linalg
is a library for linear algebra and regression implemented in C. The code is optimized for readability and clarity instead of raw efficiency (though it tries not to ignore issues of efficiency completely).
linalg
contains two datatypes in its core linear algebra engine, vector
and matrix
:
vector
is a (one dimensional) vector of real numbers (Cdouble
s). The underlying data is stored as a C array, and so occupies contiguous memory locations in the computer's memory.matrix
is a (two dimensional) matrix of real numbers (Cdouble
s). The underlying data is stored in row-major order, so each row occupies contiguous memory locations in the computer's memory.
To complement these data types, linalg
contains many functions for performing linear algebraic operations. For example
matrix_vector_multiply
computes the product vector of a matrix and vector.matrix_multiply
computes the product matrix of two matrices.matrix_multiply_MtN
computes the product of the transpose of one matrix with another.
Linear equations can be solved using linsolve_qr
, which adopts a strategy of computing the QR matrix factorization of the left hand side. To access the underlying matrix factorization, use qr_decomp
.
linalg
also includes functions for regression. Use linreg_fit
to fit a linear regression given a design matrix X
and a response vector y
.
The routines in linalg
are extensively unit tested, which also serve as simple examples of use.