@@ -376,7 +376,7 @@ private[spark] object BLAS extends Serializable with Logging {
376376 }
377377 } else {
378378 // Scale matrix first if `beta` is not equal to 0.0
379- if (beta != 0.0 ){
379+ if (beta != 0.0 ) {
380380 f2jBLAS.dscal(C .values.length, beta, C .values, 1 )
381381 }
382382 // Perform matrix multiplication and add to C. The rows of A are multiplied by the columns of
@@ -391,7 +391,7 @@ private[spark] object BLAS extends Serializable with Logging {
391391 var i = Acols (colCounterForA)
392392 val indEnd = Acols (colCounterForA + 1 )
393393 val Bval = Bvals (Bstart + colCounterForA) * alpha
394- while (i < indEnd){
394+ while (i < indEnd) {
395395 Cvals (Cstart + Arows (i)) += Avals (i) * Bval
396396 i += 1
397397 }
@@ -403,11 +403,11 @@ private[spark] object BLAS extends Serializable with Logging {
403403 while (colCounterForB < nB) {
404404 var colCounterForA = 0 // The column of A to multiply with the row of B
405405 val Cstart = colCounterForB * mA
406- while (colCounterForA < kA){
406+ while (colCounterForA < kA) {
407407 var i = Acols (colCounterForA)
408408 val indEnd = Acols (colCounterForA + 1 )
409409 val Bval = B (colCounterForB, colCounterForA) * alpha
410- while (i < indEnd){
410+ while (i < indEnd) {
411411 Cvals (Cstart + Arows (i)) += Avals (i) * Bval
412412 i += 1
413413 }
@@ -506,38 +506,38 @@ private[spark] object BLAS extends Serializable with Logging {
506506 val xValues = x.values
507507 val yValues = y.values
508508
509- val mA : Int = if (! trans) A .numRows else A .numCols
510- val nA : Int = if (! trans) A .numCols else A .numRows
509+ val mA : Int = if (! trans) A .numRows else A .numCols
510+ val nA : Int = if (! trans) A .numCols else A .numRows
511511
512512 val Avals = A .values
513513 val Arows = if (! trans) A .rowIndices else A .colPtrs
514514 val Acols = if (! trans) A .colPtrs else A .rowIndices
515515 // Slicing is easy in this case. This is the optimal multiplication setting for sparse matrices
516- if (trans){
516+ if (trans) {
517517 var rowCounter = 0
518- while (rowCounter < mA){
518+ while (rowCounter < mA) {
519519 var i = Arows (rowCounter)
520520 val indEnd = Arows (rowCounter + 1 )
521521 var sum = 0.0
522- while (i < indEnd){
522+ while (i < indEnd) {
523523 sum += Avals (i) * xValues(Acols (i))
524524 i += 1
525525 }
526- yValues(rowCounter) = beta * yValues(rowCounter) + sum * alpha
526+ yValues(rowCounter) = beta * yValues(rowCounter) + sum * alpha
527527 rowCounter += 1
528528 }
529529 } else {
530530 // Scale vector first if `beta` is not equal to 0.0
531- if (beta != 0.0 ){
531+ if (beta != 0.0 ) {
532532 scal(beta, y)
533533 }
534534 // Perform matrix-vector multiplication and add to y
535535 var colCounterForA = 0
536- while (colCounterForA < nA){
536+ while (colCounterForA < nA) {
537537 var i = Acols (colCounterForA)
538538 val indEnd = Acols (colCounterForA + 1 )
539539 val xVal = xValues(colCounterForA) * alpha
540- while (i < indEnd){
540+ while (i < indEnd) {
541541 val rowIndex = Arows (i)
542542 yValues(rowIndex) += Avals (i) * xVal
543543 i += 1
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