Changes

v0.4.4

  • Bug in solve with dense array, where base of result is not set correctly, fixed.

  • Travis tests are using conda now.

  • Supported versions updated to: - Python: 3.7, 3.6 - NumPy: 1.15, 1.14, 1.13 - SciPy: 1.1, 1.0, 0.19 - SuiteSparse: 5.2

v0.4.3

  • The method solve_L can now also use the L matrix of the LL’ decomposition.

  • Supported versions updated to: - Python: 3.6, 3.5 - NumPy: 1.14, 1.13 - SciPy: 1.0, 0.19

v0.4.2

  • Bug where the ordering method is not taken into account is fixed.

  • The Factor class has now a (public) copy method.

v0.4.1

  • Bug with relaxed stride checking in NumPy 1.12 fixed.

  • Supported versions updated to: - Python: 3.6, 3.5, 3.4, 2.7 - NumPy: 1.8 to 1.12

v0.4

  • 64-bit indices (type long) are now supported.

  • The ordering method for Cholesky decomposition is now choosable.

  • Specific exceptions subclasses are now thrown for each error condition.

  • Setup does not rely on an installed Cython anymore.

v0.3.1

  • Ensure that arrays returned by the Factor.solve_...() methods are writeable.

v0.3

  • Dropped deprecated Factor.solve_P() and Factor.solve_P().

  • Fixed a memory leak upon garbage collection of Factor.

v0.2

  • Factor solve methods now return 1d output for 1d input (just like np.dot does).

  • Factor.solve_P() and Factor.solve_P() deprecated; use Factor.apply_P() and Factor.apply_Pt() instead.

  • New methods for computing determinants of positive-definite matrices: Factor.det(), Factor.logdet(), Factor.slogdet().

  • New method for explicitly computing inverse of a positive-definite matrix: Factor.inv().

  • Factor.D() has much better implementation.

  • Build system improvements.

  • Wrapper code re-licensed under BSD terms.

v0.1

First public release.