All Known Implementing Classes:

ADictionary, DeltaDictionary, Dictionary, IdentityDictionary, IdentityDictionarySlice, MatrixBlockDictionary, PlaceHolderDict, QDictionary
```
public interface IDictionary
```

Nested Class Summary

Nested Classes
Modifier and Type Interface Description

static class IDictionary.DictType

Field Summary

Fields
Modifier and Type Field Description

static org.apache.commons.logging.Log LOG

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`void`	`addToEntry(double[] v, int fr, int to, int nCol)`	Adds the dictionary entry from this dictionary to the d dictionary
`void`	`addToEntry(double[] v, int fr, int to, int nCol, int rep)`	Adds the dictionary entry from this dictionary to the v dictionary rep times.
`void`	`addToEntryVectorized(double[] v, int f1, int f2, int f3, int f4, int f5, int f6, int f7, int f8, int t1, int t2, int t3, int t4, int t5, int t6, int t7, int t8, int nCol)`	Vectorized add to entry, this call helps with a bit of locality for the cache.
`double`	`aggregate(double init, Builtin fn)`	Aggregate all the contained values, useful in value only computations where the operation is iterating through all values contained in the dictionary.
`void`	`aggregateCols(double[] c, Builtin fn, IColIndex colIndexes)`	Aggregates the columns into the target double array provided.
`void`	`aggregateColsWithReference(double[] c, Builtin fn, IColIndex colIndexes, double[] reference, boolean def)`	Aggregates the columns into the target double array provided.
`double[]`	`aggregateRows(Builtin fn, int nCol)`	Aggregate all entries in the rows.
`double[]`	`aggregateRowsWithDefault(Builtin fn, double[] defaultTuple)`	Aggregate all entries in the rows of the dictionary with a extra cell in the end that contains the aggregate of the given defaultTuple.
`double[]`	`aggregateRowsWithReference(Builtin fn, double[] reference)`	Aggregate all entries in the rows with an offset value reference added.
`double`	`aggregateWithReference(double init, Builtin fn, double[] reference, boolean def)`	Aggregate all the contained values, with a reference offset.
`IDictionary`	`applyScalarOp(ScalarOperator op)`	Allocate a new dictionary and applies the scalar operation on each cell of to then return the new dictionary.
`IDictionary`	`applyScalarOpAndAppend(ScalarOperator op, double v0, int nCol)`	Allocate a new dictionary with one extra row and applies the scalar operation on each cell of to then return the new dictionary.
`IDictionary`	`applyScalarOpWithReference(ScalarOperator op, double[] reference, double[] newReference)`	Allocate a new dictionary and apply the scalar operation on each cell to then return a new dictionary.
`IDictionary`	`applyUnaryOp(UnaryOperator op)`	Allocate a new dictionary and apply the unary operator on each cell.
`IDictionary`	`applyUnaryOpAndAppend(UnaryOperator op, double v0, int nCol)`	Allocate a new dictionary with one extra row and apply the unary operator on each cell.
`IDictionary`	`applyUnaryOpWithReference(UnaryOperator op, double[] reference, double[] newReference)`	Allocate a new dictionary and apply the scalar operation on each cell to then return a new dictionary.
`IDictionary`	`binOpLeft(BinaryOperator op, double[] v, IColIndex colIndexes)`	Apply binary row operation on the left side
`IDictionary`	`binOpLeftAndAppend(BinaryOperator op, double[] v, IColIndex colIndexes)`	Apply binary row operation on the left side with one extra row evaluating with zeros.
`IDictionary`	`binOpLeftWithReference(BinaryOperator op, double[] v, IColIndex colIndexes, double[] reference, double[] newReference)`	Apply the binary operator such that each value is offset by the reference before application.
`IDictionary`	`binOpRight(BinaryOperator op, double[] v)`	Apply binary row operation on the right side as with no columns to extract from v.
`IDictionary`	`binOpRight(BinaryOperator op, double[] v, IColIndex colIndexes)`	Apply binary row operation on the right side.
`IDictionary`	`binOpRightAndAppend(BinaryOperator op, double[] v, IColIndex colIndexes)`	Apply binary row operation on the right side with one extra row evaluating with zeros.
`IDictionary`	`binOpRightWithReference(BinaryOperator op, double[] v, IColIndex colIndexes, double[] reference, double[] newReference)`	Apply the binary operator such that each value is offset by the reference before application.
`IDictionary`	`cbind(IDictionary that, int nCol)`	Cbind this dictionary with that dictionary
`CM_COV_Object`	`centralMoment(ValueFunction fn, int[] counts, int nRows)`	Central moment function to calculate the central moment of this column group.
`CM_COV_Object`	`centralMoment(CM_COV_Object ret, ValueFunction fn, int[] counts, int nRows)`	Central moment function to calculate the central moment of this column group.
`CM_COV_Object`	`centralMomentWithDefault(ValueFunction fn, int[] counts, double def, int nRows)`	Central moment function to calculate the central moment of this column group with a default offset on all missing tuples.
`CM_COV_Object`	`centralMomentWithDefault(CM_COV_Object ret, ValueFunction fn, int[] counts, double def, int nRows)`	Central moment function to calculate the central moment of this column group with a default offset on all missing tuples.
`CM_COV_Object`	`centralMomentWithReference(ValueFunction fn, int[] counts, double reference, int nRows)`	Central moment function to calculate the central moment of this column group with a reference offset on each tuple.
`CM_COV_Object`	`centralMomentWithReference(CM_COV_Object ret, ValueFunction fn, int[] counts, double reference, int nRows)`	Central moment function to calculate the central moment of this column group with a reference offset on each tuple.
`IDictionary`	`clone()`	Returns a deep clone of the dictionary.
`void`	`colProduct(double[] res, int[] counts, IColIndex colIndexes)`	Calculate the column product of the dictionary weighted by counts.
`void`	`colProductWithReference(double[] res, int[] counts, IColIndex colIndexes, double[] reference)`	Calculate the column product of the dictionary weighted by counts.
`void`	`colSum(double[] c, int[] counts, IColIndex colIndexes)`	Get the column sum of the values contained in the dictionary
`void`	`colSumSq(double[] c, int[] counts, IColIndex colIndexes)`	Get the column sum of the values contained in the dictionary
`void`	`colSumSqWithReference(double[] c, int[] counts, IColIndex colIndexes, double[] reference)`	Get the column sum of the values contained in the dictionary with an offset reference value added to each cell.
`boolean`	`containsValue(double pattern)`	Detect if the dictionary contains a specific value.
`boolean`	`containsValueWithReference(double pattern, double[] reference)`	Detect if the dictionary contains a specific value with reference offset.
`boolean`	`equals(double[] v)`	Indicate if this object is equal to the given array of doubles.
`boolean`	`equals(Object o)`	Indicate if this object is equal to another this takes into part sematic equivalence
`boolean`	`equals(IDictionary o)`	Indicate if the other dictionary is equal to this.
`IDictionary.DictType`	`getDictType()`	Get the dictionary type this dictionary is.
`long`	`getExactSizeOnDisk()`	Calculate the space consumption if the dictionary is stored on disk.
`long`	`getInMemorySize()`	Returns the memory usage of the dictionary.
`MatrixBlockDictionary`	`getMBDict(int nCol)`	Get this dictionary as a MatrixBlock dictionary.
`long`	`getNumberNonZeros(int[] counts, int nCol)`	Calculate the number of non zeros in the dictionary.
`long`	`getNumberNonZerosWithReference(int[] counts, double[] reference, int nRows)`	Calculate the number of non zeros in the dictionary.
`int`	`getNumberOfValues(int ncol)`	Get the number of distinct tuples given that the column group has n columns
`double`	`getSparsity()`	Get the sparsity of the dictionary.
`String`	`getString(int colIndexes)`	Get a string representation of the dictionary, that considers the layout of the data.
`double`	`getValue(int i)`	Get Specific value contained in the dictionary at index.
`double`	`getValue(int r, int col, int nCol)`	Get Specific value contain in dictionary at index.
`double[]`	`getValues()`	Get all the values contained in the dictionary as a linearized double array.
`void`	`MMDict(IDictionary right, IColIndex rowsLeft, IColIndex colsRight, MatrixBlock result)`	Matrix multiplication of dictionaries Note the left is this, and it is transposed
`void`	`MMDictDense(double[] left, IColIndex rowsLeft, IColIndex colsRight, MatrixBlock result)`	Matrix multiplication of dictionaries left side dense and transposed right side is this.
`void`	`MMDictScaling(IDictionary right, IColIndex rowsLeft, IColIndex colsRight, MatrixBlock result, int[] scaling)`	Matrix multiplication of dictionaries Note the left is this, and it is transposed
`void`	`MMDictScalingDense(double[] left, IColIndex rowsLeft, IColIndex colsRight, MatrixBlock result, int[] scaling)`	Matrix multiplication of dictionaries left side dense and transposed right side is this.
`void`	`MMDictScalingSparse(SparseBlock left, IColIndex rowsLeft, IColIndex colsRight, MatrixBlock result, int[] scaling)`	Matrix multiplication of dictionaries left side sparse and transposed right side is this.
`void`	`MMDictSparse(SparseBlock left, IColIndex rowsLeft, IColIndex colsRight, MatrixBlock result)`	Matrix multiplication of dictionaries left side sparse and transposed right side is this.
`void`	`multiplyScalar(double v, double[] ret, int off, int dictIdx, IColIndex cols)`	Multiply the v value with the dictionary entry at dictIdx and add it to the ret matrix at the columns specified in the int array.
`IDictionary`	`preaggValuesFromDense(int numVals, IColIndex colIndexes, IColIndex aggregateColumns, double[] b, int cut)`	Pre Aggregate values for Right Matrix Multiplication.
`void`	`product(double[] ret, int[] counts, int nCol)`	Calculate the product of the dictionary weighted by counts.
`double[]`	`productAllRowsToDouble(int nrColumns)`	Method to product all rows to a column vector.
`double[]`	`productAllRowsToDoubleWithDefault(double[] defaultTuple)`	Method to product all rows to a column vector with a default value added in the end.
`double[]`	`productAllRowsToDoubleWithReference(double[] reference)`	Method to product all rows to a column vector with a reference values added to all cells, and a reference product in the end
`void`	`productWithDefault(double[] ret, int[] counts, double[] def, int defCount)`	Calculate the product of the dictionary weighted by counts with a default value added .
`void`	`productWithReference(double[] ret, int[] counts, double[] reference, int refCount)`	Calculate the product of the dictionary weighted by counts and offset by reference
`IDictionary`	`reorder(int[] reorder)`	Reorder the elements in the dictionary based on the reorder specification given.
`IDictionary`	`replace(double pattern, double replace, int nCol)`	Make a copy of the values, and replace all values that match pattern with replacement value.
`IDictionary`	`replaceWithReference(double pattern, double replace, double[] reference)`	Make a copy of the values, and replace all values that match pattern with replacement value.
`IDictionary`	`rexpandCols(int max, boolean ignore, boolean cast, int nCol)`	Rexpand the dictionary (one hot encode)
`IDictionary`	`rexpandColsWithReference(int max, boolean ignore, boolean cast, int reference)`	Rexpand the dictionary (one hot encode)
`IDictionary`	`scaleTuples(int[] scaling, int nCol)`	Scale all tuples contained in the dictionary by the scaling factor given in the int list.
`IDictionary`	`sliceOutColumnRange(int idxStart, int idxEnd, int previousNumberOfColumns)`	Modify the dictionary by removing columns not within the index range.
`IDictionary`	`subtractTuple(double[] tuple)`	Allocate a new dictionary where the tuple given is subtracted from all tuples in the previous dictionary.
`double`	`sum(int[] counts, int nCol)`	Get the sum of the values contained in the dictionary
`double[]`	`sumAllRowsToDouble(int nrColumns)`	Method used as a pre-aggregate of each tuple in the dictionary, to single double values.
`double[]`	`sumAllRowsToDoubleSq(int nrColumns)`	Method used as a pre-aggregate of each tuple in the dictionary, to single double values.
`double[]`	`sumAllRowsToDoubleSqWithDefault(double[] defaultTuple)`	Method used as a pre-aggregate of each tuple in the dictionary, to single double values.
`double[]`	`sumAllRowsToDoubleSqWithReference(double[] reference)`	Method used as a pre-aggregate of each tuple in the dictionary, to single double values.
`double[]`	`sumAllRowsToDoubleWithDefault(double[] defaultTuple)`	Do exactly the same as the sumAllRowsToDouble but also sum the array given to a extra index in the end of the array.
`double[]`	`sumAllRowsToDoubleWithReference(double[] reference)`	Method used as a pre-aggregate of each tuple in the dictionary, to single double values with a reference.
`double`	`sumSq(int[] counts, int nCol)`	Get the square sum of the values contained in the dictionary
`double`	`sumSqWithReference(int[] counts, double[] reference)`	Get the square sum of the values contained in the dictionary with a reference offset on each value.
`void`	`TSMMToUpperTriangle(IDictionary right, IColIndex rowsLeft, IColIndex colsRight, MatrixBlock result)`	Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is left
`void`	`TSMMToUpperTriangleDense(double[] left, IColIndex rowsLeft, IColIndex colsRight, MatrixBlock result)`	Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is right
`void`	`TSMMToUpperTriangleDenseScaling(double[] left, IColIndex rowsLeft, IColIndex colsRight, int[] scale, MatrixBlock result)`	Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is right
`void`	`TSMMToUpperTriangleScaling(IDictionary right, IColIndex rowsLeft, IColIndex colsRight, int[] scale, MatrixBlock result)`	Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is left
`void`	`TSMMToUpperTriangleSparse(SparseBlock left, IColIndex rowsLeft, IColIndex colsRight, MatrixBlock result)`	Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is right
`void`	`TSMMToUpperTriangleSparseScaling(SparseBlock left, IColIndex rowsLeft, IColIndex colsRight, int[] scale, MatrixBlock result)`	Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is right
`void`	`TSMMWithScaling(int[] counts, IColIndex rows, IColIndex cols, MatrixBlock ret)`	Transpose self matrix multiplication with a scaling factor on each pair of values.
`void`	`write(DataOutput out)`	Write the dictionary to a DataOutput.

- Field Detail
  - LOG
```
static final org.apache.commons.logging.Log LOG
```
- Method Detail
  - getValues
```
double[] getValues()
```
    Get all the values contained in the dictionary as a linearized double array.
    
    Returns:
    
    linearized double array
  - getValue
```
double getValue(int i)
```
    Get Specific value contained in the dictionary at index.
    
    Parameters:
    
    i - The index to extract the value from
    
    Returns:
    
    The value contained at the index
  - getValue
```
double getValue(int r,
                int col,
                int nCol)
```
    Get Specific value contain in dictionary at index.
    
    Parameters:
    
    r - Row target
    
    col - Col target
    
    nCol - nCol in dictionary
    
    Returns:
    
    value
  - getInMemorySize
```
long getInMemorySize()
```
    Returns the memory usage of the dictionary.
    
    Returns:
    
    a long value in number of bytes for the dictionary.
  - aggregate
```
double aggregate(double init,
                 Builtin fn)
```
    Aggregate all the contained values, useful in value only computations where the operation is iterating through all values contained in the dictionary.
    
    Parameters:
    
    init - The initial Value, in cases such as Max value, this could be -infinity
    
    fn - The Function to apply to values
    
    Returns:
    
    The aggregated value as a double.
  - aggregateWithReference
```
double aggregateWithReference(double init,
                              Builtin fn,
                              double[] reference,
                              boolean def)
```
    Aggregate all the contained values, with a reference offset.
    
    Parameters:
    
    init - The initial value, in cases such as Max value this could be -infinity.
    
    fn - The function to apply to the values
    
    reference - The reference offset to each value in the dictionary
    
    def - If the reference should be treated as an instance of only as reference
    
    Returns:
    
    The aggregated value as a double.
  - aggregateRows
```
double[] aggregateRows(Builtin fn,
                       int nCol)
```
    Aggregate all entries in the rows.
    
    Parameters:
    
    fn - The aggregate function
    
    nCol - The number of columns contained in the dictionary.
    
    Returns:
    
    Aggregates for this dictionary tuples.
  - aggregateRowsWithDefault
```
double[] aggregateRowsWithDefault(Builtin fn,
                                  double[] defaultTuple)
```
    Aggregate all entries in the rows of the dictionary with a extra cell in the end that contains the aggregate of the given defaultTuple.
    
    Parameters:
    
    fn - The aggregate function
    
    defaultTuple - The default tuple to aggregate in last cell
    
    Returns:
    
    Aggregates for this dictionary tuples.
  - aggregateRowsWithReference
```
double[] aggregateRowsWithReference(Builtin fn,
                                    double[] reference)
```
    Aggregate all entries in the rows with an offset value reference added.
    
    Parameters:
    
    fn - The aggregate function
    
    reference - The reference offset to each value in the dictionary
    
    Returns:
    
    Aggregates for this dictionary tuples.
  - aggregateCols
```
void aggregateCols(double[] c,
                   Builtin fn,
                   IColIndex colIndexes)
```
    Aggregates the columns into the target double array provided.
    
    Parameters:
    
    c - The target double array, this contains the full number of columns, therefore the colIndexes for this specific dictionary is needed.
    
    fn - The function to apply to individual columns
    
    colIndexes - The mapping to the target columns from the individual columns
  - aggregateColsWithReference
```
void aggregateColsWithReference(double[] c,
                                Builtin fn,
                                IColIndex colIndexes,
                                double[] reference,
                                boolean def)
```
    Aggregates the columns into the target double array provided.
    
    Parameters:
    
    c - The target double array, this contains the full number of columns, therefore the colIndexes for this specific dictionary is needed.
    
    fn - The function to apply to individual columns
    
    colIndexes - The mapping to the target columns from the individual columns
    
    reference - The reference offset values to add to each cell.
    
    def - If the reference should be treated as a tuple as well
  - applyScalarOp
```
IDictionary applyScalarOp(ScalarOperator op)
```
    Allocate a new dictionary and applies the scalar operation on each cell of to then return the new dictionary.
    
    Parameters:
    
    op - The operator.
    
    Returns:
    
    The new dictionary to return.
  - applyScalarOpAndAppend
```
IDictionary applyScalarOpAndAppend(ScalarOperator op,
                                   double v0,
                                   int nCol)
```
    Allocate a new dictionary with one extra row and applies the scalar operation on each cell of to then return the new dictionary.
    
    Parameters:
    
    op - The operator
    
    v0 - The new value to put into each cell in the new row
    
    nCol - The number of columns in the dictionary
    
    Returns:
    
    The new dictionary to return.
  - applyUnaryOp
```
IDictionary applyUnaryOp(UnaryOperator op)
```
    Allocate a new dictionary and apply the unary operator on each cell.
    
    Parameters:
    
    op - The operator.
    
    Returns:
    
    The new dictionary to return.
  - applyUnaryOpAndAppend
```
IDictionary applyUnaryOpAndAppend(UnaryOperator op,
                                  double v0,
                                  int nCol)
```
    Allocate a new dictionary with one extra row and apply the unary operator on each cell.
    
    Parameters:
    
    op - The operator.
    
    v0 - The new value to put into each cell in the new row
    
    nCol - The number of columns in the dictionary
    
    Returns:
    
    The new dictionary to return.
  - applyScalarOpWithReference
```
IDictionary applyScalarOpWithReference(ScalarOperator op,
                                       double[] reference,
                                       double[] newReference)
```
    Allocate a new dictionary and apply the scalar operation on each cell to then return a new dictionary. outValues[j] = op(this.values[j] + reference[i]) - newReference[i]
    
    Parameters:
    
    op - The operator to apply to each cell.
    
    reference - The reference value to add before the operator.
    
    newReference - The reference value to subtract after the operator.
    
    Returns:
    
    A New Dictionary.
  - applyUnaryOpWithReference
```
IDictionary applyUnaryOpWithReference(UnaryOperator op,
                                      double[] reference,
                                      double[] newReference)
```
    Allocate a new dictionary and apply the scalar operation on each cell to then return a new dictionary. outValues[j] = op(this.values[j] + reference[i]) - newReference[i]
    
    Parameters:
    
    op - The unary operator to apply to each cell.
    
    reference - The reference value to add before the operator.
    
    newReference - The reference value to subtract after the operator.
    
    Returns:
    
    A New Dictionary.
  - binOpLeft
```
IDictionary binOpLeft(BinaryOperator op,
                      double[] v,
                      IColIndex colIndexes)
```
    Apply binary row operation on the left side
    
    Parameters:
    
    op - The operation to this dictionary
    
    v - The values to use on the left hand side.
    
    colIndexes - The column indexes to consider inside v.
    
    Returns:
    
    A new dictionary containing the updated values.
  - binOpLeftAndAppend
```
IDictionary binOpLeftAndAppend(BinaryOperator op,
                               double[] v,
                               IColIndex colIndexes)
```
    Apply binary row operation on the left side with one extra row evaluating with zeros.
    
    Parameters:
    
    op - The operation to this dictionary
    
    v - The values to use on the left hand side.
    
    colIndexes - The column indexes to consider inside v.
    
    Returns:
    
    A new dictionary containing the updated values.
  - binOpLeftWithReference
```
IDictionary binOpLeftWithReference(BinaryOperator op,
                                   double[] v,
                                   IColIndex colIndexes,
                                   double[] reference,
                                   double[] newReference)
```
    Apply the binary operator such that each value is offset by the reference before application. Then put the result into the new dictionary, but offset it by the new reference. outValues[j] = op(v[colIndexes[i]], this.values[j] + reference[i]) - newReference[i]
    
    Parameters:
    
    op - The operation to apply on the dictionary values.
    
    v - The values to use on the left side of the operator.
    
    colIndexes - The column indexes to use.
    
    reference - The reference value to add before operator.
    
    newReference - The reference value to subtract after operator.
    
    Returns:
    
    A new dictionary.
  - binOpRight
```
IDictionary binOpRight(BinaryOperator op,
                       double[] v,
                       IColIndex colIndexes)
```
    Apply binary row operation on the right side.
    
    Parameters:
    
    op - The operation to this dictionary
    
    v - The values to use on the right hand side.
    
    colIndexes - The column indexes to consider inside v.
    
    Returns:
    
    A new dictionary containing the updated values.
  - binOpRightAndAppend
```
IDictionary binOpRightAndAppend(BinaryOperator op,
                                double[] v,
                                IColIndex colIndexes)
```
    Apply binary row operation on the right side with one extra row evaluating with zeros.
    
    Parameters:
    
    op - The operation to this dictionary
    
    v - The values to use on the right hand side.
    
    colIndexes - The column indexes to consider inside v.
    
    Returns:
    
    A new dictionary containing the updated values.
  - binOpRight
```
IDictionary binOpRight(BinaryOperator op,
                       double[] v)
```
    Apply binary row operation on the right side as with no columns to extract from v.
    
    Parameters:
    
    op - The operation to this dictionary
    
    v - The values to apply on the dictionary (same number of cols as the dictionary)
    
    Returns:
    
    A new dictionary containing the updated values.
  - binOpRightWithReference
```
IDictionary binOpRightWithReference(BinaryOperator op,
                                    double[] v,
                                    IColIndex colIndexes,
                                    double[] reference,
                                    double[] newReference)
```
    Apply the binary operator such that each value is offset by the reference before application. Then put the result into the new dictionary, but offset it by the new reference. outValues[j] = op(this.values[j] + reference[i], v[colIndexes[i]]) - newReference[i]
    
    Parameters:
    
    op - The operation to apply on the dictionary values.
    
    v - The values to use on the right side of the operator.
    
    colIndexes - The column indexes to use.
    
    reference - The reference value to add before operator.
    
    newReference - The reference value to subtract after operator.
    
    Returns:
    
    A new dictionary.
  - clone
```
IDictionary clone()
```
    Returns a deep clone of the dictionary.
    
    Returns:
    
    A deep clone
  - write
```
void write(DataOutput out)
    throws IOException
```
    Write the dictionary to a DataOutput.
    
    Parameters:
    
    out - the output sink to write the dictionary to.
    
    Throws:
    
    IOException - if the sink fails.
  - getExactSizeOnDisk
```
long getExactSizeOnDisk()
```
    Calculate the space consumption if the dictionary is stored on disk.
    
    Returns:
    
    the long count of bytes to store the dictionary.
  - getDictType
```
IDictionary.DictType getDictType()
```
    Get the dictionary type this dictionary is.
    
    Returns:
    
    The Dictionary type this is.
  - getNumberOfValues
```
int getNumberOfValues(int ncol)
```
    Get the number of distinct tuples given that the column group has n columns
    
    Parameters:
    
    ncol - The number of Columns in the ColumnGroup.
    
    Returns:
    
    the number of value tuples contained in the dictionary.
  - sumAllRowsToDouble
```
double[] sumAllRowsToDouble(int nrColumns)
```
    Method used as a pre-aggregate of each tuple in the dictionary, to single double values. Note if the number of columns is one the actual dictionaries values are simply returned.
    
    Parameters:
    
    nrColumns - The number of columns in the ColGroup to know how to get the values from the dictionary.
    
    Returns:
    
    a double array containing the row sums from this dictionary.
  - sumAllRowsToDoubleWithDefault
```
double[] sumAllRowsToDoubleWithDefault(double[] defaultTuple)
```
    Do exactly the same as the sumAllRowsToDouble but also sum the array given to a extra index in the end of the array.
    
    Parameters:
    
    defaultTuple - The default row to sum in the end index returned.
    
    Returns:
    
    a double array containing the row sums from this dictionary.
  - sumAllRowsToDoubleWithReference
```
double[] sumAllRowsToDoubleWithReference(double[] reference)
```
    Method used as a pre-aggregate of each tuple in the dictionary, to single double values with a reference.
    
    Parameters:
    
    reference - The reference values to add to each cell.
    
    Returns:
    
    a double array containing the row sums from this dictionary.
  - sumAllRowsToDoubleSq
```
double[] sumAllRowsToDoubleSq(int nrColumns)
```
    Method used as a pre-aggregate of each tuple in the dictionary, to single double values. Note if the number of columns is one the actual dictionaries values are simply returned.
    
    Parameters:
    
    nrColumns - The number of columns in the ColGroup to know how to get the values from the dictionary.
    
    Returns:
    
    a double array containing the row sums from this dictionary.
  - sumAllRowsToDoubleSqWithDefault
```
double[] sumAllRowsToDoubleSqWithDefault(double[] defaultTuple)
```
    Method used as a pre-aggregate of each tuple in the dictionary, to single double values. But adds another cell to the return with an extra value that is the sum of the given defaultTuple.
    
    Parameters:
    
    defaultTuple - The default row to sum in the end index returned.
    
    Returns:
    
    a double array containing the row sums from this dictionary.
  - sumAllRowsToDoubleSqWithReference
```
double[] sumAllRowsToDoubleSqWithReference(double[] reference)
```
    Method used as a pre-aggregate of each tuple in the dictionary, to single double values.
    
    Parameters:
    
    reference - The reference values to add to each cell.
    
    Returns:
    
    a double array containing the row sums from this dictionary.
  - productAllRowsToDouble
```
double[] productAllRowsToDouble(int nrColumns)
```
    Method to product all rows to a column vector.
    
    Parameters:
    
    nrColumns - The number of columns in the ColGroup to know how to get the values from the dictionary.
    
    Returns:
    
    A row product
  - productAllRowsToDoubleWithDefault
```
double[] productAllRowsToDoubleWithDefault(double[] defaultTuple)
```
    Method to product all rows to a column vector with a default value added in the end.
    
    Parameters:
    
    defaultTuple - The default row that aggregate to last cell
    
    Returns:
    
    A row product
  - productAllRowsToDoubleWithReference
```
double[] productAllRowsToDoubleWithReference(double[] reference)
```
    Method to product all rows to a column vector with a reference values added to all cells, and a reference product in the end
    
    Parameters:
    
    reference - The reference row
    
    Returns:
    
    A row product
  - colSum
```
void colSum(double[] c,
            int[] counts,
            IColIndex colIndexes)
```
    Get the column sum of the values contained in the dictionary
    
    Parameters:
    
    c - The output array allocated to contain all column groups output.
    
    counts - The counts of the individual tuples.
    
    colIndexes - The columns indexes of the parent column group, this indicate where to put the column sum into the c output.
  - colSumSq
```
void colSumSq(double[] c,
              int[] counts,
              IColIndex colIndexes)
```
    Get the column sum of the values contained in the dictionary
    
    Parameters:
    
    c - The output array allocated to contain all column groups output.
    
    counts - The counts of the individual tuples.
    
    colIndexes - The columns indexes of the parent column group, this indicate where to put the column sum into the c output.
  - colSumSqWithReference
```
void colSumSqWithReference(double[] c,
                           int[] counts,
                           IColIndex colIndexes,
                           double[] reference)
```
    Get the column sum of the values contained in the dictionary with an offset reference value added to each cell.
    
    Parameters:
    
    c - The output array allocated to contain all column groups output.
    
    counts - The counts of the individual tuples.
    
    colIndexes - The columns indexes of the parent column group, this indicate where to put the column sum into the c output.
    
    reference - The reference values to add to each cell.
  - sum
```
double sum(int[] counts,
           int nCol)
```
    Get the sum of the values contained in the dictionary
    
    Parameters:
    
    counts - The counts of the individual tuples
    
    nCol - The number of columns contained
    
    Returns:
    
    The sum scaled by the counts provided.
  - sumSq
```
double sumSq(int[] counts,
             int nCol)
```
    Get the square sum of the values contained in the dictionary
    
    Parameters:
    
    counts - The counts of the individual tuples
    
    nCol - The number of columns contained
    
    Returns:
    
    The square sum scaled by the counts provided.
  - sumSqWithReference
```
double sumSqWithReference(int[] counts,
                          double[] reference)
```
    Get the square sum of the values contained in the dictionary with a reference offset on each value.
    
    Parameters:
    
    counts - The counts of the individual tuples
    
    reference - The reference value
    
    Returns:
    
    The square sum scaled by the counts and reference.
  - getString
```
String getString(int colIndexes)
```
    Get a string representation of the dictionary, that considers the layout of the data.
    
    Parameters:
    
    colIndexes - The number of columns in the dictionary.
    
    Returns:
    
    A string that is nicer to print.
  - sliceOutColumnRange
```
IDictionary sliceOutColumnRange(int idxStart,
                                int idxEnd,
                                int previousNumberOfColumns)
```
    Modify the dictionary by removing columns not within the index range.
    
    Parameters:
    
    idxStart - The column index to start at.
    
    idxEnd - The column index to end at (not inclusive)
    
    previousNumberOfColumns - The number of columns contained in the dictionary.
    
    Returns:
    
    A dictionary containing the sliced out columns values only.
  - containsValue
```
boolean containsValue(double pattern)
```
    Detect if the dictionary contains a specific value.
    
    Parameters:
    
    pattern - The value to search for
    
    Returns:
    
    true if the value is contained else false.
  - containsValueWithReference
```
boolean containsValueWithReference(double pattern,
                                   double[] reference)
```
    Detect if the dictionary contains a specific value with reference offset.
    
    Parameters:
    
    pattern - The pattern/ value to search for
    
    reference - The reference double array.
    
    Returns:
    
    true if the value is contained else false.
  - getNumberNonZeros
```
long getNumberNonZeros(int[] counts,
                       int nCol)
```
    Calculate the number of non zeros in the dictionary. The number of non zeros should be scaled with the counts given. This gives the exact number of non zero values in the parent column group.
    
    Parameters:
    
    counts - The counts of each dictionary entry
    
    nCol - The number of columns in this dictionary
    
    Returns:
    
    The nonZero count
  - getNumberNonZerosWithReference
```
long getNumberNonZerosWithReference(int[] counts,
                                    double[] reference,
                                    int nRows)
```
    Calculate the number of non zeros in the dictionary. Each value in the dictionary should be added to the reference value. The number of non zeros should be scaled with the given counts.
    
    Parameters:
    
    counts - The Counts of each dict entry.
    
    reference - The reference vector.
    
    nRows - The number of rows in the input.
    
    Returns:
    
    The NonZero Count.
  - addToEntry
```
void addToEntry(double[] v,
                int fr,
                int to,
                int nCol)
```
    Adds the dictionary entry from this dictionary to the d dictionary
    
    Parameters:
    
    v - The target dictionary (dense double array)
    
    fr - The from index is the tuple index to copy from.
    
    to - The to index is the row index to copy into.
    
    nCol - The number of columns in both cases
  - addToEntry
```
void addToEntry(double[] v,
                int fr,
                int to,
                int nCol,
                int rep)
```
    Adds the dictionary entry from this dictionary to the v dictionary rep times.
    
    Parameters:
    
    v - The target dictionary (dense double array)
    
    fr - The from index is the tuple index to copy from.
    
    to - The to index is the row index to copy into.
    
    nCol - The number of columns in both cases
    
    rep - The number of repetitions to apply (simply multiply do not loop)
  - addToEntryVectorized
```
void addToEntryVectorized(double[] v,
                          int f1,
                          int f2,
                          int f3,
                          int f4,
                          int f5,
                          int f6,
                          int f7,
                          int f8,
                          int t1,
                          int t2,
                          int t3,
                          int t4,
                          int t5,
                          int t6,
                          int t7,
                          int t8,
                          int nCol)
```
    Vectorized add to entry, this call helps with a bit of locality for the cache.
    
    Parameters:
    
    v - The target dictionary (dense double array)
    
    f1 - From index 1
    
    f2 - From index 2
    
    f3 - From index 3
    
    f4 - From index 4
    
    f5 - From index 5
    
    f6 - From index 6
    
    f7 - From index 7
    
    f8 - From index 8
    
    t1 - To index 1
    
    t2 - To index 2
    
    t3 - To index 3
    
    t4 - To index 4
    
    t5 - To index 5
    
    t6 - To index 6
    
    t7 - To index 7
    
    t8 - To index 8
    
    nCol - Number of columns in the dictionary
  - subtractTuple
```
IDictionary subtractTuple(double[] tuple)
```
    Allocate a new dictionary where the tuple given is subtracted from all tuples in the previous dictionary.
    
    Parameters:
    
    tuple - a double list representing a tuple, it is given that the tuple with is the same as this dictionaries.
    
    Returns:
    
    a new instance of dictionary with the tuple subtracted.
  - getMBDict
```
MatrixBlockDictionary getMBDict(int nCol)
```
    Get this dictionary as a MatrixBlock dictionary. This allows us to use optimized kernels coded elsewhere in the system, such as matrix multiplication. Return null if the matrix is empty.
    
    Parameters:
    
    nCol - The number of columns contained in this column group.
    
    Returns:
    
    A Dictionary containing a MatrixBlock.
  - scaleTuples
```
IDictionary scaleTuples(int[] scaling,
                        int nCol)
```
    Scale all tuples contained in the dictionary by the scaling factor given in the int list.
    
    Parameters:
    
    scaling - The amount to multiply the given tuples with
    
    nCol - The number of columns contained in this column group.
    
    Returns:
    
    A New dictionary (since we don't want to modify the underlying dictionary)
  - preaggValuesFromDense
```
IDictionary preaggValuesFromDense(int numVals,
                                  IColIndex colIndexes,
                                  IColIndex aggregateColumns,
                                  double[] b,
                                  int cut)
```
    Pre Aggregate values for Right Matrix Multiplication.
    
    Parameters:
    
    numVals - The number of values contained in this dictionary
    
    colIndexes - The column indexes that is associated with the parent column group
    
    aggregateColumns - The column to aggregate, this is preprocessed, to find remove consideration for empty columns
    
    b - The values in the right hand side matrix
    
    cut - The number of columns in b.
    
    Returns:
    
    A new dictionary with the pre aggregated values.
  - replace
```
IDictionary replace(double pattern,
                    double replace,
                    int nCol)
```
    Make a copy of the values, and replace all values that match pattern with replacement value. If needed add a new column index.
    
    Parameters:
    
    pattern - The value to look for
    
    replace - The value to replace the other value with
    
    nCol - The number of columns contained in the dictionary.
    
    Returns:
    
    A new Column Group, reusing the index structure but with new values.
  - replaceWithReference
```
IDictionary replaceWithReference(double pattern,
                                 double replace,
                                 double[] reference)
```
    Make a copy of the values, and replace all values that match pattern with replacement value. If needed add a new column index. With reference such that each value in the dict is considered offset by the values contained in the reference.
    
    Parameters:
    
    pattern - The value to look for
    
    replace - The value to replace the other value with
    
    reference - The reference tuple to add to all entries when replacing
    
    Returns:
    
    A new Column Group, reusing the index structure but with new values.
  - product
```
void product(double[] ret,
             int[] counts,
             int nCol)
```
    Calculate the product of the dictionary weighted by counts.
    
    Parameters:
    
    ret - The result dense double array (containing one value)
    
    counts - The count of individual tuples
    
    nCol - Number of columns in the dictionary.
  - productWithDefault
```
void productWithDefault(double[] ret,
                        int[] counts,
                        double[] def,
                        int defCount)
```
    Calculate the product of the dictionary weighted by counts with a default value added .
    
    Parameters:
    
    ret - The result dense double array (containing one value)
    
    counts - The count of individual tuples
    
    def - The default tuple
    
    defCount - The count of the default tuple
  - productWithReference
```
void productWithReference(double[] ret,
                          int[] counts,
                          double[] reference,
                          int refCount)
```
    Calculate the product of the dictionary weighted by counts and offset by reference
    
    Parameters:
    
    ret - The result dense double array (containing one value)
    
    counts - The counts of each entry in the dictionary
    
    reference - The reference value.
    
    refCount - The number of occurrences of the ref value.
  - colProduct
```
void colProduct(double[] res,
                int[] counts,
                IColIndex colIndexes)
```
    Calculate the column product of the dictionary weighted by counts.
    
    Parameters:
    
    res - The result vector to put the result into
    
    counts - The weighted count of individual tuples
    
    colIndexes - The column indexes.
  - colProductWithReference
```
void colProductWithReference(double[] res,
                             int[] counts,
                             IColIndex colIndexes,
                             double[] reference)
```
    Calculate the column product of the dictionary weighted by counts.
    
    Parameters:
    
    res - The result vector to put the result into
    
    counts - The weighted count of individual tuples
    
    colIndexes - The column indexes.
    
    reference - The reference value.
  - centralMoment
```
CM_COV_Object centralMoment(ValueFunction fn,
                            int[] counts,
                            int nRows)
```
    Central moment function to calculate the central moment of this column group. MUST be on a single column dictionary.
    
    Parameters:
    
    fn - The value function to apply
    
    counts - The weight of individual tuples
    
    nRows - The number of rows in total of the column group
    
    Returns:
    
    The central moment Object
  - centralMoment
```
CM_COV_Object centralMoment(CM_COV_Object ret,
                            ValueFunction fn,
                            int[] counts,
                            int nRows)
```
    Central moment function to calculate the central moment of this column group. MUST be on a single column dictionary.
    
    Parameters:
    
    ret - The Central Moment object to be modified and returned
    
    fn - The value function to apply
    
    counts - The weight of individual tuples
    
    nRows - The number of rows in total of the column group
    
    Returns:
    
    The central moment Object
  - centralMomentWithDefault
```
CM_COV_Object centralMomentWithDefault(ValueFunction fn,
                                       int[] counts,
                                       double def,
                                       int nRows)
```
    Central moment function to calculate the central moment of this column group with a default offset on all missing tuples. MUST be on a single column dictionary.
    
    Parameters:
    
    fn - The value function to apply
    
    counts - The weight of individual tuples
    
    def - The default values to offset the tuples with
    
    nRows - The number of rows in total of the column group
    
    Returns:
    
    The central moment Object
  - centralMomentWithDefault
```
CM_COV_Object centralMomentWithDefault(CM_COV_Object ret,
                                       ValueFunction fn,
                                       int[] counts,
                                       double def,
                                       int nRows)
```
    Central moment function to calculate the central moment of this column group with a default offset on all missing tuples. MUST be on a single column dictionary.
    
    Parameters:
    
    ret - The Central Moment object to be modified and returned
    
    fn - The value function to apply
    
    counts - The weight of individual tuples
    
    def - The default values to offset the tuples with
    
    nRows - The number of rows in total of the column group
    
    Returns:
    
    The central moment Object
  - centralMomentWithReference
```
CM_COV_Object centralMomentWithReference(ValueFunction fn,
                                         int[] counts,
                                         double reference,
                                         int nRows)
```
    Central moment function to calculate the central moment of this column group with a reference offset on each tuple. MUST be on a single column dictionary.
    
    Parameters:
    
    fn - The value function to apply
    
    counts - The weight of individual tuples
    
    reference - The reference values to offset the tuples with
    
    nRows - The number of rows in total of the column group
    
    Returns:
    
    The central moment Object
  - centralMomentWithReference
```
CM_COV_Object centralMomentWithReference(CM_COV_Object ret,
                                         ValueFunction fn,
                                         int[] counts,
                                         double reference,
                                         int nRows)
```
    Central moment function to calculate the central moment of this column group with a reference offset on each tuple. MUST be on a single column dictionary.
    
    Parameters:
    
    ret - The Central Moment object to be modified and returned
    
    fn - The value function to apply
    
    counts - The weight of individual tuples
    
    reference - The reference values to offset the tuples with
    
    nRows - The number of rows in total of the column group
    
    Returns:
    
    The central moment Object
  - rexpandCols
```
IDictionary rexpandCols(int max,
                        boolean ignore,
                        boolean cast,
                        int nCol)
```
    Rexpand the dictionary (one hot encode)
    
    Parameters:
    
    max - the tuple width of the output
    
    ignore - If we should ignore zero and negative values
    
    cast - If we should cast all double values to whole integer values
    
    nCol - The number of columns in the dictionary already (should be 1)
    
    Returns:
    
    A new dictionary
  - rexpandColsWithReference
```
IDictionary rexpandColsWithReference(int max,
                                     boolean ignore,
                                     boolean cast,
                                     int reference)
```
    Rexpand the dictionary (one hot encode)
    
    Parameters:
    
    max - the tuple width of the output
    
    ignore - If we should ignore zero and negative values
    
    cast - If we should cast all double values to whole integer values
    
    reference - A reference value to add to all tuples before expanding
    
    Returns:
    
    A new dictionary
  - getSparsity
```
double getSparsity()
```
    Get the sparsity of the dictionary.
    
    Returns:
    
    a sparsity between 0 and 1
  - multiplyScalar
```
void multiplyScalar(double v,
                    double[] ret,
                    int off,
                    int dictIdx,
                    IColIndex cols)
```
    Multiply the v value with the dictionary entry at dictIdx and add it to the ret matrix at the columns specified in the int array.
    
    Parameters:
    
    v - Value to multiply
    
    ret - Output dense double array location
    
    off - Offset into the ret array that the "row" output starts at
    
    dictIdx - The dictionary entry to multiply.
    
    cols - The columns to multiply into of the output.
  - TSMMWithScaling
```
void TSMMWithScaling(int[] counts,
                     IColIndex rows,
                     IColIndex cols,
                     MatrixBlock ret)
```
    Transpose self matrix multiplication with a scaling factor on each pair of values.
    
    Parameters:
    
    counts - The scaling factor
    
    rows - The row indexes
    
    cols - The col indexes
    
    ret - The output matrix block
  - MMDict
```
void MMDict(IDictionary right,
            IColIndex rowsLeft,
            IColIndex colsRight,
            MatrixBlock result)
```
    Matrix multiplication of dictionaries Note the left is this, and it is transposed
    
    Parameters:
    
    right - Right hand side of multiplication
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    result - The output matrix block
  - MMDictScaling
```
void MMDictScaling(IDictionary right,
                   IColIndex rowsLeft,
                   IColIndex colsRight,
                   MatrixBlock result,
                   int[] scaling)
```
    Matrix multiplication of dictionaries Note the left is this, and it is transposed
    
    Parameters:
    
    right - Right hand side of multiplication
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    result - The output matrix block
    
    scaling - The scaling
  - MMDictDense
```
void MMDictDense(double[] left,
                 IColIndex rowsLeft,
                 IColIndex colsRight,
                 MatrixBlock result)
```
    Matrix multiplication of dictionaries left side dense and transposed right side is this.
    
    Parameters:
    
    left - Dense left side
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    result - The output matrix block
  - MMDictScalingDense
```
void MMDictScalingDense(double[] left,
                        IColIndex rowsLeft,
                        IColIndex colsRight,
                        MatrixBlock result,
                        int[] scaling)
```
    Matrix multiplication of dictionaries left side dense and transposed right side is this.
    
    Parameters:
    
    left - Dense left side
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    result - The output matrix block
    
    scaling - The scaling
  - MMDictSparse
```
void MMDictSparse(SparseBlock left,
                  IColIndex rowsLeft,
                  IColIndex colsRight,
                  MatrixBlock result)
```
    Matrix multiplication of dictionaries left side sparse and transposed right side is this.
    
    Parameters:
    
    left - Sparse left side
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    result - The output matrix block
  - MMDictScalingSparse
```
void MMDictScalingSparse(SparseBlock left,
                         IColIndex rowsLeft,
                         IColIndex colsRight,
                         MatrixBlock result,
                         int[] scaling)
```
    Matrix multiplication of dictionaries left side sparse and transposed right side is this.
    
    Parameters:
    
    left - Sparse left side
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    result - The output matrix block
    
    scaling - The scaling
  - TSMMToUpperTriangle
```
void TSMMToUpperTriangle(IDictionary right,
                         IColIndex rowsLeft,
                         IColIndex colsRight,
                         MatrixBlock result)
```
    Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is left
    
    Parameters:
    
    right - Right side
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    result - The output matrix block
  - TSMMToUpperTriangleDense
```
void TSMMToUpperTriangleDense(double[] left,
                              IColIndex rowsLeft,
                              IColIndex colsRight,
                              MatrixBlock result)
```
    Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is right
    
    Parameters:
    
    left - Dense left side
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    result - The output matrix block
  - TSMMToUpperTriangleSparse
```
void TSMMToUpperTriangleSparse(SparseBlock left,
                               IColIndex rowsLeft,
                               IColIndex colsRight,
                               MatrixBlock result)
```
    Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is right
    
    Parameters:
    
    left - Sparse left side
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    result - The output matrix block
  - TSMMToUpperTriangleScaling
```
void TSMMToUpperTriangleScaling(IDictionary right,
                                IColIndex rowsLeft,
                                IColIndex colsRight,
                                int[] scale,
                                MatrixBlock result)
```
    Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is left
    
    Parameters:
    
    right - Right side
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    scale - Scale factor
    
    result - The output matrix block
  - TSMMToUpperTriangleDenseScaling
```
void TSMMToUpperTriangleDenseScaling(double[] left,
                                     IColIndex rowsLeft,
                                     IColIndex colsRight,
                                     int[] scale,
                                     MatrixBlock result)
```
    Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is right
    
    Parameters:
    
    left - Dense left side
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    scale - Scale factor
    
    result - The output matrix block
  - TSMMToUpperTriangleSparseScaling
```
void TSMMToUpperTriangleSparseScaling(SparseBlock left,
                                      IColIndex rowsLeft,
                                      IColIndex colsRight,
                                      int[] scale,
                                      MatrixBlock result)
```
    Matrix multiplication but allocate output in upper triangle and twice if on diagonal, note this is right
    
    Parameters:
    
    left - Sparse left side
    
    rowsLeft - Offset rows on the left
    
    colsRight - Offset cols on the right
    
    scale - Scale factor
    
    result - The output matrix block
  - cbind
```
IDictionary cbind(IDictionary that,
                  int nCol)
```
    Cbind this dictionary with that dictionary
    
    Parameters:
    
    that - the right hand side dictionary to cbind
    
    nCol - the right hand side number of columns
    
    Returns:
    
    The combined dictionary
  - equals
```
boolean equals(Object o)
```
    Indicate if this object is equal to another this takes into part sematic equivalence
    
    Overrides:
    
    equals in class Object
    
    Parameters:
    
    o - The other object
    
    Returns:
    
    If they are equal
  - equals
```
boolean equals(double[] v)
```
    Indicate if this object is equal to the given array of doubles.
    
    Parameters:
    
    v - The list of double values
    
    Returns:
    
    If they are equal to this.
  - equals
```
boolean equals(IDictionary o)
```
    Indicate if the other dictionary is equal to this.
    
    Parameters:
    
    o - The other object
    
    Returns:
    
    If it is equal
  - reorder
```
IDictionary reorder(int[] reorder)
```
    Reorder the elements in the dictionary based on the reorder specification given.
    
    Parameters:
    
    reorder - The order to move to.
    
    Returns:
    
    A new Dictionary that is reordered.s

Interface IDictionary

Nested Class Summary

Field Summary

Method Summary

Field Detail

LOG

Method Detail

getValues

getValue

getValue

getInMemorySize

aggregate

aggregateWithReference

aggregateRows

aggregateRowsWithDefault

aggregateRowsWithReference

aggregateCols

aggregateColsWithReference

applyScalarOp

applyScalarOpAndAppend

applyUnaryOp

applyUnaryOpAndAppend

applyScalarOpWithReference

applyUnaryOpWithReference

binOpLeft

binOpLeftAndAppend

binOpLeftWithReference

binOpRight

binOpRightAndAppend

binOpRight

binOpRightWithReference

clone

write

getExactSizeOnDisk

getDictType

getNumberOfValues

sumAllRowsToDouble

sumAllRowsToDoubleWithDefault

sumAllRowsToDoubleWithReference

sumAllRowsToDoubleSq

sumAllRowsToDoubleSqWithDefault

sumAllRowsToDoubleSqWithReference

productAllRowsToDouble

productAllRowsToDoubleWithDefault

productAllRowsToDoubleWithReference

colSum

colSumSq

colSumSqWithReference

sum

sumSq

sumSqWithReference

getString

sliceOutColumnRange

containsValue

containsValueWithReference

getNumberNonZeros

getNumberNonZerosWithReference

addToEntry

addToEntry

addToEntryVectorized

subtractTuple

getMBDict

scaleTuples

preaggValuesFromDense

replace

replaceWithReference

product

productWithDefault

productWithReference

colProduct

colProductWithReference

centralMoment

centralMoment

centralMomentWithDefault

centralMomentWithDefault

centralMomentWithReference

centralMomentWithReference

rexpandCols

rexpandColsWithReference

getSparsity