| /external/guava/guava-tests/benchmark/com/google/common/math/ |
| D | StatsBenchmark.java | 37 double mean(double[] values) { in mean() method
47 double mean(double[] values) { in mean() method
61 double mean(double[] values) { in mean() method
62 double mean = values[0]; in mean() local
64 mean = mean + (values[i] - mean) / (i + 1); in mean()
66 return mean; in mean()
70 abstract double mean(double[] values); in mean() method in StatsBenchmark.MeanAlgorithm
74 private final double mean; field in StatsBenchmark.MeanAndVariance
77 MeanAndVariance(double mean, double variance) { in MeanAndVariance() argument
78 this.mean = mean; in MeanAndVariance()
[all …]
|
| /external/tensorflow/tensorflow/contrib/seq2seq/python/kernel_tests/ |
| D | attention_wrapper_test.py | 63 return ResultSummary(x.shape, x.dtype, x.mean())
265 shape=(5, 3, 6), dtype=dtype('float32'), mean=-0.0052250605),
267 shape=(5, 3), dtype=dtype('int32'), mean=1.4))
271 shape=(5, 9), dtype=dtype('float32'), mean=-0.0040092287),
273 shape=(5, 9), dtype=dtype('float32'), mean=-0.0020015112)),
275 shape=(5, 6), dtype=dtype('float32'), mean=-0.0052052638),
278 shape=(5, 8), dtype=dtype('float32'), mean=0.125),
280 shape=(5, 8), dtype=dtype('float32'), mean=0.125),
283 shape=(3, 5, 8), dtype=dtype('float32'), mean=0.12500001)
299 shape=(5, 3, 6), dtype=dtype('float32'), mean=-0.00597103),
[all …]
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
| D | ExponentialDistributionImpl.java | 44 private double mean; field in ExponentialDistributionImpl
53 public ExponentialDistributionImpl(double mean) { in ExponentialDistributionImpl() argument
54 this(mean, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); in ExponentialDistributionImpl()
64 public ExponentialDistributionImpl(double mean, double inverseCumAccuracy) { in ExponentialDistributionImpl() argument
66 setMeanInternal(mean); in ExponentialDistributionImpl()
77 public void setMean(double mean) { in setMean() argument
78 setMeanInternal(mean); in setMean()
90 this.mean = newMean; in setMeanInternal()
98 return mean; in getMean()
125 return FastMath.exp(-x / mean) / mean; in density()
[all …]
|
| D | NormalDistributionImpl.java | 50 private double mean = 0; field in NormalDistributionImpl
63 public NormalDistributionImpl(double mean, double sd){ in NormalDistributionImpl() argument
64 this(mean, sd, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); in NormalDistributionImpl()
76 public NormalDistributionImpl(double mean, double sd, double inverseCumAccuracy) { in NormalDistributionImpl() argument
78 setMeanInternal(mean); in NormalDistributionImpl()
96 return mean; in getMean()
105 public void setMean(double mean) { in setMean() argument
106 setMeanInternal(mean); in setMean()
114 this.mean = newMean; in setMeanInternal()
171 double x0 = x - mean; in density()
[all …]
|
| /external/tensorflow/tensorflow/python/framework/testdata/ |
| D | metrics_export_meta_graph.pb | 760 name: "mean/total/Initializer/zeros"
766 s: "loc:@mean/total"
798 name: "mean/total"
805 s: "loc:@mean/total"
845 name: "mean/total/Assign"
847 input: "mean/total"
848 input: "mean/total/Initializer/zeros"
860 s: "loc:@mean/total"
887 name: "mean/total/read"
889 input: "mean/total"
[all …]
|
| /external/tensorflow/tensorflow/compiler/tests/ |
| D | fused_batchnorm_test.py | 40 mean = x_sum / element_count
41 var = x_square_sum / element_count - mean * mean
42 normalized = (x - mean) / np.sqrt(var + epsilon)
43 return (normalized * scale + offset), mean, var
45 def _reference_grad(self, x, grad_y, scale, mean, var, epsilon, data_format): argument
57 grad_x = scale * (grad_y - np.mean(grad_y, axis=(0, 1, 2)) -
58 (x - mean) * np.mean(grad_y *
59 (x - mean), axis=(0, 1, 2)) /
62 grad_y * (x - mean) / np.sqrt(var + epsilon), axis=(0, 1, 2))
84 y, mean, variance = nn.fused_batch_norm(
[all …]
|
| /external/opencv/cxcore/src/ |
| D | cxmean.cpp | 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; \
192 mean[3] = t1
[all …]
|
| /external/libcxx/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/ |
| D | eval.pass.cpp | 47 double mean = std::accumulate(u.begin(), u.end(), in test1() local
54 double dbl = (u[i] - mean); in test1()
69 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in test1()
90 double mean = std::accumulate(u.begin(), u.end(), in test2() local
97 double dbl = (u[i] - mean); in test2()
112 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in test2()
133 double mean = std::accumulate(u.begin(), u.end(), in test3() local
140 double dbl = (u[i] - mean); in test3()
155 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in test3()
176 double mean = std::accumulate(u.begin(), u.end(), in test4() local
[all …]
|
| /external/libcxx/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/ |
| D | eval.pass.cpp | 47 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); in main() local
53 double dbl = (u[i] - mean); in main()
64 double x_mean = d.mean(); in main()
65 double x_var = d.mean(); in main()
68 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in main()
86 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); in main() local
92 double dbl = (u[i] - mean); in main()
103 double x_mean = d.mean(); in main()
104 double x_var = d.mean(); in main()
107 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in main()
[all …]
|
| D | eval_param.pass.cpp | 49 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); in main() local
55 double dbl = (u[i] - mean); in main()
66 double x_mean = p.mean(); in main()
67 double x_var = p.mean(); in main()
70 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in main()
90 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); in main() local
96 double dbl = (u[i] - mean); in main()
107 double x_mean = p.mean(); in main()
108 double x_var = p.mean(); in main()
111 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in main()
[all …]
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/random/ |
| D | UncorrelatedRandomVectorGenerator.java | 40 private final double[] mean; field in UncorrelatedRandomVectorGenerator
53 public UncorrelatedRandomVectorGenerator(double[] mean, in UncorrelatedRandomVectorGenerator() argument
56 if (mean.length != standardDeviation.length) { in UncorrelatedRandomVectorGenerator()
57 throw new DimensionMismatchException(mean.length, standardDeviation.length); in UncorrelatedRandomVectorGenerator()
59 this.mean = mean.clone(); in UncorrelatedRandomVectorGenerator()
73 mean = new double[dimension]; in UncorrelatedRandomVectorGenerator()
84 double[] random = new double[mean.length]; in nextVector()
86 random[i] = mean[i] + standardDeviation[i] * generator.nextNormalizedDouble(); in nextVector()
|
| D | CorrelatedRandomVectorGenerator.java | 67 private final double[] mean; field in CorrelatedRandomVectorGenerator
97 public CorrelatedRandomVectorGenerator(double[] mean, in CorrelatedRandomVectorGenerator() argument
103 if (mean.length != order) { in CorrelatedRandomVectorGenerator()
104 throw new DimensionMismatchException(mean.length, order); in CorrelatedRandomVectorGenerator()
106 this.mean = mean.clone(); in CorrelatedRandomVectorGenerator()
131 mean = new double[order]; in CorrelatedRandomVectorGenerator()
133 mean[i] = 0; in CorrelatedRandomVectorGenerator()
292 double[] correlated = new double[mean.length];
294 correlated[i] = mean[i];
|
| /external/drrickorang/LoopbackApp/app/src/main/java/org/drrickorang/loopback/ |
| D | PerformanceMeasurement.java | 73 double mean = computeMean(mBufferData); in measurePerformance() local
74 double standardDeviation = computeStandardDeviation(mBufferData, mean); in measurePerformance()
75 log("mean before discarding 99% data: " + mean); in measurePerformance()
77 log("stdev/mean before discarding 99% data: " + (standardDeviation / mean)); in measurePerformance()
88 log("percent difference between two means: " + (Math.abs(meanAfterDiscard - mean) / mean)); in measurePerformance()
234 double mean; in computeMean() local
236 mean = (double) sum / count; in computeMean()
238 mean = 0; in computeMean()
242 return mean; in computeMean()
250 private double computeStandardDeviation(int[] data, double mean) { in computeStandardDeviation() argument
[all …]
|
| /external/tensorflow/tensorflow/python/layers/ |
| D | normalization_test.py | 335 self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
341 mean = np.mean(np_inputs, axis=(0, 2))
344 self.assertAllClose(mean, moving_mean, atol=1e-2)
352 self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
375 self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
381 mean = np.mean(np_inputs, axis=(0, 1))
384 self.assertAllClose(mean, moving_mean, atol=1e-2)
392 self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
416 self.assertAlmostEqual(np.mean(normed_np_output), 0., places=1)
422 mean = np.mean(np_inputs, axis=(0, 2, 3))
[all …]
|
| /external/tensorflow/tensorflow/python/keras/_impl/keras/applications/ |
| D | imagenet_utils.py | 65 mean = [0.485, 0.456, 0.406]
77 mean = [103.939, 116.779, 123.68]
83 x[0, :, :] -= mean[0]
84 x[1, :, :] -= mean[1]
85 x[2, :, :] -= mean[2]
91 x[:, 0, :, :] -= mean[0]
92 x[:, 1, :, :] -= mean[1]
93 x[:, 2, :, :] -= mean[2]
99 x[..., 0] -= mean[0]
100 x[..., 1] -= mean[1]
[all …]
|
| /external/python/cpython3/Doc/library/ |
| D | statistics.rst | 41 :func:`mean` Arithmetic mean ("average") of data.
42 :func:`harmonic_mean` Harmonic mean of data.
70 .. function:: mean(data)
72 Return the sample arithmetic mean of *data* which can be a sequence or iterator.
74 The arithmetic mean is the sum of the data divided by the number of data
85 >>> mean([1, 2, 3, 4, 4])
87 >>> mean([-1.0, 2.5, 3.25, 5.75])
91 >>> mean([F(3, 7), F(1, 21), F(5, 3), F(1, 3)])
95 >>> mean([D("0.5"), D("0.75"), D("0.625"), D("0.375")])
100 The mean is strongly affected by outliers and is not a robust estimator
[all …]
|
| /external/libcxx/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/ |
| D | eval.pass.cpp | 48 double mean = std::accumulate(u.begin(), u.end(), in main() local
55 double dbl = (u[i] - mean); in main()
71 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in main()
89 double mean = std::accumulate(u.begin(), u.end(), in main() local
96 double dbl = (u[i] - mean); in main()
112 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in main()
130 double mean = std::accumulate(u.begin(), u.end(), in main() local
137 double dbl = (u[i] - mean); in main()
153 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in main()
171 double mean = std::accumulate(u.begin(), u.end(), in main() local
[all …]
|
| /external/guava/guava/src/com/google/common/math/ |
| D | DoubleMath.java | 390 private double mean = 0.0; field in DoubleMath.MeanAccumulator
396 mean += (value - mean) / count; in add()
399 double mean() { in mean() method in DoubleMath.MeanAccumulator
401 return mean; in mean()
410 public static double mean(double... values) { in mean() method in DoubleMath
415 return accumulator.mean(); in mean()
423 public static double mean(int... values) { in mean() method in DoubleMath
428 return accumulator.mean(); in mean()
437 public static double mean(long... values) { in mean() method in DoubleMath
442 return accumulator.mean(); in mean()
[all …]
|
| /external/libcxx/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/ |
| D | eval.pass.cpp | 48 D::result_type mean = std::accumulate(u.begin(), u.end(), in main() local
55 D::result_type dbl = (u[i] - mean); in main()
70 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in main()
88 D::result_type mean = std::accumulate(u.begin(), u.end(), in main() local
95 D::result_type dbl = (u[i] - mean); in main()
110 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in main()
128 D::result_type mean = std::accumulate(u.begin(), u.end(), in main() local
135 D::result_type dbl = (u[i] - mean); in main()
150 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in main()
168 D::result_type mean = std::accumulate(u.begin(), u.end(), in main() local
[all …]
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/moment/ |
| D | Variance.java | 252 Mean mean = new Mean(); in evaluate() local
253 double m = mean.evaluate(values, begin, length); in evaluate()
312 Mean mean = new Mean(); in evaluate() local
313 double m = mean.evaluate(values, weights, begin, length); in evaluate()
388 public double evaluate(final double[] values, final double mean, in evaluate() argument
401 dev = values[i] - mean; in evaluate()
441 public double evaluate(final double[] values, final double mean) { in evaluate() argument
442 return evaluate(values, mean, 0, values.length); in evaluate()
491 final double mean, final int begin, final int length) { in evaluate() argument
503 dev = values[i] - mean; in evaluate()
[all …]
|
| /external/clang/test/FixIt/ |
| D | typo.m | 12 …NSstring *str = @"A string"; // expected-error{{unknown type name 'NSstring'; did you mean 'NSStri…
50 herivar = a; // expected-error{{use of undeclared identifier 'herivar'; did you mean 'her_ivar'?}}
51 hisivar = a; // expected-error{{use of undeclared identifier 'hisivar'; did you mean 'his_ivar'?}}
52 …self->herivar = a; // expected-error{{'B' does not have a member named 'herivar'; did you mean 'he…
53 …self->hisivar = a; // expected-error{{'B' does not have a member named 'hisivar'; did you mean 'hi…
54 …// expected-error{{property 'hisprop' not found on object of type 'B *'; did you mean 'his_prop'?}}
55 …// expected-error{{property 'herprop' not found on object of type 'B *'; did you mean 'her_prop'?}}
56 … 0; // expected-error{{property 's_prop' not found on object of type 'B *'; did you mean 'sprop'?}}
64 [NSstring method:17]; // expected-error{{unknown receiver 'NSstring'; did you mean 'NSString'?}}
81 …// expected-error{{property 'valu' not found on object of type 'Collide *'; did you mean 'value'?}}
[all …]
|
| /external/guava/guava-tests/test/com/google/common/math/ |
| D | DoubleMathTest.java | 649 assertEquals(-1.375, DoubleMath.mean(1.1, -2.2, 4.4, -8.8), 1.0e-10); in testMean_doubleVarargs()
650 assertEquals(1.1, DoubleMath.mean(1.1), 1.0e-10); in testMean_doubleVarargs()
652 DoubleMath.mean(Double.NaN); in testMean_doubleVarargs()
657 DoubleMath.mean(Double.POSITIVE_INFINITY); in testMean_doubleVarargs()
665 assertEquals(-13.75, DoubleMath.mean(11, -22, 44, -88), 1.0e-10); in testMean_intVarargs()
666 assertEquals(11.0, DoubleMath.mean(11), 1.0e-10); in testMean_intVarargs()
671 assertEquals(-13.75, DoubleMath.mean(11L, -22L, 44L, -88L), 1.0e-10); in testMean_longVarargs()
672 assertEquals(11.0, DoubleMath.mean(11L), 1.0e-10); in testMean_longVarargs()
678 DoubleMath.mean(); in testMean_emptyVarargs()
686 assertEquals(-1.375, DoubleMath.mean(ImmutableList.of(1.1, -2.2, 4.4, -8.8)), 1.0e-10); in testMean_doubleIterable()
[all …]
|
| /external/libcxx/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/ |
| D | eval.pass.cpp | 47 double mean = std::accumulate(u.begin(), u.end(), in test1() local
54 double dbl = (u[i] - mean); in test1()
69 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in test1()
90 double mean = std::accumulate(u.begin(), u.end(), in test2() local
97 double dbl = (u[i] - mean); in test2()
112 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in test2()
133 double mean = std::accumulate(u.begin(), u.end(), in test3() local
140 double dbl = (u[i] - mean); in test3()
155 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in test3()
176 double mean = std::accumulate(u.begin(), u.end(), in test4() local
[all …]
|
| /external/libcxx/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/ |
| D | eval.pass.cpp | 47 double mean = std::accumulate(u.begin(), u.end(), in test1() local
54 double dbl = (u[i] - mean); in test1()
69 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in test1()
90 double mean = std::accumulate(u.begin(), u.end(), in test2() local
97 double dbl = (u[i] - mean); in test2()
112 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in test2()
133 double mean = std::accumulate(u.begin(), u.end(), in test3() local
140 double dbl = (u[i] - mean); in test3()
155 assert(std::abs((mean - x_mean) / x_mean) < 0.01); in test3()
176 double mean = std::accumulate(u.begin(), u.end(), in test4() local
[all …]
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | parameterized_truncated_normal_op_test.py | 40 mean = None variable in TruncatedNormalMoments
45 def __init__(self, mean, stddev, minval, maxval): argument
47 self.mean = np.double(mean)
69 dist = scipy.stats.norm(loc=self.mean, scale=self.stddev)
76 m = ((k - 1) * self.stddev**2 * m_k_minus_2 + self.mean * m_k_minus_1 -
112 def validateMoments(self, shape, mean, stddev, minval, maxval, seed=1618): argument
119 samples = random_ops.parameterized_truncated_normal(shape, mean, stddev,
124 expected_moments = TruncatedNormalMoments(mean, stddev, minval, maxval)
134 mean, argument
143 samples = random_ops.parameterized_truncated_normal(shape, mean, stddev,
[all …]
|