Default measure evaluation methods

Project.toml

@@ -9,6 +9,7 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+FastGaussQuadrature = "442a2c76-b920-505d-bb47-c5924d526838"
 
 [compat]
 julia = "1"

docs/src/guide/objective.md

@@ -66,7 +66,7 @@ julia> objective_function(model)
 0.5 x[1] + 0.5 x[2] + expect(y(ξ)² - y(ξ))
 
 julia> objective_function_type(model)
-GenericQuadExpr{Float64,MeasureFiniteVariableRef}
+GenericAffExpr{Float64,MeasureFiniteVariableRef}
 ```
 The objective sense can be one of three possibilities: `MIN_SENSE`, `MAX_SENSE`,
 or `FEASIBILITY_SENSE`. The later sense applies to models that contain no
@@ -94,7 +94,7 @@ macro. The objective function is specified via [`set_objective_function`](@ref J
 simply updates the expression stored in the objective. For example, let's update
 out objective to simply be ``0.5x_1 + 0.5x_2``:
 ```jldoctest obj
-julia> set_objective_function(model, 0.5 x[1] + 0.5 x[2])
+julia> set_objective_function(model, 0.5x[1] + 0.5x[2])
 
 julia> objective_function(model)
 0.5 x[1] + 0.5 x[2]

src/InfiniteOpt.jl

@@ -29,6 +29,9 @@ include("utilities.jl")
 include("TranscriptionOpt/TranscriptionOpt.jl")
 using .TranscriptionOpt
 
+include("MeasureEvalMethods/MeasureEvalMethods.jl")
+using .MeasureEvalMethods
+
 # Export model object datatype
 export InfiniteModel
 
@@ -79,7 +82,11 @@ Measure, MeasureRef
 
 # Export measure methods
 export add_measure, measure, measure_function, measure_data, expand,
-expand_all_measures!
+expand_all_measures!, expect, support_sum
+
+# Export measure evaluation functions
+export generate_measure_data, MC_sampling, Gauss_Legendre, Gauss_Hermite,
+Gauss_Laguerre, infinite_transform, support_formatting, measure_dispatch
 
 # Export transcription datatypes
 export TranscriptionData, TranscriptionModel

src/MeasureEvalMethods/MeasureEvalMethods.jl

@@ -0,0 +1,16 @@
+module MeasureEvalMethods
+
+# Import the necessary packages.
+import FastGaussQuadrature
+import JuMP
+import Distributions
+const JuMPC = JuMP.Containers
+using ..InfiniteOpt
+
+# include jl files here
+include("methods.jl")
+# Export functions here
+export generate_measure_data, MC_sampling, Gauss_Legendre, Gauss_Hermite,
+Gauss_Laguerre, infinite_transform, support_formatting, measure_dispatch
+
+end # end module