Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/15628#discussion_r107835989
--- Diff:
mllib-local/src/test/scala/org/apache/spark/ml/linalg/MatricesSuite.scala ---
@@ -160,22 +160,395 @@ class MatricesSuite extends SparkMLFunSuite {
assert(sparseMat.values(2) === 10.0)
}
- test("toSparse, toDense") {
- val m = 3
- val n = 2
- val values = Array(1.0, 2.0, 4.0, 5.0)
- val allValues = Array(1.0, 2.0, 0.0, 0.0, 4.0, 5.0)
- val colPtrs = Array(0, 2, 4)
- val rowIndices = Array(0, 1, 1, 2)
+ test("dense to dense") {
+ /*
+ dm1 = 4.0 2.0 -8.0
+ -1.0 7.0 4.0
+
+ dm2 = 5.0 -9.0 4.0
+ 1.0 -3.0 -8.0
+ */
+ val dm1 = new DenseMatrix(2, 3, Array(4.0, -1.0, 2.0, 7.0, -8.0, 4.0))
+ val dm2 = new DenseMatrix(2, 3, Array(5.0, -9.0, 4.0, 1.0, -3.0,
-8.0), isTransposed = true)
+
+ val dm3 = dm1.toDense
+ assert(dm3 === dm1)
+ assert(!dm3.isTransposed)
+ assert(dm3.values.equals(dm1.values))
+
+ val dm4 = dm1.toDenseRowMajor
+ assert(dm4 === dm1)
+ assert(dm4.isTransposed)
+ assert(dm4.values === Array(4.0, 2.0, -8.0, -1.0, 7.0, 4.0))
+
+ val dm5 = dm2.toDenseColMajor
+ assert(dm5 === dm2)
+ assert(!dm5.isTransposed)
+ assert(dm5.values === Array(5.0, 1.0, -9.0, -3.0, 4.0, -8.0))
+
+ val dm6 = dm2.toDenseRowMajor
+ assert(dm6 === dm2)
+ assert(dm6.isTransposed)
+ assert(dm6.values.equals(dm2.values))
+
+ val dm7 = dm1.toDenseRowMajor
+ assert(dm7 === dm1)
+ assert(dm7.isTransposed)
+ assert(dm7.values === Array(4.0, 2.0, -8.0, -1.0, 7.0, 4.0))
+
+ val dm8 = dm1.toDenseColMajor
+ assert(dm8 === dm1)
+ assert(!dm8.isTransposed)
+ assert(dm8.values.equals(dm1.values))
+
+ val dm9 = dm2.toDense
+ assert(dm9 === dm2)
+ assert(dm9.isTransposed)
+ assert(dm9.values.equals(dm2.values))
+ }
- val spMat1 = new SparseMatrix(m, n, colPtrs, rowIndices, values)
- val deMat1 = new DenseMatrix(m, n, allValues)
+ test("dense to sparse") {
+ /*
+ dm1 = 0.0 4.0 5.0
+ 0.0 2.0 0.0
+
+ dm2 = 0.0 4.0 5.0
+ 0.0 2.0 0.0
- val spMat2 = deMat1.toSparse
- val deMat2 = spMat1.toDense
+ dm3 = 0.0 0.0 0.0
+ 0.0 0.0 0.0
+ */
+ val dm1 = new DenseMatrix(2, 3, Array(0.0, 0.0, 4.0, 2.0, 5.0, 0.0))
+ val dm2 = new DenseMatrix(2, 3, Array(0.0, 4.0, 5.0, 0.0, 2.0, 0.0),
isTransposed = true)
+ val dm3 = new DenseMatrix(2, 3, Array(0.0, 0.0, 0.0, 0.0, 0.0, 0.0))
+
+ val sm1 = dm1.toSparseColMajor
+ assert(sm1 === dm1)
+ assert(!sm1.isTransposed)
+ assert(sm1.values === Array(4.0, 2.0, 5.0))
+
+ val sm2 = dm1.toSparseRowMajor
+ assert(sm2 === dm1)
+ assert(sm2.isTransposed)
+ assert(sm2.values === Array(4.0, 5.0, 2.0))
+
+ val sm3 = dm2.toSparseColMajor
+ assert(sm3 === dm2)
+ assert(!sm3.isTransposed)
+ assert(sm3.values === Array(4.0, 2.0, 5.0))
+
+ val sm4 = dm2.toSparseRowMajor
+ assert(sm4 === dm2)
+ assert(sm4.isTransposed)
+ assert(sm4.values === Array(4.0, 5.0, 2.0))
+
+ val sm5 = dm3.toSparseColMajor
+ assert(sm5 === dm3)
+ assert(sm5.values === Array.empty[Double])
+ assert(!sm5.isTransposed)
+
+ val sm6 = dm3.toSparseRowMajor
+ assert(sm6 === dm3)
+ assert(sm6.values === Array.empty[Double])
+ assert(sm6.isTransposed)
+
+ val sm7 = dm1.toSparse
+ assert(sm7 === dm1)
+ assert(sm7.values === Array(4.0, 2.0, 5.0))
+ assert(!sm7.isTransposed)
+
+ val sm8 = dm1.toSparseColMajor
+ assert(sm8 === dm1)
+ assert(sm8.values === Array(4.0, 2.0, 5.0))
+ assert(!sm8.isTransposed)
+
+ val sm9 = dm2.toSparseRowMajor
+ assert(sm9 === dm2)
+ assert(sm9.values === Array(4.0, 5.0, 2.0))
+ assert(sm9.isTransposed)
+
+ val sm10 = dm2.toSparse
+ assert(sm10 === dm2)
+ assert(sm10.values === Array(4.0, 5.0, 2.0))
+ assert(sm10.isTransposed)
+ }
+
+ test("sparse to sparse") {
+ /*
+ sm1 = sm2 = sm3 = sm4 = 0.0 4.0 5.0
+ 0.0 2.0 0.0
+ smZeros = 0.0 0.0 0.0
+ 0.0 0.0 0.0
+ */
+ val sm1 = new SparseMatrix(2, 3, Array(0, 0, 2, 3), Array(0, 1, 0),
Array(4.0, 2.0, 5.0))
+ val sm2 = new SparseMatrix(2, 3, Array(0, 2, 3), Array(1, 2, 1),
Array(4.0, 5.0, 2.0),
+ isTransposed = true)
+ val sm3 = new SparseMatrix(2, 3, Array(0, 0, 2, 4), Array(0, 1, 0, 1),
+ Array(4.0, 2.0, 5.0, 0.0))
+ val sm4 = new SparseMatrix(2, 3, Array(0, 2, 4), Array(1, 2, 1, 2),
+ Array(4.0, 5.0, 2.0, 0.0), isTransposed = true)
+ val smZeros = new SparseMatrix(2, 3, Array(0, 2, 4, 6), Array(0, 1, 0,
1, 0, 1),
+ Array(0.0, 0.0, 0.0, 0.0, 0.0, 0.0))
+
+ val sm5 = sm1.toSparseRowMajor
+ assert(sm5 === sm1)
+ assert(sm5.isTransposed)
+ assert(sm5.values === Array(4.0, 5.0, 2.0))
+
+ val sm6 = sm1.toSparseColMajor
+ assert(sm6 === sm1)
+ assert(!sm6.isTransposed)
+ assert(sm6.values.equals(sm1.values))
+
+ val sm7 = sm2.toSparseColMajor
+ assert(sm7 === sm2)
+ assert(!sm7.isTransposed)
+ assert(sm7.values === Array(4.0, 2.0, 5.0))
+
+ val sm8 = sm2.toSparseRowMajor
+ assert(sm8 === sm2)
+ assert(sm8.isTransposed)
+ assert(sm8.values.equals(sm2.values))
+
+ val sm9 = sm3.toSparse
+ assert(sm9 === sm3)
+ assert(sm9.values === Array(4.0, 2.0, 5.0))
+ assert(!sm9.isTransposed)
+
+ val sm10 = sm3.toSparseRowMajor
+ assert(sm10 === sm3)
+ assert(sm10.values === Array(4.0, 5.0, 2.0))
+ assert(sm10.isTransposed)
+
+ val sm11 = sm4.toSparseRowMajor
+ assert(sm11 === sm4)
+ assert(sm11.values === Array(4.0, 5.0, 2.0))
+ assert(sm11.isTransposed)
+
+ val sm12 = sm4.toSparse
+ assert(sm12 === sm4)
+ assert(sm12.values === Array(4.0, 5.0, 2.0))
+ assert(sm12.isTransposed)
+
+ val sm13 = smZeros.toSparse
+ assert(sm13 === smZeros)
+ assert(sm13.values === Array.empty[Double])
+ assert(!sm13.isTransposed)
+
+ val sm14 = sm4.toSparseColMajor
+ assert(sm14 === sm4)
+ assert(sm14.values === Array(4.0, 2.0, 5.0))
+ assert(!sm14.isTransposed)
+
+ val sm15 = smZeros.toSparseColMajor
+ assert(sm15 === smZeros)
+ assert(sm15.values === Array.empty[Double])
+ assert(!sm15.isTransposed)
+
+ val sm16 = sm3.toSparseRowMajor
+ assert(sm16 === sm4)
+ assert(sm16.values === Array(4.0, 5.0, 2.0))
+ assert(sm16.isTransposed)
+
+ val sm17 = smZeros.toSparseRowMajor
+ assert(sm17 === smZeros)
+ assert(sm17.values === Array.empty[Double])
+ assert(sm17.isTransposed)
+ }
+
+ test("sparse to dense") {
+ /*
+ sm1 = sm2 = 0.0 4.0 5.0
+ 0.0 2.0 0.0
+
+ sm3 = 0.0 0.0 0.0
+ 0.0 0.0 0.0
+ */
+ val sm1 = new SparseMatrix(2, 3, Array(0, 0, 2, 3), Array(0, 1, 0),
Array(4.0, 2.0, 5.0))
+ val sm2 = new SparseMatrix(2, 3, Array(0, 2, 3), Array(1, 2, 1),
Array(4.0, 5.0, 2.0),
+ isTransposed = true)
+ val sm3 = new SparseMatrix(2, 3, Array(0, 0, 0, 0), Array.empty[Int],
Array.empty[Double])
+
+ val dm1 = sm1.toDense
+ assert(dm1 === sm1)
+ assert(!dm1.isTransposed)
+ assert(dm1.values === Array(0.0, 0.0, 4.0, 2.0, 5.0, 0.0))
+
+ val dm2 = sm1.toDenseRowMajor
+ assert(dm2 === sm1)
+ assert(dm2.isTransposed)
+ assert(dm2.values === Array(0.0, 4.0, 5.0, 0.0, 2.0, 0.0))
+
+ val dm3 = sm2.toDense
+ assert(dm3 === sm2)
+ assert(dm3.isTransposed)
+ assert(dm3.values === Array(0.0, 4.0, 5.0, 0.0, 2.0, 0.0))
+
+ val dm4 = sm2.toDenseRowMajor
+ assert(dm4 === sm2)
+ assert(dm4.isTransposed)
+ assert(dm4.values === Array(0.0, 4.0, 5.0, 0.0, 2.0, 0.0))
+
+ val dm5 = sm3.toDense
+ assert(dm5 === sm3)
+ assert(!dm5.isTransposed)
+ assert(dm5.values === Array.fill(6)(0.0))
+
+ val dm6 = sm2.toDenseColMajor
+ assert(dm6 === sm2)
+ assert(!dm6.isTransposed)
+ assert(dm6.values === Array(0.0, 0.0, 4.0, 2.0, 5.0, 0.0))
+
+ val dm7 = sm2.toDenseRowMajor
+ assert(dm7 === sm2)
+ assert(dm7.isTransposed)
+ assert(dm7.values === Array(0.0, 4.0, 5.0, 0.0, 2.0, 0.0))
+ }
+
+ test("compressed dense") {
+ /*
+ dm1 = 1.0 0.0 0.0 0.0
+ 1.0 0.0 0.0 0.0
+ 0.0 0.0 0.0 0.0
+
+ dm2 = 1.0 1.0 0.0 0.0
+ 0.0 0.0 0.0 0.0
+ 0.0 0.0 0.0 0.0
+ */
+ // this should compress to a sparse matrix
+ val dm1 = new DenseMatrix(3, 4, Array.fill(2)(1.0) ++
Array.fill(10)(0.0))
+
+ // optimal compression layout is row major since numRows < numCols
+ val cm1 = dm1.compressed.asInstanceOf[SparseMatrix]
+ assert(cm1 === dm1)
+ assert(cm1.isTransposed)
+ assert(cm1.getSizeInBytes <= dm1.getSizeInBytes)
+
+ // force compressed column major
+ val cm2 = dm1.compressedColMajor.asInstanceOf[SparseMatrix]
+ assert(cm2 === dm1)
+ assert(!cm2.isTransposed)
+ assert(cm2.getSizeInBytes <= dm1.getSizeInBytes)
--- End diff --
ditto
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