Remove commended code + new test case

btwardow · Aug 21, 2015 · 9550ce8 · 9550ce8
1 parent f371f4b
commit 9550ce8
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Showing 4 changed files with 20 additions and 38 deletions.
diff --git a/src/fm.jl b/src/fm.jl
@@ -1,34 +1,3 @@
-#function fmPredictInstance(fm::FMModel, x::FMVector)
-#   result = 0.0
-#   fSum = zeros(fm.num_factor)
-#   sum_sqr = zeros(fm.num_factor)
-#   if(fm.k0)
-#       result += fm.w0
-#   end
-#   if(fm.k1)
-#       for i in 1:length(x)
-#            if x[i] != 0.0
-#                result += fm.w[i] * x[i] 
-#            end
-#       end
-#   end
-#   for f in 1:fm.num_factor
-#       for i in 1:length(x)
-#            if x[i] != 0.0
-#               d = fm.V[f,i] * x[i]
-#               fSum[f] += d
-#               sum_sqr[f] += d*d
-#            end
-#       end
-#       result += 0.5 * (fSum[f]*fSum[f] - sum_sqr[f])
-#   end
-#    #scale prediction
-#    result = min(result, fm.targetMax)
-#    result = max(result, fm.targetMin)
-#   (result, fSum, sum_sqr)
-#end
-
-
 function fmPredictInstance!(fm::FMModel, idx::Array{Int64,1}, x::Array{FMFloat,1}, fSum::Array{FMFloat}, sum_sqr::Array{FMFloat})
    fill!(fSum, .0)
    fill!(sum_sqr, .0)
@@ -141,9 +110,11 @@ function fmTrain(
     if method == :sgd
         fmTrainSGD!(fm, X, y, iterationNum, alpha)
     else
-        error("FM Model learning method: $method not implemented!")
-        error("If You think it should be, create appropriate Pull Request")
-        error("or contact me - bartlomiej.twardowski@gmail.com")
+        error("""
+        FM Model learning method: $method not implemented!
+        If You think it should be, create appropriate Pull Request
+        or contact me - bartlomiej.twardowski@gmail.com
+        """)
     end
 
     fm

diff --git a/test/ml100k.jl b/test/ml100k.jl
@@ -4,9 +4,9 @@ using FactorizationMachines
 using Base.Test
 
 info("Running tests on ml-100k dataset...")
-(ml100kTrain, ml100kTrainRatings) = @time fmReadLibSVM("test/data/ml-100k.train.libfm")
+(ml100kTrain, ml100kTrainRatings) = @time fmReadLibSVM("data/ml-100k.train.libfm")
 info("Train dim: $(size(ml100kTrain))")
-(ml100kTest, ml100kTestRatings) = @time fmReadLibSVM("test/data/ml-100k.test.libfm")
+(ml100kTest, ml100kTestRatings) = @time fmReadLibSVM("data/ml-100k.test.libfm")
 info("Test dim: $(size(ml100kTest))")
 
 info("Test ML-100K - Training model...")
@@ -20,9 +20,9 @@ p = @time fmPredict(fmMl100k, ml100kTest)
 rmse = sqrt(sum((p-ml100kTestRatings).^2)/length(p))
 info("RMSE on test data: $rmse") 
 
-if isfile("test/data/ml-100k.output.libfm")
+if isfile("data/ml-100k.output.libfm")
     info("File with output from libfm exists. Bencharking to its result...")
-    libfmOutput = readcsv("test/data/ml-100k.output.libfm")
+    libfmOutput = readcsv("data/ml-100k.output.libfm")
     rmseWithLibfm = sqrt(sum((p-libfmOutput).^2)/length(p))
     info("RMSE with Libfm output: $rmseWithLibfm")
 end

diff --git a/test/runtests.jl b/test/runtests.jl
@@ -2,4 +2,5 @@ using FactorizationMachines
 using Base.Test
 
 include("test_fm_readlibsvm.jl")
+include("test_fm.jl")
 include("test_reco.jl")
diff --git a/test/test_fm.jl b/test/test_fm.jl
@@ -0,0 +1,10 @@
+module TestFactorizationMachines
+
+using Base.Test
+
+info("Testing - unknow learning method should throw an exception")
+X = sparse(randn(10, 5))
+y = randn(5)
+@test_throws(Exception, fmTrain(X,y,:unknowMethod))
+
+end