compare-results

#!/usr/bin/env python3 -u

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import collections
import sys
import argparse
import json
import itertools
from webkitpy.benchmark_runner.benchmark_results import BenchmarkResults
from webkitpy.benchmark_runner.benchmark_json_merge import mergeJSONs

try:
    from scipy import stats
except:
    print("ERROR: scipy package is not installed. Run `pip install scipy`")
    sys.exit(1)

try:
    import numpy
except:
    print("ERROR: numpy package is not installed. Run `pip install numpy`")
    sys.exit(1)


def readJSONFile(path):
    with open(path, 'r') as contents:
        result = json.loads(contents.read())
        if 'debugOutput' in result:
            del result['debugOutput']
        return result

Speedometer3 = "Speedometer3"
Speedometer2 = "Speedometer2"
JetStream3 = "JetStream3"
JetStream2 = "JetStream2"
PLT5 = "PLT5"
CompetitivePLT = "CompetitivePLT"
PLUM3 = "PLUM3"
MotionMark = "MotionMark"
MotionMark1_1 = "MotionMark-1.1"
MotionMark1_1_1 = "MotionMark-1.1.1"
MotionMark1_2 = "MotionMark-1.2"
MotionMark1_3 = "MotionMark-1.3"
RAMification = "RAMification"

unitMarker = "__unit__"


def speedometer3Breakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "ms"
    for test in breakdown._results["Speedometer-3"]["tests"].keys():
        result[test] = breakdown._results["Speedometer-3"]["tests"][test]["metrics"]["Time"]["Total"]["current"]
    return result

def speedometer3BreakdownSyncAsync(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "ms"
    for test in breakdown._results["Speedometer-3"]["tests"].keys():
        syncTime = None
        asyncTime = None
        for value in breakdown._results["Speedometer-3"]["tests"][test]["tests"].values():
            syncArray = value["tests"]["Sync"]["metrics"]["Time"][None]["current"]
            asyncArray = value["tests"]["Async"]["metrics"]["Time"][None]["current"]
            if not syncTime:
                syncTime = syncArray
                asyncTime = asyncArray
            else:
                syncTime = [x + y for x, y in zip(syncTime, syncArray)]
                asyncTime = [x + y for x, y in zip(asyncTime, asyncArray)]
        result[test + "-sync"] = syncTime
        result[test + "-async"] = asyncTime
    return result

def speedometer2Breakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "ms"
    for test in breakdown._results["Speedometer-2"]["tests"].keys():
        result[test] = breakdown._results["Speedometer-2"]["tests"][test]["metrics"]["Time"]["Total"]["current"]
    return result

def speedometer2BreakdownSyncAsync(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "ms"
    for test in breakdown._results["Speedometer-2"]["tests"].keys():
        syncTime = None
        asyncTime = None
        for value in breakdown._results["Speedometer-2"]["tests"][test]["tests"].values():
            syncArray = value["tests"]["Sync"]["metrics"]["Time"][None]["current"]
            asyncArray = value["tests"]["Async"]["metrics"]["Time"][None]["current"]
            if not syncTime:
                syncTime = syncArray
                asyncTime = asyncArray
            else:
                syncTime = [x + y for x, y in zip(syncTime, syncArray)]
                asyncTime = [x + y for x, y in zip(asyncTime, asyncArray)]
        result[test + "-sync"] = syncTime
        result[test + "-async"] = asyncTime
    return result

def jetStream2Breakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "pts"
    for test in breakdown._results["JetStream2.0"]["tests"].keys():
        result[test] = breakdown._results["JetStream2.0"]["tests"][test]["metrics"]["Score"][None]["current"]
    return result

def detailedJetStream2Breakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "ms"
    for test in breakdown._results["JetStream2.0"]["tests"].keys():
        for subtest in breakdown._results["JetStream2.0"]["tests"][test]["tests"]:
            result[test + "-" + subtest] = breakdown._results["JetStream2.0"]["tests"][test]["tests"][subtest]["metrics"]["Time"][None]["current"]
    return result

def categoryJetStream2Breakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "ms"
    for test in breakdown._results["JetStream2.0"]["tests"].keys():
        for category in breakdown._results["JetStream2.0"]["tests"][test]["tests"]:
            if not category in result:
                result[category] = []
            result[category] += breakdown._results["JetStream2.0"]["tests"][test]["tests"][category]["metrics"]["Time"][None]["current"]
    return result

def jetStream3Breakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "pts"
    for test in breakdown._results["JetStream3.0"]["tests"].keys():
        result[test] = breakdown._results["JetStream3.0"]["tests"][test]["metrics"]["Score"][None]["current"]
    return result

def detailedJetStream3Breakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "ms"
    for test in breakdown._results["JetStream3.0"]["tests"].keys():
        for subtest in breakdown._results["JetStream3.0"]["tests"][test]["tests"]:
            result[test + "-" + subtest] = breakdown._results["JetStream3.0"]["tests"][test]["tests"][subtest]["metrics"]["Time"][None]["current"]
    return result

def categoryJetStream3Breakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "ms"
    for test in breakdown._results["JetStream3.0"]["tests"].keys():
        for category in breakdown._results["JetStream3.0"]["tests"][test]["tests"]:
            if not category in result:
                result[category] = []
            result[category] += breakdown._results["JetStream3.0"]["tests"][test]["tests"][category]["metrics"]["Time"][None]["current"]
    return result

def motionMarkBreakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)

    result = {}
    result[unitMarker] = "pts"

    if detectMotionMark(jsonObject):
        name = "MotionMark"
    elif detectMotionMark1_1(jsonObject):
        name = "MotionMark-1.1"
    elif detectMotionMark1_1_1(jsonObject):
        name = "MotionMark-1.1.1"
    elif detectMotionMark1_2(jsonObject):
        name = "MotionMark-1.2"
    elif detectMotionMark1_3(jsonObject):
        name = "MotionMark-1.3"

    for test in breakdown._results[name]["tests"].keys():
        result[test] = breakdown._results[name]["tests"][test]["metrics"]["Score"][None]["current"]

    return result

def plt5Breakdown(jsonObject):
    nameMapping = {}

    for mappings in  jsonObject["urls"]:
        for key in mappings.keys():
            nameMapping[key] = mappings[key]

    result = {}
    result[unitMarker] = "ms"
    for test in jsonObject["iterations"][0]["warm"].keys():
        if test == "Geometric":
            continue
        result["warm--" + nameMapping[test]] = []
        result["cold--" + nameMapping[test]] = []

    for payload in jsonObject["iterations"]:
        warmTests = payload["warm"]
        coldTests = payload["cold"]
        for test in warmTests.keys():
            if test == "Geometric":
                continue
            result["warm--" + nameMapping[test]].append(warmTests[test]["Geometric"])
            result["cold--" + nameMapping[test]].append(coldTests[test]["Geometric"])

    return result

def competitivePLTBreakdown(jsonObject):
    result = collections.defaultdict(list)
    result[unitMarker] = "sec"

    safari_results = jsonObject.get('Safari', {})

    cold_results = safari_results.get('cold', {})
    warm_results = safari_results.get('warm', {})

    cold_link_results = cold_results.get('add-and-click-link', {})
    warm_link_results = warm_results.get('add-and-click-link', {})

    for site_to_times in cold_link_results.values():
        for site, times in site_to_times.items():
            result["cold--fmp--" + site].append(times['first_meaningful_paint'])
            result["cold--load-end--" + site].append(times['load_end'])

    for site_to_times in warm_link_results.values():
        for site, times in site_to_times.items():
            result["warm--fmp--" + site].append(times['first_meaningful_paint'])
            result["warm--load-end--" + site].append(times['load_end'])

    return result

def plum3Breakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "B"
    for test in breakdown._results["PLUM3-PhysFootprint"]["tests"].keys():
        result[test] = breakdown._results["PLUM3-PhysFootprint"]["tests"][test]["metrics"]["Allocations"]["Geometric"]["current"]
    return result

def ramificationBreakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "B"
    for test in breakdown._results["RAMification"]["tests"].keys():
        result[test] = breakdown._results["RAMification"]["tests"][test]["metrics"]["Allocations"]["Geometric"]["current"]
    return result

def detailedRAMificationBreakdown(jsonObject):
    breakdown = BenchmarkResults(jsonObject)
    result = {}
    result[unitMarker] = "B"
    for test in breakdown._results["RAMification"]["tests"].keys():
        for subtest in breakdown._results["RAMification"]["tests"][test]["tests"]:
            result[test + "-" + subtest] = breakdown._results["RAMification"]["tests"][test]["tests"][subtest]["metrics"]["Allocations"]["Geometric"]["current"]
    return result

def displayStr(value):
    return "{:.6f}".format(float(value))

def computeMultipleHypothesesSignificance(a, b):
    # This is using the Benjamini-Hochberg procedure based on False Discovery Rate
    # for computing signifcance in multiple hypothesis testing 
    # Read more here:
    # - https://en.wikipedia.org/wiki/False_discovery_rate
    # - https://www.stat.berkeley.edu/~mgoldman/Section0402.pdf
    # This is best used for independent variables. We know subtests aren't
    # fully independent, this it's a reasonable approximation.
    # We use this instead of Bonferroni because we control for almost the same
    # false positive error rate (marking as signficant when it's not), but with a much
    # lower false negative error rate (not marking something as signficant when it is).

    sortedPValues = []
    reversePValueMap = {}

    for key in a.keys():
        if key == unitMarker:
            continue

        (tStatistic, pValue) = stats.ttest_ind(a[key], b[key], equal_var=False)

        sortedPValues.append(pValue)
        if pValue not in reversePValueMap:
            reversePValueMap[pValue] = []
        reversePValueMap[pValue].append(key)

    sortedPValues.sort()
    assert sortedPValues[0] <= sortedPValues[-1]

    isSignificant = False
    result = {}
    rank = float(len(sortedPValues))
    for pValue in reversed(sortedPValues):
        assert rank >= 1.0
        threshold = (rank * .05) / float(len(sortedPValues))
        if pValue <= threshold:
            isSignificant = True
        
        assert len(reversePValueMap[pValue]) > 0
        for test in reversePValueMap[pValue]:
            result[test] = isSignificant

        rank = rank - 1.0

    return result


def dumpBreakdowns(a, b, sort_flag=False):
    nameLength = len("subtest")
    aLength = len(a[unitMarker])
    bLength = len(a[unitMarker])
    ratioLength = len("b / a")

    pValueHeader = "pValue (significance using False Discovery Rate)"
    pLength = len(pValueHeader)

    isSignificant = computeMultipleHypothesesSignificance(a, b)

    for key in a.keys():
        if key == unitMarker:
            continue
        nameLength = max(nameLength, len(key))
        aLength = max(aLength, len(displayStr(numpy.mean(a[key]))))
        bLength = max(bLength, len(displayStr(numpy.mean(b[key]))))
        ratioLength = max(ratioLength, len(displayStr(numpy.mean(b[key]) / numpy.mean(a[key]))))

        (tStatistic, pValue) = stats.ttest_ind(a[key], b[key], equal_var=False)
        significantStr = ""
        if isSignificant[key]:
            significantStr = " (significant)"
        pLength = max(pLength, len(displayStr(pValue)) + len(significantStr))

    aLength += 2
    bLength += 2
    nameLength += 2
    ratioLength += 2
    pLength += 2

    strings = []
    strings.append("|{key:^{nameLength}}|{aScore:^{aLength}} |{bScore:^{bLength}} |{compare:^{ratioLength}}|{pMarker:^{pLength}}|".format(key="subtest", aScore=a[unitMarker], bScore=b[unitMarker], nameLength=nameLength, aLength=aLength, bLength=bLength , compare="b / a", ratioLength=ratioLength, pMarker=pValueHeader, pLength=pLength))
    keys = [k for k in a.keys() if k != unitMarker]
    if sort_flag:
        keys.sort(key=lambda k: numpy.mean(b[k]) / numpy.mean(a[k]))
    else:
        keys.sort()
    for key in keys:
        aScore = numpy.mean(a[key])
        bScore = numpy.mean(b[key])

        (tStatistic, pValue) = stats.ttest_ind(a[key], b[key], equal_var=False)

        significantStr = ""
        if isSignificant[key]:
            significantStr = " (significant)"

        strings.append("| {key:{nameLength}}|{aScore:{aLength}} |{bScore:{bLength}} |{compare:{ratioLength}}| {pValue:<{pLength}}|".format(key=key, aScore=displayStr(aScore), bScore=displayStr(bScore), nameLength=nameLength - 1, aLength=aLength, bLength=bLength, ratioLength=ratioLength, compare=displayStr(bScore / aScore), pValue = displayStr(pValue) + significantStr, pLength=pLength - 1))

    maxLen = 0
    for s in strings:
        maxLen = max(maxLen, len(s))

    verticalSeparator = "-" * maxLen
    strings.insert(0, verticalSeparator)
    strings.insert(2, verticalSeparator)
    strings.append(verticalSeparator)

    print("\n")
    for s in strings:
        print(s)
    print("\n")

def writeCSV(a, b, fileName, sort_flag):
    strings = []
    result = ""
    result += "test_name, {}, {}, b_divided_by_a, pValue, is_significant_using_False_Discovery_Rate\n".format("a_in_" + a[unitMarker], "b_in_" + b[unitMarker])

    isSignificant = computeMultipleHypothesesSignificance(a, b)

    keys = [k for k in a.keys() if k != unitMarker]
    if sort_flag:
        keys.sort(key=lambda k: numpy.mean(b[k]) / numpy.mean(a[k]))
    else:
        keys.sort()
    for key in keys:
        aScore = numpy.mean(a[key])
        bScore = numpy.mean(b[key])

        (tStatistic, pValue) = stats.ttest_ind(a[key], b[key], equal_var=False)
        significantStr = "No"
        if isSignificant[key]:
            significantStr = "Yes"
        result += "{},{},{},{},{},{}\n".format(key, displayStr(aScore), displayStr(bScore), displayStr(bScore / aScore), displayStr(pValue), significantStr)

    f = open(fileName, "w")
    f.write(result)
    f.close()

def detectJetStream3(payload):
    return "JetStream3.0" in payload

def detectJetStream2(payload):
    return "JetStream2.0" in payload

def JetStream2Results(payload):
    assert detectJetStream2(payload)

    js = payload["JetStream2.0"]

    iterations = 0
    if "gaussian-blur" in js["tests"]:
        iterations = len(js["tests"]["gaussian-blur"]["metrics"]["Score"]["current"])
    else:
        obj = js["tests"]
        first_key = list(obj.keys())[0]
        iterations = len(obj[first_key]["metrics"]["Score"]["current"])

    results = []
    for i in range(iterations):
        scores = []
        for test in js["tests"].keys():
            scores.append(js["tests"][test]["metrics"]["Score"]["current"][i])
        geomean = stats.gmean(scores)
        
        results.append(geomean)

    return results

def JetStream3Results(payload):
    assert detectJetStream3(payload)

    js = payload["JetStream3.0"]

    iterations = 0
    if "gaussian-blur" in js["tests"]:
        iterations = len(js["tests"]["gaussian-blur"]["metrics"]["Score"]["current"])
    else:
        obj = js["tests"]
        first_key = list(obj.keys())[0]
        iterations = len(obj[first_key]["metrics"]["Score"]["current"])

    results = []
    for i in range(iterations):
        scores = []
        for test in js["tests"].keys():
            scores.append(js["tests"][test]["metrics"]["Score"]["current"][i])
        geomean = stats.gmean(scores)
        
        results.append(geomean)

    return results


def detectSpeedometer2(payload):
    return "Speedometer-2" in payload

def detectSpeedometer3(payload):
    return "Speedometer-3" in payload

def Speedometer2Results(payload):
    assert detectSpeedometer2(payload)
    results = []
    for arr in payload["Speedometer-2"]["metrics"]["Score"]["current"]:
        results.append(numpy.mean(arr))
    return results

def Speedometer3Results(payload):
    assert detectSpeedometer3(payload)
    results = []
    for arr in payload["Speedometer-3"]["metrics"]["Score"]["current"]:
        results.append(numpy.mean(arr))
    return results

def detectPLT5(payload):
    if "iterations" not in payload:
        return False
    iterations = payload["iterations"]
    if not isinstance(iterations, list):
        return False
    if not len(iterations):
        return False
    if "cold" not in iterations[0]:
        return False
    if "warm" not in iterations[0]:
        return False
    if "Geometric" not in iterations[0]:
        return False
    return True

def PLT5Results(payload):
    assert detectPLT5(payload)
    results = []
    for obj in payload["iterations"]:
        results.append(obj["Geometric"])
    return results

def detectCompetitivePLT(payload):
    return 'add-and-click-link' in payload.get('Safari', {}).get('cold', {})

def CompetitivePLTResults(payload):
    def calculate_time_for_run(run):
        # We geomean all FMP and load_end times together to produce a result for the run.
        fmp_vals = [obj['first_meaningful_paint'] for obj in run.values()]
        load_end_vals = [obj['load_end'] for obj in run.values()]
        return stats.gmean(fmp_vals + load_end_vals)

    safari_results = payload.get('Safari', {})

    cold_results = safari_results.get('cold', {})
    warm_results = safari_results.get('warm', {})

    cold_link_results = cold_results.get('add-and-click-link', {})
    warm_link_results = warm_results.get('add-and-click-link', {})

    cold_times = [calculate_time_for_run(run) for run in cold_link_results.values()]
    warm_times = [calculate_time_for_run(run) for run in warm_link_results.values()]

    return [stats.gmean((cold_time, warm_time)) for cold_time, warm_time in zip(cold_times, warm_times)]

def detectPLUM3(payload):
    return "PLUM3-PhysFootprint" in payload

def PLUM3Results(payload):
    assert detectPLUM3(payload)
    breakdown = BenchmarkResults(payload)
    return breakdown._results["PLUM3-PhysFootprint"]["metrics"]["Allocations"]["Arithmetic"]["current"]

def detectMotionMark(payload):
    return "MotionMark" in payload

def detectMotionMark1_1(payload):
    return "MotionMark-1.1" in payload

def detectMotionMark1_1_1(payload):
    return "MotionMark-1.1.1" in payload

def detectMotionMark1_2(payload):
    return "MotionMark-1.2" in payload

def detectMotionMark1_3(payload):
    return "MotionMark-1.3" in payload

def motionMarkResults(payload):
    assert any(validMotionMarkDetector(payload) for validMotionMarkDetector in [detectMotionMark, detectMotionMark1_1, detectMotionMark1_1_1, detectMotionMark1_2, detectMotionMark1_3])
    if detectMotionMark(payload):
        payload = payload["MotionMark"]
    elif detectMotionMark1_1(payload):
        payload = payload["MotionMark-1.1"]
    elif detectMotionMark1_1_1(payload):
        payload = payload["MotionMark-1.1.1"]
    elif detectMotionMark1_2(payload):
        payload = payload["MotionMark-1.2"]
    else:
        payload = payload["MotionMark-1.3"]
    testNames = list(payload["tests"].keys())
    numTests = len(payload["tests"][testNames[0]]["metrics"]["Score"]["current"])
    results = []
    for i in range(numTests):
        scores = []
        for test in testNames:
            scores.append(payload["tests"][test]["metrics"]["Score"]["current"][i])
        results.append(stats.gmean(scores))

    return results

def detectRAMification(payload):
    return "RAMification" in payload

def RAMificationResults(payload):
    assert detectRAMification(payload)
    breakdown = BenchmarkResults(payload)
    return breakdown._results["RAMification"]["metrics"]["Allocations"][None]["current"]

def detectBenchmark(payload):
    if detectJetStream3(payload):
        return JetStream3
    if detectJetStream2(payload):
        return JetStream2
    if detectSpeedometer2(payload):
        return Speedometer2
    if detectSpeedometer3(payload):
        return Speedometer3
    if detectPLT5(payload):
        return PLT5
    if detectCompetitivePLT(payload):
        return CompetitivePLT
    if detectPLUM3(payload):
        return PLUM3
    if detectMotionMark(payload):
        return MotionMark
    if detectMotionMark1_1(payload):
        return MotionMark1_1
    if detectMotionMark1_1_1(payload):
        return MotionMark1_1
    if detectMotionMark1_2(payload):
        return MotionMark1_2
    if detectMotionMark1_3(payload):
        return MotionMark1_3
    if detectRAMification(payload):
        return RAMification
    return None

def biggerIsBetter(benchmarkType):
    if benchmarkType in [JetStream2, JetStream3, Speedometer2, Speedometer3, MotionMark, MotionMark1_1, MotionMark1_1_1, MotionMark1_2, MotionMark1_3]:
        return True
    elif benchmarkType in [PLT5, CompetitivePLT, PLUM3, RAMification]:
        return False
    else:
        raise Exception('An unknown benchmark type was passed into biggerIsBetter: {}. It should not be possible to hit this.'.format(benchmarkType))

def ttest(benchmarkType, a, b):
    # We use two-tailed Welch's
    (tStatistic, pValue) = stats.ttest_ind(a, b, equal_var=False)
    aMean = numpy.mean(a)
    bMean = numpy.mean(b)
    print("a mean = {:.5f}".format(aMean))
    print("b mean = {:.5f}".format(bMean))

    print("pValue = {:.10f}".format(pValue))

    if biggerIsBetter(benchmarkType):
        print("(Bigger means are better.)")
        if aMean > bMean:
            print("{:.3f} times worse".format((aMean / bMean)))
        else:
            print("{:.3f} times better".format((bMean / aMean)))
    else:
        print("(Smaller means are better.)")
        if aMean > bMean:
            print("{:.3f} times better".format((aMean / bMean)))
        else:
            print("{:.3f} times worse".format((bMean / aMean)))

    if pValue <= 0.05:
        print("Results ARE significant")
    else:
        print("Results ARE NOT significant")

def getOptions():
    parser = argparse.ArgumentParser(description="Compare two WebKit benchmark results. Pass in at least two JSON result files to compare them. This script prints the pValue along with the magnitude of the change. If more than one JSON is passed as a/b they will be merged when computing the breakdown.")

    parser.add_argument("-a",
        type=str,
        required=True,
        nargs='+',
        action="append",
        help="a JSONs of a/b. Path to JSON results file. Takes multiple values and can be passed multiple times.")

    parser.add_argument("-b",
        type=str,
        required=True,
        nargs='+',
        action="append",
        help="b JSONs of a/b. Path to JSON results file. Takes multiple values and can be passed multiple times.")

    parser.add_argument("--csv",
        type=str,
        required=False,
        help="Path to write a csv file containing subtest breakdown.")

    parser.add_argument("--breakdown", action="store_true",
        default=False, help="Print a per subtest breakdown.")

    parser.add_argument("--detailed-breakdown", action="store_true",
        default=False, help="Print a detailed breakdown per subtest.")

    parser.add_argument("--category-breakdown", action="store_true",
        default=False, help="Print a breakdown per category. (e.g. startup, average, worst)")

    parser.add_argument("--sort", action="store_true",
        default=False, help="Sort the tests/sub-tests by b / a.")

    return parser.parse_known_args()[0]


def main():
    args = getOptions()

    # Flatten the list of lists of JSON files.
    a = itertools.chain.from_iterable(args.a)
    b = itertools.chain.from_iterable(args.b)

    a = mergeJSONs(list(map(readJSONFile, a)))
    b = mergeJSONs(list(map(readJSONFile, b)))

    typeA = detectBenchmark(a)
    typeB = detectBenchmark(b)

    if typeA != typeB:
        print("-a and -b are not the same benchmark. a={} b={}".format(typeA, typeB))
        sys.exit(1)

    if not (typeA and typeB):
        print("Unknown benchmark type. a={} b={}".format(typeA, typeB))
        sys.exit(1)
    
    if typeA == JetStream2:
        if args.detailed_breakdown:
            dumpBreakdowns(detailedJetStream2Breakdown(a), detailedJetStream2Breakdown(b), args.sort)
        if args.category_breakdown:
            dumpBreakdowns(categoryJetStream2Breakdown(a), categoryJetStream2Breakdown(b), args.sort)
        if args.breakdown:
            dumpBreakdowns(jetStream2Breakdown(a), jetStream2Breakdown(b), args.sort)

        ttest(typeA, JetStream2Results(a), JetStream2Results(b))

        if args.csv:
            writeCSV(jetStream2Breakdown(a), jetStream2Breakdown(b), args.csv, args.sort)
    elif typeA == JetStream3:
        if args.detailed_breakdown:
            dumpBreakdowns(detailedJetStream3Breakdown(a), detailedJetStream3Breakdown(b), args.sort)
        if args.category_breakdown:
            dumpBreakdowns(categoryJetStream3Breakdown(a), categoryJetStream3Breakdown(b), args.sort)
        if args.breakdown:
            dumpBreakdowns(jetStream3Breakdown(a), jetStream3Breakdown(b), args.sort)

        ttest(typeA, JetStream3Results(a), JetStream3Results(b))

        if args.csv:
            writeCSV(jetStream3Breakdown(a), jetStream3Breakdown(b), args.csv, args.sort)
    elif typeA == Speedometer2:
        if args.detailed_breakdown:
            dumpBreakdowns(speedometer2BreakdownSyncAsync(a), speedometer2BreakdownSyncAsync(b), args.sort)
        if args.breakdown:
            dumpBreakdowns(speedometer2Breakdown(a), speedometer2Breakdown(b), args.sort)

        ttest(typeA, Speedometer2Results(a), Speedometer2Results(b))

        if args.csv:
            writeCSV(speedometer2Breakdown(a), speedometer2Breakdown(b), args.csv, args.sort)

    elif typeA == Speedometer3:
        if args.detailed_breakdown:
            dumpBreakdowns(speedometer3BreakdownSyncAsync(a), speedometer3BreakdownSyncAsync(b), args.sort)
        if args.breakdown:
            dumpBreakdowns(speedometer3Breakdown(a), speedometer3Breakdown(b), args.sort)

        ttest(typeA, Speedometer3Results(a), Speedometer3Results(b))

        if args.csv:
            writeCSV(speedometer3Breakdown(a), speedometer3Breakdown(b), args.csv, args.sort)
    elif any(typeA == validMotionMarkTest for validMotionMarkTest in [MotionMark, MotionMark1_1, MotionMark1_1_1, MotionMark1_2, MotionMark1_3]):
        if args.breakdown:
            dumpBreakdowns(motionMarkBreakdown(a), motionMarkBreakdown(b), args.sort)

        ttest(typeA, motionMarkResults(a), motionMarkResults(b))

        if args.csv:
            writeCSV(motionMarkBreakdown(a), motionMarkBreakdown(b), args.csv, args.sort)
    elif typeA == PLT5:
        if args.breakdown:
            dumpBreakdowns(plt5Breakdown(a), plt5Breakdown(b), args.sort)

        ttest(typeA, PLT5Results(a), PLT5Results(b))

        if args.csv:
            writeCSV(plt5Breakdown(a), plt5Breakdown(b), args.csv, args.sort)
    elif typeA == CompetitivePLT:
        if args.breakdown:
            dumpBreakdowns(competitivePLTBreakdown(a), competitivePLTBreakdown(b), args.sort)

        ttest(typeA, CompetitivePLTResults(a), CompetitivePLTResults(b))

        if args.csv:
            writeCSV(competitivePLTBreakdown(a), competitivePLTBreakdown(b), args.csv, args.sort)
    elif typeA == PLUM3:
        if args.breakdown:
            dumpBreakdowns(plum3Breakdown(a), plum3Breakdown(b), args.sort)

        ttest(typeA, PLUM3Results(a), PLUM3Results(b))

        if args.csv:
            writeCSV(plum3Breakdown(a), plum3Breakdown(b), args.csv)
    elif typeA == RAMification:
        if args.detailed_breakdown:
            dumpBreakdowns(detailedRAMificationBreakdown(a), detailedRAMificationBreakdown(b), args.sort)
        if args.breakdown:
            dumpBreakdowns(ramificationBreakdown(a), ramificationBreakdown(b), args.sort)

        ttest(typeA, RAMificationResults(a), RAMificationResults(b))

        if args.csv:
            writeCSV(ramificationBreakdown(a), ramificationBreakdown(b), args.csv, args.sort)
    else:
        print("Unknown benchmark type")
        sys.exit(1)


if __name__ == "__main__":
    main()