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[Nonlinear] change Nonlinear.add_constraint to accept function and set #1818

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Apr 25, 2022
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[Nonlinear] change Nonlinear.add_constraint to accept function and set #1818

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4 changes: 2 additions & 2 deletions docs/src/submodules/Nonlinear/overview.md
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Expand Up @@ -164,7 +164,7 @@ julia> Nonlinear.set_objective(model, :($p + $expr + $x));

Add a constraint using [`Nonlinear.add_constraint`](@ref):
```jldoctest nonlinear_developer
julia> c = Nonlinear.add_constraint(model, :(1 + sqrt($x) <= 2.0))
julia> c = Nonlinear.add_constraint(model, :(1 + sqrt($x)), MOI.LessThan(2.0))
MathOptInterface.Nonlinear.ConstraintIndex(1)

julia> model
Expand All @@ -177,7 +177,7 @@ A Nonlinear.Model with:
The return value, `c`, is a [`Nonlinear.ConstraintIndex`](@ref) that is a unique
identifier for the constraint. Interval constraints are also supported:
```jldoctest nonlinear_developer
julia> c2 = Nonlinear.add_constraint(model, :(-1.0 <= 1 + sqrt($x) <= 2.0))
julia> c2 = Nonlinear.add_constraint(model, :(1 + sqrt($x)), MOI.Interval(-1.0, 2.0))
MathOptInterface.Nonlinear.ConstraintIndex(2)

julia> model
Expand Down
4 changes: 2 additions & 2 deletions src/Nonlinear/evaluator.jl
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Expand Up @@ -18,8 +18,8 @@ Return the 1-indexed value of the constraint index `c` in `evaluator`.
```julia
model = Model()
x = MOI.VariableIndex(1)
c1 = add_constraint(model, :(\$x^2 <= 1))
c2 = add_constraint(model, :(\$x^2 <= 1))
c1 = add_constraint(model, :(\$x^2), MOI.LessThan(1.0))
c2 = add_constraint(model, :(\$x^2), MOI.LessThan(1.0))
evaluator = Evaluator(model)
MOI.initialize(evaluator, Symbol[])
ordinal_index(evaluator, c2) # Returns 2
Expand Down
33 changes: 25 additions & 8 deletions src/Nonlinear/model.jl
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Expand Up @@ -76,9 +76,18 @@ function Base.getindex(model::Model, index::ExpressionIndex)
end

"""
add_constraint(model::Model, input::Expr)::ConstraintIndex
add_constraint(
model::Model,
func,
set::Union{
MOI.GreaterThan{Float64},
MOI.LessThan{Float64},
MOI.Interval{Float64},
MOI.EqualTo{Float64},
},
)

Parse `input` into a [`Constraint`](@ref) and add to `model`. Returns a
Parse `func` and `set` into a [`Constraint`](@ref) and add to `model`. Returns a
[`ConstraintIndex`](@ref) that can be used to delete the constraint or query
solution information.

Expand All @@ -87,12 +96,20 @@ solution information.
```julia
model = Model()
x = MOI.VariableIndex(1)
c = add_constraint(model, :(\$x^2 <= 1))
c = add_constraint(model, :(\$x^2), MOI.LessThan(1.0))
```
"""
function add_constraint(model::Model, input::Expr)
expr, set = _expr_to_constraint(input)
f = parse_expression(model, expr)
function add_constraint(
model::Model,
func,
set::Union{
MOI.GreaterThan{Float64},
MOI.LessThan{Float64},
MOI.Interval{Float64},
MOI.EqualTo{Float64},
},
)
f = parse_expression(model, func)
model.last_constraint_index += 1
index = ConstraintIndex(model.last_constraint_index)
model.constraints[index] = Constraint(f, set)
Expand All @@ -109,7 +126,7 @@ Delete the constraint index `c` from `model`.
```julia
model = Model()
x = MOI.VariableIndex(1)
c = add_constraint(model, :(\$x^2 <= 1))
c = add_constraint(model, :(\$x^2), MOI.LessThan(1.0))
delete(model, c)
```
"""
Expand Down Expand Up @@ -139,7 +156,7 @@ and used to modify the value of the parameter.
model = Model()
x = MOI.VariableIndex(1)
p = add_parameter(model, 1.2)
c = add_constraint(model, :(\$x^2 <= \$p))
c = add_constraint(model, :(\$x^2 - \$p), MOI.LessThan(0.0))
```
"""
function add_parameter(model::Model, value::Float64)
Expand Down
35 changes: 0 additions & 35 deletions src/Nonlinear/parse.jl
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Expand Up @@ -223,41 +223,6 @@ function parse_expression(
)
end

function _normalize_constraint_expr(lhs::Real, body, rhs::Real)
return Float64(lhs), body, Float64(rhs)
end

function _normalize_constraint_expr(lhs, body, rhs)
return error(
"Interval constraint contains non-constant left- or right-hand " *
"sides. Reformulate as two separate constraints, or move all " *
"variables into the central term.",
)
end

_normalize_constraint_expr(lhs, rhs::Real) = lhs, Float64(rhs)

_normalize_constraint_expr(lhs, rhs) = Expr(:call, :-, lhs, rhs), 0.0

function _expr_to_constraint(expr::Expr)
if isexpr(expr, :comparison)
@assert expr.args[2] == expr.args[4]
@assert expr.args[2] in (:<=, :>=)
lhs, body, rhs =
_normalize_constraint_expr(expr.args[1], expr.args[3], expr.args[5])
return body, MOI.Interval(lhs, rhs)
end
lhs, rhs = _normalize_constraint_expr(expr.args[2], expr.args[3])
if expr.args[1] == :<=
return :($lhs - $rhs), MOI.LessThan(0.0)
elseif expr.args[1] == :>=
return :($lhs - $rhs), MOI.GreaterThan(0.0)
else
@assert expr.args[1] == :(==)
return :($lhs - $rhs), MOI.EqualTo(0.0)
end
end

"""
convert_to_expr(data::Model, expr::Expression)

Expand Down
68 changes: 26 additions & 42 deletions test/Nonlinear/Nonlinear.jl
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Expand Up @@ -295,89 +295,70 @@ end
function test_add_constraint_less_than()
model = Nonlinear.Model()
x = MOI.VariableIndex(1)
input = :($x^2 + 1 <= 1.0)
c = Nonlinear.add_constraint(model, input)
@test model[c].set == MOI.LessThan(0.0)
func = :($x^2 + 1)
set = MOI.LessThan(1.0)
c = Nonlinear.add_constraint(model, func, set)
@test model[c].set == set
evaluator = Nonlinear.Evaluator(model)
MOI.initialize(evaluator, [:ExprGraph])
@test MOI.constraint_expr(evaluator, 1) == :((x[$x]^2 + 1) - 1.0 <= 0.0)
@test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2 + 1 <= 1.0)
return
end

function test_add_constraint_delete()
model = Nonlinear.Model()
x = MOI.VariableIndex(1)
c1 = Nonlinear.add_constraint(model, :($x^2 + 1 <= 1.0))
_ = Nonlinear.add_constraint(model, :(sqrt($x) <= 1.0))
c1 = Nonlinear.add_constraint(model, :($x^2 + 1), MOI.LessThan(1.0))
_ = Nonlinear.add_constraint(model, :(sqrt($x)), MOI.LessThan(1.0))
evaluator = Nonlinear.Evaluator(model)
MOI.initialize(evaluator, [:ExprGraph])
@test MOI.constraint_expr(evaluator, 1) == :((x[$x]^2 + 1) - 1.0 <= 0.0)
@test MOI.constraint_expr(evaluator, 2) == :((sqrt(x[$x])) - 1.0 <= 0.0)
@test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2 + 1 <= 1.0)
@test MOI.constraint_expr(evaluator, 2) == :(sqrt(x[$x]) <= 1.0)
Nonlinear.delete(model, c1)
evaluator = Nonlinear.Evaluator(model)
MOI.initialize(evaluator, [:ExprGraph])
@test MOI.constraint_expr(evaluator, 1) == :(sqrt(x[$x]) - 1.0 <= 0.0)
@test MOI.constraint_expr(evaluator, 1) == :(sqrt(x[$x]) <= 1.0)
@test_throws BoundsError MOI.constraint_expr(evaluator, 2)
return
end

function test_add_constraint_less_than_normalize()
model = Nonlinear.Model()
x = MOI.VariableIndex(1)
input = :(1 <= 1.0 + $x^2)
c = Nonlinear.add_constraint(model, input)
@test model[c].set == MOI.LessThan(0.0)
evaluator = Nonlinear.Evaluator(model)
MOI.initialize(evaluator, [:ExprGraph])
@test MOI.constraint_expr(evaluator, 1) ==
:(1 - (1.0 + x[$x]^2) - 0.0 <= 0.0)
return
end

function test_add_constraint_greater_than()
model = Nonlinear.Model()
x = MOI.VariableIndex(1)
input = :($x^2 + 1 >= 1.0)
c = Nonlinear.add_constraint(model, input)
@test model[c].set == MOI.GreaterThan(0.0)
func = :($x^2 + 1)
set = MOI.GreaterThan(1.0)
c = Nonlinear.add_constraint(model, func, set)
@test model[c].set == set
evaluator = Nonlinear.Evaluator(model)
MOI.initialize(evaluator, [:ExprGraph])
@test MOI.constraint_expr(evaluator, 1) == :((x[$x]^2 + 1) - 1.0 >= 0.0)
@test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2 + 1 >= 1.0)
return
end

function test_add_constraint_equal_to()
model = Nonlinear.Model()
x = MOI.VariableIndex(1)
input = :($x^2 + 1 == 1.0)
c = Nonlinear.add_constraint(model, input)
@test model[c].set == MOI.EqualTo(0.0)
func, set = :($x^2 + 1), MOI.EqualTo(1.0)
c = Nonlinear.add_constraint(model, func, set)
@test model[c].set == set
evaluator = Nonlinear.Evaluator(model)
MOI.initialize(evaluator, [:ExprGraph])
@test MOI.constraint_expr(evaluator, 1) == :((x[$x]^2 + 1) - 1.0 == 0.0)
@test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2 + 1 == 1.0)
return
end

function test_add_constraint_interval()
model = Nonlinear.Model()
x = MOI.VariableIndex(1)
input = :(-1.0 <= $x^2 + 1 <= 1.0)
c = Nonlinear.add_constraint(model, input)
@test model[c].set == MOI.Interval(-1.0, 1.0)
func, set = :($x^2 + 1), MOI.Interval(-1.0, 1.0)
c = Nonlinear.add_constraint(model, func, set)
@test model[c].set == set
evaluator = Nonlinear.Evaluator(model)
MOI.initialize(evaluator, [:ExprGraph])
@test MOI.constraint_expr(evaluator, 1) == :(-1.0 <= x[$x]^2 + 1 <= 1.0)
return
end

function test_add_constraint_interval_normalize()
model = Nonlinear.Model()
x = MOI.VariableIndex(1)
input = :(-1.0 + $x <= $x^2 + 1 <= 1.0)
@test_throws(ErrorException, Nonlinear.add_constraint(model, input))
return
end

function test_eval_univariate_function()
r = Nonlinear.OperatorRegistry()
@test Nonlinear.eval_univariate_function(r, :+, 1.0) == 1.0
Expand Down Expand Up @@ -783,7 +764,10 @@ end
function test_add_constraint_ordinal_index()
model = Nonlinear.Model()
x = MOI.VariableIndex(1)
constraints = [Nonlinear.add_constraint(model, :($x <= $i)) for i in 1:4]
constraints = [
Nonlinear.add_constraint(model, :($x), MOI.LessThan(1.0 * i)) for
i in 1:4
]
for i in 1:4
@test MOI.is_valid(model, constraints[i])
end
Expand Down