Releases: RubixML/Tensor
Releases · RubixML/Tensor
2.0.1
- Matrix stacking now row or columnwise
- Changed method signature and behavior of repeat matrix
2.0.0
- Implemented the library as an extension using Zephir lang
- Changed namespace from Rubix\Tensor to \Tensor
- Matrix decompositions are now a separate abstraction
- Removed Dimensionality Mismatch exception
- Added inverse trigonomic methods to tensor interface
- Added Array-Like interface
- Removed Column/Row exclude methods from Matrix
- Changed method signature of matrix determinant
- Added return sub matrix
- Added positive definite and semidefinite methods to Matrix
- Added is symmetric method to Matrix
- Added Statistical and Trigonometric interfaces
- Added Arithmetic and Comparable interfaces
- Added log1p and expm1 methods to the Arithmetic interface
- Added matrix full rank method
- Added generate random Poisson distribution
- Added Cholesky decomposition
- Variance now takes an optional mean argument
1.0.4
- Added transpose to Tensor API
- Reduced memory footprint of matmul operation
- Removed magic getters
- Added shape string method to Tensor API
- Improved error messages for matrix dimensionality mismatch
1.0.3
- Added clip upper and lower bounds
- Added isSquare method to Matrix
- Added vector late static binding
1.0.2
- Added ref using row elimination method
- Added universal comparison methods to tensor API
- Added convolve operation to Vector and Matrix
1.0.1
- Added Column Vector
- Implemented Eigenvalue decomposition
- Added solve system of linear equations
- Integration with 3rd party JAMA libray
- Fixed variance covariance calculation
- Added percentile calculation for Vector and Matrix
- Blanket optimizations
1.0.0
- Implemented LU decomposition
- Added vector projection
- Implemented Matrix inverse
- Implemented Row Echelon and Reduced Row Echelon decomposition
- Added Matrix determinant
- Added Matrix rank
- Added Matrix/Vector products
- Implemented universal element-wise tensor operations
- Added statistical functions
- Added trigonometric functions
- Added exponential and logarithmic functions
- Added tensor factories