API Reference

Matrix Determinant

Functions for computing determinant and related quantities of matrices.

detkit.logdet(A[, sym_pos, overwrite_A, ...])	Compute the logdet of a matrix.
detkit.loggdet(A, X[, Xp, method, sym_pos, ...])	Compute the loggdet of a matrix.
detkit.logpdet(A, X[, Xp, method, sym_pos, ...])	Compute the logpdet of a matrix.
detkit.memdet(A[, max_mem, num_blocks, ...])	Compute log-determinant under memory constraint.

Matrix Decompositions

LU, LDL and Cholesky factorizations for sub-matrices, as well as matrix orthogonalizations.

detkit.orthogonalize(A)	Orthogonalize the columns of matrix.
detkit.ortho_complement(Xp, X[, X_orth])	Orthogonalize the columns of matrix Xp against X.
detkit.lu_factor(A[, shape, overwrite])	LU decomposition of a sub-matrix.
detkit.ldl_factor(A[, m, lower, overwrite, ...])	LDL decomposition of a sub-matrix.
detkit.cho_factor(A[, m, lower, overwrite])	Cholesky decomposition of a sub-matrix.

Solving Linear Systems

Solving linear systems for sub-matrices based on LU, LDL and Cholesky decompositions.

detkit.lu_solve(lu, perm, B[, shape, trans, ...])	Solve linear system given a sub-matrix output of LU decomposition.
detkit.ldl_solve(ldu, piv, B[, shape, ...])	Solve symmetric positive-definite linear system given a sub-matrix of LDL decomposition.
detkit.cho_solve(cho, B[, shape, lower, ...])	Solve symmetric positive-definite linear system given a sub-matrix output of Cholesky decomposition.
detkit.solve_triangular(A, B[, shape, ...])	Solve triangular linear system given a sub-matrix.

BLAS Operations

BLAS operations for sub-matrices.

detkit.matmul(A, B, C[, shape, trans_a, ...])

Matrix-matrix multiplication for sub-matrices.

Datasets

Functions to create sample dataset to be used for test and benchmarking purposes.

detkit.electrocardiogram([start, end, ...])	Load an electrocardiogram signal as an example for a 1D signal.
detkit.covariance_matrix([size, sample, ...])	Create covariance matrix based on the autocorrelation of electrocardiogram signal.
detkit.design_matrix([num_rows, num_cols, ortho])	Generate design matrix.

Profiling

Utility classes for profiling memory and process.

detkit.Memory([unit])	Trace memory allocation.
detkit.Disk([unit])	Measure read and write to disk.
detkit.Profile()	Profile a process.

Profiling Utilities

Utility functions for profiling memory and process.

detkit.get_config([key])	Returns the definitions used in the compile-time of the package.
detkit.get_instructions_per_task([task, dtype])	Counts the hardware instructions of computing a single FLOP of a benchmark task on the current processor.
detkit.get_processor_name()	Returns name of processor.
detkit.human_readable_time(t[, pad])	Converts time (in seconds) as float to string with time unit.
detkit.human_readable_mem(m[, pad])	Converts memory (in bytes) as float to string with memory unit.