Stratax
Scientific computing containers and operations
Loading...
Searching...
No Matches
Stratax Roadmap

Developer notes for planned Stratax feature work.

Purpose

Tracks the expected build-out of the library from core infrastructure through containers, generic operations, numerical features, bindings, and documentation.

Main API

Phase 1: Core Infrastructure

  • Buffer
  • Shape
  • Strides
  • Slice
  • Types
  • Concepts
  • Config
  • Validation

Phase 2: Containers

  • Vector
  • Matrix
  • Tensor
  • Creation helpers
  • Conversion helpers

Phase 3: Generic Operators

  • Comparison
  • Indexing offsets
  • Slicing
  • Logical operators
  • Bitwise operators
  • Broadcasting

Phase 4: Shape Operations

  • reshape
  • flatten
  • ravel
  • squeeze
  • expand_dims
  • transpose
  • swapaxes
  • permute_axes

Phase 5: Linear Algebra

  • Matrix multiplication
  • Dot product
  • Cross product
  • Determinant
  • Inverse
  • Solve
  • LU
  • QR
  • Cholesky
  • SVD
  • Eigenvalues
  • Eigenvectors
  • Norms

Phase 6: Input and Output

  • Stream printing
  • CSV I/O
  • Binary I/O
  • Serialization policy

Phase 7: Documentation and Examples

  • Developer docs for implemented core files
  • Developer docs for implemented containers
  • Developer docs for implemented ops
  • Developer docs for printing
  • User-facing guide
  • API reference
  • Example refresh

Later Phases

  • Calculus
  • Statistics
  • Random number support
  • Python bindings
  • Optimization

Validation Notes

  • The roadmap describes intended scope, not guaranteed current behavior.
  • Checked items should have tests before they are treated as complete.
  • Validation remains unchecked because the validation module is currently deferred.
  • Placeholder headers are intentionally not marked complete until they expose real behavior.
  • Empty and zero-dimension shape behavior is tested for implemented containers and ops.

Implementation Notes

  • Complete core and container correctness before expanding into larger numerical features.
  • Generic operators should work across all containers before specialized algorithms are added.
  • Shape operations should preserve storage invariants and make copy/view semantics explicit.
  • Optimization work should come after correctness tests and baseline behavior are stable.
  • Current implemented APIs are copy-based; view semantics are future work.

Future Work

  • Broadcasting
  • Views and slices
  • Type promotion rules
  • Sparse arrays
  • GPU backend
  • Automatic differentiation
  • FFT
  • Symbolic mathematics