| /external/webrtc/webrtc/modules/video_processing/test/ |
| denoiser_test.cc | 47 TEST_F(VideoProcessingTest, Variance) {
57 // Compute the 16x8 variance of the 16x16 block.
|
| /test/suite_harness/common/util/src/com/android/compatibility/common/util/ |
| Stat.java | 70 double variance = sumOfSquares / (data.length - 1); local
71 double stddev = Math.sqrt(variance);
|
| /external/libevent/test/ |
| test-ratelim.c | 263 double variance; local
458 variance = total_sq_persec/cfg_n_connections - total_persec*total_persec/(cfg_n_connections*cfg_n_connections);
460 printf(" stddev: %f per second\n", sqrt(variance));
462 sqrt(variance) > cfg_stddev_tolerance) {
463 fprintf(stderr, "Connection variance out of bounds\n");
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| inverse_gamma_test.py | 166 self.assertEqual(inv_gamma.variance().get_shape(), (3,))
167 self.assertAllClose(inv_gamma.variance().eval(), expected_variances)
176 inv_gamma.variance().eval()
186 self.assertEqual(inv_gamma.variance().get_shape(), (3,))
187 self.assertAllClose(inv_gamma.variance().eval(), expected_variances)
|
| wishart_test.py | 46 """Compute Wishart variance for numpy scale matrix."""
108 self.assertAllEqual(wishart_var(df, scale), w.variance().eval())
153 # The Variance estimate uses the squares rather than outer-products
154 # because Wishart.Variance is the diagonal of the Wishart covariance
160 chol_w.variance().eval(), variance_estimate, rtol=0.05)
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| mixture_same_family.py | 60 gm.variance()
119 (e.g., mean, mode, variance) use the value "`NaN`" to indicate the
276 # Law of total variance: Var(Y) = E[Var(Y|X)] + Var(E[Y|X])
281 probs * self.components_distribution.variance(),
297 # Law of total variance: Var(Y) = E[Var(Y|X)] + Var(E[Y|X])
|
| inverse_gamma.py | 119 (e.g., mean, mode, variance) use the value "`NaN`" to indicate the
243 """Variance for inverse gamma is defined only for `concentration > 2`. If
261 message="variance undefined when any concentration <= 2"),
|
| /external/tensorflow/tensorflow/contrib/gan/python/features/python/ |
| virtual_batchnorm_impl.py | 56 variance.
63 # on 32-bit floats before converting the mean and variance back to fp16
118 those statistics for each example. We use mean square instead of variance,
147 We precompute 'square mean' instead of 'variance', because the square mean
157 epsilon: Small float added to variance to avoid dividing by zero.
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/inference/ |
| TTest.java | 29 * <li>Homoscedastic (equal variance assumption) or heteroscedastic
194 * and <strong><code>var</code></strong> is the pooled variance estimate:
198 * with <strong><code>var1<code></strong> the variance of the first sample and
199 * <strong><code>var2</code></strong> the variance of the second sample.
228 * <strong><code> var1</code></strong> is the variance of the first sample;
229 * <strong><code> var2</code></strong> is the variance of the second sample;
260 * <strong><code> var1</code></strong> is the variance of the first sample;
261 * <strong><code> var2</code></strong> is the variance of the second sample
295 * and <strong><code>var</code></strong> is the pooled variance estimate:
299 * with <strong><code>var1<code></strong> the variance of the first sample an
[all...] |
| /device/google/wahoo/ |
| media_codecs_performance.xml | 55 <!-- measured 98%:155-917 med:364/365 FLAKY(mn=132.7 < 150 - 956) variance:2.4 -->
59 <!-- measured 98%:79-351 med:278/277 FLAKY(mn=73.9 < 78 - 554) variance:2.1 -->
63 <!-- measured 98%:12-72 med:54/54 FLAKY(mn=12.1 < 13 - 108) variance:2.4 -->
69 <!-- measured 98%:150-1017 med:412/406 FLAKY(mn=126.9 < 147 - 1062) variance:2.6 -->
124 <!-- measured 98%:141-1306 med:155/156 FLAKY(78 - 682 < mx=1328.0) RG.VARIANCE:2.1 -->
128 <!-- measured 98%:92-723 med:353/336 FLAKY(77 - 672 < mx=744.6) variance:2.8 -->
145 <!-- measured 98%:172-1548 med:187/187 FLAKY(94 - 822 < mx=1579.8) RG.VARIANCE:2.1 -->
|
| /external/tensorflow/tensorflow/python/ops/ |
| nn_fused_batchnorm_test.py | 74 var = constant_op.constant(var_val, name='variance')
81 variance=var,
137 # the denominator in the formula to calculate variance, while
208 variance=pop_var,
224 variance=pop_var,
271 variance=pop_var,
312 variance=pop_var,
|
| /frameworks/native/services/sensorservice/ |
| Fusion.cpp | 38 * GYRO_VAR gives the measured variance of the gyro's output per
39 * Hz (or variance at 1 Hz). This is an "intrinsic" parameter of the gyro,
42 * The variance of gyro's output at a given sampling period can be
44 * variance(T) = GYRO_VAR / T
46 * The variance of the INTEGRATED OUTPUT at a given sampling period can be
237 // variance of integrated output at 1/dT Hz (random drift)
240 // variance of drift rate ramp
|
| /cts/tests/tests/transition/src/android/transition/cts/ |
| FadeTest.java | 269 * Finds the variance of the two sets of pixels, as well as the covariance of the windows. The
270 * return value is an array of doubles, the first is the variance of the first set of pixels,
271 * the second is the variance of the second set of pixels, and the third is the covariance.
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
| FDistributionImpl.java | 331 * Returns the variance of the distribution.
335 * the variance is
344 * @return the variance
|
| GammaDistributionImpl.java | 342 * Returns the variance.
345 * parameter <code>beta</code>, the variance is
348 * @return the variance
|
| HypergeometricDistributionImpl.java | 405 * Returns the variance.
409 * sample size <code>n</code>, the variance is
412 * @return the variance
|
| NormalDistributionImpl.java | 337 * Returns the variance.
340 * the variance is <code>s^2</code>
342 * @return the variance
|
| PoissonDistributionImpl.java | 332 * Returns the variance of the distribution.
334 * For mean parameter <code>p</code>, the variance is <code>p</code>
336 * @return the variance
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/moment/ |
| SemiVariance.java | 37 * and the "variance direction" (upside or downside) defaults to downside. The variance direction
331 * Sets the variance direction
|
| /external/tensorflow/tensorflow/compiler/xla/service/gpu/ |
| cudnn_batchnorm_thunk.cc | 83 const BufferAllocation::Slice& variance, float epsilon, int64 feature_index,
90 variance_(variance),
166 // batch mean, and batch variance. We want to make our descriptors based on
|
| /external/tensorflow/tensorflow/docs_src/programmers_guide/ |
| tensorboard_histograms.md | 140 # Make a normal distribution with shrinking variance
165 above. Now we also have a "shrinking variance" distribution. Side-by-side, they
188 # Make a normal distribution with shrinking variance
|
| /external/tensorflow/tensorflow/python/keras/_impl/keras/preprocessing/ |
| image_test.py | 41 variance = np.random.rand(img_w, img_h, 1) * (255 - 64)
42 imarray = np.random.rand(img_w, img_h, 3) * variance + bias
46 imarray = np.random.rand(img_w, img_h, 1) * variance + bias
|
| /external/tensorflow/tensorflow/python/ops/distributions/ |
| distribution.py | 66 "variance",
262 (e.g., mean, variance) of random variables (e.g, Bernoulli, Gaussian).
399 (e.g., mean, mode, variance) use the value "`NaN`" to indicate the
523 Stats return +/- infinity when it makes sense. E.g., the variance of a
527 undefined, then by definition the variance is undefined. E.g. the mean for
529 infinity), so the variance = E[(X - mean)**2] is also undefined.
935 raise NotImplementedError("variance is not implemented")
937 def variance(self, name="variance"): member in class:Distribution
938 """Variance
[all...] |
| /external/libvpx/libvpx/vp8/encoder/ |
| mcomp.c | 201 /* returns subpixel variance error function. */
414 /* "halfpix" horizontal variance */
426 /* "halfpix" horizontal variance */
440 /* "halfpix" vertical variance */
452 /* "halfpix" vertical variance */
471 /* "halfpix" horizontal/vertical variance */
478 /* "halfpix" horizontal/vertical variance */
484 /* "halfpix" horizontal/vertical variance */
491 /* "halfpix" horizontal/vertical variance */
710 /* "halfpix" horizontal variance */
[all...] |
| /device/google/contexthub/firmware/os/algos/calibration/sample_rate_estimator/ |
| sample_rate_estimator.h | 76 * distributed and drawn from a zero-mean normal distribution with variance
|
