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Numpy appears to have changed what a percentile means with numpy 2.0, as well as maybe what it means to divide.
I added the following lines at the end of 'event_discharge_energy', right before the return statement, in pyxlma.lmalib.flash.properties
I got the following results: https://www.diffchecker.com/lvlbQjU2/ (original is numpy 1.26.4, changed is 2.0.0).
-zinit/8
is reported with less precision (maybe a dtypes thing) which trickles down intonp.exp(-(zinit/8.4))
(fortunately numpy 2.0 does not change the value of Euler's number, as I had originally suspected), and same thing with the percentile values.somehow specifying the DEFAULT VALUES
rtol
andatol
kwargs tonp.allclose
fixes all of this? I don't understand anything anymore...