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import sys
import json
from dbaccess import execQuery, database
from singlecontextbmstats import (
SingleContextBMStats, extractSingleContextBMStats)
import math
from statlib import stats
from misc import (
idToText, textToId, benchmarkToComponents, getContext, printJSONHeader)
class GetStats2:
def __init__(
self, host1, platform1, branch1, sha11, host2, platform2, branch2,
sha12, test_case_filter):
self.host1 = host1
self.platform1 = platform1
self.branch1 = branch1
self.sha11 = sha11
self.host2 = host2
self.platform2 = platform2
self.branch2 = branch2
self.sha12 = sha12
self.test_case_filter = test_case_filter
self.host1_id = textToId("host", host1)
self.platform1_id = textToId("platform", platform1)
self.branch1_id = textToId("branch", branch1)
self.sha11_id = textToId("sha1", sha11)
self.host2_id = textToId("host", host2)
self.platform2_id = textToId("platform", platform2)
self.branch2_id = textToId("branch", branch2)
self.sha12_id = textToId("sha1", sha12)
def execute(self):
self.overall_stats = self.computeOverallStats()
self.bmstats_list = self.computeBMStatsList()
self.per_bm_stats = []
log2fact = 1.0 / math.log(2)
median_improv_list = []
self.test_case_exists = {}
for bmstats1, bmstats2 in self.bmstats_list:
# assert bmstats1.metric_id == bmstats2.metric_id
# assert bmstats1.lower_is_better == bmstats2.lower_is_better
# assert bmstats1.benchmark_id == bmstats2.benchmark_id
s_median1 = s_median2 = s_median_improv = ""
s_rse1 = s_rse2 = s_rse_improv = ""
if bmstats1.nvalid > 0 and bmstats2.nvalid > 0:
s_median1 = str(bmstats1.median)
s_median2 = str(bmstats2.median)
if (bmstats1.median > 0 and bmstats2.median > 0):
if bmstats1.lower_is_better:
median_improv = (
math.log(bmstats1.median / float(bmstats2.median))
* log2fact)
else:
median_improv = (
math.log(bmstats2.median / float(bmstats1.median))
* log2fact)
s_median_improv = str(median_improv)
median_improv_list.append(median_improv)
if bmstats1.nvalid > 1 and not bmstats1.mean_is_zero:
s_rse1 = str(bmstats1.rse)
if bmstats2.nvalid > 1 and not bmstats2.mean_is_zero:
s_rse2 = str(bmstats2.rse)
if (bmstats1.nvalid > 1 and bmstats2.nvalid > 1 and
not bmstats1.mean_is_zero and not bmstats2.mean_is_zero):
s_rse_improv = str((bmstats1.rse - bmstats2.rse) / 100.0)
s_metric = idToText("metric", bmstats1.metric_id)
s_lower_is_better = "1" if bmstats1.lower_is_better else "0"
benchmark = idToText("benchmark", bmstats1.benchmark_id)
s_test_case, s_test_function, s_data_tag = (
benchmarkToComponents(benchmark))
# Register test case existence:
if not s_test_case in self.test_case_exists:
self.test_case_exists[s_test_case] = True
self.per_bm_stats.append(
[ s_median1,
s_median2,
s_median_improv,
s_rse1,
s_rse2,
s_rse_improv,
s_metric,
s_lower_is_better,
benchmark ]
)
# Overall stats:
self.s_mean_of_median_improvs = ""
self.s_perc_10_of_median_improvs = ""
self.s_perc_25_of_median_improvs = ""
self.s_perc_50_of_median_improvs = ""
self.s_perc_75_of_median_improvs = ""
self.s_perc_90_of_median_improvs = ""
self.s_better_than_fact_1_1_count = ""
self.s_worse_than_fact_inv_1_1_count = ""
self.nmedian_improvs = len(median_improv_list)
if self.nmedian_improvs > 0:
self.s_mean_of_median_improvs = str(stats.mean(median_improv_list))
self.s_perc_10_of_median_improvs = str(
self.valueForPercentile(median_improv_list, 10))
self.s_perc_25_of_median_improvs = str(
self.valueForPercentile(median_improv_list, 25))
self.s_perc_50_of_median_improvs = str(
self.valueForPercentile(median_improv_list, 50))
self.s_perc_75_of_median_improvs = str(
self.valueForPercentile(median_improv_list, 75))
self.s_perc_90_of_median_improvs = str(
self.valueForPercentile(median_improv_list, 90))
self.s_better_than_fact_1_1_count = str(
self.higherThanCount(
median_improv_list, math.log(1.1) * log2fact))
self.s_worse_than_fact_inv_1_1_count = str(
self.lowerThanCount(
median_improv_list, math.log(1.0 / 1.1) * log2fact))
self.writeOutput()
# Computes and returns a dictionary of overall statistics.
def computeOverallStats(self):
stats = {}
# 2 B DONE!
return stats
# Returns the value below which 'p' % of the observations
# in 'values' fall.
def valueForPercentile(self, values, p):
assert len(values) > 0
assert p >= 0 and p <= 100
if p == 100:
return max(values)
i = int(math.floor((len(values) - 1) * (p / 100.0) + 0.5))
i = min(max(i, 0), len(values) - 1)
values.sort()
return values[i]
# Returns the number of observations in 'values' that are lower than 'v'.
def lowerThanCount(self, values, v):
n = 0
for v_ in values:
if v_ < v:
n = n + 1;
return n
# Returns the number of observations in 'values' that are higher than 'v'.
def higherThanCount(self, values, v):
n = 0
for v_ in values:
if v_ > v:
n = n + 1;
return n
# Computes per-benchmark statistics. Returns an n-tuple of
# 2-tuples, each of which consists of the SingleContextBMStats objects for
# context 1 and 2 respectively.
def computeBMStatsList(self):
context1_id = getContext(
self.host1_id, self.platform1_id, self.branch1_id, self.sha11_id)
context2_id = getContext(
self.host2_id, self.platform2_id, self.branch2_id, self.sha12_id)
# Get all distinct benchmark/metric combinations matching both contexts
# into a 'benchmarks' list:
bmark_metrics = execQuery(
"SELECT DISTINCT benchmarkId, metricId"
" FROM result"
" WHERE contextId = %s"
" INTERSECT "
"SELECT DISTINCT benchmarkId, metricId"
" FROM result"
" WHERE contextId = %s"
#" LIMIT 10"
";",
(context1_id, context2_id)
)
bmstats_list = []
# Loop over benchmarks and compute stats for both contexts:
for benchmark_id, metric_id in bmark_metrics:
benchmark = idToText("benchmark", benchmark_id)
test_case, test_function, data_tag = (
benchmarkToComponents(benchmark))
if ((self.test_case_filter != None)
and (not test_case in self.test_case_filter)):
continue
bmstats1 = extractSingleContextBMStats(
context1_id, benchmark_id, metric_id)
bmstats2 = extractSingleContextBMStats(
context2_id, benchmark_id, metric_id)
bmstats_list.append(tuple([bmstats1, bmstats2]))
return tuple(bmstats_list)
def writeOutputAsJSON(self):
printJSONHeader()
json.dump({
'database': database(),
'host1': self.host1,
'platform1': self.platform1,
'branch1': self.branch1,
'sha11': self.sha11,
'host2': self.host2,
'platform2': self.platform2,
'branch2': self.branch2,
'sha12': self.sha12,
'per_bm_stats': self.per_bm_stats,
'nbenchmarks': len(self.bmstats_list),
'ntestcases': len(self.test_case_exists),
'nmedian_improvs': self.nmedian_improvs,
'mean_of_median_improvs': self.s_mean_of_median_improvs,
'perc_10_of_median_improvs': self.s_perc_10_of_median_improvs,
'perc_25_of_median_improvs': self.s_perc_25_of_median_improvs,
'perc_50_of_median_improvs': self.s_perc_50_of_median_improvs,
'perc_75_of_median_improvs': self.s_perc_75_of_median_improvs,
'perc_90_of_median_improvs': self.s_perc_90_of_median_improvs,
'better_than_fact_1_1_count': self.s_better_than_fact_1_1_count,
'worse_than_fact_inv_1_1_count':
self.s_worse_than_fact_inv_1_1_count
}, sys.stdout)
class GetStats2AsJSON(GetStats2):
def writeOutput(self):
self.writeOutputAsJSON()
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