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.