`scipy.sparse.linalg._expm_multiply:_expm_multiply_interval`

source: /scipy/sparse/linalg/_expm_multiply.py :597

Signature

   def     _expm_multiply_interval (    A    ,    B    ,    start    =  None   ,    stop    =  None   ,    num    =  None   ,    endpoint    =  None   ,    traceA    =  None   ,    balance    =  False   ,    status_only    =  False     )

Summary

Compute the action of the matrix exponential at multiple time points.

Parameters

A : transposable linear operator: The operator whose exponential is of interest.
B : ndarray: The matrix to be multiplied by the matrix exponential of A.
start : scalar, optional: The starting time point of the sequence.
stop : scalar, optional: The end time point of the sequence, unless endpoint is set to False. In that case, the sequence consists of all but the last of num + 1 evenly spaced time points, so that stop is excluded. Note that the step size changes when endpoint is False.
num : int, optional: Number of time points to use.
traceA : scalar, optional: Trace of A. If not given the trace is estimated for linear operators, or calculated exactly for sparse matrices. It is used to precondition A, thus an approximate trace is acceptable
endpoint : bool, optional: If True, stop is the last time point. Otherwise, it is not included.
balance : bool: Indicates whether or not to apply balancing.
status_only : bool: A flag that is set to True for some debugging and testing operations.

Returns

F : ndarray: $e^{t_{k} A} B$
status : int: An integer status for testing and debugging.

Notes

This is algorithm (5.2) in Al-Mohy and Higham (2011).

There seems to be a typo, where line 15 of the algorithm should be moved to line 6.5 (between lines 6 and 7).

Aliases

scipy.sparse.linalg._expm_multiply._expm_multiply_interval