opencv/modules/ts/misc/summary.py

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#!/usr/bin/env python
import testlog_parser, sys, os, xml, glob, re
from table_formatter import *
from optparse import OptionParser
numeric_re = re.compile("(\d+)")
cvtype_re = re.compile("(8U|8S|16U|16S|32S|32F|64F)C(\d{1,3})")
cvtypes = { '8U': 0, '8S': 1, '16U': 2, '16S': 3, '32S': 4, '32F': 5, '64F': 6 }
convert = lambda text: int(text) if text.isdigit() else text
keyselector = lambda a: cvtype_re.sub(lambda match: " " + str(cvtypes.get(match.group(1), 7) + (int(match.group(2))-1) * 8) + " ", a)
alphanum_keyselector = lambda key: [ convert(c) for c in numeric_re.split(keyselector(key)) ]
def getSetName(tset, idx, columns, short = True):
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if columns and len(columns) > idx:
prefix = columns[idx]
else:
prefix = None
if short and prefix:
return prefix
name = tset[0].replace(".xml","").replace("_", "\n")
if prefix:
return prefix + "\n" + ("-"*int(len(max(prefix.split("\n"), key=len))*1.5)) + "\n" + name
return name
if __name__ == "__main__":
if len(sys.argv) < 2:
print >> sys.stderr, "Usage:\n", os.path.basename(sys.argv[0]), "<log_name1>.xml [<log_name2>.xml ...]"
exit(0)
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parser = OptionParser()
parser.add_option("-o", "--output", dest="format", help="output results in text format (can be 'txt', 'html' or 'auto' - default)", metavar="FMT", default="auto")
parser.add_option("-m", "--metric", dest="metric", help="output metric", metavar="NAME", default="gmean")
parser.add_option("-u", "--units", dest="units", help="units for output values (s, ms (default), mks, ns or ticks)", metavar="UNITS", default="ms")
parser.add_option("-f", "--filter", dest="filter", help="regex to filter tests", metavar="REGEX", default=None)
parser.add_option("", "--module", dest="module", default=None, metavar="NAME", help="module prefix for test names")
parser.add_option("", "--columns", dest="columns", default=None, metavar="NAMES", help="comma-separated list of column aliases")
parser.add_option("", "--no-relatives", action="store_false", dest="calc_relatives", default=True, help="do not output relative values")
parser.add_option("", "--with-cycles-reduction", action="store_true", dest="calc_cr", default=False, help="output cycle reduction percentages")
parser.add_option("", "--with-score", action="store_true", dest="calc_score", default=False, help="output automatic classification of speedups")
parser.add_option("", "--show-all", action="store_true", dest="showall", default=False, help="also include empty and \"notrun\" lines")
parser.add_option("", "--match", dest="match", default=None)
parser.add_option("", "--match-replace", dest="match_replace", default="")
parser.add_option("", "--regressions-only", dest="regressionsOnly", default=None, metavar="X-FACTOR", help="show only tests with performance regressions not")
(options, args) = parser.parse_args()
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options.generateHtml = detectHtmlOutputType(options.format)
if options.metric not in metrix_table:
options.metric = "gmean"
if options.metric.endswith("%") or options.metric.endswith("$"):
options.calc_relatives = False
options.calc_cr = False
if options.columns:
options.columns = [s.strip().replace("\\n", "\n") for s in options.columns.split(",")]
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# expand wildcards and filter duplicates
files = []
seen = set()
for arg in args:
if ("*" in arg) or ("?" in arg):
flist = [os.path.abspath(f) for f in glob.glob(arg)]
flist = sorted(flist, key= lambda text: str(text).replace("M", "_"))
files.extend([ x for x in flist if x not in seen and not seen.add(x)])
else:
fname = os.path.abspath(arg)
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if fname not in seen and not seen.add(fname):
files.append(fname)
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# read all passed files
test_sets = []
for arg in files:
try:
tests = testlog_parser.parseLogFile(arg)
if options.filter:
expr = re.compile(options.filter)
tests = [t for t in tests if expr.search(str(t))]
if options.match:
tests = [t for t in tests if t.get("status") != "notrun"]
if tests:
test_sets.append((os.path.basename(arg), tests))
except IOError as err:
sys.stderr.write("IOError reading \"" + arg + "\" - " + str(err) + os.linesep)
except xml.parsers.expat.ExpatError as err:
sys.stderr.write("ExpatError reading \"" + arg + "\" - " + str(err) + os.linesep)
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if not test_sets:
sys.stderr.write("Error: no test data found" + os.linesep)
quit()
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# find matches
setsCount = len(test_sets)
test_cases = {}
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name_extractor = lambda name: str(name)
if options.match:
reg = re.compile(options.match)
name_extractor = lambda name: reg.sub(options.match_replace, str(name))
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for i in range(setsCount):
for case in test_sets[i][1]:
name = name_extractor(case)
if options.module:
name = options.module + "::" + name
if name not in test_cases:
test_cases[name] = [None] * setsCount
test_cases[name][i] = case
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# build table
getter = metrix_table[options.metric][1]
getter_score = metrix_table["score"][1]
if options.calc_relatives:
getter_p = metrix_table[options.metric + "%"][1]
if options.calc_cr:
getter_cr = metrix_table[options.metric + "$"][1]
tbl = table(metrix_table[options.metric][0])
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# header
tbl.newColumn("name", "Name of Test", align = "left", cssclass = "col_name")
i = 0
for set in test_sets:
tbl.newColumn(str(i), getSetName(set, i, options.columns, False), align = "center")
i += 1
metric_sets = test_sets[1:]
if options.calc_cr:
i = 1
for set in metric_sets:
tbl.newColumn(str(i) + "$", getSetName(set, i, options.columns) + "\nvs\n" + getSetName(test_sets[0], 0, options.columns) + "\n(cycles reduction)", align = "center", cssclass = "col_cr")
i += 1
if options.calc_relatives:
i = 1
for set in metric_sets:
tbl.newColumn(str(i) + "%", getSetName(set, i, options.columns) + "\nvs\n" + getSetName(test_sets[0], 0, options.columns) + "\n(x-factor)", align = "center", cssclass = "col_rel")
i += 1
if options.calc_score:
i = 1
for set in metric_sets:
tbl.newColumn(str(i) + "S", getSetName(set, i, options.columns) + "\nvs\n" + getSetName(test_sets[0], 0, options.columns) + "\n(score)", align = "center", cssclass = "col_name")
i += 1
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# rows
prevGroupName = None
needNewRow = True
lastRow = None
for name in sorted(test_cases.iterkeys(), key=alphanum_keyselector):
cases = test_cases[name]
if needNewRow:
lastRow = tbl.newRow()
if not options.showall:
needNewRow = False
tbl.newCell("name", name)
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groupName = next(c for c in cases if c).shortName()
if groupName != prevGroupName:
prop = lastRow.props.get("cssclass", "")
if "firstingroup" not in prop:
lastRow.props["cssclass"] = prop + " firstingroup"
prevGroupName = groupName
for i in range(setsCount):
case = cases[i]
if case is None:
tbl.newCell(str(i), "-")
if options.calc_relatives and i > 0:
tbl.newCell(str(i) + "%", "-")
if options.calc_cr and i > 0:
tbl.newCell(str(i) + "$", "-")
if options.calc_score and i > 0:
tbl.newCell(str(i) + "$", "-")
else:
status = case.get("status")
if status != "run":
tbl.newCell(str(i), status, color = "red")
if status != "notrun":
needNewRow = True
if options.calc_relatives and i > 0:
tbl.newCell(str(i) + "%", "-", color = "red")
if options.calc_cr and i > 0:
tbl.newCell(str(i) + "$", "-", color = "red")
if options.calc_score and i > 0:
tbl.newCell(str(i) + "S", "-", color = "red")
else:
val = getter(case, cases[0], options.units)
if options.calc_relatives and i > 0 and val:
valp = getter_p(case, cases[0], options.units)
else:
valp = None
if options.calc_cr and i > 0 and val:
valcr = getter_cr(case, cases[0], options.units)
else:
valcr = None
if options.calc_score and i > 0 and val:
val_score = getter_score(case, cases[0], options.units)
else:
val_score = None
if not valp or i == 0:
color = None
elif valp > 1.05:
color = "green"
elif valp < 0.95:
color = "red"
else:
color = None
if val:
needNewRow = True
tbl.newCell(str(i), formatValue(val, options.metric, options.units), val, color = color)
if options.calc_relatives and i > 0:
tbl.newCell(str(i) + "%", formatValue(valp, "%"), valp, color = color, bold = color)
if options.calc_cr and i > 0:
tbl.newCell(str(i) + "$", formatValue(valcr, "$"), valcr, color = color, bold = color)
if options.calc_score and i > 0:
tbl.newCell(str(i) + "S", formatValue(val_score, "S"), val_score, color = color, bold = color)
if not needNewRow:
tbl.trimLastRow()
if options.regressionsOnly:
for r in reversed(range(len(tbl.rows))):
delete = True
i = 1
for set in metric_sets:
val = tbl.rows[r].cells[len(tbl.rows[r].cells)-i].value
if val is not None and val < float(options.regressionsOnly):
delete = False
i += 1
if (delete):
tbl.rows.pop(r)
# output table
if options.generateHtml:
if options.format == "moinwiki":
tbl.htmlPrintTable(sys.stdout, True)
else:
htmlPrintHeader(sys.stdout, "Summary report for %s tests from %s test logs" % (len(test_cases), setsCount))
tbl.htmlPrintTable(sys.stdout)
htmlPrintFooter(sys.stdout)
else:
tbl.consolePrintTable(sys.stdout)
if options.regressionsOnly:
sys.exit(len(tbl.rows))