function via the dispatch:
 
 ```julia
 # `N` arguments are accepted by the relevant method of `my_function`
-ModelingToolkit.Derivative(::typeof(my_function), args::NTuple{N,Any}, ::Val{i})
+ModelingToolkit.derivative(::typeof(my_function), args::NTuple{N,Any}, ::Val{i})
 ```
 
 where `i` means that it's the derivative of the `i`th argument. `args` is the
@@ -233,7 +233,7 @@ You should return an `Operation` for the derivative of your function.
 For example, `sin(t)`'s derivative (by `t`) is given by the following:
 
 ```julia
-ModelingToolkit.Derivative(::typeof(sin), args::NTuple{1,Any}, ::Val{1}) = cos(args[1])
+ModelingToolkit.derivative(::typeof(sin), args::NTuple{1,Any}, ::Val{1}) = cos(args[1])
 ```
 
 ### Macro-free Usage
@@ -243,9 +243,9 @@ is accessible via a function-based interface. This means that all macros are
 syntactic sugar in some form. For example, the variable construction:
 
 ```julia
-@Param t σ ρ β
-@Variable x(t) y(t) z(t)
-@Deriv D'~t
+@param t σ ρ β
+@variable x(t) y(t) z(t)
+@deriv D'~t
 ```
 
 is syntactic sugar for:
@@ -266,8 +266,8 @@ D = Differential(t)
 The system building functions can handle intermediate calculations. For example,
 
 ```julia
-@Variable x y z
-@Param σ ρ β
+@variable x y z
+@param σ ρ β
 a = y - x
 eqs = [0 ~ σ*a,
        0 ~ x*(ρ-z)-y,

src/differentials.jl

@@ -21,21 +21,21 @@ function expand_derivatives(O::Operation)
         D = O.op
         o = O.args[1]
         isa(o, Operation) || return O
-        return simplify_constants(sum(i->Derivative(o,i)*expand_derivatives(D(o.args[i])),1:length(o.args)))
+        return simplify_constants(sum(i->derivative(o,i)*expand_derivatives(D(o.args[i])),1:length(o.args)))
     end
 
     return O
 end
 expand_derivatives(x) = x
 
 # Don't specialize on the function here
-Derivative(O::Operation, idx) = Derivative(O.op, (O.args...,), Val(idx))
+derivative(O::Operation, idx) = derivative(O.op, (O.args...,), Val(idx))
 
 # Pre-defined derivatives
 import DiffRules, SpecialFunctions, NaNMath
 for (modu, fun, arity) ∈ DiffRules.diffrules()
     for i ∈ 1:arity
-        @eval function Derivative(::typeof($modu.$fun), args::NTuple{$arity,Any}, ::Val{$i})
+        @eval function derivative(::typeof($modu.$fun), args::NTuple{$arity,Any}, ::Val{$i})
             M, f = $(modu, fun)
             partials = DiffRules.diffrule(M, f, args...)
             dx = @static $arity == 1 ? partials : partials[$i]
@@ -60,7 +60,7 @@ function _differential_macro(x)
     lhss = Symbol[]
     x = flatten_expr!(x)
     for di in x
-        @assert di isa Expr && di.args[1] == :~ "@Deriv expects a form that looks like `@Deriv D''~t E'~t`"
+        @assert di isa Expr && di.args[1] == :~ "@deriv expects a form that looks like `@deriv D''~t E'~t`"
         lhs = di.args[2]
         rhs = di.args[3]
         order, lhs = count_order(lhs)
@@ -72,12 +72,12 @@ function _differential_macro(x)
     ex
 end
 
-macro Deriv(x...)
+macro deriv(x...)
     esc(_differential_macro(x))
 end
 
 function calculate_jacobian(eqs,vars)
     Expression[Differential(vars[j])(eqs[i]) for i in 1:length(eqs), j in 1:length(vars)]
 end
 
-export Differential, expand_derivatives, @Deriv, calculate_jacobian
+export Differential, expand_derivatives, @deriv, calculate_jacobian

src/systems/diffeqs/first_order_transform.jl

@@ -1,7 +1,7 @@
 function lower_varname(var::Variable, idv, order)
     order == 0 && return var
     name = Symbol(var.name, :_, string(idv.name)^order)
-    return Variable(name, var.known, var.dependents)
+    return Variable(name, var.dependents; known = var.known)
 end
 
 function ode_order_lowering(sys::DiffEqSystem)

src/variables.jl

@@ -1,4 +1,4 @@
-export Variable, @Variable, @Param
+export Variable, @variable, @param
 
 
 struct Variable <: Expression
@@ -70,9 +70,9 @@ function _parse_vars(macroname, known, x)
     push!(ex.args, build_expr(:tuple, var_names))
     return ex
 end
-macro Variable(xs...)
+macro variable(xs...)
     esc(_parse_vars(:Variable, false, xs))
 end
-macro Param(xs...)
+macro param(xs...)
     esc(_parse_vars(:Param, true, xs))
 end

test/derivatives.jl

@@ -2,9 +2,9 @@ using ModelingToolkit
 using Test
 
 # Derivatives
-@Param t σ ρ β
-@Variable x(t) y(t) z(t)
-@Deriv D'~t D2''~t
+@param t σ ρ β
+@variable x(t) y(t) z(t)
+@deriv D'~t D2''~t
 
 @test isequal(expand_derivatives(D(t)), 1)
 @test isequal(expand_derivatives(D(D(t))), 0)
@@ -47,7 +47,7 @@ jac = calculate_jacobian(sys)
 @test isequal(jac[3,3], -1*β)
 
 # Variable dependence checking in differentiation
-@Variable a(t) b(a)
+@variable a(t) b(a)
 @test !isequal(D(b), 0)
 
 @test isequal(expand_derivatives(D(x * y)), simplify_constants(y*D(x) + x*D(y)))

test/simplify.jl

@@ -1,8 +1,8 @@
 using ModelingToolkit
 using Test
 
-@Param t
-@Variable x(t) y(t) z(t)
+@param t
+@variable x(t) y(t) z(t)
 
 null_op = 0*t
 @test isequal(simplify_constants(null_op), 0)

test/system_construction.jl

@@ -2,9 +2,9 @@ using ModelingToolkit
 using Test
 
 # Define some variables
-@Param t σ ρ β
-@Variable x(t) y(t) z(t)
-@Deriv D'~t
+@param t σ ρ β
+@variable x(t) y(t) z(t)
+@deriv D'~t
 
 # Define a differential equation
 eqs = [D(x) ~ σ*(y-x),
@@ -32,7 +32,7 @@ end
 test_vars_extraction(de, de2)
 
 @testset "time-varying parameters" begin
-    @Param σ′(t)
+    @param σ′(t)
     eqs = [D(x) ~ σ′*(y-x),
            D(y) ~ x*(ρ-z)-y,
            D(z) ~ x*y - β*z]
@@ -46,9 +46,9 @@ test_vars_extraction(de, de2)
 end
 
 # Conversion to first-order ODEs #17
-@Deriv D3'''~t
-@Deriv D2''~t
-@Variable u(t) u_tt(t) u_t(t) x_t(t)
+@deriv D3'''~t
+@deriv D2''~t
+@variable u(t) u_tt(t) u_t(t) x_t(t)
 eqs = [D3(u) ~ 2(D2(u)) + D(u) + D(x) + 1
        D2(x) ~ D(x) + 2]
 de = DiffEqSystem(eqs, t)
@@ -84,8 +84,8 @@ end
 
 generate_function(ns)
 
-@Deriv D'~t
-@Param A B C
+@deriv D'~t
+@param A B C
 _x = y / C
 eqs = [D(x) ~ -A*x,
        D(y) ~ A*x - B*_x]
@@ -100,8 +100,8 @@ test_vars_extraction(de, DiffEqSystem(eqs))
 end
 
 # Now nonlinear system with only variables
-@Variable x y z
-@Param σ ρ β
+@variable x y z
+@param σ ρ β
 
 # Define a nonlinear system
 eqs = [0 ~ σ*(y-x),

test/variable_parsing.jl

@@ -1,10 +1,10 @@
 using ModelingToolkit
 using Test
 
-@Param t
-@Variable x(t)
-@Variable y(t)
-@Variable z(t)
+@param t
+@variable x(t)
+@variable y(t)
+@variable z(t)
 x1 = Variable(:x, [t])
 y1 = Variable(:y, [t])
 z1 = Variable(:z, [t])
@@ -15,7 +15,7 @@ z1 = Variable(:z, [t])
 @test convert(Expr, y) == :y
 @test convert(Expr, z) == :z
 
-@Param begin
+@param begin
     t
     s
 end
@@ -27,7 +27,7 @@ s1 = Variable(:s; known = true)
 @test convert(Expr, s) == :s
 @test convert(Expr, cos(t + sin(s))) == :(cos(t + sin(s)))
 
-@Deriv D'~t
+@deriv D'~t
 D1 = Differential(t)
 @test D1 == D
 @test convert(Expr, D) == D