From 72b45cfe662107c8e1bb549df71ba51352a898ee Mon Sep 17 00:00:00 2001 From: Vratko Polak Date: Mon, 6 Dec 2021 13:54:34 +0100 Subject: [PATCH] PLRsearch: Update docscrings Previous code changes updated code comments, but not docstring. Change-Id: I5be3fd07620cc97c9088efceb72c2f68ab103915 Signed-off-by: Vratko Polak --- resources/libraries/python/PLRsearch/PLRsearch.py | 14 +++++++++++--- 1 file changed, 11 insertions(+), 3 deletions(-) diff --git a/resources/libraries/python/PLRsearch/PLRsearch.py b/resources/libraries/python/PLRsearch/PLRsearch.py index cdfd308149..ce65fd2ec8 100644 --- a/resources/libraries/python/PLRsearch/PLRsearch.py +++ b/resources/libraries/python/PLRsearch/PLRsearch.py @@ -426,13 +426,21 @@ class PLRsearch: Integrator assumes uniform distribution, but over different parameters. Weight and likelihood are used interchangeably here anyway. - Each trial has an offered load, a duration and a loss count. - Fitting function is used to compute the average loss per second. - Poisson distribution (with average loss per trial) is used + Each trial has an intended load, a sent count and a loss count + (probably counting unsent packets as loss, as they signal + the load is too high for the traffic generator). + The fitting function is used to compute the average loss rate. + Geometric distribution (with average loss per trial) is used to get likelihood of one trial result, the overal likelihood is a product of all trial likelihoods. As likelihoods can be extremely small, logarithms are tracked instead. + The current implementation does not use direct loss rate + from the fitting function, as the input and output units may not match + (e.g. intended load in TCP transactions, loss in packets). + Instead, the expected average loss is scaled according to the number + of packets actually sent. + TODO: Copy ReceiveRateMeasurement from MLRsearch. :param trace: A multiprocessing-friendly logging function (closure). -- 2.16.6