Base class for doing useful general operations on second rank tensors (stress, strain etc.).
Create a SquareTensor object. Note that the constructor uses __new__ rather than __init__ according to the standard method of subclassing numpy ndarrays. Error is thrown when the class is initialized with non-square matrix.
- input_array (3x3 array-like) – the 3x3 array-like representing the content of the tensor
- vscale (6x1 array-like) – 6x1 array-like scaling the voigt-notation vector with the tensor entries
shorthand for the determinant of the SquareTensor
Scales the tensor by a certain multiplicative scale factor
Parameters: scale_factor (float) – scalar multiplier to be applied to the SquareTensor object
shorthand for matrix inverse on SquareTensor
Test to see if tensor is a valid rotation matrix, performs a test to check whether the inverse is equal to the transpose and if the determinant is equal to one within the specified tolerance
Parameters: tol (float) – tolerance to both tests of whether the the determinant is one and the inverse is equal to the transpose
calculates matrices for polar decomposition
Returns a list of principal invariants for the tensor, which are the values of the coefficients of the characteristic polynomial for the matrix
shorthand for transpose on SquareTensor
Base class for doing useful general operations on Nth order tensors, without restrictions on the type (stress, elastic, strain, piezo, etc.)
Create a TensorBase object. Note that the constructor uses __new__ rather than __init__ according to the standard method of subclassing numpy ndarrays.
- input_array – (3xN array-like): the 3xN array-like representing a tensor quantity
- vscale – (N x M array-like): a matrix corresponding to the coefficients of the voigt-notation tensor
Given a structure associated with a tensor, attempts a calculation of the tensor in IEEE format according to the 1987 IEEE standards.
Parameters: structure (Structure) – a structure associated with the tensor to be converted to the IEEE standard
Returns a tensor that is invariant with respect to symmetry operations corresponding to a structure
- structure (Structure) – structure from which to generate symmetry operations
- symprec (float) – symmetry tolerance for the Spacegroup Analyzer used to generate the symmetry operations
Constructor based on the voigt notation vector or matrix.
Returns a dictionary that maps indices in the tensor to those in a voigt representation based on input rank
Parameters: Rank (int) – Tensor rank to generate the voigt map
Tests whether a tensor is invariant with respect to the symmetry operations of a particular structure by testing whether the residual of the symmetric portion is below a tolerance
Parameters: tol (float) – tolerance for symmetry testing
Tests whether a tensor is symmetric or not based on the residual with its symmetric part, from self.symmetrized
Parameters: tol (float) – tolerance to test for symmetry
Tests symmetry of tensor to that necessary for voigt-conversion by grouping indices into pairs and constructing a sequence of possible permutations to be used in a tensor transpose
Applies a rotation directly, and tests input matrix to ensure a valid rotation.
- matrix (3x3 array-like) – rotation matrix to be applied to tensor
- tol (float) – tolerance for testing rotation matrix validity
Returns a generally symmetrized tensor, calculated by taking the sum of the tensor and its transpose with respect to all possible permutations of indices
Applies a transformation (via a symmetry operation) to a tensor.
Parameters: symm_op (SymmOp) – a symmetry operation to apply to the tensor
Returns the tensor in Voigt notation
returns the matrix with all entries below a certain threshold (i.e. tol) set to zero