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"func": lambda x: fnumber(x.max()),
"format": self._float_format,
cell = None
pair = self.stats.get_pair(i, j)
rel_diff = None
if property is None:
popover.content = r"""
Geometric mean of the first means relative to the second means:
\[\sqrt[\|properties\|]{
\prod_{p \in \text{properties}}
\frac{\overline{\text{first[p]}}}{
\overline{\text{second[p]}}}}\]
<p>Using the more widely known arithmetic mean would be like
<a href="http://ece.uprm.edu/~nayda/Courses/Icom6115F06/Papers/paper4.pdf?origin=publication_detail">
lying</a>.</p>
<p>The geometric standard deviation is <b>%s</b></p>.
""" % self._percent_format.format(pair.first_rel_to_second_std())
rel_diff = fnumber(pair.first_rel_to_second(), rel_deviation=pair.first_rel_to_second_std() - 1, is_percent=True)
popover.trigger = "hover click"
else:
pair = pair[property]
popover.content="""First mean relative to the second mean:
\\begin{align}
& \\frac{\\overline{\\text{first[%s]}}}{\\overline{\\text{second[%s]}}} \\\\
&= \\frac{%5.4f}{%5.4f}
\\end{align}
<p>The maximum standard deviation of both benchmarks relative to the mean of the second one is <b>%s</b>.</p>
""" % (property, property, pair.first.mean(), pair.second.mean(),
self._percent_format.format(pair.max_std_dev() / pair.second.mean()))
rel_diff = FNumber(pair.first_rel_to_second(), rel_deviation=pair.max_std_dev() / pair.second.mean(), is_percent=True)
cell = _Cell(self, content=str(rel_diff), popover=popover, color_class_obj=pair, show_click_on_info=True)
cell.modal_id = self._short_summary_modal(pair)
table[i, j] = cell
return table
"func": lambda x: fnumber(x.mean_diff(), abs_deviation=x.max_std_dev()),
"format": self._float_format
"func": lambda x: fnumber(x.std_dev_per_mean(), rel_deviation=x.sem() / (x.mean() ** 2),
is_percent=True),
"format": self._percent_format,
"func": lambda x: fnumber(x.mean_diff_ci(self.misc["alpha"])[1]),
"format": self._float_format,
"func": lambda x: fnumber(x.mean_diff_per_mean(), abs_deviation=x.max_std_dev() / x.first.mean(),
is_percent=True),
"format": self._percent_format,
"func": lambda x: fnumber((x.first.min() - x.second.min()) / x.max_std_dev(), is_percent=True),
"format": self._percent_format,
"func": lambda x: fnumber(x.sem(), abs_deviation=x.sem() / math.sqrt(x.observations())),
"format": self._float_format,
"func": lambda x: fnumber(x.mean_diff(), abs_deviation=x.max_std_dev()),
"format": self._float_format
"func": lambda x: fnumber(x.mean_diff_per_mean(), #rel_deviation=x.max_rel_std_dev(),
is_percent=True),
"format": self._percent_format,