pg_utils.numerics.utils

Miscellaneous utilities for numerical calculation

Functions

allclose_sparse(array_1, array_2[, rtol, atol])	Compare if two sparse matrices are close enough
array_to_str(x[, str_fun])	Convert array to List of strings
cluster_modes(eig_vals[, rtol, atol])	Clustering of eigenvalues.
eigen_drift(eig_base, eig_comp[, waterlevel])	Calculate eigenvalue drift ratio using Boyd's method ([Boyd])
eigenfreq_Malkus_3d(m, n, Le[, mode, timescale])	Analytic eigenfrequency for 3D eigemodes with Malkus bg field
eigenfreq_Malkus_pg(m, n, Le[, mode, ...])	Analytic eigenfrequency for the PG model with Malkus bg field
eigenfreq_inertial3d(m, n)	Analytic eigenfrequency for the 3D inertial modes
eigenfreq_psi_op(m, n[, prec])	Analytic eigenfrequency for the self-adjoint operator for stream function Psi in the vorticity equation
intermodal_separation(eig_vals, **opt_cluster)	Calculate intermodal separation ([Boyd])
is_eq_coo(array_1, array_2)	Compare if two COORdinate format sparse arrays are identical
is_eq_sparse(array_1, array_2)	Compare if two sparse matrices are identical
spec_tail_exp_rate(spectrum)	Calculate maximum exponential rate of convergence from the trailing part of a spectrum.
to_dense_gmpy2(gmpy2_array, prec[, mode])	Convert a sparse gmpy2 array to dense form
to_dense_obj(obj_array, fill_zero)	Convert a sparse object array to dense form
to_gpmy2_c(x[, dps, prec])	Convert float array to gmpy2 float array
to_gpmy2_f(x[, dps, prec])	Convert float array to gmpy2 float array
to_mpmath_c(x[, dps, prec])	Convert float array to mpmath float array
to_mpmath_f(x[, dps, prec])	Convert float array to mpmath float array
to_numpy_c(x)	Convert complex array to numpy complex128 array
to_numpy_f(x)	Convert float array to numpy float64 array
transform_dps_prec([dps, prec, dps_default, ...])	Conversion between decimal points and precision