| /external/libcxx/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/ |
| eval.pass.cpp | 62 double x_var = sqr(d.stddev());
|
| eval_param.pass.cpp | 64 double x_var = sqr(p.stddev());
|
| /external/libcxx/utils/google-benchmark/test/ |
| statistics_test.cc | 47 TEST(StatisticsTest, StdDev) {
|
| /external/tensorflow/tensorflow/core/kernels/ |
| parameterized_truncated_normal_op.h | 28 // Sample a truncated normal random variable, with mean, stddev, minval, and
|
| /external/tensorflow/tensorflow/docs_src/api_guides/python/ |
| constant_op.md | 45 norm = tf.random_normal([2, 3], mean=-1, stddev=4)
|
| /external/tensorflow/tensorflow/docs_src/programmers_guide/ |
| summaries_and_tensorboard.md | 92 with tf.name_scope('stddev'):
93 stddev = tf.sqrt(tf.reduce_mean(tf.square(var - mean)))
94 tf.summary.scalar('stddev', stddev)
|
| /external/tensorflow/tensorflow/python/profiler/internal/ |
| print_model_analysis_test.py | 59 initializer=init_ops.random_normal_initializer(stddev=0.001))
|
| /prebuilts/go/darwin-x86/src/runtime/ |
| hash_test.go | 111 stddev := math.Sqrt(expected)
112 if float64(collisions) > expected+SLOP*(3*stddev+1) {
113 t.Errorf("unexpected number of collisions: got=%d mean=%f stddev=%f", collisions, expected, stddev)
486 // find c such that Prob(mean-c*stddev < x < mean+c*stddev)^N > .9999
491 stddev := .5 * math.Sqrt(REP)
492 low := int(mean - c*stddev)
493 high := int(mean + c*stddev)
|
| /prebuilts/go/linux-x86/src/runtime/ |
| hash_test.go | 111 stddev := math.Sqrt(expected)
112 if float64(collisions) > expected+SLOP*(3*stddev+1) {
113 t.Errorf("unexpected number of collisions: got=%d mean=%f stddev=%f", collisions, expected, stddev)
486 // find c such that Prob(mean-c*stddev < x < mean+c*stddev)^N > .9999
491 stddev := .5 * math.Sqrt(REP)
492 low := int(mean - c*stddev)
493 high := int(mean + c*stddev)
|
| /prebuilts/ndk/r16/sources/cxx-stl/llvm-libc++/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/ |
| eval.pass.cpp | 62 double x_var = sqr(d.stddev());
|
| eval_param.pass.cpp | 64 double x_var = sqr(p.stddev());
|
| /external/webrtc/webrtc/base/ |
| virtualsocketserver.cc | 940 std::cout << "Mean = " << mean << " StdDev = "
959 static double Normal(double x, double mean, double stddev) {
960 double a = (x - mean) * (x - mean) / (2 * stddev * stddev);
961 return exp(-a) / (stddev * sqrt(2 * PI));
975 uint32_t stddev,
979 if (0 == stddev) {
983 if (mean >= 4 * static_cast<double>(stddev))
984 start = mean - 4 * static_cast<double>(stddev);
985 double end = mean + 4 * static_cast<double>(stddev);
[all...] |
| /cts/apps/CtsVerifier/src/com/android/cts/verifier/sensors/ |
| MagneticFieldMeasurementTestActivity.java | 102 * Deviation for each of the axes the Sensor reports data for. The StdDev is compared against
106 * the Sensor's sampled data indeed falls into a large StdDev.
|
| /external/antlr/antlr-3.4/runtime/CSharp2/Sources/Antlr3.Runtime/Antlr.Runtime.Misc/ |
| Stats.cs | 64 public static double Stddev(int[] X) {
77 public static double Stddev(List<int> X) {
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/moment/ |
| Kurtosis.java | 174 double stdDev = FastMath.sqrt(variance.getResult());
182 accum3 /= FastMath.pow(stdDev, 4.0d);
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| normal_conjugate_posteriors.py | 55 The known stddev parameter(s).
122 The known stddev parameter(s).
|
| /external/tensorflow/tensorflow/contrib/slim/python/slim/nets/ |
| alexnet.py | 49 trunc_normal = lambda stddev: init_ops.truncated_normal_initializer(0.0, stddev)
|
| overfeat.py | 45 trunc_normal = lambda stddev: init_ops.truncated_normal_initializer(0.0, stddev)
|
| /external/tensorflow/tensorflow/java/src/main/java/org/tensorflow/op/ |
| Scope.java | 143 * public static Stddev create(Scope scope, ...) {
145 * Scope group = scope.withSubScope("stddev");
|
| /external/tensorflow/tensorflow/python/keras/_impl/keras/ |
| initializers_test.py | 63 self._runner(keras.initializers.RandomNormal(mean=0, stddev=1, seed=153),
71 stddev=1,
|
| /tools/tradefederation/core/prod-tests/src/com/android/performance/tests/ |
| FioBenchmarkTest.java | 66 "read-slat-min", "read-slat-max", "read-slat-mean", "read-slat-stddev",
67 "read-clat-min", "read-clat-max", "read-clat-mean", "read-clat-stddev",
69 "read-bandwidth-stddev",
72 "write-slat-min", "write-slat-max", "write-slat-mean", "write-slat-stddev",
73 "write-clat-min", "write-clat-max", "write-clat-mean", "write-clat-stddev",
75 "write-bandwidth-mean", "write-bandwidth-stddev",
91 "read-slat-min", "read-slat-max", "read-slat-mean", "read-slat-stddev",
92 "read-clat-min", "read-clat-max", "read-clat-mean", "read-clat-stddev",
95 "read-lat-min", "read-lat-max", "read-lat-mean", "read-lat-stddev",
97 "read-bandwidth-stddev",
[all...] |
| /external/fio/tools/plot/ |
| fio2gnuplot | 234 stddev_file=open(gnuplot_output_dir+gnuplot_output_filename+'.stddev', 'w')
239 temporary_files.append(gnuplot_output_dir+gnuplot_output_filename+'.stddev')
255 # print "Disk%d [ min=%.2f max=%.2f avg=%.2f stddev=%.2f \n" % (disk,min(disk_perf[disk]),max(disk_perf[disk]),avg, standard_deviation)
273 global_file.write('stddev=%.2f\n' % standard_deviation)
276 #print "Global [ min=%.2f max=%.2f avg=%.2f stddev=%.2f \n" % (min(global_disk_perf),max(global_disk_perf),avg, standard_deviation)
291 generate_gnuplot_math_script("Standard Deviation of "+title,gnuplot_output_filename+'.stddev',mode,int(standard_deviation),gnuplot_output_dir,gpm_dir)
374 print ' - Available types are : min, max, avg, stddev'
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| mixture_test.py | 304 dev = dist.stddev()
308 dist_devs = [d.stddev() for d in dist.components]
313 # Manual computation of stddev.
324 # Perform stddev computation on a flattened batch.
347 dev = dist.stddev()
351 dist_devs = [d.stddev() for d in dist.components]
356 # Manual computation of stddev.
367 # Perform stddev computation on a flattened batch.
394 mix_dev = mixture_dist.stddev()
[all...] |
| /external/tensorflow/tensorflow/python/layers/ |
| normalization.py | 348 # stddev with the minibatch stddev early in training, and (2) compute
349 # the unbiased average stddev by dividing renorm_stddev by the weight.
434 stddev = math_ops.sqrt(variance + self.epsilon)
440 (1. - self.renorm_stddev_weight) * stddev)
442 r = stddev / mixed_renorm_stddev
447 stddev = array_ops.identity(stddev)
489 stddev)
[all...] |
| /external/v8/tools/ |
| callstats.py | 324 stddev = numpy.std(data, ddof=1)
330 'abs': t_bounds[1] * stddev / sqrt(N),
331 'low': average + t_bounds[0] * stddev / sqrt(N),
332 'high': average + t_bounds[1] * stddev / sqrt(N)
335 stddev = 0
337 if abs(stddev) > 0.0001 and abs(average) > 0.0001:
338 ci['perc'] = t_bounds[1] * stddev / sqrt(N) / average * 100
342 'stddev': stddev, 'min': low, 'max': high, 'ci': ci }
|
