deeptime.numeric

The numeric package contains numerical utilities.

General numerical tools

drop_nan_rows(arr, *args)	Remove rows in all inputs for which arr has _np.nan entries.
is_diagonal_matrix(matrix)	Checks whether a provided matrix is a diagonal matrix, i.e., $A = \mathrm{diag}(a_1,\ldots, a_n)$.
is_square_matrix(arr)	Determines whether an array is a square matrix.
schatten_norm(mat[, order, hermitian])	Computes the r-Schatten norm

Numerical tools for eigenvalue problems

eigs(matrix[, n_eigs, which])	Computes the eigenvalues and eigenvectors of matrix.
eig_corr(C0, Ct[, epsilon, method, ...])	Solve generalized eigenvalue problem with correlation matrices C0 and Ct
sort_eigs(evals, evecs[, order])	Sorts the eigenvalues and eigenvectors by descending norm of the eigenvalues or lexicographically.
spd_eig(W[, epsilon, method, ...])	Rank-reduced eigenvalue decomposition of symmetric positive definite matrix.
spd_truncated_svd(mat[, dim, eps])	Rank-reduced singular value decomposition of symmetric positive (semi-)definite matrix.
spd_inv(W[, epsilon, method])	Compute matrix inverse of symmetric positive-definite matrix $W$.
spd_inv_split(W[, epsilon, method, ...])	Compute $W^{-1} = L L^T$ of the symmetric positive-definite matrix $W$.
spd_inv_sqrt(W[, epsilon, method, return_rank])	Computes $W^{-1/2}$ of symmetric positive-definite matrix $W$.
ZeroRankError	Input matrix has rank zero.