Ignore:
Timestamp:
Jul 26, 2025, 3:04:16 PM (2 months ago)
Author:
Michael Brooks <mlbrooks@…>
Branches:
master
Children:
f449d1e
Parents:
7806f91
Message:

Use plots-based data crunching for quick analysis of ad-hoc testing, supporting tailq data not being present

File:
1 edited

Legend:

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  • doc/theses/mike_brooks_MMath/plots/ListCommon.py

    r7806f91 r29c6a7d  
    5757    byPeer = timings.groupby(['NumNodes', 'op', 'InterleaveFrac'])
    5858    for [NumNodes, op, intrlFrac], peerGroup in byPeer:
    59         baselineRows = peerGroup.groupby(['fx']).get_group(baseline_fx)
    60         baselineDur = meanNoOutlr( baselineRows['mean_op_dur_ns'] )
     59        grpfx = peerGroup.groupby(['fx'])
     60        if baseline_fx in grpfx.groups:
     61            baselineRows = grpfx.get_group(baseline_fx)
     62            baselineDur = meanNoOutlr( baselineRows['mean_op_dur_ns'] )
     63        else:
     64            baselineDur = 1.0
    6165        timings.loc[peerGroup.index, 'BaselineFxOpDurNs'] = baselineDur
    6266    timings['OpDurRelFx'] = timings['mean_op_dur_ns'] / timings['BaselineFxOpDurNs']
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