SDDPTree -> SDDPGraph

Author: blegat

src/graph.jl

@@ -1,23 +1,23 @@
-export AbstractSDDPTree, haschildren, nchidren, children, getchild, getproba, getprobas, cutgen, numberofpaths
-abstract type AbstractSDDPTree{S} end
+export AbstractSDDPGraph, haschildren, nchidren, children, getchild, getproba, getprobas, cutgen, numberofpaths
+abstract type AbstractSDDPGraph{S} end
 
-mutable struct GraphSDDPTree{S} <: AbstractSDDPTree{S}
+mutable struct SDDPGraph{S} <: AbstractSDDPGraph{S}
 	root::SDDPNode{S}
 end
 
-getmaster(g::GraphSDDPTree) = g.root, g.root
+getmaster(g::SDDPGraph) = g.root, g.root
 
 # Get children scenarios
-haschildren(g::GraphSDDPTree, node::SDDPNode) = !isempty(node.children)
-nchildren(g::GraphSDDPTree, node::SDDPNode) = length(node.children)
-children(g::GraphSDDPTree, node::SDDPNode) = node.children
-getchild(g::GraphSDDPTree, node::SDDPNode, i) = node.children[i]
+haschildren(g::SDDPGraph, node::SDDPNode) = !isempty(node.children)
+nchildren(g::SDDPGraph, node::SDDPNode) = length(node.children)
+children(g::SDDPGraph, node::SDDPNode) = node.children
+getchild(g::SDDPGraph, node::SDDPNode, i) = node.children[i]
 # Get proba of children scenario
-getproba(g::GraphSDDPTree, node::SDDPNode, i) = node.proba[i]
-getprobas(g::GraphSDDPTree, node::SDDPNode) = node.proba
+getproba(g::SDDPGraph, node::SDDPNode, i) = node.proba[i]
+getprobas(g::SDDPGraph, node::SDDPNode) = node.proba
 
 # Get number of paths
-numberofpaths(g::GraphSDDPTree, num_stages) = numberofpaths(g.root, 1, num_stages)
-numberofpaths(g::GraphSDDPTree, node::SDDPNode, t, num_stages) = numberofpaths(node, t, num_stages)
+numberofpaths(g::SDDPGraph, num_stages) = numberofpaths(g.root, 1, num_stages)
+numberofpaths(g::SDDPGraph, node::SDDPNode, t, num_stages) = numberofpaths(node, t, num_stages)
 
-cutgen(g::GraphSDDPTree, node::SDDPNode) = node.nlds.cutgen
+cutgen(g::SDDPGraph, node::SDDPNode) = node.nlds.cutgen

src/interface.jl

@@ -44,7 +44,7 @@ If `cutgen` is `MultiCutGenerator`, one variable `θ_i` is created for each scen
 """
 function model2lattice(m::Model, num_stages, solver, pruningalgo::AbstractCutPruningAlgo, cutgen::AbstractOptimalityCutGenerator=MultiCutGenerator, detectlb::Bool=true, newcut::Symbol=:InvalidateSolver)
     root = getSDDPNode(m, 1, num_stages, solver, nothing, pruningalgo, cutgen, detectlb, newcut)
-	GraphSDDPTree(root)
+	SDDPGraph(root)
 end
 
 function SDDPclear(m::Model)

src/path.jl

@@ -91,7 +91,7 @@ function mergesamepaths{NodeT}(pathsd::Vector{Tuple{NodeT, Vector{SDDPPath}}}, s
     newpathsd
 end
 
-function childjobs{NodeT}(g::AbstractSDDPTree, pathsd::Vector{Tuple{NodeT, Vector{SDDPPath}}}, pathsampler, t, num_stages)
+function childjobs{NodeT}(g::AbstractSDDPGraph, pathsd::Vector{Tuple{NodeT, Vector{SDDPPath}}}, pathsampler, t, num_stages)
     jobsd = Dict{NodeT, Vector{SDDPJob{NodeT}}}()
     for (node, paths) in pathsd
         if haschildren(g, node)
@@ -112,7 +112,7 @@ function childjobs{NodeT}(g::AbstractSDDPTree, pathsd::Vector{Tuple{NodeT, Vecto
     jobsd
 end
 
-function jobstopaths{NodeT}(jobsd::Dict{NodeT, Vector{SDDPJob{NodeT}}}, g::AbstractSDDPTree)
+function jobstopaths{NodeT}(jobsd::Dict{NodeT, Vector{SDDPJob{NodeT}}}, g::AbstractSDDPGraph)
     pathsd = Tuple{NodeT, Vector{SDDPPath}}[]
     for (node, jobs) in jobsd
         K = [find(job.K .!= 0) for job in jobs]

src/sampler.jl

@@ -49,7 +49,7 @@ function _samplepaths(npaths, pmf, semirandom::Bool, canmodifypmf::Bool)
 end
 infpaths(g, node) = fill(-1, nchildren(g, node))
 
-function samplepaths(pathsampler::AbstractPathSampler, g::GraphSDDPTree, node, npaths::Vector{Int}, t, num_stages)
+function samplepaths(pathsampler::AbstractPathSampler, g::AbstractSDDPGraph, node, npaths::Vector{Int}, t, num_stages)
     npathss = Vector{Int}[similar(npaths) for i in 1:nchildren(g, node)]
     for i in 1:length(npaths)
         _npaths = samplepaths(pathsampler, g, node, npaths[i], t, num_stages)
@@ -63,7 +63,7 @@ end
 struct ProbaPathSampler <: AbstractPathSampler
     semirandom::Bool
 end
-function samplepaths(pathsampler::ProbaPathSampler, g::GraphSDDPTree, node, npaths::Int, t, num_stages)
+function samplepaths(pathsampler::ProbaPathSampler, g::AbstractSDDPGraph, node, npaths::Int, t, num_stages)
     if npaths == -1
         infpaths(g, node)
     else
@@ -74,7 +74,7 @@ end
 struct NumPathsPathSampler <: AbstractPathSampler
     semirandom::Bool
 end
-function samplepaths(pathsampler::NumPathsPathSampler, g::GraphSDDPTree, node, npaths::Int, t, num_stages)
+function samplepaths(pathsampler::NumPathsPathSampler, g::AbstractSDDPGraph, node, npaths::Int, t, num_stages)
     if npaths == -1
         infpaths(g, node)
     else

src/sddp.jl

@@ -50,7 +50,7 @@ The paths will be selected according to `pathsampler` and equivalent paths might
 The parameter `ztol` is also used to check whether a new cut is useful.
 When a scenario is infeasible and `stopatinf` is true then no other scenario with the same ancestor is run. Note that since the order in which the different scenarios is run is not deterministic, this might introduce nondeterminism even if the sampling is deterministic.
 """
-function iteration{S}(g::AbstractSDDPTree{S}, Ktot::Int, num_stages, verbose, pathsampler; ztol=1e-6, stopatinf=false, mergepaths=true, forwardcuts=false, backwardcuts=true)
+function iteration{S}(g::AbstractSDDPGraph{S}, Ktot::Int, num_stages, verbose, pathsampler; ztol=1e-6, stopatinf=false, mergepaths=true, forwardcuts=false, backwardcuts=true)
     stats = SDDPStats()
 
 	master, initialnode = getmaster(g)
@@ -138,7 +138,7 @@ The parameter `ztol` is also used to check whether a new cut is useful.
 When a scenario is infeasible and `stopatinf` is true then no other scenario with the same ancestor is run. Note that since the order in which the different scenarios is run is not deterministic, this might introduce nondeterminism even if the sampling is deterministic.
 By default, the cuts are added backward. However, if `forwardcuts` is set to `true` and `backwardcuts` is set to `false` the cuts are added forward.
 """
-function SDDP(g::AbstractSDDPTree, num_stages; K::Int=25, stopcrit::AbstractStoppingCriterion=Pereira(), verbose=0, pathsampler::AbstractPathSampler=ProbaPathSampler(true), ztol=1e-6, stopatinf=false, mergepaths=true, forwardcuts=false, backwardcuts=true)
+function SDDP(g::AbstractSDDPGraph, num_stages; K::Int=25, stopcrit::AbstractStoppingCriterion=Pereira(), verbose=0, pathsampler::AbstractPathSampler=ProbaPathSampler(true), ztol=1e-6, stopatinf=false, mergepaths=true, forwardcuts=false, backwardcuts=true)
     mastersol = nothing
     totalstats = SDDPStats()
     stats = SDDPStats()

src/waitandsee.jl

@@ -15,7 +15,7 @@ function meanstdpaths(paths::Vector{WSPath}, totalK)
     meanstdpaths(z, proba, npaths, totalK)
 end
 
-function waitandsee(g::AbstractSDDPTree, num_stages, solver, totalK=25, verbose=0)
+function waitandsee(g::AbstractSDDPGraph, num_stages, solver, totalK=25, verbose=0)
 	root = g.root
     paths = WSPath[WSPath(root, NLDS[root.nlds], .0, 1., totalK)]
     for t in 2:num_stages