Eigen
3.4.90 (git rev 67eeba6e720c5745abc77ae6c92ce0a44aa7b7ae)

This module provides an interface to the Apple Accelerate library. It provides the seven following main factorization classes:
In order to use this module, the Accelerate headers must be accessible from the include paths, and your binary must be linked to the Accelerate framework. The Accelerate library is only available on Apple hardware.
Note that many of the algorithms require additional information about your matrices. This can be provided by setting the UpLo template argument when defining the factorization class. For example, the following creates an LDLT factorization where your matrix is symmetric and uses the lower triangle:
Failure to do so may result in your application crashing.
Classes  
class  AccelerateCholeskyAtA 
A QR factorization and solver based on Accelerate without storing Q (equivalent to A^TA = R^T R) More...  
class  AccelerateLDLT 
The default Cholesky (LDLT) factorization and solver based on Accelerate. More...  
class  AccelerateLDLTSBK 
A direct Cholesky (LDLT) factorization and solver based on Accelerate with Supernode BunchKaufman and static pivoting. More...  
class  AccelerateLDLTTPP 
A direct Cholesky (LDLT) factorization and solver based on Accelerate with full threshold partial pivoting. More...  
class  AccelerateLDLTUnpivoted 
A direct Choleskylike LDL^T factorization and solver based on Accelerate with only 1x1 pivots and no pivoting. More...  
class  AccelerateLLT 
A direct Cholesky (LLT) factorization and solver based on Accelerate. More...  
class  AccelerateQR 
A QR factorization and solver based on Accelerate. More...  