Expand description
Contains all the tooling for working with arbitrary rank tensors, symbolically, numerically, and parametrically.
It includes special support for a minkowski metric, and a way to add any custom diagonal (sign based) metric.
All tensor types make use of a tensor structure type, either the minimum Vec of [Slot]s or a more complete (but slightly more computationally heavy) [HistoryStructure].
Data is then added, to make parametric, or fully numeric tensors.
If no data is added, some [TensorStructure]s behave like symbolic tensors: namely [HistoryStructure] and [SymbolicTensor]
There are two main types of data tensors, [DenseTensor] and [SparseTensor].
They each implement a different type of storage for data.
All types of tensors can be contracted together using the [Contract] trait.
This can be done manually, or using a [TensorNetwork] and specifying a contraction algorithm.
Several Enums are defined to be able to store heterogenous tensors. Namely
- [
DataTensor] - [
NumTensor] - [
MixedTensor]