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/*-
*
* * Copyright 2015 Skymind,Inc.
* *
* * Licensed under the Apache License, Version 2.0 (the "License");
* * you may not use this file except in compliance with the License.
* * You may obtain a copy of the License at
* *
* * http://www.apache.org/licenses/LICENSE-2.0
* *
* * Unless required by applicable law or agreed to in writing, software
* * distributed under the License is distributed on an "AS IS" BASIS,
* * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* * See the License for the specific language governing permissions and
* * limitations under the License.
*
*
*/
package org.nd4j.linalg.api.ndarray;
import com.google.flatbuffers.FlatBufferBuilder;
import org.nd4j.linalg.api.blas.params.MMulTranspose;
import org.nd4j.linalg.api.buffer.DataBuffer;
import org.nd4j.linalg.api.complex.IComplexNDArray;
import org.nd4j.linalg.api.complex.IComplexNumber;
import org.nd4j.linalg.exception.Nd4jNoSuchWorkspaceException;
import org.nd4j.linalg.indexing.INDArrayIndex;
import org.nd4j.linalg.indexing.ShapeOffsetResolution;
import org.nd4j.linalg.indexing.conditions.Condition;
import java.io.Serializable;
import java.nio.IntBuffer;
import java.util.List;
/**
* Interface for an ndarray
*
* @author Adam Gibson
*/
public interface INDArray extends Serializable {
/**
* Returns the shape information debugging
* information
* @return the shape information debugging information
*/
String shapeInfoToString();
/**
* Shape info
* @return
*/
DataBuffer shapeInfoDataBuffer();
/**
* Sparse info
* @return
*/
DataBuffer sparseInfoDataBuffer();
/**
* Shape info
* @return
*/
IntBuffer shapeInfo();
/**
* Returns true if this array is a view or not
* @return
*/
boolean isView();
/**
* Returns true if this array is sparse
* @return
*/
boolean isSparse();
/**
* Returns true if this array is compressed, and false otherwise
* @return
*/
boolean isCompressed();
/**
* This method marks INDArray instance as compressed
* PLEASE NOTE: Do not use this method unless you 100% have to
*
* @param reallyCompressed
*/
void markAsCompressed(boolean reallyCompressed);
/**
* Set the ndarray to wrap around
* @param wrapAround thewrap around
*/
void setWrapAround(boolean wrapAround);
/**
* Returns true if the ndarray
* on linear indexing wraps around
* based on the stride(1) of the ndarray
* This is a useful optimization in linear view
* where strides that might otherwise
* go out of bounds but wrap around instead.
*
* @return true if this ndarray wraps around on linear
* indexing, false otherwise
*/
boolean isWrapAround();
/**
* Returns the rank of the ndarray (the number of dimensions).
*
* @return the rank for the ndarray.
*/
int rank();
/**
* Calculate the stride along a particular dimension
* @param dimension the dimension to get the stride for
* @return the stride for a particular dimension
*/
int stride(int dimension);
/**
* Element stride (one element to the next,
* also called the defualt stride: 1 for normal
* 2 for complex)
* @return
*/
int elementStride();
/**
* Element wise stride
*/
int elementWiseStride();
/**
* Returns true if the ndarray has already been freed
* @return
*/
boolean isCleanedUp();
/**
* Cleanup resources
*/
void cleanup();
/**
* Resets the linear view
*/
void resetLinearView();
/**
* Return the second stride for an ndarray.
* Think of this as the stride for the next element in a column.
*
* @return the secondary stride for an ndarray
*/
int secondaryStride();
/**
* Get a scalar
* at the given linear offset
* @param offset the offset to get at
* @return this
*/
double getDoubleUnsafe(long offset);
/**
* Insert a scalar
* at the given linear offset
* @param offset the offset to insert at
* @param value the value to insert
* @return this
*/
INDArray putScalarUnsafe(long offset, double value);
/**
* Return the major stride for an ndarray
*
* @return the major stride for an ndarray
*/
int majorStride();
/**
* Get the inner most stride
* wrt the ordering of the array
* @return
*/
int innerMostStride();
/**
* Returns a linear view reference of shape
* 1,length(ndarray)
*
* @return the linear view of this ndarray
*/
INDArray linearView();
/**
* Returns a linear view reference of shape
* 1,length(ndarray)
*
* @return the linear view of this ndarray
*/
INDArray linearViewColumnOrder();
/**
* Returns the number of possible vectors for a given dimension
*
* @param dimension the dimension to calculate the number of vectors for
* @return the number of possible vectors along a dimension
*/
int vectorsAlongDimension(int dimension);
/**
* Get the vector along a particular dimension
*
* @param index the index of the vector to getScalar
* @param dimension the dimension to getScalar the vector from
* @return the vector along a particular dimension
*/
INDArray vectorAlongDimension(int index, int dimension);
/**
* Returns the number of possible vectors for a given dimension
*
* @param dimension the dimension to calculate the number of vectors for
* @return the number of possible vectors along a dimension
*/
int tensorssAlongDimension(int... dimension);
/**
* Get the vector along a particular dimension
*
* @param index the index of the vector to getScalar
* @param dimension the dimension to getScalar the vector from
* @return the vector along a particular dimension
*/
INDArray tensorAlongDimension(int index, int... dimension);
/**
* Get the vector along a particular dimension
*
* @param index the index of the vector to getScalar
* @param dimension the dimension to getScalar the vector from
* @return the vector along a particular dimension
*/
INDArray javaTensorAlongDimension(int index, int... dimension);
/**
* Returns the cumulative sum along a dimension. In-place method.
*
* @param dimension the dimension to perform cumulative sum along.
* @return this object.
*/
INDArray cumsumi(int dimension);
/**
* Returns the cumulative sum along a dimension.
*
* @param dimension the dimension to perform cumulative sum along.
* @return the cumulative sum along the specified dimension
*/
INDArray cumsum(int dimension);
/**
* Assign all of the elements in the given
* ndarray to this ndarray
*
* @param arr the elements to assign
* @return this
*/
INDArray assign(INDArray arr);
/**
* Assign all elements from given ndarray that are matching given condition,
* ndarray to this ndarray
*
* @param arr the elements to assign
* @return this
*/
INDArray assignIf(INDArray arr, Condition condition);
/**
* Replaces all elements in this ndarray that are matching give condition, with corresponding elements from given array
*
* @param arr Source array
* @param condition Condition to apply
* @return New array with values conditionally replaced
*/
INDArray replaceWhere(INDArray arr, Condition condition);
/**
* Insert the number linearly in to the ndarray
*
* @param i the index to insert into
* @param value the value to insert
* @return this
*/
INDArray putScalar(int i, double value);
/**
* Insert a scalar float at the specified index
*
* @param i The index to insert into
* @param value Value to insert
* @return This array
*/
INDArray putScalar(int i, float value);
/**
* Insert a scalar int at the specified index
*
* @param i The index to insert into
* @param value Value to insert
* @return This array
*/
INDArray putScalar(int i, int value);
/**
* Insert the item at the specified indices
*
* @param i the indices to insert at
* @param value the number to insert
* @return this
*/
INDArray putScalar(int[] i, double value);
/**
* Insert the value at the specified indices, in a 2d (rank 2) NDArray
* Equivalent to {@link #putScalar(int[], double)} but avoids int[] creation
* @param row Row (dimension 0) index
* @param col Column (dimension 1) index
* @param value Value to put
* @return This INDArray
*/
INDArray putScalar(int row, int col, double value);
/**
* Insert the value at the specified indices, in a 3d (rank 3) NDArray
* Equivalent to {@link #putScalar(int[], double)} but avoids int[] creation
* @param dim0 Dimension 0 index
* @param dim1 Dimension 1 index
* @param dim2 Dimension 2 index
* @param value Value to put
* @return This INDArray
*/
INDArray putScalar(int dim0, int dim1, int dim2, double value);
/**
* Insert the value at the specified indices, in a 4d (rank 4) NDArray
* Equivalent to {@link #putScalar(int[], double)} but avoids int[] creation
* @param dim0 Dimension 0 index
* @param dim1 Dimension 1 index
* @param dim2 Dimension 2 index
* @param dim3 Dimension 3 index
* @param value Value to put
* @return This INDArray
*/
INDArray putScalar(int dim0, int dim1, int dim2, int dim3, double value);
/**
* Returns the binary ndarray for "Less" comparison.
*
* @param other the number to compare.
* @return the binary ndarray for "Less" comparison.
*/
INDArray lt(Number other);
/**
* Returns the binary ndarray for "Less" comparison. In-place method.
*
* @param other the number to compare.
* @return this object.
*/
INDArray lti(Number other);
/**
* Put the specified float value at the specified indices in this array
*
* @param indexes Indices to place the value
* @param value Value to insert
* @return This array
*/
INDArray putScalar(int[] indexes, float value);
/**
* Put the specified integer value at the specified indices in this array
*
* @param indexes Indices to place the value
* @param value Value to insert
* @return This array
*/
INDArray putScalar(int[] indexes, int value);
/**
* Returns the binary ndarray for "Epsilon equals" comparison.
*
* @param other the number to compare.
* @return the binary ndarray for "Epsilon equals" comparison.
*/
INDArray eps(Number other);
/**
* Returns the binary ndarray for "Epsilon equals" comparison. In-place method.
*
* @param other the number to compare.
* @return this object.
*/
INDArray epsi(Number other);
/**
* Returns the binary ndarray for "Equals" comparison.
*
* @param other the number to compare.
* @return the binary ndarray for "Equals" comparison.
*/
INDArray eq(Number other);
/**
* Returns the binary ndarray for "Equals" comparison. In-place method.
*
* @param other the number to compare.
* @return this object.
*/
INDArray eqi(Number other);
/**
* Returns the binary ndarray for "Greater" comparison.
*
* @param other the number to compare.
* @return the binary ndarray for "Greater" comparison.
*/
INDArray gt(Number other);
/**
* Returns binary ndarray for "Greter or equals" comparison.
*
* @param other the number to compare.
* @return binary ndarray for "Greter or equals" comparison.
*/
INDArray gte(Number other);
/**
* Returns the binary ndarray for "Less or equals" comparison.
*
* @param other the number to compare.
* @return the binary ndarray for "Less or equals" comparison.
*/
INDArray lte(Number other);
/**
* Returns the binary ndarray for "Greter or equals" comparison. In-place method.
*
* @param other the number to compare.
* @return this object.
*/
INDArray gtei(Number other);
/**
* Returns the binary ndarray for "Less or equals" comparison. In-place method.
*
* @param other the number to compare.
* @return this object.
*/
INDArray ltei(Number other);
/**
* Returns the binary ndarray for "Greter" comparison. In-place method.
*
* @param other the number to compare.
* @return this object.
*/
INDArray gti(Number other);
/**
* Returns the binary ndarray for "Less" comparison.
*
* @param other the ndarray to compare.
* @return the binary ndarray for "Less" comparison.
*/
INDArray lt(INDArray other);
/**
* Returns the binary ndarray for "Less" comparison. In-place method.
*
* @param other the ndarray to compare.
* @return this object.
*/
INDArray lti(INDArray other);
/**
* Returns the binary ndarray for "Epsilon equals" comparison.
*
* @param other the ndarray to compare.
* @return the binary ndarray for "Epsilon equals" comparison.
*/
INDArray eps(INDArray other);
/**
* Returns the binary ndarray for "Epsilon equals" comparison. In-place method.
*
* @param other the ndarray to compare.
* @return this object.
*/
INDArray epsi(INDArray other);
/**
* Returns the binary ndarray for "Not equals" comparison.
*
* @param other the number to compare.
* @return the binary ndarray for "Not equals" comparison.
*/
INDArray neq(Number other);
/**
* Returns the binary ndarray for "Not equals" comparison. In-place method.
*
* @param other the number to compare.
* @return this object.
*/
INDArray neqi(Number other);
/**
* Returns the binary ndarray for "Not equals" comparison.
*
* @param other the ndarray to compare.
* @return the binary ndarray for "Not equals" comparison.
*/
INDArray neq(INDArray other);
/**
* Returns the binary ndarray for "Not equals" comparison. In-place method.
*
* @param other the ndarray to compare.
* @return this object.
*/
INDArray neqi(INDArray other);
/**
* Returns the binary ndarray for "Equals" comparison.
*
* @param other the ndarray to compare.
* @return the binary ndarray for "Equals" comparison.
*/
INDArray eq(INDArray other);
/**
* Returns the binary ndarray for "Equals" comparison. In-place method.
*
* @param other the ndarray to compare.
* @return this object.
*/
INDArray eqi(INDArray other);
/**
* Returns the binary ndarray for "Greter" comparison.
*
* @param other the ndarray to compare.
* @return the binary ndarray for "Greter" comparison.
*/
INDArray gt(INDArray other);
/**
* Returns the binary ndarray for "Greter" comparison. In-place method.
*
* @param other the ndarray to compare.
* @return this object.
*/
INDArray gti(INDArray other);
/**
* Returns the ndarray negative (cloned)
*
* @return Array copy with all values negated
*/
INDArray neg();
/**
* In place setting of the negative version of this ndarray
*
* @return This array with all values negated
*/
INDArray negi();
/**
* Reverse division with a scalar - i.e., (n / thisArrayValues)
*
* @param n Value to use for reverse division
* @return Copy of array after applying reverse division
*/
INDArray rdiv(Number n);
/**
* In place reverse division - i.e., (n / thisArrayValues)
*
* @param n Value to use for reverse division
* @return This array after applying reverse division
*/
INDArray rdivi(Number n);
/**
* Reverse subtraction with duplicates - i.e., (n - thisArrayValues)
*
* @param n Value to use for reverse subtraction
* @return Copy of array after reverse subtraction
*/
INDArray rsub(Number n);
/**
* Reverse subtraction in place - i.e., (n - thisArrayValues)
*
* @param n Value to use for reverse subtraction
* @return This array after reverse subtraction
*/
INDArray rsubi(Number n);
/**
* Division by a number
*
* @param n Number to divide values by
* @return Copy of array after division
*/
INDArray div(Number n);
/**
* In place scalar division
*
* @param n Number to divide values by
* @return This array, after applying division operation
*/
INDArray divi(Number n);
/**
* Scalar multiplication (copy)
*
* @param n the number to multiply by
* @return a copy of this ndarray multiplied by the given number
*/
INDArray mul(Number n);
/**
* In place scalar multiplication
*
* @param n The number to multiply by
* @return This array, after applying scaler multiplication
*/
INDArray muli(Number n);
/**
* Scalar subtraction (copied)
*
* @param n the number to subtract by
* @return Copy of this array after applying subtraction operation
*/
INDArray sub(Number n);
/**
* In place scalar subtraction
*
* @param n Number to subtract
* @return This array, after applying subtraction operation
*/
INDArray subi(Number n);
/**
* Scalar addition (cloning)
*
* @param n the number to add
* @return a clone with this matrix + the given number
*/
INDArray add(Number n);
/**
* In place scalar addition
*
* @param n Number to add
* @return This array, after adding value
*/
INDArray addi(Number n);
/**
* Reverse division (number / ndarray)
*
* @param n the number to divide by
* @param result Array to place the result in. Must match shape of this array
* @return Result array
*/
INDArray rdiv(Number n, INDArray result);
/**
* Reverse in place division
*
* @param n the number to divide by by
* @param result the result ndarray
* @return the result ndarray
*/
INDArray rdivi(Number n, INDArray result);
/**
* Reverse subtraction
*
* @param n the number to subtract by
* @param result the result ndarray
* @return
*/
INDArray rsub(Number n, INDArray result);
/**
* Reverse in place subtraction
*
* @param n the number to subtract by
* @param result the result ndarray
* @return the result ndarray
*/
INDArray rsubi(Number n, INDArray result);
/**
* @param n
* @param result
* @return
*/
INDArray div(Number n, INDArray result);
/**
* In place division of this ndarray
*
* @param n the number to divide by
* @param result the result ndarray
* @return
*/
INDArray divi(Number n, INDArray result);
INDArray mul(Number n, INDArray result);
/**
* In place multiplication of this ndarray
*
* @param n the number to divide by
* @param result the result ndarray
* @return
*/
INDArray muli(Number n, INDArray result);
INDArray sub(Number n, INDArray result);
/**
* In place subtraction of this ndarray
*
* @param n the number to subtract by
* @param result the result ndarray
* @return the result ndarray
*/
INDArray subi(Number n, INDArray result);
INDArray add(Number n, INDArray result);
/**
* In place addition
*
* @param n the number to add
* @param result the result ndarray
* @return the result ndarray
*/
INDArray addi(Number n, INDArray result);
/**
* Returns a subset of this array based on the specified
* indexes
*
* @param indexes the indexes in to the array
* @return a view of the array with the specified indices
*/
INDArray get(INDArrayIndex... indexes);
/**
* Return a mask on whether each element
* matches the given condition
* @param comp
* @param condition
* @return
*/
INDArray match(INDArray comp,Condition condition);
/**
* Returns a mask
* @param comp
* @param condition
* @return
*/
INDArray match(Number comp,Condition condition);
/**
* Boolean indexing:
* Return the element if it fulfills the condition in
* result array
* @param comp the comparison array
* @param condition the condition to apply
* @return the array fulfilling the criteria
*/
INDArray getWhere(INDArray comp,Condition condition);
/**
* Boolean indexing:
* Return the element if it fulfills the condition in
* result array
* @param comp the comparison array
* @param condition the condition to apply
* @return the array fulfilling the criteria
*/
INDArray getWhere(Number comp,Condition condition);
/**
* Assign the element according
* to the comparison array
* @param comp the comparison array
* @param put the elements to put
* @param condition the condition for masking on
* @return
*/
INDArray putWhere(INDArray comp,INDArray put,Condition condition);
/**
* Assign the element according
* to the comparison array
* @param comp the comparison array
* @param put the elements to put
* @param condition the condition for masking on
* @return
*/
INDArray putWhere(Number comp,INDArray put,Condition condition);
/**
* Use a pre computed mask
* for assigning arrays
* @param mask the mask to use
* @param put the array to put
* @return the resulting array
*/
INDArray putWhereWithMask(INDArray mask,INDArray put);
/**
* Use a pre computed mask
* for assigning arrays
* @param mask the mask to use
* @param put the array to put
* @return the resulting array
*/
INDArray putWhereWithMask(INDArray mask,Number put);
/**
* Assign the element according
* to the comparison array
* @param comp the comparison array
* @param put the elements to put
* @param condition the condition for masking on
* @return
*/
INDArray putWhere(Number comp,Number put,Condition condition);
/**
* Get the elements from this ndarray based on the specified indices
* @param indices an ndaray of the indices to get the elements for
* @return the elements to get the array for
*/
INDArray get(INDArray indices);
/**
* Get the elements from this ndarray based on the specified indices
* @param indices an ndaray of the indices to get the elements for
* @return the elements to get the array for
*/
INDArray get(List> indices);
/**
* Get an INDArray comprised of the specified columns only. Copy operation.
*
* @param columns Columns to extract out of the current array
* @return Array with only the specified columns
*/
INDArray getColumns(int... columns);
/**
* Get an INDArray comprised of the specified rows only. Copy operation
*
* @param rows Rose to extract from this array
* @return Array with only the specified rows
*/
INDArray getRows(int... rows);
/**
* Reverse division, elements wise. i.e., other / this
*
* @param other the matrix to divide from
* @return Copy of this array after performing element wise reverse division
*/
INDArray rdiv(INDArray other);
/**
* Reverse divsion (in place). i.e., other / this
*
* @param other The matrix to divide from
* @return This array after performing element wise reverse division
*/
INDArray rdivi(INDArray other);
/**
* Reverse division
*
* @param other the matrix to subtract from
* @param result the result ndarray
* @return
*/
INDArray rdiv(INDArray other, INDArray result);
/**
* Reverse division (in-place)
*
* @param other the other ndarray to subtract
* @param result the result ndarray
* @return the ndarray with the operation applied
*/
INDArray rdivi(INDArray other, INDArray result);
/**
* Reverse subtraction
*
* @param other the matrix to subtract from
* @param result the result ndarray
* @return
*/
INDArray rsub(INDArray other, INDArray result);
/**
* Element-wise reverse subtraction (copy op). i.e., other - this
*
* @param other Other array to use in reverse subtraction
* @return Copy of this array, after applying reverse subtraction
*/
INDArray rsub(INDArray other);
/**
* Element-wise reverse subtraction (in the place op) - i.e., other - this
*
* @param other Other way to use in reverse subtraction operation
* @return This array, after applying reverse subtraction
*/
INDArray rsubi(INDArray other);
/**
* Reverse subtraction (in-place)
*
* @param other the other ndarray to subtract
* @param result the result ndarray
* @return the ndarray with the operation applied
*/
INDArray rsubi(INDArray other, INDArray result);
/**
* Set all entries of the ndarray to the specified value
*
* @param value the value to assign
* @return the ndarray with the values
*/
INDArray assign(Number value);
/**
* Get the linear index of the data in to
* the array
*
* @param i the index to getScalar
* @return the linear index in to the data
*/
int linearIndex(int i);
/**
* Validate dimensions are equal
*
* @param other the other ndarray to compare
*/
void checkDimensions(INDArray other);
/**
*
* @param list
*/
void sliceVectors(List list);
/**
* Assigns the given matrix (put) to the specified slice
*
* @param slice the slice to assign
* @param put the slice to applyTransformToDestination
* @return this for chainability
*/
INDArray putSlice(int slice, INDArray put);
/**
* 1 in the ndarray if the element matches
* the condition 0 otherwise
*
* @param condition Condition to apply
* @return Copy of this array with values 0 (condition does not apply), or one (condition applies)
*/
INDArray cond(Condition condition);
/**
* In-place: 1 in the ndarray if the element matches the condition 0 otherwise
*
* @param condition Condition to apply
* @return This array, modified with values 0 (condition does not apply), or one (condition applies)
*/
INDArray condi(Condition condition);
/**
* Replicate and tile array to fill out to the given shape
*
* @param shape the new shape of this ndarray
* @return the shape to fill out to
*/
INDArray repmat(int... shape);
/**
* Repeat elements along a specified dimension.
*
* @param dimension the dimension to repeat
* @param repeats the number of elements to repeat on each element
* @return
*/
INDArray repeat(int dimension, int... repeats);
/**
* Insert a row in to this array
* Will throw an exception if this
* ndarray is not a matrix
*
* @param row the row insert into
* @param toPut the row to insert
* @return this
*/
INDArray putRow(int row, INDArray toPut);
/**
* Insert a column in to this array
* Will throw an exception if this
* ndarray is not a matrix
*
* @param column the column to insert
* @param toPut the array to put
* @return this
*/
INDArray putColumn(int column, INDArray toPut);
/**
* Returns the element at the specified row/column
* This will throw an exception if the
*
* @param row the row of the element to return
* @param column the row of the element to return
* @return a scalar indarray of the element at this index
*/
INDArray getScalar(int row, int column);
/**
* Returns the element at the specified index
*
* @param i the index of the element to return
* @return a scalar ndarray of the element at this index
*/
INDArray getScalar(int i);
/**
* Return the linear index of the specified row and column
*
* @param row the row to getScalar the linear index for
* @param column the column to getScalar the linear index for
* @return the linear index of the given row and column
*/
int index(int row, int column);
/**
* Returns the square of the Euclidean distance.
*/
double squaredDistance(INDArray other);
/**
* Returns the (euclidean) distance.
*/
double distance2(INDArray other);
/**
* Returns the (1-norm) distance.
*/
double distance1(INDArray other);
/**
* Put element in to the indices denoted by
* the indices ndarray.
* This is equivalent to:
* a[indices] = element
*
* in numpy.
*
* @param indices the indices to put
* @param element the element array to put
* @return this array
*/
INDArray put(List> indices,INDArray element);
/**
* Put element in to the indices denoted by
* the indices ndarray.
* This is equivalent to:
* a[indices] = element
*
* in numpy.
*
* @param indices the indices to put
* @param element the element array to put
* @return this array
*/
INDArray put(INDArray indices,INDArray element);
/**
* Put the elements of the ndarray
* in to the specified indices
*
* @param indices the indices to put the ndarray in to
* @param element the ndarray to put
* @return this ndarray
*/
INDArray put(INDArrayIndex[] indices, INDArray element);
/**
* Put the elements of the ndarray
* in to the specified indices
*
* @param indices the indices to put the ndarray in to
* @param element the ndarray to put
* @return this ndarray
*/
INDArray put(INDArrayIndex[] indices, Number element);
/**
* Inserts the element at the specified index
*
* @param indices the indices to insert into
* @param element a scalar ndarray
* @return a scalar ndarray of the element at this index
*/
INDArray put(int[] indices, INDArray element);
/**
* Inserts the element at the specified index
*
* @param i the row insert into
* @param j the column to insert into
* @param element a scalar ndarray
* @return a scalar ndarray of the element at this index
*/
INDArray put(int i, int j, INDArray element);
/**
* Inserts the element at the specified index
*
* @param i the row insert into
* @param j the column to insert into
* @param element a scalar ndarray
* @return a scalar ndarray of the element at this index
*/
INDArray put(int i, int j, Number element);
/**
* Inserts the element at the specified index
*
* @param i the index insert into
* @param element a scalar ndarray
* @return a scalar ndarray of the element at this index
*/
INDArray put(int i, INDArray element);
/**
* In place division of a column vector
*
* @param columnVector the column vector used for division
* @return the result of the division
*/
INDArray diviColumnVector(INDArray columnVector);
/**
* Division of a column vector (copy)
*
* @param columnVector the column vector used for division
* @return the result of the division
*/
INDArray divColumnVector(INDArray columnVector);
/**
* In place division of a row vector
*
* @param rowVector the row vector used for division
* @return the result of the division
*/
INDArray diviRowVector(INDArray rowVector);
/**
* Division of a row vector (copy)
*
* @param rowVector the row vector used for division
* @return the result of the division
*/
INDArray divRowVector(INDArray rowVector);
/**
* In place reverse divison of a column vector
*
* @param columnVector the column vector used for division
* @return the result of the division
*/
INDArray rdiviColumnVector(INDArray columnVector);
/**
* Reverse division of a column vector (copy)
*
* @param columnVector the column vector used for division
* @return the result of the division
*/
INDArray rdivColumnVector(INDArray columnVector);
/**
* In place reverse division of a column vector
*
* @param rowVector the row vector used for division
* @return the result of the division
*/
INDArray rdiviRowVector(INDArray rowVector);
/**
* Reverse division of a column vector (copy)
*
* @param rowVector the row vector used for division
* @return the result of the division
*/
INDArray rdivRowVector(INDArray rowVector);
/**
* In place multiplication of a column vector
*
* @param columnVector the column vector used for multiplication
* @return the result of the multiplication
*/
INDArray muliColumnVector(INDArray columnVector);
/**
* Multiplication of a column vector (copy)
*
* @param columnVector the column vector used for multiplication
* @return the result of the multiplication
*/
INDArray mulColumnVector(INDArray columnVector);
/**
* In place multiplication of a row vector
*
* @param rowVector the row vector used for multiplication
* @return the result of the multiplication
*/
INDArray muliRowVector(INDArray rowVector);
/**
* Multiplication of a row vector (copy)
*
* @param rowVector the row vector used for multiplication
* @return the result of the multiplication
*/
INDArray mulRowVector(INDArray rowVector);
/**
* In place reverse subtraction of a column vector
*
* @param columnVector the column vector to subtract
* @return the result of the subtraction
*/
INDArray rsubiColumnVector(INDArray columnVector);
/**
* Reverse subtraction of a column vector (copy)
*
* @param columnVector the column vector to subtract
* @return the result of the subtraction
*/
INDArray rsubColumnVector(INDArray columnVector);
/**
* In place reverse subtraction of a row vector
*
* @param rowVector the row vector to subtract
* @return the result of the subtraction
*/
INDArray rsubiRowVector(INDArray rowVector);
/**
* Reverse subtraction of a row vector (copy)
*
* @param rowVector the row vector to subtract
* @return the result of the subtraction
*/
INDArray rsubRowVector(INDArray rowVector);
/**
* In place subtraction of a column vector
*
* @param columnVector the column vector to subtract
* @return the result of the subtraction
*/
INDArray subiColumnVector(INDArray columnVector);
/**
* Subtraction of a column vector (copy)
*
* @param columnVector the column vector to subtract
* @return the result of the subtraction
*/
INDArray subColumnVector(INDArray columnVector);
/**
* In place subtraction of a row vector
*
* @param rowVector the row vector to subtract
* @return the result of the subtraction
*/
INDArray subiRowVector(INDArray rowVector);
/**
* Subtraction of a row vector (copy)
*
* @param rowVector the row vector to subtract
* @return the result of the subtraction
*/
INDArray subRowVector(INDArray rowVector);
/**
* In place addition of a column vector
*
* @param columnVector the column vector to add
* @return the result of the addition
*/
INDArray addiColumnVector(INDArray columnVector);
/**
* In place assignment of a column vector
*
* @param columnVector the column vector to add
* @return the result of the addition
*/
INDArray putiColumnVector(INDArray columnVector);
/**
* Addition of a column vector (copy)
*
* @param columnVector the column vector to add
* @return the result of the addition
*/
INDArray addColumnVector(INDArray columnVector);
/**
* In place addition of a row vector
*
* @param rowVector the row vector to add
* @return the result of the addition
*/
INDArray addiRowVector(INDArray rowVector);
/**
* in place assignment of row vector, to each row of this array
*
* @param rowVector Row vector to put
* @return This array, after assigning every road to the specified value
*/
INDArray putiRowVector(INDArray rowVector);
/**
* Addition of a row vector (copy)
*
* @param rowVector the row vector to add
* @return the result of the addition
*/
INDArray addRowVector(INDArray rowVector);
INDArray mmul(INDArray other, MMulTranspose mMulTranspose);
/**
* Perform a copy matrix multiplication
*
* @param other the other matrix to perform matrix multiply with
* @return the result of the matrix multiplication
*/
INDArray mmul(INDArray other);
/**
* Convert this ndarray to a 2d double matrix.
* Note that THIS SHOULD NOT BE USED FOR SPEED.
* This is mainly used for integrations with other libraries.
* Due to nd4j's off heap nature, moving data on heap is very expensive
* and should not be used if possible.
* @return a copy of this array as a 2d double array
*/
double[][] toDoubleMatrix();
/**
* Convert this ndarray to a 1d double matrix.
* Note that THIS SHOULD NOT BE USED FOR SPEED.
* This is mainly used for integrations with other libraries.
* Due to nd4j's off heap nature, moving data on heap is very expensive
* and should not be used if possible.
* @return a copy of this array as a 1d double array
*/
double[] toDoubleVector();
/**
* Convert this ndarray to a 1d float vector.
* Note that THIS SHOULD NOT BE USED FOR SPEED.
* This is mainly used for integrations with other libraries.
* Due to nd4j's off heap nature, moving data on heap is very expensive
* and should not be used if possible.
* @return a copy of this array as a 1d float array
*/
float[] toFloatVector();
/**
* Convert this ndarray to a 2d float matrix.
* Note that THIS SHOULD NOT BE USED FOR SPEED.
* This is mainly used for integrations with other libraries.
* Due to nd4j's off heap nature, moving data on heap is very expensive
* and should not be used if possible.
* @return a copy of this array as a 2d float array
*/
float[][] toFloatMatrix();
/**
* Convert this ndarray to a 1d int matrix.
* Note that THIS SHOULD NOT BE USED FOR SPEED.
* This is mainly used for integrations with other libraries.
* Due to nd4j's off heap nature, moving data on heap is very expensive
* and should not be used if possible.
* @return a copy of this array as a 1d int array
*/
int[] toIntVector();
/**
* Convert this ndarray to a 2d int matrix.
* Note that THIS SHOULD NOT BE USED FOR SPEED.
* This is mainly used for integrations with other libraries.
* Due to nd4j's off heap nature, moving data on heap is very expensive
* and should not be used if possible.
* @return a copy of this array as a 2d int array
*/
int[][] toIntMatrix();
/**
* Perform an copy matrix multiplication
*
* @param other the other matrix to perform matrix multiply with
* @param result the result ndarray
* @return the result of the matrix multiplication
*/
INDArray mmul(INDArray other, INDArray result);
/**
* Perform an copy matrix multiplication
*
* @param other the other matrix to perform matrix multiply with
* @param result the result ndarray
* @param mMulTranspose the transpose status of each array
* @return the result of the matrix multiplication
*/
INDArray mmul(INDArray other, INDArray result,MMulTranspose mMulTranspose);
/**
* Copy (element wise) division of two NDArrays
*
* @param other the second ndarray to divide
* @return the result of the divide
*/
INDArray div(INDArray other);
/**
* copy (element wise) division of two NDArrays
*
* @param other the second ndarray to divide
* @param result the result ndarray
* @return the result of the divide
*/
INDArray div(INDArray other, INDArray result);
/**
* copy (element wise) multiplication of two NDArrays
*
* @param other the second ndarray to multiply
* @return the result of the addition
*/
INDArray mul(INDArray other);
/**
* copy (element wise) multiplication of two NDArrays
*
* @param other the second ndarray to multiply
* @param result the result ndarray
* @return the result of the multiplication
*/
INDArray mul(INDArray other, INDArray result);
/**
* copy subtraction of two NDArrays
*
* @param other the second ndarray to subtract
* @return the result of the addition
*/
INDArray sub(INDArray other);
/**
* copy subtraction of two NDArrays
*
* @param other the second ndarray to subtract
* @param result the result ndarray
* @return the result of the subtraction
*/
INDArray sub(INDArray other, INDArray result);
/**
* Element-wise copy addition of two NDArrays
*
* @param other the second ndarray to add
* @return the result of the addition
*/
INDArray add(INDArray other);
/**
* Element-wise copy addition of two NDArrays
*
* @param other the second ndarray to add
* @param result the result ndarray
* @return the result of the addition
*/
INDArray add(INDArray other, INDArray result);
INDArray mmuli(INDArray other, MMulTranspose transpose);
/**
* Perform an inplace matrix multiplication
*
* @param other the other matrix to perform matrix multiply with
* @return the result of the matrix multiplication
*/
INDArray mmuli(INDArray other);
INDArray mmuli(INDArray other, INDArray result, MMulTranspose transpose);
/**
* Perform an inplace matrix multiplication
*
* @param other the other matrix to perform matrix multiply with
* @param result the result ndarray
* @return the result of the matrix multiplication
*/
INDArray mmuli(INDArray other, INDArray result);
/**
* in place (element wise) division of two NDArrays
*
* @param other the second ndarray to divide
* @return the result of the divide
*/
INDArray divi(INDArray other);
/**
* in place (element wise) division of two NDArrays
*
* @param other the second ndarray to divide
* @param result the result ndarray
* @return the result of the divide
*/
INDArray divi(INDArray other, INDArray result);
/**
* in place (element wise) multiplication of two NDArrays
*
* @param other the second ndarray to multiply
* @return the result of the multiplication
*/
INDArray muli(INDArray other);
/**
* in place (element wise) multiplication of two NDArrays
*
* @param other the second ndarray to multiply
* @param result the result ndarray
* @return the result of the multiplication
*/
INDArray muli(INDArray other, INDArray result);
/**
* in place (element wise) subtraction of two NDArrays
*
* @param other the second ndarray to subtract
* @return the result of the subtraction
*/
INDArray subi(INDArray other);
/**
* in place (element wise) subtraction of two NDArrays
*
* @param other the second ndarray to subtract
* @param result the result ndarray
* @return the result of the subtraction
*/
INDArray subi(INDArray other, INDArray result);
/**
* in place (element wise) addition of two NDArrays
*
* @param other the second ndarray to add
* @return the result of the addition
*/
INDArray addi(INDArray other);
/**
* in place (element wise) addition of two NDArrays
*
* @param other the second ndarray to add
* @param result the result ndarray
* @return the result of the addition
*/
INDArray addi(INDArray other, INDArray result);
/**
* Returns the max norm (aka infinity norm, equal to the maximum absolute value) along the specified dimension(s)
*
* @param dimension the dimension to the max norm along
* @return Max norm along the specified dimension
*/
INDArray normmax(int... dimension);
/**
* Return the max norm (aka infinity norm, equal to the maximum absolute value) for the entire array
*
* @return Max norm for the entire array
*/
Number normmaxNumber();
/**
*
* @return
*/
IComplexNumber normmaxComplex();
/**
* Returns the norm2 (L2 norm, sqrt(sum(x_i^2), also known as Euclidean norm) along the specified dimension(s)
*
* @param dimension the dimension to getScalar the norm2 along
* @return the norm2 along the specified dimension
*/
INDArray norm2(int... dimension);
/**
* Return the norm2 (L2 norm, sqrt(sum(x_i^2), also known as Euclidean norm) for the entire array
*
* @return L2 norm for the array
*/
Number norm2Number();
/**
*
* @return
*/
IComplexNumber norm2Complex();
/**
* Returns the norm1 (L1 norm, i.e., sum of absolute values; also known as Taxicab or Manhattan norm) along the
* specified dimension
*
* @param dimension the dimension to getScalar the norm1 along
* @return the norm1 along the specified dimension
*/
INDArray norm1(int... dimension);
/**
* Calculate and return norm1 (L1 norm, i.e., sum of absolute values; also known as Taxicab or Manhattan norm) for
* the entire array
*
* @return Norm 1 for the array
*/
Number norm1Number();
/**
* Calculate and return norm1 (L1 norm, i.e., sum of absolute values; also known as Taxicab or Manhattan norm) for
* the entire array
*
* @return
*/
IComplexNumber norm1Complex();
/**
* Standard deviation of an INDArray along one or more dimensions
*
* @param dimension the dimension to getScalar the std along
* @return the standard deviation along a particular dimension
*/
INDArray std(int... dimension);
/**
* Calculate the standard deviation for the entire array
*
* @return
*/
Number stdNumber();
/**
* Standard deviation of an ndarray along a dimension
*
* @param dimension the dimension to getScalar the std along
* @return the standard deviation along a particular dimension
*/
INDArray std(boolean biasCorrected, int... dimension);
/**
* Calculate the standard deviation for the entire array, specifying whether it is bias corrected or not
*
* @param biasCorrected If true: bias corrected standard deviation. False: not bias corrected
* @return Standard dev
*/
Number stdNumber(boolean biasCorrected);
/**
*
* @return
*/
IComplexNumber stdComplex();
/**
* Returns the product along a given dimension
*
* @param dimension the dimension to getScalar the product along
* @return the product along the specified dimension
*/
INDArray prod(int... dimension);
/**
* Calculate the product of all values in the array
*
* @return Product of all values in the array
*/
Number prodNumber();
/**
*
* @return
*/
IComplexNumber prodComplex();
/**
* Returns the overall mean of this ndarray
*
* @param dimension the dimension to getScalar the mean along
* @return the mean along the specified dimension of this ndarray
*/
INDArray mean(int... dimension);
/**
* Returns the overall mean of this ndarray
*
* @param dimension the dimension to getScalar the mean along
* @return the mean along the specified dimension of this ndarray
*/
INDArray mean(INDArray result, int... dimension);
/**
* Returns the absolute overall mean of this ndarray
*
* @param dimension the dimension to getScalar the mean along
* @return the mean along the specified dimension of this ndarray
*/
INDArray amean(int... dimension);
/**
* Returns the overall mean of this ndarray
*
* @return the mean along the specified dimension of this ndarray
*/
Number meanNumber();
/**
* Returns the absolute overall mean of this ndarray
*
* @return the mean along the specified dimension of this ndarray
*/
Number ameanNumber();
IComplexNumber meanComplex();
/**
* Returns the overall variance of this ndarray
*
* @param dimension the dimension to getScalar the mean along
* @return the mean along the specified dimension of this ndarray
*/
INDArray var(int... dimension);
/**
* Returns the overall variance of this ndarray
*
* @param biasCorrected boolean on whether to apply corrected bias
* @param dimension the dimension to getScalar the mean along
* @return the mean along the specified dimension of this ndarray
*/
INDArray var(boolean biasCorrected, int... dimension);
/**
* Returns the overall variance of all values in this INDArray
*
* @return variance
*/
Number varNumber();
/**
*
* @return
*/
IComplexNumber varComplex();
/**
* Returns the overall max of this ndarray along given dimensions
*
* @param dimension the dimension to getScalar the mean along
* @return the mean along the specified dimension of this ndarray
*/
INDArray max(int... dimension);
/**
* Returns the absolute overall max of this ndarray along given dimensions
*
* @param dimension the dimension to getScalar the mean along
* @return the mean along the specified dimension of this ndarray
*/
INDArray amax(int... dimension);
/**
* Returns maximum value in this INDArray
* @return maximum value
*/
Number maxNumber();
/**
* Returns maximum (absolute) value in this INDArray
* @return Max absolute value
*/
Number amaxNumber();
/**
*
* @return
*/
IComplexNumber maxComplex();
/**
* Returns the overall min of this ndarray
*
* @param dimension the dimension to getScalar the mean along
* @return the mean along the specified dimension of this ndarray
*/
INDArray min(int... dimension);
/**
* Returns minimum (absolute) value in this INDArray, along the specified dimensions
*
* @return Minimum absolute value
*/
INDArray amin(int... dimension);
/**
* Returns min value in this INDArray
* @return Minimum value in the array
*/
Number minNumber();
/**
* Returns absolute min value in this INDArray
*
* @return Absolute min value
*/
Number aminNumber();
IComplexNumber minComplex();
/**
* Returns the sum along the last dimension of this ndarray
*
* @param dimension the dimension to getScalar the sum along
* @return the sum along the specified dimension of this ndarray
*/
INDArray sum(int... dimension);
/**
* This method takes boolean condition, and returns number of elements matching this condition
*
* @param condition Condition to calculate matches for
* @return Number of elements matching condition
*/
Number scan(Condition condition);
/**
* Returns the sum along the last dimension of this ndarray
*
* @param result result of this operation will be stored here
* @param dimension the dimension to getScalar the sum along
* @return the sum along the specified dimension of this ndarray
*/
INDArray sum(INDArray result, int... dimension);
/**
* Sum the entire array
* @return Sum of array
*/
Number sumNumber();
/**
* Returns entropy value for this INDArray
* @return
*/
Number entropyNumber();
/**
* Returns non-normalized Shannon entropy value for this INDArray
* @return
*/
Number shannonEntropyNumber();
/**
* Returns log entropy value for this INDArray
* @return
*/
Number logEntropyNumber();
/**
* Returns entropy value for this INDArray along specified dimension(s)
* @return
*/
INDArray entropy(int... dimension);
/**
* Returns entropy value for this INDArray along specified dimension(s)
* @return
*/
INDArray shannonEntropy(int... dimension);
/**
* Returns entropy value for this INDArray along specified dimension(s)
* @return
*/
INDArray logEntropy(int... dimension);
/**
* Sum the entire array
* @return
*/
IComplexNumber sumComplex();
/**
* stride setter
* @param stride
* @deprecated, use {@link #reshape(int...) }
*/
@Deprecated
void setStride(int... stride);
/**
* Shape setter
* @param shape
* @deprecated, use {@link #reshape(int...) }
*/
@Deprecated
void setShape(int... shape);
/**
* Shape and stride setter
* @param shape
* @param stride
*/
public void setShapeAndStride(int[] shape, int[] stride);
/**
* Set the ordering
* @param order the ordering to set
*/
void setOrder(char order);
/**
* Sub array based on the
* pre calculated shape,strides, offsets
* @param resolution the resolution to use
* @return the sub array based on the calculations from the resolution
*/
INDArray subArray(ShapeOffsetResolution resolution);
//INDArray subArray(ShapeOffsetResolution resolution, ShapeOffsetResolution resolutionWithoutNewAxis);
/**
* @param offsets
* @param shape
* @param stride
* @return
*/
INDArray subArray(long[] offsets, int[] shape, int[] stride);
/**
* Returns the elements at the the specified indices
*
* @param indices the indices to getScalar
* @return the array with the specified elements
*/
INDArray getScalar(int... indices);
/**
* Get an integer value at the specified indices. Result will be cast to an integer, precision loss is possible.
* @param indices Indices to get the integer at. Number of indices must match the array rank.
* @return Integer value at the specified index
*/
int getInt(int... indices);
/**
* Get a double value at the specified indices.
* @param indices Indices to get the double at. Number of indices must match the array rank.
* @return Double value at the specified index
*/
double getDouble(int... indices);
/**
* Returns the elements at the the specified indices
*
* @param indices the indices to getScalar
* @return the array with the specified elements
*/
float getFloat(int[] indices);
/**
* Get the double value at the specified linear index in the array
*
* @param i Index
* @return Double value at the specified index
*/
double getDouble(int i);
/**
* Get the double value at the specified indices. Can only be used for 2D (rank 2) arrays.
*
* @param i Dimension 0 (row) index
* @param j Dimension 1 (column) index
* @return
*/
double getDouble(int i, int j);
/**
* Return the item at the linear index i
*
* @param i the index of the item to getScalar
* @return the item at index j
*/
float getFloat(int i);
/**
* Return the item at row i column j
* Note that this is the same as calling getScalar(new int[]{i,j}
*
* @param i the row to getScalar
* @param j the column to getScalar
* @return the item at row i column j
*/
float getFloat(int i, int j);
/**
* Returns a copy of this ndarray
*
* @return a copy of this ndarray
*/
INDArray dup();
/**
* Returns a copy of this ndarray, where the returned ndarray has the specified order
*
* @param order order of the NDArray. 'f' or 'c'
* @return copy of ndarray with specified order
*/
INDArray dup(char order);
/**
* Returns a flattened version (row vector) of this ndarray
*
* @return a flattened version (row vector) of this ndarray
*/
INDArray ravel();
/**
* Returns a flattened version (row vector) of this ndarray
*
* @return a flattened version (row vector) of this ndarray
*/
INDArray ravel(char order);
/**
*
* @param data
*/
void setData(DataBuffer data);
/**
* Returns the number of slices in this ndarray
*
* @return the number of slices in this ndarray
*/
int slices();
/**
* Get the number of trailing ones in the array shape. For example, a rank 3 array with shape [10, 1, 1] would
* return 2 for this method
*
* @return Number of trailing ones in shape
*/
int getTrailingOnes();
/**
* Get the number of leading ones in the array shape. For example, a rank 3 array with shape [1, 10, 1] would
* return value 1 for this method
*
* @return Number of leading ones in shape
*/
int getLeadingOnes();
/**
* Returns the specified slice of this ndarray
*
* @param i the index of the slice to return
* @param dimension the dimension to return the slice for
* @return the specified slice of this ndarray
*/
INDArray slice(int i, int dimension);
/**
* Returns the specified slice of this ndarray
*
* @param i the index of the slice to return
* @return the specified slice of this ndarray
*/
INDArray slice(int i);
/**
* Returns the start of where the ndarray is
* for the underlying data
*
* @return the starting offset
*/
long offset();
/**
* Returns the start of where the ndarray is for the original data buffer
* @return
*/
long originalOffset();
/**
* Reshapes the ndarray (can't change the length of the ndarray). Typically this will be a view, unless reshaping
* without copying is impossible.
*
* @param newShape the new shape of the ndarray
* @return the reshaped ndarray
*/
INDArray reshape(char order, int... newShape);
/**
* Reshapes the ndarray (can't change the length of the ndarray). Typically this will be a view, unless reshaping
* without copying is impossible.
*
* @param rows the rows of the matrix
* @param columns the columns of the matrix
* @return the reshaped ndarray
*/
INDArray reshape(char order, int rows, int columns);
/**
* Reshapes the ndarray (can't change the length of the ndarray). Typically this will be a view, unless reshaping
* without copying is impossible.
*
* @param newShape the new shape of the ndarray
* @return the reshaped ndarray
*/
INDArray reshape(int... newShape);
/**
* Reshapes the ndarray (can't change the length of the ndarray). Typically this will be a view, unless reshaping
* without copying is impossible.
*
* @param rows the rows of the matrix
* @param columns the columns of the matrix
* @return the reshaped ndarray
*/
INDArray reshape(int rows, int columns);
/**
* Flip the rows and columns of a matrix
*
* @return the flipped rows and columns of a matrix
*/
INDArray transpose();
/**
* Flip the rows and columns of a matrix, in-place
*
* @return the flipped rows and columns of a matrix
*/
INDArray transposei();
/**
* Mainly here for people coming from numpy.
* This is equivalent to a call to permute
*
* @param dimension the dimension to swap
* @param with the one to swap it with
* @return the swapped axes view
*/
INDArray swapAxes(int dimension, int with);
/**
* See: http://www.mathworks.com/help/matlab/ref/permute.html
*
* @param rearrange the dimensions to swap to
* @return the newly permuted array
*/
INDArray permute(int... rearrange);
/**
* An in-place version of permute. The array shape information (shape, strides)
* is modified by this operation (but not the data itself)
* See: http://www.mathworks.com/help/matlab/ref/permute.html
*
* @param rearrange the dimensions to swap to
* @return the current array
*/
INDArray permutei(int... rearrange);
/**
* Dimshuffle: an extension of permute that adds the ability
* to broadcast various dimensions.
* This will only accept integers and xs.
*
* An x indicates a dimension should be broadcasted rather than permuted.
*
* Examples originally from the theano docs:
* http://deeplearning.net/software/theano/library/tensor/basic.html
*
* Returns a view of this tensor with permuted dimensions. Typically the pattern will include the integers 0, 1, ... ndim-1, and any number of ‘x’ characters in dimensions where this tensor should be broadcasted.
A few examples of patterns and their effect:
(‘x’) -> make a 0d (scalar) into a 1d vector
(0, 1) -> identity for 2d vectors
(1, 0) -> inverts the first and second dimensions
(‘x’, 0) -> make a row out of a 1d vector (N to 1xN)
(0, ‘x’) -> make a column out of a 1d vector (N to Nx1)
(2, 0, 1) -> AxBxC to CxAxB
(0, ‘x’, 1) -> AxB to Ax1xB
(1, ‘x’, 0) -> AxB to Bx1xA
(1,) -> This remove dimensions 0. It must be a broadcastable dimension (1xA to A)
* @param rearrange the dimensions to swap to
* @param newOrder the new order (think permute)
* @param broadCastable (whether the dimension is broadcastable) (must be same length as new order)
* @return the newly permuted array
*/
INDArray dimShuffle(Object[] rearrange, int[] newOrder, boolean[] broadCastable);
/**
* Returns the specified column.
* Throws an exception if its not a matrix
*
* @param i the column to getScalar
* @return the specified column
*/
INDArray getColumn(int i);
/**
* Returns the specified row.
* Throws an exception if its not a matrix
*
* @param i the row to getScalar
* @return the specified row
*/
INDArray getRow(int i);
/**
* Returns the number of columns in this matrix (throws exception if not 2d)
*
* @return the number of columns in this matrix
*/
int columns();
/**
* Returns the number of rows in this matrix (throws exception if not 2d)
*
* @return the number of rows in this matrix
*/
int rows();
/**
* Returns true if the number of columns is 1
*
* @return true if the number of columns is 1
*/
boolean isColumnVector();
/**
* Returns true if the number of rows is 1
*
* @return true if the number of rows is 1
*/
boolean isRowVector();
/**
* Returns true if the number of columns is 1
*
* @return true if the number of columns is 1
*/
boolean isColumnVectorOrScalar();
/**
* Returns true if the number of rows is 1
*
* @return true if the number of rows is 1
*/
boolean isRowVectorOrScalar();
/**
* Returns true if this ndarray is a vector
*
* @return whether this ndarray is a vector
*/
boolean isVector();
/**
* Returns true if this ndarray is a vector or scalar
*
* @return whether this ndarray is a vector or scalar
*/
boolean isVectorOrScalar();
/**
* Returns whether the matrix
* has the same rows and columns
*
* @return true if the matrix has the same rows and columns
* false otherwise
*/
boolean isSquare();
/**
* Returns true if this ndarray is a matrix
*
* @return whether this ndarray is a matrix
*/
boolean isMatrix();
/**
* Returns true if this ndarray is a scalar
*
* @return whether this ndarray is a scalar
*/
boolean isScalar();
/**
* Returns the shape of this ndarray
*
* @return the shape of this ndarray
*/
int[] shape();
/**
* Returns the stride of this ndarray
*
* @return the stride of this ndarray
*/
int[] stride();
/**
* Return the ordering (fortran or c 'f' and 'c' respectively) of this ndarray
* @return the ordering of this ndarray
*/
char ordering();
/**
* Returns the size along a specified dimension
*
* @param dimension the dimension to return the size for
* @return the size of the array along the specified dimension
*/
int size(int dimension);
/**
* Returns the total number of elements in the ndarray
*
* @return the number of elements in the ndarray
*/
int length();
/**
* Returns the total number of elements in the ndarray
*
* @return the number of elements in the ndarray
*/
long lengthLong();
/**
* Broadcasts this ndarray to be the specified shape
*
* @param shape the new shape of this ndarray
* @return the broadcasted ndarray
*/
INDArray broadcast(int... shape);
/**
* Broadcasts this ndarray to be the specified shape
*
* @return the broadcasted ndarray
*/
INDArray broadcast(INDArray result);
/**
* Returns a scalar (individual element)
* of a scalar ndarray
*
* @return the individual item in this ndarray
*/
Object element();
/**
* Returns a linear double array representation of this ndarray
*
* @return the linear double array representation of this ndarray
*/
DataBuffer data();
/**
*
* @param n
* @return
*/
IComplexNDArray rdiv(IComplexNumber n);
/**
*
* @param n
* @return
*/
IComplexNDArray rdivi(IComplexNumber n);
/**
*
* @param n
* @return
*/
IComplexNDArray rsub(IComplexNumber n);
/**
*
* @param n
* @return
*/
IComplexNDArray rsubi(IComplexNumber n);
/**
*
* @param n
* @return
*/
IComplexNDArray div(IComplexNumber n);
/**
*
* @param n
* @return
*/
IComplexNDArray divi(IComplexNumber n);
/**
*
* @param n
* @return
*/
IComplexNDArray mul(IComplexNumber n);
/**
*
* @param n
* @return
*/
IComplexNDArray muli(IComplexNumber n);
/**
*
* @param n
* @return
*/
IComplexNDArray sub(IComplexNumber n);
/**
*
* @param n
* @return
*/
IComplexNDArray subi(IComplexNumber n);
/**
*
* @param n
* @return
*/
IComplexNDArray add(IComplexNumber n);
/**
*
* @param n
* @return
*/
IComplexNDArray addi(IComplexNumber n);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray rdiv(IComplexNumber n, IComplexNDArray result);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray rdivi(IComplexNumber n, IComplexNDArray result);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray rsub(IComplexNumber n, IComplexNDArray result);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray rsubi(IComplexNumber n, IComplexNDArray result);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray div(IComplexNumber n, IComplexNDArray result);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray divi(IComplexNumber n, IComplexNDArray result);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray mul(IComplexNumber n, IComplexNDArray result);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray muli(IComplexNumber n, IComplexNDArray result);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray sub(IComplexNumber n, IComplexNDArray result);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray subi(IComplexNumber n, IComplexNDArray result);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray add(IComplexNumber n, IComplexNDArray result);
/**
*
* @param n
* @param result
* @return
*/
IComplexNDArray addi(IComplexNumber n, IComplexNDArray result);
/**
* This method checks 2 INDArrays equality with given eps
*
* @param o
* @param eps Epsilon value to use for the quality operation
* @return
*/
boolean equalsWithEps(Object o, double eps);
/**
* Perform efficient (but unsafe) duplication. Don't use this method unless you know exactly what you are doing.
* Instead, use {@link #dup()}
*
* @return Unsafe duplicate of array
*/
INDArray unsafeDuplication();
/**
* Perform efficient (but unsafe) duplication. Don't use this method unless you know exactly what you are doing.
* Instead, use {@link #dup()}
*
* @return Unsafe duplicate of array
*/
INDArray unsafeDuplication(boolean blocking);
/**
* Remainder operator
* @param denominator the denominator
* @return
*/
INDArray remainder(INDArray denominator);
/**
* Remainder operator
* @param denominator the denominator
* @param result the result array to put this in
* @return
*/
INDArray remainder(INDArray denominator, INDArray result);
/**
* The scalar denominator
* @param denominator the denominator as a scalar
* @return
*/
INDArray remainder(Number denominator);
/**
*
* @param denominator
* @param result
* @return
*/
INDArray remainder(Number denominator, INDArray result);
/**
* In place remainder
* @param denominator
* @return
*/
INDArray remainderi(INDArray denominator);
/**
* In place remainder
* @param denominator
* @return
*/
INDArray remainderi(Number denominator);
/**
* remainder of division
* @param denominator the array of denominators for each element
* in this array
* @return
*/
INDArray fmod(INDArray denominator);
/**
* remainder of division
* @param denominator the
* @param result the result array
* @return
*/
INDArray fmod(INDArray denominator, INDArray result);
/**
*
* @param denominator
* @return
*/
INDArray fmod(Number denominator);
INDArray fmod(Number denominator, INDArray result);
/**
* In place fmod
* @param denominator
* @return
*/
INDArray fmodi(INDArray denominator);
/**
* In place fmod
* @param denominator
* @return
*/
INDArray fmodi(Number denominator);
/**
* This method returns index of highest value along specified dimension(s)
*
* @param dimension Dimension along which to perform the argMax operation
* @return Array containing indices
*/
INDArray argMax(int... dimension);
/**
* This method returns True, if this INDArray instance is attached to some Workspace. False otherwise.
* @return True if attached to workspace, false otherwise
*/
boolean isAttached();
/**
* This method checks, if given attached INDArray is still in scope of its parent Workspace
*
* PLEASE NOTE: if this INDArray isn't attached to any Workspace, this method will return true
* @return
*/
boolean isInScope();
/**
* This method detaches INDArray from Workspace, returning copy.
* Basically it's dup() into new memory chunk.
*
* PLEASE NOTE: If this INDArray instance is NOT attached - it will be returned unmodified.
*
* @return The attached copy of array, or original if not in workspace
*/
INDArray detach();
/**
* This method detaches INDArray from current Workspace, and attaches it to Workspace above, if any.
*
* PLEASE NOTE: If this INDArray instance is
* NOT attached - it will be returned unmodified.
* PLEASE NOTE: If current Workspace is the top-tier one,
* effect will be equal to detach() call - detached copy will be returned
*
* @return
*/
INDArray leverage();
/**
* This method detaches INDArray from current Workspace, and attaches it to Workspace with a given Id - if a workspace
* with that ID exists. If no workspace with the specified ID exists, the current INDArray is returned unmodified.
*
* @param id ID of the workspace to leverage to
* @return
* @see #leverageTo(String, boolean)
*/
INDArray leverageTo(String id);
/**
* This method detaches INDArray from current Workspace, and attaches it to Workspace with a given Id.
* If enforceExistence == true, and no workspace with the specified ID exists, then an {@link Nd4jNoSuchWorkspaceException}
* is thrown. Otherwise, if enforceExistance == false and no workspace with the specified ID exists, then the current
* INDArray is returned unmodified (same as {@link #leverage()}
*
* @param id ID of the workspace to leverage to
* @param enforceExistence If true, and the specified workspace does not exist: an {@link Nd4jNoSuchWorkspaceException}
* will be thrown.
* @return The INDArray, leveraged to the specified workspace
* @see #leverageTo(String)
*/
INDArray leverageTo(String id, boolean enforceExistence) throws Nd4jNoSuchWorkspaceException;
/**
* This method detaches INDArray from current Workspace, and attaches it to Workspace with a given Id, if a workspace
* with the given ID is open and active.
*
* If the workspace does not exist, or is not active, the array is detached from any workspaces.
*
* @param id ID of the workspace to leverage to
* @return The INDArray, leveraged to the specified workspace (if it exists and is active) otherwise the detached array
* @see #leverageTo(String)
*/
INDArray leverageOrDetach(String id);
/**
* This method pulls this INDArray into current Workspace.
*
* PLEASE NOTE: If there's no current Workspace - INDArray returned as is
*
* @return Migrated INDArray or this if no current workspace
* @see #migrate(boolean)
*/
INDArray migrate();
/**
* This method pulls this INDArray into current Workspace, or optionally detaches if no workspace is present.
* That is:
* If current workspace is present/active, INDArray is migrated to it.
* If no current workspace is present/active, one of two things occur:
* 1. If detachOnNoWs arg is true: if there is no current workspace, INDArray is detached
* 2. If detachOnNoWs arg is false: this INDArray is returned as-is (no-op) - equivalent to {@link #migrate()}
*
* @param detachOnNoWs If true: detach on no WS. If false and no workspace: return this.
* @return Migrated INDArray
*/
INDArray migrate(boolean detachOnNoWs);
/**
* This method returns percentile value for this INDArray
*
* @param percentile target percentile in range of 0..100
* @return
*/
Number percentileNumber(Number percentile);
/**
* This method returns median value for this INDArray
*
* @return Median value for array
*/
Number medianNumber();
/**
* This method returns median along given dimension(s)
* @param dimension
* @return Median along specified dimensions
*/
INDArray median(int... dimension);
/**
* This method returns median along given dimension(s)
* @param percentile target percentile in range of 0..100
* @param dimension Dimension to calculate percentile for
* @return
*/
INDArray percentile(Number percentile, int... dimension);
/**
* ------------ Sparse methods ------------
*/
/**
* Return a array of non-major pointers
* i.e. return the column indexes in case of row-major ndarray
* @return a DataBuffer of indexes
* */
DataBuffer getVectorCoordinates();
/**
* Return a dense representation of the sparse ndarray
* */
INDArray toDense();
/**
* Return the number of non-null element
* @return nnz
* */
int nnz();
/**
* Return the sparse format (i.e COO, CSR, ...)
* @return format
* @see SparseFormat
* */
SparseFormat getFormat();
int[] flags();
int[] hiddenDimensions();
int[] sparseOffsets();
int underlyingRank();
/**
* Add an {@link INDArray}
* to flatbuffers builder
* @param builder the builder to use
* @return the offset to add
*/
int toFlatArray(FlatBufferBuilder builder);
INDArray convertToFloats();
INDArray convertToDoubles();
}
