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GearsADGearsAD
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Removing DataFrame references
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11 files changed

+6
-95
lines changed

11 files changed

+6
-95
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‎Project.toml

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@@ -4,7 +4,6 @@ version = "0.4.0"
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[deps]
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Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
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DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
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Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
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Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
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DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"

‎docs/src/func_ref.md

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@@ -63,8 +63,3 @@ getSubgraph
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toDot
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toDotFile
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```
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### DataFrame Extension Functions
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```@docs
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getAdjacencyMatrixDataFrame
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```

‎src/CloudGraphsDFG/CloudGraphsDFG.jl

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@@ -20,7 +20,6 @@ export getVariable, getFactor
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export updateVariable!, updateFactor!
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export deleteVariable!, deleteFactor!
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export getAdjacencyMatrix
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export getAdjacencyMatrixDataFrame
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export getNeighbors
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export getSubgraphAroundNode
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export getSubgraph

‎src/CloudGraphsDFG/services/CloudGraphsDFG.jl

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@@ -815,30 +815,3 @@ end
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# end
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# return nothing
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# end
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#
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# function __init__()
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# @require DataFrames="a93c6f00-e57d-5684-b7b6-d8193f3e46c0" begin
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# if isdefined(Main, :DataFrames)
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# """
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# $(SIGNATURES)
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# Get an adjacency matrix for the DFG as a DataFrame.
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# Rows are all factors, columns are all variables, and each cell contains either nothing or the symbol of the relating factor.
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# The first column is the factor headings.
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# """
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# function getAdjacencyMatrixDataFrame(dfg::CloudGraphsDFG)::Main.DataFrames.DataFrame
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# varLabels = sort(map(v->v.label, getVariables(dfg)))
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# factLabels = sort(map(f->f.label, getFactors(dfg)))
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# adjDf = DataFrames.DataFrame(:Factor => Union{Missing, Symbol}[])
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# for varLabel in varLabels
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# adjDf[varLabel] = Union{Missing, Symbol}[]
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# end
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# for (i, factLabel) in enumerate(factLabels)
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# push!(adjDf, [factLabel, DataFrames.missings(length(varLabels))...])
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# factVars = getNeighbors(dfg, getFactor(dfg, factLabel))
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# map(vLabel -> adjDf[vLabel][i] = factLabel, factVars)
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# end
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# return adjDf
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# end
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# end
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# end
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# end

‎src/DistributedFactorGraphs.jl

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@@ -60,31 +60,6 @@ include("LightDFG/LightDFG.jl")
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export saveDFG, loadDFG
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function __init__()
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@require DataFrames="a93c6f00-e57d-5684-b7b6-d8193f3e46c0" begin
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if isdefined(Main, :DataFrames)
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"""
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$(SIGNATURES)
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Get an adjacency matrix for the DFG as a DataFrame.
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Rows are all factors, columns are all variables, and each cell contains either nothing or the symbol of the relating factor.
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The first column is the factor headings.
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"""
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function getAdjacencyMatrixDataFrame(dfg::Union{GraphsDFG, MetaGraphsDFG, SymbolDFG, LightDFG})::Main.DataFrames.DataFrame
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varLabels = sort(map(v->v.label, getVariables(dfg)))
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factLabels = sort(map(f->f.label, getFactors(dfg)))
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adjDf = DataFrames.DataFrame(:Factor => Union{Missing, Symbol}[])
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for varLabel in varLabels
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adjDf[varLabel] = Union{Missing, Symbol}[]
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end
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for (i, factLabel) in enumerate(factLabels)
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push!(adjDf, [factLabel, DataFrames.missings(length(varLabels))...])
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factVars = getNeighbors(dfg, getFactor(dfg, factLabel))
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map(vLabel -> adjDf[vLabel][i] = factLabel, factVars)
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end
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return adjDf
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end
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end
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end
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@require Neo4j="d2adbeaf-5838-5367-8a2f-e46d570981db" begin
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# Include the Cloudgraphs API
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include("CloudGraphsDFG/CloudGraphsDFG.jl")

‎src/GraphsDFG/GraphsDFG.jl

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@@ -16,7 +16,6 @@ export getVariable, getFactor
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export updateVariable!, updateFactor!
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export deleteVariable!, deleteFactor!
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export getAdjacencyMatrix
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export getAdjacencyMatrixDataFrame
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export getNeighbors
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export getSubgraphAroundNode
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export getSubgraph

‎src/GraphsDFG/services/GraphsDFG.jl

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@@ -527,30 +527,3 @@ function toDotFile(dfg::GraphsDFG, fileName::String="/tmp/dfg.dot")::Nothing
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end
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return nothing
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end
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# function __init__()
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# @require DataFrames="a93c6f00-e57d-5684-b7b6-d8193f3e46c0" begin
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# if isdefined(Main, :DataFrames)
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# """
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# $(SIGNATURES)
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# Get an adjacency matrix for the DFG as a DataFrame.
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# Rows are all factors, columns are all variables, and each cell contains either nothing or the symbol of the relating factor.
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# The first column is the factor headings.
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# """
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# function getAdjacencyMatrixDataFrame(dfg::GraphsDFG)::Main.DataFrames.DataFrame
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# varLabels = sort(map(v->v.label, getVariables(dfg)))
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# factLabels = sort(map(f->f.label, getFactors(dfg)))
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# adjDf = DataFrames.DataFrame(:Factor => Union{Missing, Symbol}[])
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# for varLabel in varLabels
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# adjDf[varLabel] = Union{Missing, Symbol}[]
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# end
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# for (i, factLabel) in enumerate(factLabels)
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# push!(adjDf, [factLabel, DataFrames.missings(length(varLabels))...])
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# factVars = getNeighbors(dfg, getFactor(dfg, factLabel))
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# map(vLabel -> adjDf[vLabel][i] = factLabel, factVars)
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# end
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# return adjDf
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# end
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# end
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# end
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# end

‎src/MetaGraphsDFG/MetaGraphsDFG.jl

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@@ -17,7 +17,6 @@ export getVariable, getFactor
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export updateVariable!, updateFactor!
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export deleteVariable!, deleteFactor!
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export getAdjacencyMatrix, getAdjacencyMatrixSparse
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export getAdjacencyMatrixDataFrame
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export getNeighbors
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export getSubgraphAroundNode
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export getSubgraph

‎test/FileDFG.jl

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using Revise
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using Test
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using DistributedFactorGraphs
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using IncrementalInference, RoME

‎test/interfaceTests.jl

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@@ -4,7 +4,7 @@ v2 = DFGVariable(:b)
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f1 = DFGFactor{Int, :Symbol}(:f1)
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#add tags for filters
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append!(v1.tags,[:VARIABLE, :POSE])
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append!(v1.tags, [:VARIABLE, :POSE])
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append!(v2.tags, [:VARIABLE, :LANDMARK])
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append!(f1.tags, [:FACTOR])
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# @test adjMat[1, 3] == 1
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@test symdiff(v_ll, [:a, :b, :orphan]) == Symbol[]
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@test symdiff(f_ll, [:f1, :f1, :f1]) == Symbol[]
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# Dataframe
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adjDf = getAdjacencyMatrixDataFrame(dfg)
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@test size(adjDf) == (1,4)
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end
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# Deletions

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