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  /frameworks/base/media/mca/filterfw/native/core/
statistics.h 31 float Mean() const { return mean_; }
  /art/runtime/base/
histogram.h 28 // Histogram analysis goes beyond simple mean and standard deviation to provide
53 double Mean() const;
histogram-inl.h 126 template <class Value> inline double Histogram<Value>::Mean() const {
166 TimeUnit unit = GetAppropriateTimeUnit(Mean() * kAdjust);
169 os << "Avg: " << FormatDuration(Mean() * kAdjust, unit) << " Max: ";
histogram_test.cc 39 double mean; local
43 mean = hist->Mean();
44 EXPECT_EQ(mean, 50);
50 mean = hist->Mean();
51 EXPECT_EQ(20.5, mean);
  /external/opencv/cxcore/src/
cxmean.cpp 46 * Mean value over the region *
165 mean[0] = scale*(double)tmp##0
171 mean[0] = t0; \
172 mean[1] = t1
179 mean[0] = t0; \
180 mean[1] = t1; \
181 mean[2] = t2
187 mean[0] = t0; \
188 mean[1] = t1; \
191 mean[2] = t0;
384 CvScalar mean = {{0,0,0,0}}; local
    [all...]
  /external/chromium_org/chrome/test/functional/
perf.py 81 avg = Mean(values)
88 def Mean(values):
89 """Returns the arithmetic mean of |values|."""
96 """Returns the geometric mean of |values|."""
101 return math.exp(Mean([math.log(x) for x in values]))
448 autotest_value = Mean(value)
602 logging.info(' Average: %f %s', Mean(values), units)
    [all...]
  /external/chromium_org/third_party/WebKit/PerformanceTests/Dromaeo/resources/dromaeo/web/
webrunner.js 170 // Make Mean
171 results.mean = results.sum / num;
182 results.variance += Math.pow(times[i] - results.mean, 2);
189 // Compute Standard Errors Mean
193 results.error = ((results.sem / results.mean) * 100) || 0;
472 runs[data.id].mean = 0;
490 results[curID].total[run] = {max:0, mean:0, median:0, min:0, deviation:0, error:0, num:0};
494 result.error = ((((result.deviation / Math.sqrt(result.runs)) * tDistribution) / result.mean) * 100) || 0;
497 var error = (parseFloat(result.error) / 100) * parseFloat(result.mean);
505 } else if ( type == "mean" ) {
    [all...]
  /external/chromium_org/tools/
bisect-perf-regression.py 157 """Calculates the truncated mean of a set of values.
165 The truncated mean as a float.
198 mean = CalculateTruncatedMean(v, 0.0)
199 variances = [float(x) - mean for x in v]
    [all...]

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