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bundles / scipy latest / scipy / linalg / _matfuncs / logm

function

scipy.linalg._matfuncs:logm

source: /scipy/linalg/_matfuncs.py :149

Signature

def   logm ( A ,  disp = <object object at 0x0000> )

Summary

Compute matrix logarithm.

Extended Summary

The matrix logarithm is the inverse of expm: expm(logm(A)) == A

The documentation is written assuming array arguments are of specified "core" shapes. However, array argument(s) of this function may have additional "batch" dimensions prepended to the core shape. In this case, the array is treated as a batch of lower-dimensional slices; see linalg_batch for details. Note that calls with zero-size batches are unsupported and will raise a ValueError.

Parameters

A : (N, N) array_like

Matrix whose logarithm to evaluate

disp : bool, optional

Emit warning if error in the result is estimated large instead of returning estimated error. (Default: True)

Returns

logm : (N, N) ndarray

Matrix logarithm of A

errest : float

(if disp == False)

1-norm of the estimated error, ||err||_1 / ||A||_1

Examples

import numpy as np
from scipy.linalg import logm, expm
a = np.array([[1.0, 3.0], [1.0, 4.0]])
b = logm(a)
✓
b
expm(b)         # Verify expm(logm(a)) returns a
✗

Aliases

  • scipy.linalg.logm

Referenced by

This package