updating package tests

ccoffrin · ccoffrin · commit 500e5158766f · 2018-04-09T11:43:05.000-06:00
diff --git a/REQUIRE b/REQUIRE
@@ -1,6 +1,6 @@
-julia 0.5
+julia 0.6
 
-JuMP
+JuMP 0.17 0.19-
 Ipopt
 StatsBase
 
diff --git a/test/common.jl b/test/common.jl
@@ -30,3 +30,9 @@ gms = Dict(
         0.3 0.3 0.3 0.0
     ])
 )
+
+type AccuracyTest
+   formulation::GMLFormulation
+   samples::Int
+   threshold::Float64
+end
diff --git a/test/data/a_RISE_learned.csv b/test/data/a_RISE_learned.csv
@@ -1,3 +1,3 @@
--0.0005644539832557725,0.09935126129037157,0.19869841320186762
-0.09935126129037157,-0.0002266984556640061,0.29812280097539
-0.19869841320186762,0.29812280097539,0.0005569966953142167
+-0.0005644539832557185,0.09935126129037153,0.1986984132018676
+0.09935126129037153,-0.00022669845566399626,0.29812280097539
+0.1986984132018676,0.29812280097539,0.0005569966953141799
diff --git a/test/data/a_RPLE_learned.csv b/test/data/a_RPLE_learned.csv
@@ -1,3 +1,3 @@
--0.0005425346270890286,0.09970999479909189,0.19906643710899757
-0.09970999479909189,-0.0001925738531085063,0.2985018564677143
-0.19906643710899757,0.2985018564677143,0.0006267673266416884
+-0.0005425346270890555,0.0997099947990919,0.19906643710899757
+0.0997099947990919,-0.00019257385310852312,0.2985018564677143
+0.19906643710899757,0.2985018564677143,0.0006267673266417567
diff --git a/test/data/a_logRISE_learned.csv b/test/data/a_logRISE_learned.csv
@@ -1,3 +1,3 @@
--0.0005638412954481474,0.09864961976768588,0.1979715503187717
-0.09864961976768588,-0.0002262938917791257,0.2973788533199946
-0.1979715503187717,0.2973788533199946,0.0005568321250489606
+-0.0005638412954481692,0.09864961976768587,0.19797155031877167
+0.09864961976768587,-0.00022629389177909113,0.2973788533199946
+0.19797155031877167,0.2973788533199946,0.0005568321250488892
diff --git a/test/data/a_samples.csv b/test/data/a_samples.csv
@@ -1,6 +1,6 @@
-210958,1,1,1
 211272,-1,-1,-1
 77874,-1,-1,1
+210958,1,1,1
 94873,-1,1,-1
 77930,1,1,-1
 95194,1,-1,1
diff --git a/test/data/b_RISE_learned.csv b/test/data/b_RISE_learned.csv
@@ -1,3 +1,3 @@
-0.29906912597235497,0.09920005735507931,0.19840315292080507
+0.29906912597235497,0.09920005735507931,0.1984031529208051
 0.09920005735507931,0.20017839603579826,0.2997067938180983
-0.19840315292080507,0.2997067938180983,0.10172419294690785
+0.1984031529208051,0.2997067938180983,0.10172419294690786
diff --git a/test/data/b_RPLE_learned.csv b/test/data/b_RPLE_learned.csv
@@ -1,3 +1,3 @@
-0.29888227223880853,0.09962952609624617,0.1988130141632931
-0.09962952609624617,0.19994711123684367,0.30011318550161237
-0.1988130141632931,0.30011318550161237,0.10148067001314763
+0.29888227223880853,0.09962952609624615,0.19881301416329317
+0.09962952609624615,0.19994711123684375,0.30011318550161237
+0.19881301416329317,0.30011318550161237,0.10148067001314758
diff --git a/test/data/b_logRISE_learned.csv b/test/data/b_logRISE_learned.csv
@@ -1,3 +1,3 @@
-0.29932565980200276,0.09847287597229862,0.19765790276962936
-0.09847287597229862,0.20052801726243147,0.29895766126876183
-0.19765790276962936,0.29895766126876183,0.10215993754427957
+0.29932565980200276,0.09847287597229867,0.19765790276962925
+0.09847287597229867,0.20052801726243147,0.2989576612687618
+0.19765790276962925,0.2989576612687618,0.10215993754427957
diff --git a/test/data/b_samples.csv b/test/data/b_samples.csv
@@ -1,6 +1,6 @@
-351641,1,1,1
 106038,-1,-1,-1
 47689,-1,-1,1
+351641,1,1,1
 70850,-1,1,-1
 105741,1,1,-1
 105882,1,-1,1
diff --git a/test/data/c_RISE_learned.csv b/test/data/c_RISE_learned.csv
@@ -1,4 +1,4 @@
-0.0004092549434103876,0.09987938142982938,0.19819083178464497,0.2975739381687874
-0.09987938142982938,0.0003732717754814277,0.20012494836831032,0.2996582550612298
-0.19819083178464497,0.20012494836831032,-0.0009488424558981328,0.2989817094944933
-0.2975739381687874,0.2996582550612298,0.2989817094944933,9972176558675938e-20
+0.00040925494341038747,0.09987938142982936,0.19819083178464497,0.2975739381687875
+0.09987938142982936,0.000373271775481441,0.2001249483683103,0.2996582550612298
+0.19819083178464497,0.2001249483683103,-0.0009488424558981987,0.2989817094944933
+0.2975739381687875,0.2996582550612298,0.2989817094944933,9972176558672739e-20
diff --git a/test/data/c_RPLE_learned.csv b/test/data/c_RPLE_learned.csv
@@ -1,4 +1,4 @@
-0.0005385240448212047,0.10012809625304014,0.19845547684238668,0.29781033898431086
-0.10012809625304014,0.000476983234207395,0.20038949316971183,0.29989452714971593
-0.19845547684238668,0.20038949316971183,-0.0007394292622243018,0.2991942356689826
-0.29781033898431086,0.29989452714971593,0.2991942356689826,0.0002335634696685971
+0.0005385240448211936,0.10012809625304016,0.19845547684238674,0.29781033898431075
+0.10012809625304016,0.000476983234207359,0.20038949316971177,0.2998945271497159
+0.19845547684238674,0.20038949316971177,-0.0007394292622243516,0.2991942356689826
+0.29781033898431075,0.2998945271497159,0.2991942356689826,0.0002335634696685775
diff --git a/test/data/c_logRISE_learned.csv b/test/data/c_logRISE_learned.csv
@@ -1,4 +1,4 @@
-0.000410176794154942,0.09933937481233286,0.19763164224405444,0.2970411259059874
-0.09933937481233286,0.0003741341869226009,0.19956623317875433,0.2991259486183955
-0.19763164224405444,0.19956623317875433,-0.0009465428423822616,0.29848859546351125
-0.2970411259059874,0.2991259486183955,0.29848859546351125,0.00010081433690737961
+0.00041017679415491733,0.09933937481233288,0.19763164224405438,0.2970411259059874
+0.09933937481233288,0.0003741341869226271,0.1995662331787543,0.2991259486183955
+0.19763164224405438,0.1995662331787543,-0.0009465428423823187,0.2984885954635113
+0.2970411259059874,0.2991259486183955,0.2984885954635113,0.00010081433690734084
diff --git a/test/data/c_samples.csv b/test/data/c_samples.csv
@@ -1,16 +1,16 @@
 60299,-1,1,-1,-1
 50008,1,1,-1,1
 201615,-1,-1,-1,-1
-33348,1,-1,-1,1
 33413,1,1,1,-1
+33348,1,-1,-1,1
 33315,-1,1,-1,1
 33326,-1,-1,-1,1
 33397,-1,1,1,-1
 49384,-1,-1,1,-1
 27464,1,1,-1,-1
 33450,1,-1,1,-1
-61066,-1,1,1,1
 60546,1,-1,1,1
+61066,-1,1,1,1
 201302,1,1,1,1
 27312,-1,-1,1,1
 60755,1,-1,-1,-1
diff --git a/test/runtests.jl b/test/runtests.jl
@@ -4,7 +4,8 @@ using Base.Test
 
 include("common.jl")
 
-#=
+@testset "GraphicalModelLearning" begin
+
 @testset "factor graphs" begin
     for (name, gm) in gms
         matrix = convert(Array{Float64,2}, gm)
@@ -27,6 +28,7 @@ end
         gm_tmp.order = 3
         srand(0) # fix random number generator
         samples = sample(gm_tmp, gibbs_test_samples)
+        #base_samples = readcsv("data/$(name)_samples.csv", Int64)
         base_samples = readcsv("data/$(name)_samples.csv")
         @test isapprox(samples, base_samples)
     end
@@ -95,12 +97,6 @@ end
 end
 
 
-type AccuracyTest
-   formulation::GMLFormulation
-   samples::Int
-   threshold::Float64
-end
-
 accuracy_tests = [
     AccuracyTest(RISE(),     1000, 0.15)
     AccuracyTest(logRISE(),  1000, 0.15)
@@ -124,7 +120,7 @@ srand(0) # fix random number generator
         end
     end
 end
-=#
+
 
 @testset "inverse multi-body formulations" begin
 
@@ -194,3 +190,5 @@ srand(0) # fix random number generator
     @test maximum(err) <= 0.01
 end
 
+
+end
