API Reference - Cores - SymbolicDifferentiationTensor

Constructors

add()


SymbolicDifferentiationTensorObject.add(...: tensor): SymbolicDifferentiationTensorObject

Parameters:

  • tensor: The tensor to be used by the symbolic differentiation tensor object.

Returns

  • SymbolicDifferentiationTensorObject: The generated symbolic differentiation tensor object.

subtract()


SymbolicDifferentiationTensorObject.subtract(...: tensor): SymbolicDifferentiationTensorObject

Parameters:

  • tensor: The tensor to be used by the symbolic differentiation tensor object.

Returns

  • SymbolicDifferentiationTensorObject: The generated symbolic differentiation tensor object.

multiply()


SymbolicDifferentiationTensorObject.multiply(...: tensor): SymbolicDifferentiationTensorObject

Parameters:

  • tensor: The tensor to be used by the symbolic differentiation tensor object.

Returns

  • SymbolicDifferentiationTensorObject: The generated symbolic differentiation tensor object.

divide()


SymbolicDifferentiationTensorObject.divide(...: tensor): SymbolicDifferentiationTensorObject

Parameters:

  • tensor: The tensor to be used by the symbolic differentiation tensor object.

Returns

  • SymbolicDifferentiationTensorObject: The generated symbolic differentiation tensor object.

power()


SymbolicDifferentiationTensorObject.power(baseTensor: tensor, exponentTensor: tensor): SymbolicDifferentiationTensorObject

Parameters:

  • baseTensor: The base tensor to be used by the symbolic differentiation tensor object.

  • exponentTensor: The exponent tensor to be used by the symbolic differentiation tensor object.

Returns

  • SymbolicDifferentiationTensorObject: The generated symbolic differentiation tensor object.

log()


SymbolicDifferentiationTensorObject.log(numberTensor: tensor, baseTensor: tensor): SymbolicDifferentiationTensorObject

Parameters:

  • numberTensor: The number tensor to be used by the symbolic differentiation tensor object.

  • baseTensor: The base tensor to be used by the symbolic differentiation tensor object.

Returns

  • SymbolicDifferentiationTensorObject: The generated symbolic differentiation tensor object.

sin()


SymbolicDifferentiationTensorObject.sin(radianTensor: tensor): SymbolicDifferentiationTensorObject

Parameters:

  • radianTensor: The radian tensor to be used by the symbolic differentiation tensor object.

Returns

  • SymbolicDifferentiationTensorObject: The generated symbolic differentiation tensor object.

cos()


SymbolicDifferentiationTensorObject.cos(radianTensor: tensor): SymbolicDifferentiationTensorObject

Parameters:

  • radianTensor: The radian tensor to be used by the symbolic differentiation tensor object.

Returns

  • SymbolicDifferentiationTensorObject: The generated symbolic differentiation tensor object.

tan()


SymbolicDifferentiationTensorObject.tan(radianTensor: tensor): SymbolicDifferentiationTensorObject

Parameters:

  • radianTensor: The radian tensor to be used by the symbolic differentiation tensor object.

Returns

  • SymbolicDifferentiationTensorObject: The generated symbolic differentiation tensor object.

dotProduct()


SymbolicDifferentiationTensorObject.dotProduct(tensor1: tensor, tensor2: tensor): SymbolicDifferentiationTensorObject

Parameters:

  • tensor: The tensor to be used by the symbolic differentiation tensor object.

Returns

  • SymbolicDifferentiationTensorObject: The generated symbolic differentiation tensor object.

Functions

getTensor()


SymbolicDifferentiationTensor:getTensor(doNotDeepCopy: boolean): tensor

Parameters:

  • doNotDeepCopy: Set whether or not to deep copy the tensor.

Returns:

  • tensor: The tensor generated by the symbolic differentiation tensor object.

getTensor()


SymbolicDifferentiationTensor:getTensor(tensor: tensor, doNotDeepCopy: boolean)

Parameters:

  • tensor: The tensor to be used by the symbolic differentiation tensor object.

  • doNotDeepCopy: Set whether or not to deep copy the tensor.

getFirstDerivativeTensorTable()


SymbolicDifferentiationTensor:getFirstDerivativeTensor(...: tensorToBeRespectedTo): tensor

Parameters:

  • tensorToBeRespectedTo: The tensor to be used for generating first derivative tensor.

Returns:

  • firstDerivativeTensor: The first derivative tensor in respect to arguments used in the function.