| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/rank/ |
| Median.java | 23 * Returns the median of the available values. This is the same as the 50th percentile.
33 public class Median extends Percentile implements Serializable {
41 public Median() {
46 * Copy constructor, creates a new {@code Median} identical
49 * @param original the {@code Median} instance to copy
51 public Median(Median original) {
|
| /external/google-benchmark/test/ |
| statistics_gtest.cc | 15 TEST(StatisticsTest, Median) {
|
| /external/libcxx/utils/google-benchmark/test/ |
| statistics_gtest.cc | 15 TEST(StatisticsTest, Median) {
|
| /external/swiftshader/third_party/llvm-7.0/llvm/tools/llvm-xray/ |
| xray-graph.h | 46 double Median;
170 return {A.Count + B.Count, A.Min + B.Min, A.Median + B.Median,
179 return {A.Count - B.Count, A.Min - B.Min, A.Median - B.Median,
190 A.Median / B,
202 A.Median * B,
218 return {A.Count * B.Count, A.Min * B.Min, A.Median * B.Median,
226 return {A.Count / B.Count, A.Min / B.Min, A.Median / B.Median
[all...] |
| xray-account.cpp | 85 clEnumValN(SortField::MED, "med", "median function durations"),
224 double Median;
244 R.Median = Timings[MedianOff];
271 Row.Median /= CycleFrequency;
326 return LR.Median < RR.Median;
328 return LR.Median > RR.Median;
384 // - min, median, 90pct, 99pct, max: double precision, but we want to keep
401 OS << llvm::formatv(StatsFormat, FuncId, Count, Row.Min, Row.Median,
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| xray-graph.cpp | 74 "median function durations"),
99 "median function durations"),
124 "median function durations"),
149 "median function durations"),
259 S.Median = *(begin + MedianOff);
272 M.Median = std::max(M.Median, S.Median);
334 double TimeStat::*DoubleStatPtrs[] = {&TimeStat::Min, &TimeStat::Median,
356 double TimeStat::*DoubleStatPtrs[] = {&TimeStat::Min, &TimeStat::Median,
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| /external/tensorflow/tensorflow/core/lib/histogram/ |
| histogram.h | 63 // Return the median of the values in the histogram
64 double Median() const;
79 // Min: -3.0000 Median: 5.0000 Max: 1000.0000
125 double Median() const;
|
| histogram_test.cc | 69 TEST(Histogram, Median) {
74 double median = h.Median(); local
75 EXPECT_EQ(median, -0.5);
145 EXPECT_EQ(h.Median(), tsh.Median());
|
| histogram.cc | 116 double Histogram::Median() const { return Percentile(50.0); }
176 snprintf(buf, sizeof(buf), "Min: %.4f Median: %.4f Max: %.4f\n",
177 (num_ == 0.0 ? 0.0 : min_), Median(), max_);
253 double ThreadSafeHistogram::Median() const {
255 return histogram_.Median();
|
| /cts/apps/CtsVerifier/src/com/android/cts/verifier/audio/ |
| Util.java | 6 import org.apache.commons.math.stat.descriptive.rank.Median;
38 * Calculate median of data.
40 public static double median(double[] data) { method in class:Util
41 Median median = new Median(); local
42 median.setData(data);
43 return median.evaluate();
|
| /external/tensorflow/tensorflow/core/grappler/costs/ |
| robust_stats.cc | 24 // Given a sorted vector of values, calculate the median.
36 // Given a vector of values (sorted or not), calculate the median.
37 static double Median(std::vector<double> &&values) {
59 // Given a set of values, calculates the scaled Median Absolute Deviation (a
61 // median of the absolute deviations from the median, scaled by 1.4826. Its
63 // outlier values. Returns a pair<median, mad>.
66 double median = SortedMedian(sorted_values); local
68 // Next, we calculate the absolute deviations from the median,
69 // find the median of the resulting data, and scale by 1.4826
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| /external/syzkaller/vendor/golang.org/x/net/trace/ |
| histogram.go | 164 // Median returns the estimated median of the observed values.
165 func (h *histogram) median() int64 { func
263 Count, Median int64
316 Median: h.median(),
343 <td style="padding:0.25em">Median: {{.Median}}</td>
|
| /external/walt/docs/ |
| ScreenLatency.md | 21 Median screen response latencies (N=100):
|
| /external/walt/pywalt/pywalt/ |
| walt.py | 146 Prints out stats (min, median, max).
159 median = numpy.median(times)
160 stats = (times.min() / MS, median / MS, times.max() / MS, N)
161 self.median_latency = median
163 log('min=%.2fms, median=%.2fms, max=%.2fms N=%d' % stats)
164 if (median > 2):
165 print('ERROR: the median round trip is too high: %.2f ms' % (median / MS) )
488 print('Median tap-to-audio latency: %0.1f ms' % numpy.median(deltas)
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