How can I do a numerical inverse Laplace transform of a data array?

Question

I would like to perform a numerical inverse Laplace transform on an array of data using Python.

I found an algorithm in mpmath called invertlaplace, however it accepts only lambda functions.

score 1 · Accepted Answer · edited Aug 01 '19 at 18:06

1

You could define a lambda that returns an interpolated version of your data.

Something like:

from math import floor, ceil
data = [1,2,3,4,5]
interp = lambda x: (1 - x%1)*data[floor(x)] + (x%1)*data[ceil(x)]

I am unsure if the linear interpolation will be stable or not for the version of the inverse Laplace you are using, or for your data.

edited Aug 01 '19 at 18:06

Peter Mortensen

answered Aug 01 '19 at 17:50

sgillen

Thanks, I tried this but ivertlaplace doesn't like when interp uses the modulus operator and throws an error: -------TypeError: unsupported operand type(s) for %: 'mpc' and 'int' -------- If I try int(x), it throws the error: -----TypeError: int() argument must be a string or a number, not 'mpc' – Imaginary Aug 01 '19 at 21:49
It look like you can replace the built in modulus operator with mpmath.fmod described here: http://mpmath.org/doc/current/general.html – sgillen Aug 01 '19 at 22:18

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