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update for MOI 0.3 #116

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Jun 3, 2018
Merged

update for MOI 0.3 #116

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2 changes: 1 addition & 1 deletion REQUIRE
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
julia 0.6
MathProgBase 0.5 0.8
MathOptInterface 0.2 0.3
MathOptInterface 0.3 0.4
BinaryProvider 0.2
BinDeps
Compat 0.27
112 changes: 52 additions & 60 deletions src/MOIWrapper.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -146,20 +146,18 @@ end
check_inbounds(m::IpoptOptimizer, var::MOI.SingleVariable) = check_inbounds(m, var.variable)

function check_inbounds(m::IpoptOptimizer, aff::MOI.ScalarAffineFunction)
for v in aff.variables
check_inbounds(m, v)
for term in aff.terms
check_inbounds(m, term.variable_index)
end
end

function check_inbounds(m::IpoptOptimizer, quad::MOI.ScalarQuadraticFunction)
for v in quad.affine_variables
check_inbounds(m, v)
for term in quad.affine_terms
check_inbounds(m, term.variable_index)
end
for v in quad.quadratic_rowvariables
check_inbounds(m, v)
end
for v in quad.quadratic_colvariables
check_inbounds(m, v)
for term in quad.quadratic_terms
check_inbounds(m, term.variable_index_1)
check_inbounds(m, term.variable_index_2)
end
end

Expand Down Expand Up @@ -284,18 +282,18 @@ nlp_constraint_offset(m::IpoptOptimizer) = quadratic_eq_offset(m) + length(m.qua
# Convenience functions used only in optimize!

function append_to_jacobian_sparsity!(jacobian_sparsity, aff::MOI.ScalarAffineFunction, row)
for variable_index in aff.variables
push!(jacobian_sparsity, (row, variable_index.value))
for term in aff.terms
push!(jacobian_sparsity, (row, term.variable_index.value))
end
end

function append_to_jacobian_sparsity!(jacobian_sparsity, quad::MOI.ScalarQuadraticFunction, row)
for variable_index in quad.affine_variables
push!(jacobian_sparsity, (row, variable_index.value))
for term in quad.affine_terms
push!(jacobian_sparsity, (row, term.variable_index.value))
end
for i in 1:length(quad.quadratic_rowvariables)
row_idx = quad.quadratic_rowvariables[i]
col_idx = quad.quadratic_colvariables[i]
for term in quad.quadratic_terms
row_idx = term.variable_index_1
col_idx = term.variable_index_2
if row_idx == col_idx
push!(jacobian_sparsity, (row, row_idx.value))
else
Expand Down Expand Up @@ -341,9 +339,9 @@ end
append_to_hessian_sparsity!(hessian_sparsity, ::Union{MOI.SingleVariable,MOI.ScalarAffineFunction}) = nothing

function append_to_hessian_sparsity!(hessian_sparsity, quad::MOI.ScalarQuadraticFunction)
for i in 1:length(quad.quadratic_rowvariables)
push!(hessian_sparsity, (quad.quadratic_rowvariables[i].value,
quad.quadratic_colvariables[i].value))
for term in quad.quadratic_terms
push!(hessian_sparsity, (term.variable_index_1.value,
term.variable_index_2.value))
end
end

Expand Down Expand Up @@ -372,33 +370,28 @@ end

function eval_function(aff::MOI.ScalarAffineFunction, x)
function_value = aff.constant
for i in 1:length(aff.variables)
var_idx = aff.variables[i]
coefficient = aff.coefficients[i]
for term in aff.terms
# Note the implicit assumtion that VariableIndex values match up with
# x indices. This is valid because in this wrapper ListOfVariableIndices
# is always [1, ..., NumberOfVariables].
function_value += coefficient*x[var_idx.value]
function_value += term.coefficient*x[term.variable_index.value]
end
return function_value
end

function eval_function(quad::MOI.ScalarQuadraticFunction, x)
function_value = quad.constant
for i in 1:length(quad.affine_variables)
var_idx = quad.affine_variables[i]
coefficient = quad.affine_coefficients[i]
function_value += coefficient*x[var_idx.value]
end
for i in 1:length(quad.quadratic_rowvariables)
row_idx = quad.quadratic_rowvariables[i]
col_idx = quad.quadratic_colvariables[i]
coefficient = quad.quadratic_coefficients[i]
term = coefficient*x[row_idx.value]*x[col_idx.value]
for term in quad.affine_terms
function_value += term.coefficient*x[term.variable_index.value]
end
for term in quad.quadratic_terms
row_idx = term.variable_index_1
col_idx = term.variable_index_2
coefficient = term.coefficient
if row_idx == col_idx
function_value += 0.5*term
function_value += 0.5*coefficient*x[row_idx.value]*x[col_idx.value]
else
function_value += term
function_value += coefficient*x[row_idx.value]*x[col_idx.value]
end
end
return function_value
Expand All @@ -422,24 +415,20 @@ end

function fill_gradient!(grad, x, aff::MOI.ScalarAffineFunction{Float64})
fill!(grad, 0.0)
for i in 1:length(aff.variables)
var_idx = aff.variables[i]
coefficient = aff.coefficients[i]
grad[var_idx.value] += coefficient
for term in aff.terms
grad[term.variable_index.value] += term.coefficient
end
end

function fill_gradient!(grad, x, quad::MOI.ScalarQuadraticFunction{Float64})
fill!(grad, 0.0)
for i in 1:length(quad.affine_variables)
var_idx = quad.affine_variables[i]
coefficient = quad.affine_coefficients[i]
grad[var_idx.value] += coefficient
end
for i in 1:length(quad.quadratic_rowvariables)
row_idx = quad.quadratic_rowvariables[i]
col_idx = quad.quadratic_colvariables[i]
coefficient = quad.quadratic_coefficients[i]
for term in quad.affine_terms
grad[term.variable_index.value] += term.coefficient
end
for term in quad.quadratic_terms
row_idx = term.variable_index_1
col_idx = term.variable_index_2
coefficient = term.coefficient
if row_idx == col_idx
grad[row_idx.value] += coefficient*x[row_idx.value]
else
Expand Down Expand Up @@ -486,19 +475,23 @@ function eval_constraint(m::IpoptOptimizer, g, x)
end

function fill_constraint_jacobian!(values, start_offset, x, aff::MOI.ScalarAffineFunction)
num_coefficients = length(aff.coefficients)
values[start_offset+1:start_offset+num_coefficients] .= aff.coefficients
num_coefficients = length(aff.terms)
for i in 1:num_coefficients
values[start_offset+i] = aff.terms[i].coefficient
end
return num_coefficients
end

function fill_constraint_jacobian!(values, start_offset, x, quad::MOI.ScalarQuadraticFunction)
num_affine_coefficients = length(quad.affine_coefficients)
values[start_offset+1:start_offset+num_affine_coefficients] .= quad.affine_coefficients
num_affine_coefficients = length(quad.affine_terms)
for i in 1:num_affine_coefficients
values[start_offset+i] = quad.affine_terms[i].coefficient
end
num_quadratic_coefficients = 0
for i in 1:length(quad.quadratic_rowvariables)
row_idx = quad.quadratic_rowvariables[i]
col_idx = quad.quadratic_colvariables[i]
coefficient = quad.quadratic_coefficients[i]
for term in quad.quadratic_terms
row_idx = term.variable_index_1
col_idx = term.variable_index_2
coefficient = term.coefficient
if row_idx == col_idx
values[start_offset+num_affine_coefficients+num_quadratic_coefficients+1] = coefficient*x[col_idx.value]
num_quadratic_coefficients += 1
Expand Down Expand Up @@ -541,11 +534,10 @@ function fill_hessian_lagrangian!(values, start_offset, scale_factor, ::Union{MO
end

function fill_hessian_lagrangian!(values, start_offset, scale_factor, quad::MOI.ScalarQuadraticFunction)
coefficients = quad.quadratic_coefficients
for i in 1:length(coefficients)
values[start_offset + i] = scale_factor*coefficients[i]
for i in 1:length(quad.quadratic_terms)
values[start_offset + i] = scale_factor*quad.quadratic_terms[i].coefficient
end
return length(coefficients)
return length(quad.quadratic_terms)
end

function eval_hessian_lagrangian(m::IpoptOptimizer, values, x, obj_factor, lambda)
Expand Down
4 changes: 1 addition & 3 deletions test/MOIWrapper.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -9,8 +9,6 @@ MOIU.@model(IpoptModelData, (), (EqualTo, GreaterThan, LessThan),
(), (SingleVariable,), (ScalarAffineFunction,ScalarQuadraticFunction), (VectorOfVariables,),
(VectorAffineFunction,))

MOIB.@bridge SplitInterval MOIB.SplitIntervalBridge () (Interval,) () () () (ScalarAffineFunction,) () ()

# Without fixed_variable_treatment set, duals are not computed for variables
# that have lower_bound == upper_bound.
const optimizer = IpoptOptimizer(print_level=0, fixed_variable_treatment="make_constraint")
Expand All @@ -24,7 +22,7 @@ const config = MOIT.TestConfig(atol=1e-4, rtol=1e-4)
"linear13", # FeasibilitySense not supported yet.
"linear7", # VectorAffineFunction not supported.
]
linear_optimizer = SplitInterval{Float64}(MOIU.CachingOptimizer(IpoptModelData{Float64}(), optimizer))
linear_optimizer = MOI.Bridges.SplitInterval{Float64}(MOIU.CachingOptimizer(IpoptModelData{Float64}(), optimizer))
MOIT.contlineartest(linear_optimizer, config, exclude)
end

Expand Down