# Read thesis-append-pbv.csv # Output for string-graph-peq-sharing.dat # Project details # Filter operation=peq # Split "series" goups of sut; only those in the "pretty" list # Assert one row per string-length # output: # string-len op-duration # in chunks, each headed by pertty(sut) import pandas as pd import numpy as np import os import sys sys.path.insert(0, os.path.dirname(__file__)) from common import * prettyFieldNames = { "cfa-ll-share-na": "{/Helvetica=15 C{/Symbol \\42}} share", "stl-na-na-na": "STL", } timings = loadParseTimingData('result-append-pbv.csv') # Filter operation=pbv, corpus=100-*-*+*+t0 timings = timings.groupby('operation').get_group('pbv') timings = timings.groupby('corpus-nstrs-tgt').get_group(100) timings = timings.groupby('corpus-offset-instr').get_group('t0') # Emit in groups groupedSut = timings.groupby('sut') for sut, sgroup in groupedSut: if sut in prettyFieldNames: sgroup_sorted = sgroup.sort_values(by='corpusMeanLenCharsAct') print('"{header}"'.format(header=prettyFieldNames[sut])) text = sgroup_sorted[['corpusMeanLenCharsAct', 'op-duration-ns']].to_csv(header=False, index=False, sep='\t') print(text) print()