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RunBatch.py
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RunBatch.py
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import pickle
import subprocess
import os
import sys
from sklearn.model_selection import train_test_split
import pandas as pd
import numpy as np
import math
import argparse
import StringGenerator
def stratifiedSampling(csv_filename, output_filename, percentage, rand=1):
Meta = pd.read_csv(csv_filename, sep=', ')
rows, cols = Meta.shape
column_names = Meta.columns.tolist()
print(rows, cols, column_names)
y = Meta.pop('length')
X = Meta
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=math.floor(rows * percentage),
random_state=rand, stratify=y)
# print(X_test, y_test)
print(X_test.columns, y_test.name) ##y_test a Series
X_test['length'] = y_test.values
sampling = X_test # .append(y_test)
print(sampling.columns)
sampling = sampling.reindex(columns=column_names)
print(sampling.columns)
sampling.to_csv(output_filename, sep=",", index=False, header=True, encoding='utf-8')
def generateString():
options = []
file_dir = "generatedStrs/"
character_set = ["AlphaNumeric", "Printable", "ASCII", "Unicode"]
cmd_opt = input('Enter the characterset number for string generation: \n'
'0 AlphaNumeric; \n'
'1 Printable; \n'
'2 ASCII;\n'
'3 Unicode;\n')
cmd_opt = int(cmd_opt)
if cmd_opt > 2:
raise Exception('Not supported characterset yet!!!')
character_type = character_set[cmd_opt]
options.append(character_type)
matching_types = ["startsWith", "notStartsWith", "contains", "notContains"]
cmd_opt = input("Enter the matching type for string generation: \n"
"0 startsWith; \n"
"1 notStartsWith; \n"
"2 contains; \n"
"3 notContains;\n"
"4 other;\n")
cmd_opt = int(cmd_opt)
if cmd_opt > 3:
raise Exception('Not supported matching type yet!!!')
options.append(matching_types[cmd_opt])
substring = input('''Enter the string used for string generation: ''')
options.append(substring)
print(substring)
genSize = input('''Enter the number of strings to be generated: ''')
options.append(genSize)
genSize = int(genSize)
print(genSize)
maxLen = input('''Enter the maximum length of strings to be generated: ''')
options.append(maxLen)
maxLen = int(maxLen)
print(maxLen)
default_filename = file_dir+"_".join(options) + ".csv"
output_filename = input('''Enter the csv filename where generated strings to be stored (
default name is ''' + default_filename + '''):''')
print(output_filename)
genFuncs = {
0: StringGenerator.genStartsWith,
1: StringGenerator.genNotStartsWith,
2: StringGenerator.genContains,
3: StringGenerator.genNotContains}
assertion_funcs = {
0: lambda x: x[:len(substring)] == substring,
1: lambda x: x[:len(substring)] != substring,
2: lambda x: substring in x,
3: lambda x: substring not in x
}
print("-----Starting----------")
res = genFuncs[cmd_opt](substring, genSize, 0, maxLen, character_type)
StringGenerator.asserted(res, assertion_funcs[cmd_opt])
if cmd_opt % 2 == 0: ## match options
StringGenerator.save_to_file2(res, output_filename)
else:
StringGenerator.save_to_file(res, output_filename)
print("-----Finished----------")
def stringSampling():
genStr_filename = input('''Enter the csv filename for stratified sampling: ''')
sampling_percentage = input('''Enter the sampling percentage in float (1% is 0.01): ''')
sampling_rand = input('''Enter a random number for sampling random seed: (integer 0, 1, 2, ...): ''')
default_sampling_output = genStr_filename[:-4] + "_sampling" + sampling_percentage + "_rand" + str(
sampling_rand) + ".csv"
sampling_csv_output = input(
"Enter the output csv filename of stratified ampling results (default output file name is"
+ default_sampling_output + "): ")
print("-----Starting----------")
stratifiedSampling(genStr_filename, sampling_csv_output, float(sampling_percentage), int(sampling_rand))
print("-----Finished----------")
# parser = argparse.ArgumentParser(description='Stratified sampling of generated strings.')
# parser.add_argument('--file')
# parser.add_argument('--output')
# parser.add_argument('--samplingPercent')
# parser.add_argument('--randomSeed')
#
# args = parser.parse_args()
#
# file_genStr, sampling_csv_output, sampling_percentage, sampling_rand = args.file, args.output, float(
# args.samplingPercent), int(args.randomSeed)
# print(file_genStr, sampling_csv_output, sampling_percentage)
#
# stratifiedSampling(file_genStr, sampling_csv_output, sampling_percentage, sampling_rand)
def runExperiment():
print(os.getcwd())
assert os.path.exists("target/regexbenchmarks.jar"), "jmh jar file not found!!"
package = "org.ncsu.regex.perf3."
class_methods = ["BaseLineMethod", "JavaIndexOf", "RegexNotCompiledFullMatchingMethod",
"RegexPreCompiledFullMatchingMethod", "StringContainsMethod", "StringIndexOf",
"StringMatchesMethod", "StringStartsWith"]
for idx, classMethod in enumerate(class_methods):
print(idx, classMethod)
cmd_opt = input("Enter the index from the above methods:")
benchmark_class = package + class_methods[int(cmd_opt)]
print(class_methods[int(cmd_opt)])
regex = input("Enter the regex for performance measurement:")
print(regex)
substring = input("Enter the string which have equivalent operations of regex matching")
print(substring)
genStr_filename = input("Enter the csv filename for performance measurement:")
print(substring)
expectation = input("Enter the expectation of the method is true or false (lowercase required): ")
print(expectation)
iterations = input("Enter the number of strings been used from input file or the measurement iterations: ")
print(iterations)
iterations = int(iterations)
log_filename = "log/" + genStr_filename[:-4] + ".log"
print("output log name: " + log_filename)
result_filename = "result/" + genStr_filename
print("result csv filename: " + result_filename)
cmd = [
"java", "-jar", "target/regexbenchmarks.jar", benchmark_class,
"-f", "1", "-gc", "true" "-wi", "10", "-i", iterations, "-wbs", 20, "-bs", 20,
'-p', 'regex="' + regex + '"', '-p', 'str="' + substring + '"',
"-p", 'expectation="' + expectation + '"', "-p", 'filename="' + genStr_filename + '"'
"-rf", "csv", "-rff",
result_filename, "-o", log_filename
]
command = (' '.join(cmd))
print(command)
print("-----Starting----------")
os.system(command)
print("-----Finished----------")
def performAnalysis():
print("You typed four")
pass
parser = argparse.ArgumentParser(description='Parse JMH output files (.out) into structured csv file '
'and extract the measured time to generated strings.')
parser.add_argument('--log')
parser.add_argument('--file')
parser.add_argument('--output')
parser.add_argument('--batchsize')
args = parser.parse_args()
file_genStr, result_log, csv_output, batch_size = args.file, args.log, args.output, args.batchsize
# csv_output="out.csv"
# file_genStr="test3.csv"
# result_log="log/regex_precompiled_warm10_iter100.log"
extractStringAndExecutionTimeFromIterations(parseFile(result_log), file_genStr, csv_output, batch_size)
def batchProcess():
try:
options = {1: generateString, 2: stringSampling, 3: runExperiment, 4: performAnalysis}
while True:
cmd_opt = input('''Enter the option number to perform a task:
0 exit;
1 generate string;
2 string sampling;
3 run a measurement experiment;
4 process experiment result
''')
cmd_opt = int(cmd_opt)
if cmd_opt == 0:
break
else:
options[cmd_opt]()
except KeyboardInterrupt:
print('interrupted!')
if __name__ == "__main__":
batchProcess()
sys.exit(0)