Class CooCTensor

java.lang.Object

org.flag4j.arrays.backend.AbstractTensor<CooCTensor,Complex128[],Complex128>

org.flag4j.arrays.backend.semiring_arrays.AbstractCooSemiringTensor<CooCTensor,CTensor,Complex128>

org.flag4j.arrays.backend.ring_arrays.AbstractCooRingTensor<CooCTensor,CTensor,Complex128>

org.flag4j.arrays.backend.field_arrays.AbstractCooFieldTensor<CooCTensor,CTensor,Complex128>

org.flag4j.arrays.sparse.CooCTensor

All Implemented Interfaces:

Serializable, FieldTensorMixin<CooCTensor,CooCTensor,Complex128>, TensorOverField<CooCTensor,CooCTensor,Complex128[],Complex128>, RingTensorMixin<CooCTensor,CooCTensor,Complex128>, TensorOverRing<CooCTensor,CooCTensor,Complex128[],Complex128>, SemiringTensorMixin<CooCTensor,CooCTensor,Complex128>, TensorOverSemiring<CooCTensor,CooCTensor,Complex128[],Complex128>

public class CooCTensor
extends AbstractCooFieldTensor<CooCTensor,CTensor,Complex128>

Sparse complex tensor stored in coordinate list (COO) format. The data of this COO tensor are of type Complex128

The non-zero data and non-zero indices of a COO tensor are mutable but the AbstractTensor.shape and total number of non-zero data is fixed.

Sparse tensors allow for the efficient storage of and ops on tensors that contain many zero values.

COO tensors are optimized for hyper-sparse tensors (i.e. tensors which contain almost all zeros relative to the size of the tensor).

A sparse COO tensor is stored as:

• The full shape of the tensor.
• The non-zero AbstractTensor.data of the tensor. All other data in the tensor are assumed to be zero. Zero value can also explicitly be stored in AbstractTensor.data.

• The AbstractCooSemiringTensor.indices of the non-zero value in the sparse tensor. Many ops assume indices to be sorted in a row-major format (i.e. last index increased fastest) but often this is not explicitly verified.

  The AbstractCooSemiringTensor.indices array has shape (nnz, rank) where AbstractCooSemiringTensor.nnz is the number of non-zero data in this sparse tensor and rank is the tensor rank of the tensor. This means indices[i] is the nD index of data[i].

See Also:

• Serialized Form

Field Summary

Fields inherited from class org.flag4j.arrays.backend.semiring_arrays.AbstractCooSemiringTensor

indices, nnz, sparsity, zeroElement

Fields inherited from class org.flag4j.arrays.backend.AbstractTensor

data, rank, shape

Constructor Summary

Constructors

Constructor	Description
CooCTensor(Shape shape)	Creates a tensor with the specified data and shape.
CooCTensor(Shape shape, double[] entries, int[][] indices)	Creates a tensor with the specified data and shape.
CooCTensor(Shape shape, List<Complex128> entries, List<int[]> indices)	Creates a tensor with the specified data and shape.
CooCTensor(Shape shape, Complex128[] entries, int[][] indices)	Creates a tensor with the specified data and shape.
CooCTensor(Shape shape, Complex64[] entries, int[][] indices)	Creates a tensor with the specified data and shape.
CooCTensor(CooCTensor b)	Constructs a copy of a sparse COO tensor.

Method Summary

Modifier and Type	Method	Description
boolean	equals(Object object)	Checks if an object is equal to this tensor object.
int	hashCode()
boolean	isComplex()	Checks if any entry within this matrix has non-zero imaginary component.
boolean	isReal()	Checks if all data of this matrix are real.
Complex128[]	makeEmptyDataArray(int length)	Creates an empty array of the same type as the data array of this tensor.
CTensor	makeLikeDenseTensor(Shape shape, Complex128[] entries)	Constructs a dense tensor that is a similar type as this sparse COO tensor.
CooCTensor	makeLikeTensor(Shape shape, List<Complex128> entries, List<int[]> indices)	Constructs a tensor of the same type as this tensor with the specified shape and non-zero data.
CooCTensor	makeLikeTensor(Shape shape, Complex128[] entries)	Constructs a tensor of the same type as this tensor with the given the shape and data.
CooCTensor	makeLikeTensor(Shape shape, Complex128[] entries, int[][] indices)	Constructs a tensor of the same type as this tensor with the specified shape and non-zero data.
CooCTensor	round(int precision)	Rounds all data within this tensor to the specified precision.
CooCTensor	roundToZero(double tolerance)	Sets all elements of this tensor to zero if they are within tol of zero.
CooCTensor	set(double value, int... target)	Sets the element of this tensor at the specified target index.
CooCMatrix	toMatrix(Shape newShape)	Converts this tensor to a matrix with specified shape.
CooTensor	toReal()	Converts this complex vector to a real vector.
String	toString()	Formats this sparse COO tensor as a human-readable string specifying the full shape, non-zero data, and non-zero indices.
static CooCTensor	unsafeMake(Shape shape, Complex128[] data, int[][] indices)	Factory to construct a COO tensor which bypasses any validation checks on the data and indices.

Methods inherited from class org.flag4j.arrays.backend.field_arrays.AbstractCooFieldTensor

abs, div, H, H, isFinite, isInfinite, isNaN, sqrt

Methods inherited from class org.flag4j.arrays.backend.ring_arrays.AbstractCooRingTensor

sub

Methods inherited from class org.flag4j.arrays.backend.semiring_arrays.AbstractCooSemiringTensor

add, argmax, argmin, coalesce, coalesce, copy, dataLength, density, dropZeros, elemMult, flatten, flatten, get, getZeroElement, max, min, reshape, set, setZeroElement, sortIndices, sparsity, T, T, T, tensorDot, tensorTr, toDense

Methods inherited from class org.flag4j.arrays.backend.AbstractTensor

getData, getRank, getShape, reshape, sameShape, totalEntries

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.flag4j.arrays.backend.field_arrays.FieldTensorMixin

add, add, addEq, addEq, argmax, argmaxAbs, argmin, argminAbs, conj, div, div, divEq, divEq, isOnes, isZeros, max, maxAbs, min, minAbs, mult, mult, multEq, multEq, norm, norm, prod, recip, sub, sub, subEq, subEq, sum

Methods inherited from interface org.flag4j.arrays.backend.ring_arrays.TensorOverRing

H, sub

Methods inherited from interface org.flag4j.arrays.backend.semiring_arrays.TensorOverSemiring

add, elemMult, getData, getRank, getShape, tensorDot, tensorDot, tensorDot, tensorDot, tensorTr, tensorTr

Constructor Details

CooCTensor

public CooCTensor(Shape shape,
 Complex128[] entries,
 int[][] indices)

Creates a tensor with the specified data and shape.

Parameters:

shape - Shape of this tensor.

entries - Non-zero data of this tensor of this tensor.

indices - Indices of the non-zero data of this tensor.

CooCTensor

public CooCTensor(Shape shape,
 List<Complex128> entries,
 List<int[]> indices)

Creates a tensor with the specified data and shape.

Parameters:

shape - Shape of this tensor.

entries - Non-zero data of this tensor of this tensor.

indices - Indices of the non-zero data of this tensor.

CooCTensor

public CooCTensor(Shape shape,
 Complex64[] entries,
 int[][] indices)

Creates a tensor with the specified data and shape.

Parameters:

shape - Shape of this tensor.

entries - Non-zero data of this tensor of this tensor.

indices - Indices of the non-zero data of this tensor.

CooCTensor

public CooCTensor(Shape shape)

Creates a tensor with the specified data and shape.

Parameters:

shape - Shape of this tensor.

entries - Non-zero data of this tensor of this tensor.

indices - Indices of the non-zero data of this tensor.

CooCTensor

public CooCTensor(Shape shape,
 double[] entries,
 int[][] indices)

Creates a tensor with the specified data and shape.

Parameters:

shape - Shape of this tensor.

entries - Non-zero data of this tensor of this tensor.

indices - Indices of the non-zero data of this tensor.

CooCTensor

public CooCTensor(CooCTensor b)

Constructs a copy of a sparse COO tensor.

Parameters:

b - Tensor to construct copy of.

Method Details

unsafeMake

public static CooCTensor unsafeMake(Shape shape,
 Complex128[] data,
 int[][] indices)

Factory to construct a COO tensor which bypasses any validation checks on the data and indices.

Warning: This method should be used with extreme caution. It primarily exists for internal use. Only use this factory if you are 100% certain the parameters are valid as some methods may throw exceptions or exhibit undefined behavior.

Parameters:

shape - The full size of the COO tensor.

data - The non-zero data of the COO tensor.

indices - The non-zero indices of the COO tensor.

Returns:

A COO tensor constructed from the provided parameters.

makeEmptyDataArray

public Complex128[] makeEmptyDataArray(int length)

Description copied from interface: SemiringTensorMixin

Creates an empty array of the same type as the data array of this tensor.

Parameters:

length - The length of the array to construct.

Returns:

An empty array of the same type as the data array of this tensor.

makeLikeTensor

public CooCTensor makeLikeTensor(Shape shape,
 Complex128[] entries)

Constructs a tensor of the same type as this tensor with the given the shape and data. The resulting tensor will also have the same non-zero indices as this tensor.

Specified by:

makeLikeTensor in interface TensorOverSemiring<CooCTensor,CooCTensor,Complex128[],Complex128>

Specified by:

makeLikeTensor in class AbstractTensor<CooCTensor,Complex128[],Complex128>

Parameters:

shape - Shape of the tensor to construct.

entries - Entries of the tensor to construct.

Returns:

A tensor of the same type and with the same non-zero indices as this tensor with the given the shape and data.

makeLikeTensor

public CooCTensor makeLikeTensor(Shape shape,
 Complex128[] entries,
 int[][] indices)

Constructs a tensor of the same type as this tensor with the specified shape and non-zero data.

Specified by:

makeLikeTensor in class AbstractCooSemiringTensor<CooCTensor,CTensor,Complex128>

Parameters:

shape - Shape of the tensor to construct.

entries - Non-zero data of the tensor to construct.

indices - Indices of the non-zero data of the tensor.

Returns:

A tensor of the same type as this tensor with the specified shape and non-zero data.

makeLikeTensor

public CooCTensor makeLikeTensor(Shape shape,
 List<Complex128> entries,
 List<int[]> indices)

Constructs a tensor of the same type as this tensor with the specified shape and non-zero data.

Specified by:

makeLikeTensor in class AbstractCooSemiringTensor<CooCTensor,CTensor,Complex128>

Parameters:

shape - Shape of the tensor to construct.

entries - Non-zero data of the tensor to construct.

indices - Indices of the non-zero data of the tensor.

Returns:

A tensor of the same type as this tensor with the specified shape and non-zero data.

makeLikeDenseTensor

public CTensor makeLikeDenseTensor(Shape shape,
 Complex128[] entries)

Constructs a dense tensor that is a similar type as this sparse COO tensor.

Specified by:

makeLikeDenseTensor in class AbstractCooSemiringTensor<CooCTensor,CTensor,Complex128>

Parameters:

shape - Shape of the tensor to construct.

entries - The data of the dense tensor to construct.

Returns:

A dense tensor that is a similar type as this sparse COO tensor.

toReal

public CooTensor toReal()

Converts this complex vector to a real vector.

Returns:

A real vector containing the real components of all non-zero values in this vector. The imaginary components are ignored.

isReal

public boolean isReal()

Checks if all data of this matrix are real.

Returns:

true if all data of this matrix are real; false otherwise.

isComplex

public boolean isComplex()

Checks if any entry within this matrix has non-zero imaginary component.

Returns:

true if any entry of this matrix has a non-zero imaginary component.

round

public CooCTensor round(int precision)

Rounds all data within this tensor to the specified precision.

Parameters:

precision - The precision to round to (i.e. the number of decimal places to round to). Must be non-negative.

Returns:

A new tensor containing the data of this tensor rounded to the specified precision.

roundToZero

public CooCTensor roundToZero(double tolerance)

Sets all elements of this tensor to zero if they are within tol of zero. This is not done in place.

Parameters:

precision - The precision to round to (i.e. the number of decimal places to round to). Must be non-negative.

Returns:

A copy of this tensor with all data within tol of zero set to zero.

toMatrix

public CooCMatrix toMatrix(Shape newShape)

Converts this tensor to a matrix with specified shape.

Parameters:

newShape - Shape of matrix to convert this tensor to. Shape must be broadcastable with this tensors shape and have rank 2.

Returns:

A matrix of the specified shape with the same non-zero data as this tensor.

set

public CooCTensor set(double value,
 int... target)

Sets the element of this tensor at the specified target index.

Parameters:

value - New value to set the specified index of this tensor to.

target - Index of the element to set.

Returns:

If this tensor is dense, a reference to this tensor is returned. If this tensor is sparse, a copy of this tensor with the updated value is returned.

Throws:

IndexOutOfBoundsException - If target is not within the bounds of this tensor.

equals

public boolean equals(Object object)

Checks if an object is equal to this tensor object.

Overrides:

equals in class Object

Parameters:

object - Object to check equality with this tensor.

Returns:

True if the two tensors have the same shape, are numerically equivalent, and are of type CooCTensor. False otherwise.

hashCode

public int hashCode()

Overrides:

hashCode in class Object

toString

public String toString()

Formats this sparse COO tensor as a human-readable string specifying the full shape, non-zero data, and non-zero indices.

Overrides:

toString in class Object

Returns:

A human-readable string specifying the full shape, non-zero data, and non-zero indices of this tensor.