| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/moment/ |
| Skewness.java | 107 double variance = moment.m2 / (moment.n - 1); local
108 if (variance < 10E-20) {
113 ((n0 - 1) * (n0 -2) * FastMath.sqrt(variance) * variance);
172 final double variance = (accum - (accum2 * accum2 / length)) / (length - 1); local
179 accum3 /= variance * FastMath.sqrt(variance);
|
| /device/google/contexthub/firmware/src/algos/ |
| gyro_stillness_detect.c | 35 // Set the delta about the variance threshold for calculation
43 // Set the variance threshold parameter for the stillness
62 // online mean and variance statistics:
92 // Reset current window mean and variance.
112 // Online window mean and variance ("one-pass" accumulation).
143 // Update the final calculation of variance.
155 // Define the variance thresholds.
167 // Sensor variance exceeds the upper threshold (i.e., motion detected).
177 // Sensor variance is below the lower threshold (i.e., stillness detected).
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/ |
| SummaryStatistics.java | 26 import org.apache.commons.math.stat.descriptive.moment.Variance;
45 * default implementation for the variance can be overridden by calling
67 /** SecondMoment is used to compute the mean and variance */
91 /** variance of values that have been added */
92 protected Variance variance = new Variance(); field in class:SummaryStatistics
115 /** Variance statistic implementation - can be reset by setter. */
116 private StorelessUnivariateStatistic varianceImpl = variance;
154 // If mean, variance or geomean have been overridden
[all...] |
| StatisticalSummary.java | 33 * Returns the variance of the available values.
34 * @return The variance, Double.NaN if no values have been added
|
| /external/autotest/server/tests/netpipe/ |
| netpipe.py | 7 def run_once(self, pair, buffer, upper_bound, variance):
43 buffer, upper_bound, variance,
46 buffer, upper_bound, variance,
|
| /external/libmpeg2/common/arm/ |
| icv_variance_a9.s | 26 @* This file contains definitions of routines for variance caclulation
42 @* @brief computes variance of a 8x4 block
46 @* This functions computes variance of a 8x4 block
61 @* variance value in r0
|
| /external/libmpeg2/common/armv8/ |
| icv_variance_av8.s | 25 //* This file contains definitions of routines for variance caclulation
41 //* @brief computes variance of a 8x4 block
45 //* This functions computes variance of a 8x4 block
60 //* variance value in x0
|
| /external/libmpeg2/common/ |
| icv_variance.h | 26 * This file contains the functions to compute variance
|
| /external/libvpx/libvpx/vp9/common/ |
| vp9_mfqe.h | 23 // the current block and correlated block, the variance of the block
|
| /external/webrtc/webrtc/test/ |
| statistics.h | 25 double Variance() const;
|
| /external/webrtc/webrtc/voice_engine/test/auto_test/standard/ |
| video_sync_test.cc | 58 // Computes the standard deviation by first estimating the sample variance
66 float variance = 0; local
68 variance += (*start - mean) * (*start - mean) / (num_elements - 1);
70 return sqrt(variance);
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/clustering/ |
| KMeansPlusPlusClusterer.java | 27 import org.apache.commons.math.stat.descriptive.moment.Variance;
41 /** Split the cluster with largest distance variance. */
64 * algorithm iterations is to split the cluster with largest distance variance.
201 * Get a random point from the {@link Cluster} with the largest distance variance.
213 // compute the distance variance of the current cluster
215 final Variance stat = new Variance();
219 final double variance = stat.getResult(); local
221 // select the cluster with the largest variance
222 if (variance > maxVariance)
[all...] |
| /cts/apps/CameraITS/tests/scene1/ |
| test_dng_noise_model.py | 32 # defined as being within an absolute variance delta of 0.0005, or within
33 # 20% of the expected variance, whichever is larger; this is to allow the
77 # non-uniform lighting or vignetting doesn't affect the variance
87 # Calculate the expected variance based on the model, and the
88 # measured variance from the tile.
99 pylab.ylabel("Center patch variance")
|
| /external/chromium-trace/catapult/tracing/tracing/base/ |
| running_statistics.html | 64 get variance() {
75 return Math.sqrt(this.variance);
91 // and variance. See http://www.johndcook.com/blog/standard_deviation.
121 // Combine the mean and the variance using the formulas from
148 variance: this.variance_
159 result.variance_ = d.variance;
|
| /external/libvpx/libvpx/vp9/encoder/ |
| vp9_blockiness.c | 23 static int variance(int sum, int sum_squared, int size) { function
45 // by dividing the blockiness by the variance of the pixels on either side
70 var_0 = variance(sum_0, sum_sq_0, size);
71 var_1 = variance(sum_1, sum_sq_1, size);
102 var_0 = variance(sum_0, sum_sq_0, size);
103 var_1 = variance(sum_1, sum_sq_1, size);
|
| /frameworks/base/packages/SystemUI/src/com/android/systemui/classifier/ |
| AnglesClassifier.java | 26 * A classifier which calculates the variance of differences between successive angles in a stroke.
30 * previously calculated angle. Then it calculates the variance of the differences from a stroke.
36 * angle is. It calculates the angle variance of the two parts and sums them up. The reason the
39 * final result is the minimum of angle variance of the whole stroke and the sum of angle variances
144 // the angle variance so far and start to count the values for the angle
145 // variance of the second part.
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/regression/ |
| AbstractMultipleLinearRegression.java | 25 import org.apache.commons.math.stat.descriptive.moment.Variance;
289 * Estimates the variance of the error.
291 * @return estimate of the error variance
317 * Calculates the beta variance of multiple linear regression in matrix
320 * @return beta variance
326 * Calculates the variance of the y values.
328 * @return Y variance
331 return new Variance().evaluate(Y.getData());
335 * <p>Calculates the variance of the error term.</p>
342 * @return error variance estimat
[all...] |
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/ |
| StatUtils.java | 25 import org.apache.commons.math.stat.descriptive.moment.Variance;
63 /** variance */
64 private static final Variance VARIANCE = new Variance();
301 * Returns the variance of the entries in the input array, or
304 * See {@link org.apache.commons.math.stat.descriptive.moment.Variance} for
312 * @return the variance of the values or Double.NaN if the array is empty
315 public static double variance(final double[] values) { method in class:StatUtils
316 return VARIANCE.evaluate(values)
339 public static double variance(final double[] values, final int begin, method in class:StatUtils
370 public static double variance(final double[] values, final double mean, method in class:StatUtils
397 public static double variance(final double[] values, final double mean) { method in class:StatUtils
[all...] |
| /external/opencv3/modules/flann/include/opencv2/flann/ |
| kmeans_index.h | 537 DistanceType variance; local
540 int clusterCount = getMinVarianceClusters(root_, clusters, numClusters, variance);
580 * The cluster variance.
582 DistanceType variance; member in struct:cvflann::KMeansIndex::KMeansNode
660 * Computes the statistics of a node (mean, radius, variance).
670 DistanceType variance = 0; local
681 variance += distance_(vec, ZeroIterator<ElementType>(), veclen_);
686 variance /= size_;
687 variance -= distance_(mean, ZeroIterator<ElementType>(), veclen_);
697 node->variance = variance
850 DistanceType variance = 0; local
1074 DistanceType variance = meanVariance - clusters[i]->variance*clusters[i]->size; local
[all...] |
| /external/webrtc/webrtc/common_audio/ |
| audio_converter_unittest.cc | 58 float variance = 0; local
64 variance += ref.channels()[i][j] * ref.channels()[i][j];
71 variance /= length;
73 variance -= mean * mean;
76 snr = 10 * std::log10(variance / mse);
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/inference/ |
| TTestImpl.java | 191 return t(StatUtils.mean(observed), mu, StatUtils.variance(observed),
235 * and <strong><code>var</code></strong> is the pooled variance estimate:
239 * with <strong><code>var1<code></strong> the variance of the first sample and
240 * <strong><code>var2</code></strong> the variance of the second sample.
256 StatUtils.variance(sample1), StatUtils.variance(sample2),
276 * <strong><code> var1</code></strong> is the variance of the first sample;
277 * <strong><code> var2</code></strong> is the variance of the second sample;
293 StatUtils.variance(sample1), StatUtils.variance(sample2)
[all...] |
| /hardware/intel/common/omx-components/videocodec/libvpx_internal/libvpx/vp9/encoder/ |
| vp9_variance.c | 21 void variance(const uint8_t *src_ptr, function
174 variance(src_ptr, source_stride, ref_ptr, recon_stride, 64, 32, &var, &avg);
231 variance(src_ptr, source_stride, ref_ptr, recon_stride, 32, 64, &var, &avg);
288 variance(src_ptr, source_stride, ref_ptr, recon_stride, 32, 16, &var, &avg);
345 variance(src_ptr, source_stride, ref_ptr, recon_stride, 16, 32, &var, &avg);
402 variance(src_ptr, source_stride, ref_ptr, recon_stride, 64, 64, &var, &avg);
415 variance(src_ptr, source_stride, ref_ptr, recon_stride, 32, 32, &var, &avg);
428 variance(src_ptr, source_stride, ref_ptr, recon_stride, 16, 16, &var, &avg);
441 variance(src_ptr, source_stride, ref_ptr, recon_stride, 8, 16, &var, &avg);
454 variance(src_ptr, source_stride, ref_ptr, recon_stride, 16, 8, &var, &avg)
[all...] |
| /cts/apps/CameraITS/tests/scene0/ |
| test_jitter.py | 31 MAX_VAR_FRAME_DELTA = 0.01 # variance of frame deltas
51 print "Variance:", var
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
| WeibullDistributionImpl.java | 61 /** Cached numerical variance */
64 /** Whether or not the numerical variance has been calculated */
320 * Calculates the variance.
322 * The variance is
326 * @return the variance
355 * Returns the variance of the distribution.
357 * @return the variance (possibly Double.POSITIVE_INFINITY as
372 * Invalidates the cached mean and variance.
|
| /external/opencv/cvaux/src/ |
| cvbgfg_gaussmix.cpp | 79 icvMatchTest(...) assumes what all color channels component exhibit the same variance
120 //Rw is the learning rate for weight and Rg is leaning rate for mean and variance
126 //The list is maintained in sorted order using w/sqrt(variance) as a key
132 //v[n+1] = v[n] + Rg*((x[n+1] - u[n])*(x[n+1] - u[n])) - v[n]) variance
206 bg_model->g_point[n].g_values[0].variance[m] = var_init;
214 bg_model->g_point[n].g_values[k].variance[m] = var_init;
390 var_threshold += g_point->g_values[k].variance[m];
420 sum_d2 += (d*d) / (g_point->g_values[k].variance[m] * g_point->g_values[k].variance[m]);
452 g_point->g_values[k].variance[m] = g_point->g_values[k].variance[m]
[all...] |
