def format(self, results):
self.open_output()
for r in results:
self.write("Summary of %s test run " % r.meta('NAME'))
if r.meta('TITLE'):
self.write("'%s' (at %s)" % (r.meta('TITLE'), r.meta("TIME")))
else:
self.write("at %s" % r.meta("TIME"))
self.write(":\n\n")
if 'FROM_COMBINER' in r.meta():
m = {}
else:
m = r.meta().get("SERIES_META", {})
txtlen = max([len(n) for n in r.series_names])
unit_len = max((len(s['units']) for s in
self.settings.DATA_SETS.values()))
self.write("{spc:{txtlen}s} {avg:>{width}s}"
" {med:>{width}s} {datapoints:>{lwidth}s}\n".format(
spc="", avg="avg", med="median",
datapoints="# data pts", txtlen=txtlen + 3,
width=self.COL_WIDTH,
lwidth=self.COL_WIDTH + unit_len))
for s in sorted(r.series_names):
self.write((" %-" + str(txtlen) + "s : ") % s)
d = [i for i in r.series(s) if i is not None]
median = mean = None
if s in m and 'MEAN_VALUE' in m[s]:
mean = m[s]['MEAN_VALUE']
elif not d:
self.write("No data.\n")
continue
units = self.settings.DATA_SETS[s]['units'] if s in \
self.settings.DATA_SETS else ''
if d and self.np is not None:
mean = self.np.mean(d) if not mean else mean
median = self.np.median(d)
elif d:
mean = sum(d) / len(d) if not mean else mean
median = sorted(d)[len(d) // 2]
if mean and units == 'bytes':
factor, units = format_bytes(max(mean, median))
mean /= factor
median /= factor
if mean is not None:
self.write("{0:{width}.2f} ".format(mean,
width=self.COL_WIDTH))
else:
self.write("{0:>{width}}".format("N/A", width=self.COL_WIDTH))
if median is not None:
self.write("{0:{width}.2f} {1}".format(median, units,
width=self.COL_WIDTH))
else:
self.write("{0:>{width}} {1}".format("N/A", units,
width=self.COL_WIDTH))
self.write("{0:{width}d}\n".format(len(d),
width=(self.COL_WIDTH +
unit_len - len(units))))
def format(self, results):
self.open_output()
for r in results:
self.write("Summary of %s test run " % r.meta('NAME'))
if r.meta('TITLE'):
self.write("'%s' (at %s)" % (r.meta('TITLE'), r.meta("TIME")))
else:
self.write("at %s" % r.meta("TIME"))
self.write(":\n\n")
if 'FROM_COMBINER' in r.meta():
m = {}
else:
m = r.meta().get("SERIES_META", {})
txtlen = max([len(n) for n in r.series_names])
unit_len = max(
(len(s['units']) for s in self.settings.DATA_SETS.values()))
self.write("{spc:{txtlen}s} {avg:>{width}s}"
" {med:>{width}s} {datapoints:>{lwidth}s}\n".format(
spc="",
avg="avg",
med="median",
datapoints="# data pts",
txtlen=txtlen + 3,
width=self.COL_WIDTH,
lwidth=self.COL_WIDTH + unit_len))
for s in sorted(r.series_names):
self.write((" %-" + str(txtlen) + "s : ") % s)
try:
d = [i[1] for i in r.raw_series(s) if i[1] is not None]
except KeyError:
d = None
if not d:
d = [i for i in r.series(s) if i is not None]
md = m.get(s, {})
units = (md.get('UNITS')
or self.settings.DATA_SETS.get(s, {}).get(
'units', ''))
mean = md.get('MEAN_VALUE')
median = md.get('RTT_MEDIAN') if units == 'ms' else None
if not mean and not d:
self.write("No data.\n")
continue
if d and self.np is not None:
mean = mean or self.np.mean(d)
median = median or self.np.median(d)
elif d:
mean = mean or sum(d) / len(d)
median = median or sorted(d)[len(d) // 2]
if mean and units == 'bytes':
factor, units = format_bytes(max(mean, median))
mean /= factor
median /= factor
if mean is not None:
self.write("{0:{width}.2f} ".format(mean,
width=self.COL_WIDTH))
else:
self.write("{0:>{width}}".format("N/A",
width=self.COL_WIDTH))
if median is not None:
self.write("{0:{width}.2f} {1}".format(
median, units, width=self.COL_WIDTH))
else:
self.write("{0:>{width}} {1}".format("N/A",
units,
width=self.COL_WIDTH))
self.write("{0:{width}d}\n".format(
len(d), width=(self.COL_WIDTH + unit_len - len(units))))
def format(self, results):
self.open_output()
for r in results:
self.write("\nSummary of %s test run from %s" % (r.meta('NAME'),
r.meta("TIME")))
if r.meta('TITLE'):
self.write("\n Title: '%s'" % r.meta('TITLE'))
if self.settings.DATA_CUTOFF:
self.write("\n Cut data to interval: [%.2f, %.2f]" %
self.settings.DATA_CUTOFF)
self.write("\n\n")
if 'FROM_COMBINER' in r.meta():
m = {}
else:
m = r.meta().get("SERIES_META", {})
txtlen = max([len(n) for n in r.series_names])
unit_len = max((len(s['units']) for s in
self.settings.DATA_SETS.values()))
self.write("{spc:{txtlen}s} {avg:>{width}s}"
" {med:>{width}s} {datapoints:>{lwidth}s}\n".format(
spc="", avg="avg", med="median",
datapoints="# data pts", txtlen=txtlen + 3,
width=self.COL_WIDTH,
lwidth=self.COL_WIDTH + unit_len))
self.make_combines(r, ['mean', 'median'])
for s in sorted(r.series_names):
self.write((" %-" + str(txtlen) + "s : ") % s)
try:
d = [i[1] for i in r.raw_series(s) if i[1] is not None]
except KeyError:
d = None
if not d:
d = [i for i in r.series(s) if i is not None]
md = m.get(s, {})
units = (md.get('UNITS') or
self.settings.DATA_SETS.get(s, {}).get('units', ''))
mean = self.get_res(s, 'mean')
median = self.get_res(s, 'median')
n = self.get_res(s, 'N')
is_computed = 'COMPUTED_LATE' in m.get(s, {})
if mean is None:
self.write("No data.\n")
continue
if mean and units == 'bytes':
factor, units = format_bytes(max(mean, median))
mean /= factor
median /= factor
if mean is not None:
self.write("{0:{width}.2f} ".format(mean,
width=self.COL_WIDTH))
else:
self.write("{0:>{width}}".format("N/A", width=self.COL_WIDTH))
if median is not None and not is_computed:
self.write("{0:{width}.2f} {1}".format(median, units,
width=self.COL_WIDTH))
else:
self.write("{0:>{width}} {1}".format("N/A", units,
width=self.COL_WIDTH))
self.write("{0:{width}d}\n".format(n,
width=(self.COL_WIDTH +
unit_len - len(units))))