Merge pull request #661 from JuliaRobotics/master

v0.10.4-rc1

Author: dehann

Project.toml

@@ -1,6 +1,6 @@
 name = "DistributedFactorGraphs"
 uuid = "b5cc3c7e-6572-11e9-2517-99fb8daf2f04"
-version = "0.10.3"
+version = "0.10.4"
 
 [deps]
 Base64 = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"

src/CloudGraphsDFG/services/CommonFunctions.jl

@@ -133,6 +133,10 @@ Build a Cypher-compliant set of properies from a subnode type.
 Note: Individual values are serialized if they are not already.
 If the additional properties is provided, the additional
 properties will be added in verbatim when serializing.
+
+Related
+
+_Neo4jTo???
 """
 function _structToNeo4jProps(inst::Union{User, Robot, Session, PVND, N, APPE, ABDE},
                              addProps::Dict{String, String}=Dict{String, String}();
@@ -175,7 +179,7 @@ function _structToNeo4jProps(inst::Union{User, Robot, Session, PVND, N, APPE, AB
             if fieldname == :solverData
                 fnctype = getSolverData(inst).fnc.usrfnc!
                 try
-                    packtype = getfield(_getmodule(fnctype), Symbol("Packed$(_getname(fnctype))"))
+                    packtype = convertPackedType(fnctype)
                     packed = convert(PackedFunctionNodeData{packtype}, getSolverData(inst))
                     packedJson = JSON2.write(packed)
                     val = "\"$(replace(packedJson, "\"" => "\\\""))\"" # Escape slashes too

src/Common.jl

@@ -1,11 +1,11 @@
 
 ## Utility functions for getting type names and modules (from IncrementalInference)
-function _getmodule(t::T) where T
-  T.name.module
-end
-function _getname(t::T) where T
-  T.name.name
-end
+_getmodule(t::T) where T = T.name.module
+_getname(t::T) where T = T.name.name
+
+
+convertPackedType(t::Union{T, Type{T}}) where {T <: FunctorInferenceType} = getfield(_getmodule(t), Symbol("Packed$(_getname(t))"))
+convertStructType(::Type{PT}) where {PT <: PackedInferenceType} = getfield(PT.name.module, Symbol(string(PT.name.name)[7:end]))
 
 
 ##==============================================================================

src/DistributedFactorGraphs.jl

@@ -200,6 +200,9 @@ export getFactorType, getFactorFunction
 # Node Data
 export mergeVariableData!, mergeGraphVariableData!
 
+# Serialization type conversion
+export convertPackedType, convertStructType
+
 ##------------------------------------------------------------------------------
 ## Other utility functions
 ##------------------------------------------------------------------------------

src/services/Serialization.jl

@@ -227,6 +227,7 @@ end
 ## Factor Packing and unpacking
 ##==============================================================================
 
+
 function packFactor(dfg::G, f::DFGFactor)::Dict{String, Any} where G <: AbstractDFG
     # Construct the properties to save
     props = Dict{String, Any}()
@@ -237,7 +238,7 @@ function packFactor(dfg::G, f::DFGFactor)::Dict{String, Any} where G <: Abstract
     # Pack the node data
     fnctype = getSolverData(f).fnc.usrfnc!
     try
-        packtype = getfield(_getmodule(fnctype), Symbol("Packed$(_getname(fnctype))"))
+        packtype = convertPackedType(fnctype)
         packed = convert(PackedFunctionNodeData{packtype}, getSolverData(f))
         props["data"] = JSON2.write(packed)
     catch ex
@@ -255,11 +256,10 @@ function packFactor(dfg::G, f::DFGFactor)::Dict{String, Any} where G <: Abstract
     return props
 end
 
-
 function decodePackedType(::Type{T}, packeddata::GenericFunctionNodeData{PT}) where {T<:FactorOperationalMemory, PT}
   # usrtyp = convert(FunctorInferenceType, packeddata.fnc)
   # Also look at parentmodule
-  usrtyp = getfield(PT.name.module, Symbol(string(PT.name.name)[7:end]))
+  usrtyp = convertStructType(PT)
   fulltype = DFG.FunctionNodeData{T{usrtyp}}
   factordata = convert(fulltype, packeddata)
   return factordata