Searched defs:mean (Results 101 - 125 of 182) sorted by relevance

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/external/webrtc/webrtc/modules/audio_coding/test/
H A Dutility.cc235 int16_t CircularBuffer::ArithMean(double& mean) { argument
240 mean = _sum / (double) _buffLen;
244 mean = _sum / (double) _idx;
/external/webrtc/webrtc/modules/audio_processing/intelligibility/
H A Dintelligibility_utils.cc43 complex<float> NewMean(complex<float> mean, complex<float> data, size_t count) { argument
44 return mean + (data - mean) / static_cast<float>(count);
47 void AddToMean(complex<float> data, size_t count, complex<float>* mean) { argument
48 (*mean) = NewMean(*mean, data, count);
163 complex<float> mean; local
168 mean = history_[i][history_cursor_];
175 complex<float> old_mean = mean;
177 mean
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/external/ImageMagick/Magick++/lib/
H A DStatistic.cpp357 double Magick::ChannelStatistics::mean() const function in class:Magick::ChannelStatistics
410 _mean(channelStatistics_->mean),
/external/ImageMagick/MagickCore/
H A Dstatistic.h41 mean, member in struct:_ChannelStatistics
H A Dthreshold.c177 % o bias: the mean bias.
308 mean;
333 mean=(double) (channel_sum[channel]/number_pixels+bias);
335 p[center+i] <= mean ? 0 : QuantumRange),q);
302 mean; local
/external/apache-commons-math/src/main/java/org/apache/commons/math/random/
H A DRandomDataImpl.java347 * The Poisson process (and hence value returned) is bounded by 1000 * mean.</li>
353 * @param mean mean of the Poisson distribution.
355 * @throws NotStrictlyPositiveException if {@code mean <= 0}.
357 public long nextPoisson(double mean) { argument
358 if (mean <= 0) {
359 throw new NotStrictlyPositiveException(LocalizedFormats.MEAN, mean);
365 if (mean < pivot) {
366 double p = FastMath.exp(-mean);
371 while (n < 1000 * mean) {
482 nextExponential(double mean) argument
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/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/
H A DSummaryStatistics.java67 /** SecondMoment is used to compute the mean and variance */
88 /** mean of values that have been added */
89 protected Mean mean = new Mean(); field in class:SummaryStatistics
109 /** Geometric mean statistic implementation - can be reset by setter. */
113 private StorelessUnivariateStatistic meanImpl = mean;
154 // If mean, variance or geomean have been overridden,
196 * Returns the mean of the values that have been added.
200 * @return the mean
203 if (mean == meanImpl) {
267 * Returns the geometric mean o
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/external/eigen/Eigen/src/Core/
H A DRedux.h445 * \sa trace(), prod(), mean()
456 /** \returns the mean of all coefficients of *this
462 DenseBase<Derived>::mean() const function in class:Eigen::DenseBase
479 * \sa sum(), mean(), trace()
H A DVectorwiseOp.h105 EIGEN_MEMBER_FUNCTOR(mean, (Size-1)*NumTraits<Scalar>::AddCost + NumTraits<Scalar>::MulCost);
401 /** \returns a row (or column) vector expression of the mean
404 * \sa DenseBase::mean() */
406 const MeanReturnType mean() const function in class:Eigen::VectorwiseOp
/external/harfbuzz_ng/test/shaping/
H A Dhb_test_tools.py258 def mean (self): member in class:Stats
276 return (self.mean () - population.mean ()) / population.stddev ()
/external/libopus/src/
H A Dmlp_train.c95 double mean = 0; local
98 mean += outputs[i*outDim+j];
99 mean /= nbSamples;
101 net->weights[nbLayers-2][j*(topo[nbLayers-2]+1)] = mean;
/external/libvpx/libvpx/vpx_dsp/
H A Davg.c169 int sse = 0, mean = 0, var; local
173 mean += diff; // mean: dynamic range 16 bits.
177 // (mean * mean): dynamic range 31 bits.
178 var = sse - ((mean * mean) >> (bwl + 2));
/external/libvpx/libvpx/vpx_dsp/x86/
H A Davg_intrin_sse2.c386 int16_t mean; local
421 mean = _mm_extract_epi16(sum, 0);
423 return _mm_cvtsi128_si32(sse) - ((mean * mean) >> (bwl + 2));
/external/ltp/testcases/misc/math/fptests/
H A Dfptest01.c134 dtw = 1. / nproc; /* mean process work time */
337 static double mean; variable
344 mean = m;
367 return (mean + stdev * x1);
371 return (mean + stdev * x2);
H A Dfptest02.c133 dtw = 1. / nproc; /* mean process work time */
318 static double mean; variable
327 mean = m;
342 return (mean + stdev * x1);
346 return (mean + stdev * x2);
/external/opencv/cv/src/
H A D_cvkdtree.hpp91 accum_type mean = 0; local
93 mean += deref(ctor(*k), j);
94 mean /= last - first;
97 accum_type diff = accum_type(deref(ctor(*k), j)) - mean;
/external/opencv/cxcore/src/
H A Dcxmeansdv.cpp314 mean[idx] = tmp = scale*(double)total##idx; \
378 CvSize size, double* mean, double* sdv ), \
379 (src, step, size, mean, sdv) ) \
413 CvSize size, double* mean, double* sdv ), \
414 (src, step, size, mean, sdv) ) \
438 double* mean, double* sdv ) \
473 int cn, int coi, double* mean, double* sdv )\
498 CvSize size, double* mean, double* sdv ), \
499 (src, step, mask, maskstep, size, mean, sdv))\
533 CvSize size, double* mean, doubl
678 CvScalar mean = {{0,0,0,0}}; local
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/external/tensorflow/tensorflow/examples/android/jni/object_tracking/
H A Dutils.h236 const float mean);
247 // Get mean.
267 const float mean) {
271 squared_sum += Square(values[i] - mean);
279 const float mean) {
282 (num_vals >= 8) ? ComputeStdDevNeon(values, num_vals, mean) :
284 ComputeStdDevCpu(values, num_vals, mean);
329 // Find the mean and then subtract so that the new mean is 0.0.
330 const float mean local
265 ComputeStdDevCpu(const float* const values, const int num_vals, const float mean) argument
277 ComputeStdDev(const float* const values, const int num_vals, const float mean) argument
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/external/tensorflow/tensorflow/python/ops/
H A Dmetrics_impl.py268 @tf_export('metrics.mean')
269 def mean(values, function
274 """Computes the (weighted) mean of the given values.
276 The `mean` function creates two local variables, `total` and `count`
278 returned as `mean` which is an idempotent operation that simply divides
282 `update_op` operation that updates these variables and returns the `mean`.
293 metrics_collections: An optional list of collections that `mean`
300 mean: A `Tensor` representing the current mean, the value of `total` divided
312 raise RuntimeError('tf.metrics.mean i
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/external/deqp/modules/gles2/performance/
H A Des2pDrawCallBatchingTests.cpp788 double mean; member in struct:deqp::gles2::Performance::__anon5023::Statistics
795 double mean = 0.0; local
798 mean += (double)samples[i];
800 mean /= (double)samples.size();
807 standardDeviation += (x - mean) * (x - mean);
817 stats.mean = mean;
880 log << TestLog::Message << "Batched samples; Count: " << m_batchedSamplesUs.size() << ", Mean: " << batchedStats.mean << "us, Standard deviation: " << batchedStats.standardDeviation << "us, Standard error of mean
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/external/deqp/modules/glshared/
H A DglsStateChangePerfTestCases.cpp58 double mean; member in struct:deqp::gls::__anon5527::ResultStats
74 result.mean = ((double)sum) / (double)values.size();
79 result.variance += (val - result.mean) * (val - result.mean);
546 log << TestLog::Message << "Interleaved mean: " << interleaved.mean << TestLog::EndMessage;
552 log << TestLog::Message << "Batched mean: " << batched.mean << TestLog::EndMessage;
558 log << TestLog::Message << "Batched/Interleaved mean ratio: " << (interleaved.mean/batche
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/external/fio/
H A Dgettime.c263 double delta, mean, S; local
268 S = delta = mean = 0.0;
271 delta = cycles[i] - mean;
273 mean += delta / (i + 1.0);
274 S += delta * (cycles[i] - mean);
295 if ((fmax(this, mean) - fmin(this, mean)) > S)
308 dprint(FD_TIME, "min=%llu, max=%llu, mean=%f, S=%f\n",
310 (unsigned long long) maxc, mean, S);
H A Diolog.h17 fio_fp64_t mean; member in struct:io_stat
/external/tensorflow/tensorflow/compiler/xla/
H A Dreference_util.cc409 const Array4D<float>& input, const Array4D<float>& mean,
413 *MapArray4D(input, mean, [](float a, float b) { return a - b; });
408 BatchNorm4D( const Array4D<float>& input, const Array4D<float>& mean, const Array4D<float>& var, const Array4D<float>& scale, const Array4D<float>& offset, float epsilon) argument
/external/tensorflow/tensorflow/compiler/xla/service/
H A Dbatchnorm_expander.cc232 auto mean = add(HloInstruction::CreateBinary( local
236 HloInstruction::CreateBroadcast(operand_shape, mean, {feature_index}));
244 feature_shape, HloOpcode::kMultiply, mean, mean));
283 auto tuple = HloInstruction::CreateTuple({shifted_normalized, mean, var});
317 HloInstruction* mean = batch_norm->mutable_operand(3); local
349 HloInstruction::CreateBroadcast(operand_shape, mean, {feature_index}));
406 // sum(output_grad * (activation - mean(activation))) * rsqrt(var + epsilon)
413 // (N * output_grad - sum(output_grad) - (activation - mean(activation)) *
414 // sum(output_grad * (activation - mean(activatio
432 HloInstruction* mean = batch_norm->mutable_operand(2); local
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