Class MatrixBlock
- java.lang.Object
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- org.apache.sysds.runtime.matrix.data.MatrixValue
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- org.apache.sysds.runtime.matrix.data.MatrixBlock
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- All Implemented Interfaces:
Externalizable,Serializable,Comparable,org.apache.hadoop.io.Writable,org.apache.hadoop.io.WritableComparable,CacheBlock
- Direct Known Subclasses:
CompressedMatrixBlock
public class MatrixBlock extends MatrixValue implements CacheBlock, Externalizable
- See Also:
- Serialized Form
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Nested Class Summary
Nested Classes Modifier and Type Class Description static classMatrixBlock.SparsityEstimate-
Nested classes/interfaces inherited from class org.apache.sysds.runtime.matrix.data.MatrixValue
MatrixValue.CellIndex
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Field Summary
Fields Modifier and Type Field Description static booleanCONVERT_MCSR_TO_CSR_ON_DEEP_SERIALIZEstatic SparseBlock.TypeDEFAULT_INPLACE_SPARSEBLOCKstatic SparseBlock.TypeDEFAULT_SPARSEBLOCKstatic intHEADER_SIZEstatic doubleMAX_SHALLOW_SERIALIZE_OVERHEADstatic doubleSPARSITY_TURN_POINTstatic intULTRA_SPARSE_BLOCK_NNZstatic doubleULTRA_SPARSITY_TURN_POINTstatic doubleULTRA_SPARSITY_TURN_POINT2
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Constructor Summary
Constructors Constructor Description MatrixBlock()MatrixBlock(double val)MatrixBlock(int rl, int cl, boolean sp)MatrixBlock(int rl, int cl, boolean sp, long estnnz)MatrixBlock(int rl, int cl, double val)MatrixBlock(int rl, int cl, double[] vals)MatrixBlock(int rl, int cl, long estnnz)MatrixBlock(int rl, int cl, long nnz, SparseBlock sblock)Constructs a sparseMatrixBlockwith a given instance of aSparseBlockMatrixBlock(int rl, int cl, DenseBlock dBlock)MatrixBlock(MatrixBlock that)MatrixBlock(MatrixBlock that, boolean sp)MatrixBlock(MatrixBlock that, SparseBlock.Type stype, boolean deep)
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description MatrixBlockaggregateBinaryOperations(MatrixBlock m1, MatrixBlock m2, MatrixBlock ret, AggregateBinaryOperator op)MatrixBlockaggregateBinaryOperations(MatrixBlock m1, MatrixBlock m2, AggregateBinaryOperator op)MatrixBlockaggregateTernaryOperations(MatrixBlock m1, MatrixBlock m2, MatrixBlock m3, MatrixBlock ret, AggregateTernaryOperator op, boolean inCP)MatrixBlockaggregateUnaryOperations(AggregateUnaryOperator op, MatrixValue result, int blen, MatrixIndexes indexesIn)MatrixBlockaggregateUnaryOperations(AggregateUnaryOperator op, MatrixValue result, int blen, MatrixIndexes indexesIn, boolean inCP)voidallocateAndResetSparseBlock(boolean clearNNZ, SparseBlock.Type stype)MatrixBlockallocateBlock()Future<MatrixBlock>allocateBlockAsync()MatrixBlockallocateDenseBlock()booleanallocateDenseBlock(boolean clearNNZ)voidallocateDenseBlockUnsafe(int rl, int cl)This should be called only in the read and write functions for CP This function should be called before calling any setValueDenseUnsafe()booleanallocateSparseRowsBlock()booleanallocateSparseRowsBlock(boolean clearNNZ)MatrixBlockappend(MatrixBlock[] that, MatrixBlock result, boolean cbind)MatrixBlockappend(MatrixBlock that, MatrixBlock ret)MatrixBlockappend(MatrixBlock that, MatrixBlock ret, boolean cbind)voidappend(MatrixValue v2, ArrayList<IndexedMatrixValue> outlist, int blen, boolean cbind, boolean m2IsLast, int nextNCol)voidappendRow(int r, SparseRow row)voidappendRow(int r, SparseRow row, boolean deep)voidappendRowToSparse(SparseBlock dest, MatrixBlock src, int i, int rowoffset, int coloffset, boolean deep)voidappendToSparse(MatrixBlock that, int rowoffset, int coloffset)voidappendValue(int r, int c, double v)Append value is only used when values are appended at the end of each row for the sparse representation This can only be called, when the caller knows the access pattern of the blockvoidappendValuePlain(int r, int c, double v)MatrixBlockbinaryOperations(BinaryOperator op, MatrixValue thatValue)MatrixBlockbinaryOperations(BinaryOperator op, MatrixValue thatValue, MatrixValue result)MatrixBlockbinaryOperationsInPlace(BinaryOperator op, MatrixValue thatValue)MatrixBlockchainMatrixMultOperations(MatrixBlock v, MatrixBlock w, MatrixBlock out, MapMultChain.ChainType ctype)MatrixBlockchainMatrixMultOperations(MatrixBlock v, MatrixBlock w, MatrixBlock out, MapMultChain.ChainType ctype, int k)static voidcheckCMOperations(MatrixBlock mb, CMOperator op)voidcheckDimensionsForAppend(MatrixBlock[] in, boolean cbind)voidcheckNaN()Checks for existing NaN values in the matrix block.voidcheckNonZeros()Basic debugging primitive to check correctness of nnz.voidcheckSparseRows()voidcheckSparseRows(int rl, int ru)Basic debugging primitive to check sparse block column ordering.voidcleanupBlock(boolean dense, boolean sparse)Allows to cleanup all previously allocated sparserows or denseblocks.CM_COV_ObjectcmOperations(CMOperator op)CM_COV_ObjectcmOperations(CMOperator op, MatrixBlock weights)MatrixBlockcolMax()Wrapper method for reduceall-colMin of a matrix.MatrixBlockcolMin()Wrapper method for reduceall-colMin of a matrix.MatrixBlockcolSum()Wrapper method for single threaded reduceall-colSum of a matrix.voidcompactEmptyBlock()Free unnecessarily allocated empty block.intcompareTo(Object arg0)static doublecomputeIQMCorrection(double sum, double sum_wt, double q25Part, double q25Val, double q75Part, double q75Val)booleancontainsValue(double pattern)voidcopy(int rl, int ru, int cl, int cu, MatrixBlock src, boolean awareDestNZ)In-place copy of matrix src into the index range of the existing current matrix.voidcopy(MatrixValue thatValue)Copy that MatrixValue into this MatrixValue.voidcopy(MatrixValue thatValue, boolean sp)Copy that MatrixValue into this MatrixValue.MatrixBlockcopyShallow(MatrixBlock that)CM_COV_ObjectcovOperations(COVOperator op, MatrixBlock that)CM_COV_ObjectcovOperations(COVOperator op, MatrixBlock that, MatrixBlock weights)voidctableOperations(Operator op, double scalarThat, double scalarThat2, CTableMap resultMap, MatrixBlock resultBlock)D = ctable(A,v2,w) this <- A; scalar_that <- v2; scalar_that2 <- w; result <- D (i1,j1,v1) from input1 (this) (v2) from sclar_input2 (scalarThat) (w) from scalar_input3 (scalarThat2)voidctableOperations(Operator op, double scalarThat, MatrixValue that2Val, CTableMap resultMap, MatrixBlock resultBlock)D = ctable(A,v2,W) this <- A; scalarThat <- v2; that2 <- W; result <- D (i1,j1,v1) from input1 (this) (v2) from sclar_input2 (scalarThat) (i3,j3,w) from input3 (that2)voidctableOperations(Operator op, MatrixIndexes ix1, double scalarThat, boolean left, int blen, CTableMap resultMap, MatrixBlock resultBlock)Specific ctable case of ctable(seq(...),X), where X is the only matrix input.voidctableOperations(Operator op, MatrixValue thatVal, double scalarThat2, boolean ignoreZeros, CTableMap resultMap, MatrixBlock resultBlock)D = ctable(A,B,w) this <- A; that <- B; scalar_that2 <- w; result <- D (i1,j1,v1) from input1 (this) (i1,j1,v2) from input2 (that) (w) from scalar_input3 (scalarThat2) NOTE: This method supports both vectors and matrices.voidctableOperations(Operator op, MatrixValue thatVal, MatrixValue that2Val, CTableMap resultMap)D = ctable(A,B,W) this <- A; that <- B; that2 <- W; result <- D (i1,j1,v1) from input1 (this) (i1,j1,v2) from input2 (that) (i1,j1,w) from input3 (that2)voidctableOperations(Operator op, MatrixValue thatVal, MatrixValue that2Val, CTableMap resultMap, MatrixBlock resultBlock)MatrixBlockctableSeqOperations(MatrixValue thatMatrix, double thatScalar, MatrixBlock resultBlock)D = ctable(seq,A,w) this <- seq; thatMatrix <- A; thatScalar <- w; result <- D (i1,j1,v1) from input1 (this) (i1,j1,v2) from input2 (that) (w) from scalar_input3 (scalarThat2)MatrixBlockctableSeqOperations(MatrixValue thatMatrix, double thatScalar, MatrixBlock ret, boolean updateClen)voiddenseToSparse(boolean allowCSR)voiddropLastRowsOrColumns(Types.CorrectionLocationType correctionLocation)booleanequals(Object arg0)longestimateSizeDenseInMemory()static longestimateSizeDenseInMemory(long nrows, long ncols)longestimateSizeInMemory()static longestimateSizeInMemory(long nrows, long ncols, double sparsity)longestimateSizeOnDisk()static longestimateSizeOnDisk(long nrows, long ncols, long nnz)longestimateSizeSparseInMemory()static longestimateSizeSparseInMemory(long nrows, long ncols, double sparsity)static longestimateSizeSparseInMemory(long nrows, long ncols, double sparsity, boolean allowCSR)static longestimateSizeSparseInMemory(long nrows, long ncols, double sparsity, SparseBlock.Type stype)longestimateSizeSparseInMemory(SparseBlock.Type stype)booleanevalSparseFormatInMemory()Evaluates if this matrix block should be in sparse format in memory.booleanevalSparseFormatInMemory(boolean allowCSR)static booleanevalSparseFormatInMemory(long nrows, long ncols, long nnz)Evaluates if a matrix block with the given characteristics should be in sparse format in memory.static booleanevalSparseFormatInMemory(long nrows, long ncols, long nnz, boolean allowCSR)static booleanevalSparseFormatInMemory(DataCharacteristics dc)booleanevalSparseFormatOnDisk()Evaluates if this matrix block should be in sparse format on disk.static booleanevalSparseFormatOnDisk(long nrows, long ncols, long nnz)Evaluates if a matrix block with the given characteristics should be in sparse format on disk (or in any other serialized representation).voidexamSparsity()Evaluates if this matrix block should be in sparse format in memory.voidexamSparsity(boolean allowCSR)Evaluates if this matrix block should be in sparse format in memory.MatrixBlockextractTriangular(MatrixBlock ret, boolean lower, boolean diag, boolean values)DataCharacteristicsgetDataCharacteristics()DenseBlockgetDenseBlock()double[]getDenseBlockValues()doublegetDouble(int r, int c)Returns the double value at the passed row and column.doublegetDoubleNaN(int r, int c)Returns the double value at the passed row and column.longgetExactSerializedSize()Get the exact serialized size in bytes of the cache block.longgetExactSizeOnDisk()NOTE: The used estimates must be kept consistent with the respective write functions.static longgetHeaderSize()longgetInMemorySize()Get the in-memory size in bytes of the cache block.longgetLength()longgetNonZeros()intgetNumColumns()intgetNumRows()SparseBlockgetSparseBlock()Iterator<IJV>getSparseBlockIterator()Iterator<IJV>getSparseBlockIterator(int rl, int ru)doublegetSparsity()StringgetString(int r, int c)Returns the string of the value at the passed row and column.doublegetValue(int r, int c)doublegetValueDenseUnsafe(int r, int c)MatrixBlockgroupedAggOperations(MatrixValue tgt, MatrixValue wghts, MatrixValue ret, int ngroups, Operator op)Invocation from CP instructions.MatrixBlockgroupedAggOperations(MatrixValue tgt, MatrixValue wghts, MatrixValue ret, int ngroups, Operator op, int k)inthashCode()voidincrementalAggregate(AggregateOperator aggOp, MatrixValue newWithCorrection)voidincrementalAggregate(AggregateOperator aggOp, MatrixValue correction, MatrixValue newWithCorrection, boolean deep)voidinit(double[][] arr, int r, int c)NOTE: This method is designed only for dense representation.voidinit(double[] arr, int r, int c)NOTE: This method is designed only for dense representation.doubleinterQuartileMean()booleanisAllocated()booleanisEmpty()booleanisEmptyBlock()booleanisEmptyBlock(boolean safe)booleanisInSparseFormat()Returns the current representation (true for sparse).booleanisShallowSerialize()Indicates if the cache block is subject to shallow serialized, which is generally true if in-memory size and serialized size are almost identical allowing to avoid unnecessary deep serialize.booleanisShallowSerialize(boolean inclConvert)Indicates if the cache block is subject to shallow serialized, which is generally true if in-memory size and serialized size are almost identical allowing to avoid unnecessary deep serialize.booleanisSparsePermutationMatrix()booleanisThreadSafe()Indicates if concurrent modifications of disjoint rows are thread-safe.static booleanisThreadSafe(boolean sparse)Indicates if concurrent modifications of disjoint rows are thread-safe.booleanisUltraSparse()booleanisUltraSparse(boolean checkNnz)booleanisVector()MatrixBlockleftIndexingOperations(ScalarObject scalar, int rl, int cl, MatrixBlock ret, MatrixObject.UpdateType update)Explicitly allow left indexing for scalars.MatrixBlockleftIndexingOperations(MatrixBlock rhsMatrix, int rl, int ru, int cl, int cu, MatrixBlock ret, MatrixObject.UpdateType update)MatrixBlockleftIndexingOperations(MatrixBlock rhsMatrix, IndexRange ixrange, MatrixBlock ret, MatrixObject.UpdateType update)doublemax()Wrapper method for reduceall-max of a matrix.doublemean()Wrapper method for reduceall-mean of a matrix.doublemedian()voidmerge(CacheBlock that, boolean appendOnly)Merge the given block into the current block.voidmerge(MatrixBlock that, boolean appendOnly)Merge disjoint: merges all non-zero values of the given input into the current matrix block.voidmerge(MatrixBlock that, boolean appendOnly, boolean par)voidmerge(MatrixBlock that, boolean appendOnly, boolean par, boolean deep)doublemin()Wrapper method for reduceall-min of a matrix.doubleminNonZero()Utility function for computing the min non-zero value.static MatrixBlocknaryOperations(Operator op, MatrixBlock[] matrices, ScalarObject[] scalars, MatrixBlock ret)voidpermutationMatrixMultOperations(MatrixValue m2Val, MatrixValue out1Val, MatrixValue out2Val)voidpermutationMatrixMultOperations(MatrixValue m2Val, MatrixValue out1Val, MatrixValue out2Val, int k)doublepickValue(double quantile)doublepickValue(double quantile, boolean average)MatrixBlockpickValues(MatrixValue quantiles, MatrixValue ret)MatrixBlockprepareAggregateUnaryOutput(AggregateUnaryOperator op, MatrixValue result, int blen)doubleprod()Wrapper method for reduceall-product of a matrix.voidputInto(MatrixBlock target, int rowOffset, int colOffset, boolean sparseCopyShallow)Method for copying this matrix into a target matrix.MatrixBlockquaternaryOperations(QuaternaryOperator qop, MatrixBlock um, MatrixBlock vm, MatrixBlock wm, MatrixBlock out)MatrixBlockquaternaryOperations(QuaternaryOperator qop, MatrixBlock U, MatrixBlock V, MatrixBlock wm, MatrixBlock out, int k)doublequickGetValue(int r, int c)doublequickGetValueThreadSafe(int r, int c)voidquickSetValue(int r, int c, double v)static MatrixBlockrandOperations(int rows, int cols, double sparsity, double min, double max, String pdf, long seed)Function to generate the random matrix with specified dimensions (block sizes are not specified).static MatrixBlockrandOperations(int rows, int cols, double sparsity, double min, double max, String pdf, long seed, int k)Function to generate the random matrix with specified dimensions (block sizes are not specified).static MatrixBlockrandOperations(RandomMatrixGenerator rgen, long seed)Function to generate the random matrix with specified dimensions and block dimensions.static MatrixBlockrandOperations(RandomMatrixGenerator rgen, long seed, int k)Function to generate the random matrix with specified dimensions and block dimensions.MatrixBlockrandOperationsInPlace(RandomMatrixGenerator rgen, org.apache.commons.math3.random.Well1024a bigrand, long bSeed)Function to generate a matrix of random numbers.MatrixBlockrandOperationsInPlace(RandomMatrixGenerator rgen, org.apache.commons.math3.random.Well1024a bigrand, long bSeed, int k)Function to generate a matrix of random numbers.voidreadExternal(ObjectInput is)Redirects the default java serialization via externalizable to our default hadoop writable serialization for efficient broadcast/rdd deserialization.voidreadFields(DataInput in)longrecomputeNonZeros()Recomputes and materializes the number of non-zero values of the entire matrix block.longrecomputeNonZeros(int rl, int ru)longrecomputeNonZeros(int rl, int ru, int cl, int cu)Recomputes the number of non-zero values of a specified range of the matrix block.MatrixBlockremoveEmptyOperations(MatrixBlock ret, boolean rows, boolean emptyReturn)MatrixBlockremoveEmptyOperations(MatrixBlock ret, boolean rows, boolean emptyReturn, MatrixBlock select)MatrixBlockreorgOperations(ReorgOperator op, MatrixValue ret, int startRow, int startColumn, int length)MatrixBlockreplaceOperations(MatrixValue result, double pattern, double replacement)voidreset()voidreset(int rl, int cl)voidreset(int rl, int cl, boolean sp)voidreset(int rl, int cl, boolean sp, long estnnz)voidreset(int rl, int cl, boolean sp, long estnnz, double val)Internal canonical reset of dense and sparse matrix blocks.voidreset(int rl, int cl, double val)voidreset(int rl, int cl, long estnnz)MatrixBlockrexpandOperations(MatrixBlock ret, double max, boolean rows, boolean cast, boolean ignore, int k)MatrixBlockrowSum()Wrapper method for single threaded reduceall-rowSum of a matrix.MatrixBlockrowSum(int k)Wrapper method for multi threaded reduceall-rowSum of a matrix.static MatrixBlocksampleOperations(long range, int size, boolean replace, long seed)MatrixBlockscalarOperations(ScalarOperator op, MatrixValue result)static MatrixBlockseqOperations(double from, double to, double incr)Method to generate a sequence according to the given parameters.MatrixBlockseqOperationsInPlace(double from, double to, double incr)longsetAllNonZeros()voidsetDenseBlock(DenseBlock dblock)longsetNonZeros(long nnz)voidsetNumColumns(int c)voidsetNumRows(int r)NOTE: setNumRows() and setNumColumns() are used only in ternaryInstruction (for contingency tables) and pmm for meta corrections.voidsetSparseBlock(SparseBlock sblock)voidsetValue(int r, int c, double v)MatrixBlockslice(int rl, int ru)Slice out a row blockMatrixBlockslice(int rl, int ru, boolean deep)MatrixBlockslice(int rl, int ru, int cl, int cu)MatrixBlockslice(int rl, int ru, int cl, int cu, boolean deep)Slice out a row blockMatrixBlockslice(int rl, int ru, int cl, int cu, boolean deep, CacheBlock ret)Method to perform rightIndex operation for a given lower and upper bounds in row and column dimensions.MatrixBlockslice(int rl, int ru, int cl, int cu, CacheBlock ret)Slice a sub block out of the current block and write into the given output block.voidslice(ArrayList<IndexedMatrixValue> outlist, IndexRange range, int rowCut, int colCut, int blen, int boundaryRlen, int boundaryClen)Slice out up to 4 matrixBlocks that are separated by the row and col Cuts.MatrixBlockslice(IndexRange ixrange, MatrixBlock ret)MatrixBlocksortOperations()MatrixBlocksortOperations(MatrixValue weights)MatrixBlocksortOperations(MatrixValue weights, MatrixBlock result)MatrixBlocksortOperations(MatrixValue weights, MatrixBlock result, int k)voidsortSparseRows()Sorts all existing sparse rows by column indexes.voidsortSparseRows(int rl, int ru)Sorts all existing sparse rows in range [rl,ru) by column indexes.voidsparseToDense()doublesum()Wrapper method for reduceall-sum of a matrix.doublesumSq()Wrapper method for reduceall-sumSq of a matrix.doublesumWeightForQuantile()In a given two column matrix, the second column denotes weights.MatrixBlockternaryOperations(TernaryOperator op, MatrixBlock m2, MatrixBlock m3, MatrixBlock ret)voidtoShallowSerializeBlock()Converts a cache block that is not shallow serializable into a form that is shallow serializable.StringtoString()MatrixBlocktransposeSelfMatrixMultOperations(MatrixBlock out, MMTSJ.MMTSJType tstype)MatrixBlocktransposeSelfMatrixMultOperations(MatrixBlock out, MMTSJ.MMTSJType tstype, int k)MatrixBlockuaggouterchainOperations(MatrixBlock mbLeft, MatrixBlock mbRight, MatrixBlock mbOut, BinaryOperator bOp, AggregateUnaryOperator uaggOp)MatrixBlockunaryOperations(UnaryOperator op, MatrixValue result)voidwrite(DataOutput out)voidwriteExternal(ObjectOutput os)Redirects the default java serialization via externalizable to our default hadoop writable serialization for efficient broadcast/rdd serialization.MatrixBlockzeroOutOperations(MatrixValue result, IndexRange range, boolean complementary)
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Field Detail
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SPARSITY_TURN_POINT
public static final double SPARSITY_TURN_POINT
- See Also:
- Constant Field Values
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ULTRA_SPARSITY_TURN_POINT
public static final double ULTRA_SPARSITY_TURN_POINT
- See Also:
- Constant Field Values
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ULTRA_SPARSITY_TURN_POINT2
public static final double ULTRA_SPARSITY_TURN_POINT2
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- Constant Field Values
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ULTRA_SPARSE_BLOCK_NNZ
public static final int ULTRA_SPARSE_BLOCK_NNZ
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- Constant Field Values
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DEFAULT_SPARSEBLOCK
public static final SparseBlock.Type DEFAULT_SPARSEBLOCK
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DEFAULT_INPLACE_SPARSEBLOCK
public static final SparseBlock.Type DEFAULT_INPLACE_SPARSEBLOCK
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MAX_SHALLOW_SERIALIZE_OVERHEAD
public static final double MAX_SHALLOW_SERIALIZE_OVERHEAD
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- Constant Field Values
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CONVERT_MCSR_TO_CSR_ON_DEEP_SERIALIZE
public static final boolean CONVERT_MCSR_TO_CSR_ON_DEEP_SERIALIZE
- See Also:
- Constant Field Values
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HEADER_SIZE
public static final int HEADER_SIZE
- See Also:
- Constant Field Values
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Constructor Detail
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MatrixBlock
public MatrixBlock()
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MatrixBlock
public MatrixBlock(int rl, int cl, boolean sp)
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MatrixBlock
public MatrixBlock(int rl, int cl, long estnnz)
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MatrixBlock
public MatrixBlock(int rl, int cl, boolean sp, long estnnz)
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MatrixBlock
public MatrixBlock(MatrixBlock that)
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MatrixBlock
public MatrixBlock(MatrixBlock that, boolean sp)
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MatrixBlock
public MatrixBlock(double val)
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MatrixBlock
public MatrixBlock(int rl, int cl, double val)
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MatrixBlock
public MatrixBlock(int rl, int cl, long nnz, SparseBlock sblock)Constructs a sparseMatrixBlockwith a given instance of aSparseBlock- Parameters:
rl- number of rowscl- number of columnsnnz- number of non zeroessblock- sparse block
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MatrixBlock
public MatrixBlock(MatrixBlock that, SparseBlock.Type stype, boolean deep)
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MatrixBlock
public MatrixBlock(int rl, int cl, DenseBlock dBlock)
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MatrixBlock
public MatrixBlock(int rl, int cl, double[] vals)
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Method Detail
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reset
public final void reset()
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resetin classMatrixValue
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reset
public final void reset(int rl, int cl)- Specified by:
resetin classMatrixValue
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reset
public final void reset(int rl, int cl, long estnnz)
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reset
public final void reset(int rl, int cl, boolean sp)- Specified by:
resetin classMatrixValue
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reset
public final void reset(int rl, int cl, boolean sp, long estnnz)- Specified by:
resetin classMatrixValue
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reset
public final void reset(int rl, int cl, double val)- Specified by:
resetin classMatrixValue
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reset
public void reset(int rl, int cl, boolean sp, long estnnz, double val)Internal canonical reset of dense and sparse matrix blocks.- Parameters:
rl- number of rowscl- number of columnssp- sparse representationestnnz- estimated number of non-zerosval- initialization value
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init
public void init(double[][] arr, int r, int c)NOTE: This method is designed only for dense representation.- Parameters:
arr- 2d double array matrixr- number of rowsc- number of columns
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init
public void init(double[] arr, int r, int c)NOTE: This method is designed only for dense representation.- Parameters:
arr- double array matrixr- number of rowsc- number of columns
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isAllocated
public boolean isAllocated()
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allocateDenseBlock
public final MatrixBlock allocateDenseBlock()
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allocateBlockAsync
public Future<MatrixBlock> allocateBlockAsync()
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allocateBlock
public final MatrixBlock allocateBlock()
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allocateDenseBlock
public boolean allocateDenseBlock(boolean clearNNZ)
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allocateSparseRowsBlock
public final boolean allocateSparseRowsBlock()
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allocateSparseRowsBlock
public boolean allocateSparseRowsBlock(boolean clearNNZ)
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allocateAndResetSparseBlock
public void allocateAndResetSparseBlock(boolean clearNNZ, SparseBlock.Type stype)
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allocateDenseBlockUnsafe
public final void allocateDenseBlockUnsafe(int rl, int cl)This should be called only in the read and write functions for CP This function should be called before calling any setValueDenseUnsafe()- Parameters:
rl- number of rowscl- number of columns
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cleanupBlock
public final void cleanupBlock(boolean dense, boolean sparse)Allows to cleanup all previously allocated sparserows or denseblocks. This is for example required in reading a matrix with many empty blocks via distributed cache into in-memory list of blocks - not cleaning blocks from non-empty blocks would significantly increase the total memory consumption.- Parameters:
dense- if true, set dense block to nullsparse- if true, set sparse block to null
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getNumRows
public final int getNumRows()
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getNumRowsin interfaceCacheBlock- Specified by:
getNumRowsin classMatrixValue
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setNumRows
public final void setNumRows(int r)
NOTE: setNumRows() and setNumColumns() are used only in ternaryInstruction (for contingency tables) and pmm for meta corrections.- Parameters:
r- number of rows
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getNumColumns
public final int getNumColumns()
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getNumColumnsin interfaceCacheBlock- Specified by:
getNumColumnsin classMatrixValue
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setNumColumns
public final void setNumColumns(int c)
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getNonZeros
public final long getNonZeros()
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getNonZerosin classMatrixValue
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setNonZeros
public final long setNonZeros(long nnz)
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setAllNonZeros
public final long setAllNonZeros()
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getSparsity
public final double getSparsity()
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getDataCharacteristics
public final DataCharacteristics getDataCharacteristics()
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getDataCharacteristicsin interfaceCacheBlock
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isVector
public final boolean isVector()
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getLength
public final long getLength()
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isEmpty
public final boolean isEmpty()
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isEmptyin classMatrixValue
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isEmptyBlock
public final boolean isEmptyBlock()
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isEmptyBlock
public boolean isEmptyBlock(boolean safe)
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getDenseBlock
public DenseBlock getDenseBlock()
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setDenseBlock
public void setDenseBlock(DenseBlock dblock)
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getDenseBlockValues
public double[] getDenseBlockValues()
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getSparseBlock
public SparseBlock getSparseBlock()
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setSparseBlock
public void setSparseBlock(SparseBlock sblock)
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getValue
public double getValue(int r, int c)- Specified by:
getValuein classMatrixValue
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setValue
public void setValue(int r, int c, double v)- Specified by:
setValuein classMatrixValue
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quickGetValue
public double quickGetValue(int r, int c)
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quickSetValue
public void quickSetValue(int r, int c, double v)
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quickGetValueThreadSafe
public double quickGetValueThreadSafe(int r, int c)
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getValueDenseUnsafe
public double getValueDenseUnsafe(int r, int c)
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containsValue
public boolean containsValue(double pattern)
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appendValue
public void appendValue(int r, int c, double v)Append value is only used when values are appended at the end of each row for the sparse representation This can only be called, when the caller knows the access pattern of the block- Parameters:
r- rowc- columnv- value
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appendValuePlain
public void appendValuePlain(int r, int c, double v)
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appendRow
public void appendRow(int r, SparseRow row)
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appendRow
public void appendRow(int r, SparseRow row, boolean deep)
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appendToSparse
public void appendToSparse(MatrixBlock that, int rowoffset, int coloffset)
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appendRowToSparse
public void appendRowToSparse(SparseBlock dest, MatrixBlock src, int i, int rowoffset, int coloffset, boolean deep)
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sortSparseRows
public void sortSparseRows()
Sorts all existing sparse rows by column indexes.
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sortSparseRows
public void sortSparseRows(int rl, int ru)Sorts all existing sparse rows in range [rl,ru) by column indexes.- Parameters:
rl- row lower bound, inclusiveru- row upper bound, exclusive
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minNonZero
public double minNonZero()
Utility function for computing the min non-zero value.- Returns:
- minimum non-zero value
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prod
public double prod()
Wrapper method for reduceall-product of a matrix.- Returns:
- the product sum of the matrix content
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mean
public double mean()
Wrapper method for reduceall-mean of a matrix.- Returns:
- the mean value of all values in the matrix
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min
public double min()
Wrapper method for reduceall-min of a matrix.- Returns:
- the minimum value of all values in the matrix
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colMin
public MatrixBlock colMin()
Wrapper method for reduceall-colMin of a matrix.- Returns:
- A new MatrixBlock containing the column mins of this matrix
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colMax
public MatrixBlock colMax()
Wrapper method for reduceall-colMin of a matrix.- Returns:
- A new MatrixBlock containing the column mins of this matrix
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max
public double max()
Wrapper method for reduceall-max of a matrix.- Returns:
- the maximum value of all values in the matrix
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sum
public double sum()
Wrapper method for reduceall-sum of a matrix.- Returns:
- Sum of the values in the matrix.
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colSum
public MatrixBlock colSum()
Wrapper method for single threaded reduceall-colSum of a matrix.- Returns:
- A new MatrixBlock containing the column sums of this matrix.
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rowSum
public final MatrixBlock rowSum()
Wrapper method for single threaded reduceall-rowSum of a matrix.- Returns:
- A new MatrixBlock containing the row sums of this matrix.
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rowSum
public final MatrixBlock rowSum(int k)
Wrapper method for multi threaded reduceall-rowSum of a matrix.- Parameters:
k- the number of threads allowed to be used.- Returns:
- A new MatrixBlock containing the row sums of this matrix.
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sumSq
public double sumSq()
Wrapper method for reduceall-sumSq of a matrix.- Returns:
- Sum of the squared values in the matrix.
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isInSparseFormat
public boolean isInSparseFormat()
Returns the current representation (true for sparse).- Specified by:
isInSparseFormatin classMatrixValue- Returns:
- true if sparse
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isUltraSparse
public boolean isUltraSparse()
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isUltraSparse
public boolean isUltraSparse(boolean checkNnz)
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isSparsePermutationMatrix
public boolean isSparsePermutationMatrix()
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evalSparseFormatInMemory
public boolean evalSparseFormatInMemory()
Evaluates if this matrix block should be in sparse format in memory. Note that this call does not change the representation - for this please call examSparsity.- Returns:
- true if matrix block should be in sparse format in memory
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evalSparseFormatInMemory
public boolean evalSparseFormatInMemory(boolean allowCSR)
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evalSparseFormatOnDisk
public boolean evalSparseFormatOnDisk()
Evaluates if this matrix block should be in sparse format on disk. This applies to any serialized matrix representation, i.e., when writing to in-memory buffer pool pages or writing to local fs or hdfs.- Returns:
- true if matrix block should be in sparse format on disk
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examSparsity
public void examSparsity()
Evaluates if this matrix block should be in sparse format in memory. Depending on the current representation, the state of the matrix block is changed to the right representation if necessary. Note that this consumes for the time of execution memory for both representations. Allowing CSR format is default for this operation.
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examSparsity
public void examSparsity(boolean allowCSR)
Evaluates if this matrix block should be in sparse format in memory. Depending on the current representation, the state of the matrix block is changed to the right representation if necessary. Note that this consumes for the time of execution memory for both representations.- Parameters:
allowCSR- allow CSR format on dense to sparse conversion
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evalSparseFormatInMemory
public static boolean evalSparseFormatInMemory(DataCharacteristics dc)
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evalSparseFormatInMemory
public static boolean evalSparseFormatInMemory(long nrows, long ncols, long nnz)Evaluates if a matrix block with the given characteristics should be in sparse format in memory.- Parameters:
nrows- number of rowsncols- number of columnsnnz- number of non-zeros- Returns:
- true if matrix block shold be in sparse format in memory
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evalSparseFormatInMemory
public static boolean evalSparseFormatInMemory(long nrows, long ncols, long nnz, boolean allowCSR)
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evalSparseFormatOnDisk
public static boolean evalSparseFormatOnDisk(long nrows, long ncols, long nnz)Evaluates if a matrix block with the given characteristics should be in sparse format on disk (or in any other serialized representation).- Parameters:
nrows- number of rowsncols- number of columnsnnz- number of non-zeros- Returns:
- true if matrix block shold be in sparse format on disk
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denseToSparse
public void denseToSparse(boolean allowCSR)
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sparseToDense
public void sparseToDense()
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recomputeNonZeros
public long recomputeNonZeros()
Recomputes and materializes the number of non-zero values of the entire matrix block.- Returns:
- number of non-zeros
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recomputeNonZeros
public long recomputeNonZeros(int rl, int ru)
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recomputeNonZeros
public long recomputeNonZeros(int rl, int ru, int cl, int cu)Recomputes the number of non-zero values of a specified range of the matrix block. NOTE: This call does not materialize the compute result in any form.- Parameters:
rl- row lower index, 0-based, inclusiveru- row upper index, 0-based, inclusivecl- column lower index, 0-based, inclusivecu- column upper index, 0-based, inclusive- Returns:
- the number of non-zero values
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checkNonZeros
public void checkNonZeros()
Basic debugging primitive to check correctness of nnz. This method is not intended for production use.
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checkSparseRows
public void checkSparseRows()
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checkSparseRows
public void checkSparseRows(int rl, int ru)Basic debugging primitive to check sparse block column ordering. This method is not intended for production use.- Parameters:
rl- row lower bound (inclusive)ru- row upper bound (exclusive)
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copy
public void copy(MatrixValue thatValue)
Description copied from class:MatrixValueCopy that MatrixValue into this MatrixValue. If the MatrixValue is a MatrixBlock evaluate the sparsity of the original matrix, and copy into either a sparse or a dense matrix.- Specified by:
copyin classMatrixValue- Parameters:
thatValue- object to copy the values into.
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copy
public void copy(MatrixValue thatValue, boolean sp)
Description copied from class:MatrixValueCopy that MatrixValue into this MatrixValue. But select sparse destination block depending on boolean parameter.- Specified by:
copyin classMatrixValue- Parameters:
thatValue- object to copy the values into.sp- boolean specifying if output should be forced sparse or dense. (only applicable if the 'that' is a MatrixBlock)
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copyShallow
public MatrixBlock copyShallow(MatrixBlock that)
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putInto
public void putInto(MatrixBlock target, int rowOffset, int colOffset, boolean sparseCopyShallow)
Method for copying this matrix into a target matrix. Note that this method does not maintain number of non zero values. The method should output into the allocated block type of the target, therefore before any calls an appropriate block must be allocated. CSR sparse format is not supported. If allocating into a sparse matrix MCSR block the rows have to be sorted afterwards with a call to target.sortSparseRows()- Parameters:
target- Target MatrixBlock, that can be allocated dense or sparserowOffset- The Row offset to allocate into.colOffset- The column offset to allocate into.sparseCopyShallow- If the output is sparse, and shallow copy of rows is allowed from this block
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copy
public void copy(int rl, int ru, int cl, int cu, MatrixBlock src, boolean awareDestNZ)In-place copy of matrix src into the index range of the existing current matrix. Note that removal of existing nnz in the index range and nnz maintenance is only done if 'awareDestNZ=true',- Parameters:
rl- row lower index, 0-basedru- row upper index, 0-based, inclusivecl- column lower index, 0-basedcu- column upper index, 0-based, inclusivesrc- matrix blockawareDestNZ- true, forces (1) to remove existing non-zeros in the index range of the destination if not present in src and (2) to internally maintain nnz false, assume empty index range in destination and do not maintain nnz (the invoker is responsible to recompute nnz after all copies are done)
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merge
public void merge(CacheBlock that, boolean appendOnly)
Description copied from interface:CacheBlockMerge the given block into the current block. Both blocks needs to be of equal dimensions and contain disjoint non-zero cells.- Specified by:
mergein interfaceCacheBlock- Parameters:
that- cache blockappendOnly- ?
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merge
public void merge(MatrixBlock that, boolean appendOnly)
Merge disjoint: merges all non-zero values of the given input into the current matrix block. Note that this method does NOT check for overlapping entries; it's the callers reponsibility of ensuring disjoint matrix blocks. The appendOnly parameter is only relevant for sparse target blocks; if true, we only append values and do not sort sparse rows for each call; this is useful whenever we merge iterators of matrix blocks into one target block.- Parameters:
that- matrix blockappendOnly- ?
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merge
public void merge(MatrixBlock that, boolean appendOnly, boolean par)
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merge
public void merge(MatrixBlock that, boolean appendOnly, boolean par, boolean deep)
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readFields
public void readFields(DataInput in) throws IOException
- Specified by:
readFieldsin interfaceorg.apache.hadoop.io.Writable- Throws:
IOException
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write
public void write(DataOutput out) throws IOException
- Specified by:
writein interfaceorg.apache.hadoop.io.Writable- Throws:
IOException
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readExternal
public void readExternal(ObjectInput is) throws IOException
Redirects the default java serialization via externalizable to our default hadoop writable serialization for efficient broadcast/rdd deserialization.- Specified by:
readExternalin interfaceExternalizable- Parameters:
is- object input- Throws:
IOException- if IOException occurs
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writeExternal
public void writeExternal(ObjectOutput os) throws IOException
Redirects the default java serialization via externalizable to our default hadoop writable serialization for efficient broadcast/rdd serialization.- Specified by:
writeExternalin interfaceExternalizable- Parameters:
os- object output- Throws:
IOException- if IOException occurs
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getExactSizeOnDisk
public long getExactSizeOnDisk()
NOTE: The used estimates must be kept consistent with the respective write functions.- Returns:
- exact size on disk
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getHeaderSize
public static long getHeaderSize()
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estimateSizeInMemory
public long estimateSizeInMemory()
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estimateSizeInMemory
public static long estimateSizeInMemory(long nrows, long ncols, double sparsity)
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estimateSizeDenseInMemory
public long estimateSizeDenseInMemory()
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estimateSizeDenseInMemory
public static long estimateSizeDenseInMemory(long nrows, long ncols)
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estimateSizeSparseInMemory
public long estimateSizeSparseInMemory()
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estimateSizeSparseInMemory
public static long estimateSizeSparseInMemory(long nrows, long ncols, double sparsity)
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estimateSizeSparseInMemory
public static long estimateSizeSparseInMemory(long nrows, long ncols, double sparsity, boolean allowCSR)
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estimateSizeSparseInMemory
public long estimateSizeSparseInMemory(SparseBlock.Type stype)
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estimateSizeSparseInMemory
public static long estimateSizeSparseInMemory(long nrows, long ncols, double sparsity, SparseBlock.Type stype)
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estimateSizeOnDisk
public long estimateSizeOnDisk()
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estimateSizeOnDisk
public static long estimateSizeOnDisk(long nrows, long ncols, long nnz)
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getInMemorySize
public long getInMemorySize()
Description copied from interface:CacheBlockGet the in-memory size in bytes of the cache block.- Specified by:
getInMemorySizein interfaceCacheBlock- Returns:
- in-memory size in bytes of cache block
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getExactSerializedSize
public long getExactSerializedSize()
Description copied from interface:CacheBlockGet the exact serialized size in bytes of the cache block.- Specified by:
getExactSerializedSizein interfaceCacheBlock- Returns:
- exact serialized size in bytes of cache block
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isShallowSerialize
public boolean isShallowSerialize()
Description copied from interface:CacheBlockIndicates if the cache block is subject to shallow serialized, which is generally true if in-memory size and serialized size are almost identical allowing to avoid unnecessary deep serialize.- Specified by:
isShallowSerializein interfaceCacheBlock- Returns:
- true if shallow serialized
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isShallowSerialize
public boolean isShallowSerialize(boolean inclConvert)
Description copied from interface:CacheBlockIndicates if the cache block is subject to shallow serialized, which is generally true if in-memory size and serialized size are almost identical allowing to avoid unnecessary deep serialize.- Specified by:
isShallowSerializein interfaceCacheBlock- Parameters:
inclConvert- if true report blocks as shallow serialize that are currently not amenable but can be brought into an amenable form viatoShallowSerializeBlock.- Returns:
- true if shallow serialized
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toShallowSerializeBlock
public void toShallowSerializeBlock()
Description copied from interface:CacheBlockConverts a cache block that is not shallow serializable into a form that is shallow serializable. This methods has no affect if the given cache block is not amenable.- Specified by:
toShallowSerializeBlockin interfaceCacheBlock
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compactEmptyBlock
public void compactEmptyBlock()
Description copied from interface:CacheBlockFree unnecessarily allocated empty block.- Specified by:
compactEmptyBlockin interfaceCacheBlock
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scalarOperations
public MatrixBlock scalarOperations(ScalarOperator op, MatrixValue result)
- Specified by:
scalarOperationsin classMatrixValue
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unaryOperations
public MatrixBlock unaryOperations(UnaryOperator op, MatrixValue result)
- Specified by:
unaryOperationsin classMatrixValue
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binaryOperations
public final MatrixBlock binaryOperations(BinaryOperator op, MatrixValue thatValue)
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binaryOperations
public MatrixBlock binaryOperations(BinaryOperator op, MatrixValue thatValue, MatrixValue result)
- Specified by:
binaryOperationsin classMatrixValue
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binaryOperationsInPlace
public MatrixBlock binaryOperationsInPlace(BinaryOperator op, MatrixValue thatValue)
- Specified by:
binaryOperationsInPlacein classMatrixValue
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ternaryOperations
public MatrixBlock ternaryOperations(TernaryOperator op, MatrixBlock m2, MatrixBlock m3, MatrixBlock ret)
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incrementalAggregate
public void incrementalAggregate(AggregateOperator aggOp, MatrixValue correction, MatrixValue newWithCorrection, boolean deep)
- Specified by:
incrementalAggregatein classMatrixValue
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incrementalAggregate
public void incrementalAggregate(AggregateOperator aggOp, MatrixValue newWithCorrection)
- Specified by:
incrementalAggregatein classMatrixValue
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reorgOperations
public MatrixBlock reorgOperations(ReorgOperator op, MatrixValue ret, int startRow, int startColumn, int length)
- Specified by:
reorgOperationsin classMatrixValue
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append
public final MatrixBlock append(MatrixBlock that, MatrixBlock ret)
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append
public final MatrixBlock append(MatrixBlock that, MatrixBlock ret, boolean cbind)
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append
public MatrixBlock append(MatrixBlock[] that, MatrixBlock result, boolean cbind)
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checkDimensionsForAppend
public void checkDimensionsForAppend(MatrixBlock[] in, boolean cbind)
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naryOperations
public static MatrixBlock naryOperations(Operator op, MatrixBlock[] matrices, ScalarObject[] scalars, MatrixBlock ret)
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transposeSelfMatrixMultOperations
public MatrixBlock transposeSelfMatrixMultOperations(MatrixBlock out, MMTSJ.MMTSJType tstype)
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transposeSelfMatrixMultOperations
public MatrixBlock transposeSelfMatrixMultOperations(MatrixBlock out, MMTSJ.MMTSJType tstype, int k)
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chainMatrixMultOperations
public MatrixBlock chainMatrixMultOperations(MatrixBlock v, MatrixBlock w, MatrixBlock out, MapMultChain.ChainType ctype)
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chainMatrixMultOperations
public MatrixBlock chainMatrixMultOperations(MatrixBlock v, MatrixBlock w, MatrixBlock out, MapMultChain.ChainType ctype, int k)
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permutationMatrixMultOperations
public void permutationMatrixMultOperations(MatrixValue m2Val, MatrixValue out1Val, MatrixValue out2Val)
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permutationMatrixMultOperations
public void permutationMatrixMultOperations(MatrixValue m2Val, MatrixValue out1Val, MatrixValue out2Val, int k)
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leftIndexingOperations
public final MatrixBlock leftIndexingOperations(MatrixBlock rhsMatrix, IndexRange ixrange, MatrixBlock ret, MatrixObject.UpdateType update)
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leftIndexingOperations
public MatrixBlock leftIndexingOperations(MatrixBlock rhsMatrix, int rl, int ru, int cl, int cu, MatrixBlock ret, MatrixObject.UpdateType update)
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leftIndexingOperations
public MatrixBlock leftIndexingOperations(ScalarObject scalar, int rl, int cl, MatrixBlock ret, MatrixObject.UpdateType update)
Explicitly allow left indexing for scalars. Note: This operation is now 0-based. * Operations to be performed: 1) result=this; 2) result[row,column] = scalar.getDoubleValue();- Parameters:
scalar- scalar objectrl- row lowercl- column lowerret- ?update- ?- Returns:
- matrix block
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slice
public MatrixBlock slice(IndexRange ixrange, MatrixBlock ret)
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slice
public final MatrixBlock slice(int rl, int ru)
Slice out a row block- Parameters:
rl- The row lower to start fromru- The row lower to end at- Returns:
- The sliced out matrix block.
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slice
public final MatrixBlock slice(int rl, int ru, boolean deep)
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slice
public final MatrixBlock slice(int rl, int ru, int cl, int cu)
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slice
public final MatrixBlock slice(int rl, int ru, int cl, int cu, CacheBlock ret)
Description copied from interface:CacheBlockSlice a sub block out of the current block and write into the given output block. This method returns the passed instance if not null.- Specified by:
slicein interfaceCacheBlock- Parameters:
rl- row lowerru- row uppercl- column lowercu- column upperret- cache block- Returns:
- sub-block of cache block
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slice
public final MatrixBlock slice(int rl, int ru, int cl, int cu, boolean deep)
Slice out a row block- Parameters:
rl- The row lower to start fromru- The row lower to end atcl- The col lower to start fromcu- The col lower to end atdeep- Deep copy or not- Returns:
- The sliced out matrix block.
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slice
public MatrixBlock slice(int rl, int ru, int cl, int cu, boolean deep, CacheBlock ret)
Method to perform rightIndex operation for a given lower and upper bounds in row and column dimensions. Extracted submatrix is returned as "result". Note: This operation is now 0-based. This means that if you call with rl == ru then you get 1 row output.- Specified by:
slicein interfaceCacheBlock- Parameters:
rl- row lower if this value is below 0 or above the number of rows contained in the matrix an exception is thrownru- row upper if this value is below rl or above the number of rows contained in the matrix an exception is throwncl- column lower if this value us below 0 or above the number of columns contained in the matrix an exception is throwncu- column upper if this value us below cl or above the number of columns contained in the matrix an exception is throwndeep- should perform deep copy, this is relevant in cases where the matrix is in sparse format, or the entire matrix is sliced outret- output sliced out matrix block- Returns:
- matrix block output matrix block
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slice
public void slice(ArrayList<IndexedMatrixValue> outlist, IndexRange range, int rowCut, int colCut, int blen, int boundaryRlen, int boundaryClen)
Description copied from class:MatrixValueSlice out up to 4 matrixBlocks that are separated by the row and col Cuts. This is used in the context of spark execution to distributed sliced out matrix blocks of correct block size.- Specified by:
slicein classMatrixValue- Parameters:
outlist- The output matrix blocks that is extracted from the matrixrange- An index range containing overlapping information.rowCut- The row to cut and split the matrix.colCut- The column to cut ans split the matrix.blen- The Block size of the output matrices.boundaryRlen- The row length of the edge case matrix block, used for the final blocks that does not have enough rows to construct a full block.boundaryClen- The col length of the edge case matrix block, used for the final blocks that does not have enough cols to construct a full block.
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append
public void append(MatrixValue v2, ArrayList<IndexedMatrixValue> outlist, int blen, boolean cbind, boolean m2IsLast, int nextNCol)
- Specified by:
appendin classMatrixValue
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zeroOutOperations
public MatrixBlock zeroOutOperations(MatrixValue result, IndexRange range, boolean complementary)
- Specified by:
zeroOutOperationsin classMatrixValue
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aggregateUnaryOperations
public final MatrixBlock aggregateUnaryOperations(AggregateUnaryOperator op, MatrixValue result, int blen, MatrixIndexes indexesIn)
- Specified by:
aggregateUnaryOperationsin classMatrixValue
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aggregateUnaryOperations
public MatrixBlock aggregateUnaryOperations(AggregateUnaryOperator op, MatrixValue result, int blen, MatrixIndexes indexesIn, boolean inCP)
- Specified by:
aggregateUnaryOperationsin classMatrixValue
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prepareAggregateUnaryOutput
public MatrixBlock prepareAggregateUnaryOutput(AggregateUnaryOperator op, MatrixValue result, int blen)
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dropLastRowsOrColumns
public void dropLastRowsOrColumns(Types.CorrectionLocationType correctionLocation)
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cmOperations
public CM_COV_Object cmOperations(CMOperator op)
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checkCMOperations
public static void checkCMOperations(MatrixBlock mb, CMOperator op)
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cmOperations
public CM_COV_Object cmOperations(CMOperator op, MatrixBlock weights)
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covOperations
public CM_COV_Object covOperations(COVOperator op, MatrixBlock that)
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covOperations
public CM_COV_Object covOperations(COVOperator op, MatrixBlock that, MatrixBlock weights)
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sortOperations
public final MatrixBlock sortOperations()
-
sortOperations
public final MatrixBlock sortOperations(MatrixValue weights)
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sortOperations
public MatrixBlock sortOperations(MatrixValue weights, MatrixBlock result)
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sortOperations
public MatrixBlock sortOperations(MatrixValue weights, MatrixBlock result, int k)
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interQuartileMean
public double interQuartileMean()
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computeIQMCorrection
public static double computeIQMCorrection(double sum, double sum_wt, double q25Part, double q25Val, double q75Part, double q75Val)
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pickValues
public MatrixBlock pickValues(MatrixValue quantiles, MatrixValue ret)
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median
public double median()
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pickValue
public final double pickValue(double quantile)
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pickValue
public double pickValue(double quantile, boolean average)
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sumWeightForQuantile
public double sumWeightForQuantile()
In a given two column matrix, the second column denotes weights. This function computes the total weight- Returns:
- sum weight for quantile
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aggregateBinaryOperations
public final MatrixBlock aggregateBinaryOperations(MatrixBlock m1, MatrixBlock m2, AggregateBinaryOperator op)
-
aggregateBinaryOperations
public MatrixBlock aggregateBinaryOperations(MatrixBlock m1, MatrixBlock m2, MatrixBlock ret, AggregateBinaryOperator op)
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aggregateTernaryOperations
public MatrixBlock aggregateTernaryOperations(MatrixBlock m1, MatrixBlock m2, MatrixBlock m3, MatrixBlock ret, AggregateTernaryOperator op, boolean inCP)
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uaggouterchainOperations
public MatrixBlock uaggouterchainOperations(MatrixBlock mbLeft, MatrixBlock mbRight, MatrixBlock mbOut, BinaryOperator bOp, AggregateUnaryOperator uaggOp)
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groupedAggOperations
public final MatrixBlock groupedAggOperations(MatrixValue tgt, MatrixValue wghts, MatrixValue ret, int ngroups, Operator op)
Invocation from CP instructions. The aggregate is computed on the groups object against target and weights. Notes: * The computed number of groups is reused for multiple invocations with different target. * This implementation supports that the target is passed as column or row vector, in case of row vectors we also use sparse-safe implementations for sparse safe aggregation operators.- Parameters:
tgt- ?wghts- ?ret- ?ngroups- ?op- operator- Returns:
- matrix block
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groupedAggOperations
public MatrixBlock groupedAggOperations(MatrixValue tgt, MatrixValue wghts, MatrixValue ret, int ngroups, Operator op, int k)
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removeEmptyOperations
public MatrixBlock removeEmptyOperations(MatrixBlock ret, boolean rows, boolean emptyReturn, MatrixBlock select)
-
removeEmptyOperations
public final MatrixBlock removeEmptyOperations(MatrixBlock ret, boolean rows, boolean emptyReturn)
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rexpandOperations
public MatrixBlock rexpandOperations(MatrixBlock ret, double max, boolean rows, boolean cast, boolean ignore, int k)
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replaceOperations
public MatrixBlock replaceOperations(MatrixValue result, double pattern, double replacement)
- Specified by:
replaceOperationsin classMatrixValue
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extractTriangular
public MatrixBlock extractTriangular(MatrixBlock ret, boolean lower, boolean diag, boolean values)
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ctableOperations
public void ctableOperations(Operator op, double scalarThat, MatrixValue that2Val, CTableMap resultMap, MatrixBlock resultBlock)
D = ctable(A,v2,W) this <- A; scalarThat <- v2; that2 <- W; result <- D (i1,j1,v1) from input1 (this) (v2) from sclar_input2 (scalarThat) (i3,j3,w) from input3 (that2)- Specified by:
ctableOperationsin classMatrixValue
-
ctableOperations
public void ctableOperations(Operator op, double scalarThat, double scalarThat2, CTableMap resultMap, MatrixBlock resultBlock)
D = ctable(A,v2,w) this <- A; scalar_that <- v2; scalar_that2 <- w; result <- D (i1,j1,v1) from input1 (this) (v2) from sclar_input2 (scalarThat) (w) from scalar_input3 (scalarThat2)- Specified by:
ctableOperationsin classMatrixValue
-
ctableOperations
public void ctableOperations(Operator op, MatrixIndexes ix1, double scalarThat, boolean left, int blen, CTableMap resultMap, MatrixBlock resultBlock)
Specific ctable case of ctable(seq(...),X), where X is the only matrix input. The 'left' input parameter specifies if the seq appeared on the left, otherwise it appeared on the right.- Specified by:
ctableOperationsin classMatrixValue
-
ctableOperations
public void ctableOperations(Operator op, MatrixValue thatVal, double scalarThat2, boolean ignoreZeros, CTableMap resultMap, MatrixBlock resultBlock)
D = ctable(A,B,w) this <- A; that <- B; scalar_that2 <- w; result <- D (i1,j1,v1) from input1 (this) (i1,j1,v2) from input2 (that) (w) from scalar_input3 (scalarThat2) NOTE: This method supports both vectors and matrices. In case of matrices and ignoreZeros=true we can also use a sparse-safe implementation- Specified by:
ctableOperationsin classMatrixValue
-
ctableSeqOperations
public MatrixBlock ctableSeqOperations(MatrixValue thatMatrix, double thatScalar, MatrixBlock ret, boolean updateClen)
- Parameters:
thatMatrix- matrix valuethatScalar- scalar doubleret- result matrix blockupdateClen- when this matrix already has the desired number of columns updateClen can be set to false- Returns:
- result matrix block
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ctableSeqOperations
public final MatrixBlock ctableSeqOperations(MatrixValue thatMatrix, double thatScalar, MatrixBlock resultBlock)
D = ctable(seq,A,w) this <- seq; thatMatrix <- A; thatScalar <- w; result <- D (i1,j1,v1) from input1 (this) (i1,j1,v2) from input2 (that) (w) from scalar_input3 (scalarThat2)- Parameters:
thatMatrix- matrix valuethatScalar- scalar doubleresultBlock- result matrix block- Returns:
- resultBlock
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ctableOperations
public final void ctableOperations(Operator op, MatrixValue thatVal, MatrixValue that2Val, CTableMap resultMap)
D = ctable(A,B,W) this <- A; that <- B; that2 <- W; result <- D (i1,j1,v1) from input1 (this) (i1,j1,v2) from input2 (that) (i1,j1,w) from input3 (that2)- Parameters:
op- operatorthatVal- matrix value 1that2Val- matrix value 2resultMap- table map
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ctableOperations
public void ctableOperations(Operator op, MatrixValue thatVal, MatrixValue that2Val, CTableMap resultMap, MatrixBlock resultBlock)
- Specified by:
ctableOperationsin classMatrixValue
-
quaternaryOperations
public final MatrixBlock quaternaryOperations(QuaternaryOperator qop, MatrixBlock um, MatrixBlock vm, MatrixBlock wm, MatrixBlock out)
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quaternaryOperations
public MatrixBlock quaternaryOperations(QuaternaryOperator qop, MatrixBlock U, MatrixBlock V, MatrixBlock wm, MatrixBlock out, int k)
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randOperations
public static MatrixBlock randOperations(int rows, int cols, double sparsity, double min, double max, String pdf, long seed)
Function to generate the random matrix with specified dimensions (block sizes are not specified).- Parameters:
rows- number of rowscols- number of columnssparsity- sparsity as a percentagemin- minimum valuemax- maximum valuepdf- pdfseed- random seed- Returns:
- matrix block
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randOperations
public static MatrixBlock randOperations(int rows, int cols, double sparsity, double min, double max, String pdf, long seed, int k)
Function to generate the random matrix with specified dimensions (block sizes are not specified).- Parameters:
rows- number of rowscols- number of columnssparsity- sparsity as a percentagemin- minimum valuemax- maximum valuepdf- pdfseed- random seedk- ?- Returns:
- matrix block
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randOperations
public static MatrixBlock randOperations(RandomMatrixGenerator rgen, long seed)
Function to generate the random matrix with specified dimensions and block dimensions.- Parameters:
rgen- random matrix generatorseed- seed value- Returns:
- matrix block
-
randOperations
public static MatrixBlock randOperations(RandomMatrixGenerator rgen, long seed, int k)
Function to generate the random matrix with specified dimensions and block dimensions.- Parameters:
rgen- random matrix generatorseed- seed valuek- ?- Returns:
- matrix block
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randOperationsInPlace
public MatrixBlock randOperationsInPlace(RandomMatrixGenerator rgen, org.apache.commons.math3.random.Well1024a bigrand, long bSeed)
Function to generate a matrix of random numbers. This is invoked both from CP as well as from MR. In case of CP, it generates an entire matrix block-by-block. Abigrandis passed so that block-level seeds are generated internally. In case of MR, it generates a single block for given block-level seedbSeed. When pdf="uniform", cell values are drawn from uniform distribution in range[min,max]. When pdf="normal", cell values are drawn from standard normal distribution N(0,1). The range of generated values will always be (-Inf,+Inf).- Parameters:
rgen- random matrix generatorbigrand- ?bSeed- seed value- Returns:
- matrix block
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randOperationsInPlace
public MatrixBlock randOperationsInPlace(RandomMatrixGenerator rgen, org.apache.commons.math3.random.Well1024a bigrand, long bSeed, int k)
Function to generate a matrix of random numbers. This is invoked both from CP as well as from MR. In case of CP, it generates an entire matrix block-by-block. Abigrandis passed so that block-level seeds are generated internally. In case of MR, it generates a single block for given block-level seedbSeed. When pdf="uniform", cell values are drawn from uniform distribution in range[min,max]. When pdf="normal", cell values are drawn from standard normal distribution N(0,1). The range of generated values will always be (-Inf,+Inf).- Parameters:
rgen- random matrix generatorbigrand- ?bSeed- seed valuek- ?- Returns:
- matrix block
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seqOperations
public static MatrixBlock seqOperations(double from, double to, double incr)
Method to generate a sequence according to the given parameters. The generated sequence is always in dense format. Both end points specifiedfromandtomust be included in the generated sequence i.e., [from,to] both inclusive. Note that,tois included only if (to-from) is perfectly divisible byincr. For example, seq(0,1,0.5) generates (0.0 0.5 1.0) whereas seq(0,1,0.6) generates (0.0 0.6) but not (0.0 0.6 1.0)- Parameters:
from- ?to- ?incr- ?- Returns:
- matrix block
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seqOperationsInPlace
public MatrixBlock seqOperationsInPlace(double from, double to, double incr)
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sampleOperations
public static MatrixBlock sampleOperations(long range, int size, boolean replace, long seed)
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isThreadSafe
public boolean isThreadSafe()
Indicates if concurrent modifications of disjoint rows are thread-safe.- Returns:
- true if thread-safe
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isThreadSafe
public static boolean isThreadSafe(boolean sparse)
Indicates if concurrent modifications of disjoint rows are thread-safe.- Parameters:
sparse- true if sparse- Returns:
- true if ?
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checkNaN
public void checkNaN()
Checks for existing NaN values in the matrix block.- Throws:
DMLRuntimeException- if the blocks contains at least one NaN.
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compareTo
public final int compareTo(Object arg0)
- Specified by:
compareToin interfaceComparable
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getDouble
public double getDouble(int r, int c)Description copied from interface:CacheBlockReturns the double value at the passed row and column. If the value is missing 0 is returned.- Specified by:
getDoublein interfaceCacheBlock- Parameters:
r- row of the valuec- column of the value- Returns:
- double value at the passed row and column
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getDoubleNaN
public double getDoubleNaN(int r, int c)Description copied from interface:CacheBlockReturns the double value at the passed row and column. If the value is missing NaN is returned.- Specified by:
getDoubleNaNin interfaceCacheBlock- Parameters:
r- row of the valuec- column of the value- Returns:
- double value at the passed row and column
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getString
public String getString(int r, int c)
Description copied from interface:CacheBlockReturns the string of the value at the passed row and column. If the value is missing or NaN, null is returned.- Specified by:
getStringin interfaceCacheBlock- Parameters:
r- row of the valuec- column of the value- Returns:
- string of the value at the passed row and column
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