| /external/v8/tools/ |
| perf-to-html.py | 63 def __init__(self, test_name, count, hasScoreUnits, result, sigma,
66 self.sigma_ = float(sigma)
91 def sigma(self): member in class:Result
|
| /external/ImageMagick/MagickCore/ |
| effect.c | 111 % (sigma). For reasonable results, radius should be larger than sigma. Use a
117 % const double sigma,ExceptionInfo *exception)
126 % o sigma: the standard deviation of the Laplacian, in pixels.
132 const double sigma,ExceptionInfo *exception)
135 #define MagickSigma (fabs(sigma) < MagickEpsilon ? MagickEpsilon : sigma)
179 if (fabs(sigma) < MagickEpsilon)
196 gaussian_image=BlurImage(edge_image,radius,sigma,exception);
204 Create a set of kernels from maximum (radius,sigma) to minimum
2256 sigma, local
[all...] |
| geometry.h | 106 sigma, member in struct:_GeometryInfo
|
| constitute.c | 635 geometry_info.sigma=1.0;
637 if (geometry_info.sigma != 0)
638 next->resolution.x=geometry_info.rho/geometry_info.sigma;
645 geometry_info.sigma=1.0;
647 if (geometry_info.sigma != 0)
648 next->resolution.y=geometry_info.rho/geometry_info.sigma;
746 next->ticks_per_second=(ssize_t) floor(geometry_info.sigma+0.5);
751 next->ticks_per_second=(ssize_t) floor(geometry_info.sigma+0.5);
[all...] |
| /external/tensorflow/tensorflow/contrib/gan/python/eval/python/ |
| classifier_metrics_impl.py | 400 def trace_sqrt_product(sigma, sigma_v):
404 cannot just take _symmetric_matrix_square_root(sigma * sigma_v).
405 ('sigma' and 'sigma_v' are symmetric, but their product is not necessarily).
407 Let sigma = A A so A = sqrt(sigma), and sigma_v = B B.
408 We want to find trace(sqrt(sigma sigma_v)) = trace(sqrt(A A B B))
413 => eigenvalues(sqrt(sigma sigma_v)) = sqrt(eigenvalues(A B B A))
415 => trace(sqrt(sigma sigma_v)) = sum(eigenvalues(sqrt(sigma sigma_v)))
420 A = sqrt(sigma). Both sigma and A sigma_v A are symmetric, so we **can*
[all...] |
| classifier_metrics_test.py | 56 sigma = np.cov(real_imgs, rowvar=False)
58 sqcc = scp_linalg.sqrtm(np.dot(sigma, sigma_v))
60 trace = np.trace(sigma + sigma_v - 2 * sqcc)
65 def _expected_trace_sqrt_product(sigma, sigma_v):
66 return np.trace(scp_linalg.sqrtm(np.dot(sigma, sigma_v)))
|
| /external/ImageMagick/MagickWand/ |
| mogrify.c | 781 geometry_info.sigma=1.0;
783 geometry_info.sigma,exception);
805 geometry_info.sigma=1.0;
807 geometry_info.sigma,exception);
847 geometry_info.sigma=geometry_info.rho;
862 fmod(geometry_info.sigma,360.0))));
864 fmod(geometry_info.sigma,360.0)));
[all...] |
| /device/linaro/bootloader/edk2/AppPkg/Applications/Python/Python-2.7.10/Lib/ |
| random.py | 386 def normalvariate(self, mu, sigma):
389 mu is the mean, and sigma is the standard deviation.
392 # mu = mean, sigma = standard deviation
407 return mu + z*sigma
411 def lognormvariate(self, mu, sigma):
415 normal distribution with mean mu and standard deviation sigma.
416 mu can have any value, and sigma must be greater than zero.
419 return _exp(self.normalvariate(mu, sigma))
562 def gauss(self, mu, sigma):
565 mu is the mean, and sigma is the standard deviation. This is
[all...] |
| /device/linaro/bootloader/edk2/AppPkg/Applications/Python/Python-2.7.2/Lib/ |
| random.py | 380 def normalvariate(self, mu, sigma):
383 mu is the mean, and sigma is the standard deviation.
386 # mu = mean, sigma = standard deviation
401 return mu + z*sigma
405 def lognormvariate(self, mu, sigma):
409 normal distribution with mean mu and standard deviation sigma.
410 mu can have any value, and sigma must be greater than zero.
413 return _exp(self.normalvariate(mu, sigma))
560 def gauss(self, mu, sigma):
563 mu is the mean, and sigma is the standard deviation. This is
[all...] |
| /external/python/cpython2/Lib/ |
| random.py | 386 def normalvariate(self, mu, sigma):
389 mu is the mean, and sigma is the standard deviation.
392 # mu = mean, sigma = standard deviation
407 return mu + z*sigma
411 def lognormvariate(self, mu, sigma):
415 normal distribution with mean mu and standard deviation sigma.
416 mu can have any value, and sigma must be greater than zero.
419 return _exp(self.normalvariate(mu, sigma))
562 def gauss(self, mu, sigma):
565 mu is the mean, and sigma is the standard deviation. This i
[all...] |
| /external/python/cpython3/Lib/ |
| random.py | 394 def normalvariate(self, mu, sigma):
397 mu is the mean, and sigma is the standard deviation.
400 # mu = mean, sigma = standard deviation
415 return mu + z*sigma
419 def lognormvariate(self, mu, sigma):
423 normal distribution with mean mu and standard deviation sigma.
424 mu can have any value, and sigma must be greater than zero.
427 return _exp(self.normalvariate(mu, sigma))
570 def gauss(self, mu, sigma):
573 mu is the mean, and sigma is the standard deviation. This i
[all...] |
| /external/skia/resources/lua/ |
| slides_transitions.lua | 41 local sigma = sqr(1 - alpha) * 20
43 paint:setImageFilter(Sk.newBlurImageFilter(sigma, sigma))
|
| /external/skqp/platform_tools/android/apps/skqp/src/main/assets/resources/lua/ |
| slides_transitions.lua | 41 local sigma = sqr(1 - alpha) * 20
43 paint:setImageFilter(Sk.newBlurImageFilter(sigma, sigma))
|
| /external/skqp/resources/lua/ |
| slides_transitions.lua | 41 local sigma = sqr(1 - alpha) * 20
43 paint:setImageFilter(Sk.newBlurImageFilter(sigma, sigma))
|
| /prebuilts/gdb/darwin-x86/lib/python2.7/ |
| random.py | 380 def normalvariate(self, mu, sigma):
383 mu is the mean, and sigma is the standard deviation.
386 # mu = mean, sigma = standard deviation
401 return mu + z*sigma
405 def lognormvariate(self, mu, sigma):
409 normal distribution with mean mu and standard deviation sigma.
410 mu can have any value, and sigma must be greater than zero.
413 return _exp(self.normalvariate(mu, sigma))
556 def gauss(self, mu, sigma):
559 mu is the mean, and sigma is the standard deviation. This i
[all...] |
| /prebuilts/gdb/linux-x86/lib/python2.7/ |
| random.py | 380 def normalvariate(self, mu, sigma):
383 mu is the mean, and sigma is the standard deviation.
386 # mu = mean, sigma = standard deviation
401 return mu + z*sigma
405 def lognormvariate(self, mu, sigma):
409 normal distribution with mean mu and standard deviation sigma.
410 mu can have any value, and sigma must be greater than zero.
413 return _exp(self.normalvariate(mu, sigma))
556 def gauss(self, mu, sigma):
559 mu is the mean, and sigma is the standard deviation. This i
[all...] |
| /prebuilts/python/darwin-x86/2.7.5/lib/python2.7/ |
| random.py | 380 def normalvariate(self, mu, sigma):
383 mu is the mean, and sigma is the standard deviation.
386 # mu = mean, sigma = standard deviation
401 return mu + z*sigma
405 def lognormvariate(self, mu, sigma):
409 normal distribution with mean mu and standard deviation sigma.
410 mu can have any value, and sigma must be greater than zero.
413 return _exp(self.normalvariate(mu, sigma))
556 def gauss(self, mu, sigma):
559 mu is the mean, and sigma is the standard deviation. This i
[all...] |
| /prebuilts/python/linux-x86/2.7.5/lib/python2.7/ |
| random.py | 380 def normalvariate(self, mu, sigma):
383 mu is the mean, and sigma is the standard deviation.
386 # mu = mean, sigma = standard deviation
401 return mu + z*sigma
405 def lognormvariate(self, mu, sigma):
409 normal distribution with mean mu and standard deviation sigma.
410 mu can have any value, and sigma must be greater than zero.
413 return _exp(self.normalvariate(mu, sigma))
556 def gauss(self, mu, sigma):
559 mu is the mean, and sigma is the standard deviation. This i
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| eigen_attention.h | 165 // Initialize the glimpse with white noise: compute the mean and sigma
178 TensorFixedSize<float, Sizes<> > sigma; local
179 sigma.device(device) =
198 sigma.reshape(Sizes<1, 1>()).broadcast(glimpse_size))
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/random/ |
| RandomDataImpl.java | 452 * <code>sigma</code>.
456 * @param sigma
459 * @throws NotStrictlyPositiveException if {@code sigma <= 0}.
461 public double nextGaussian(double mu, double sigma) {
462 if (sigma <= 0) {
463 throw new NotStrictlyPositiveException(LocalizedFormats.STANDARD_DEVIATION, sigma);
465 return sigma * getRan().nextGaussian() + mu;
[all...] |
| /external/libxcam/modules/ocl/ |
| cl_retinex_handler.cpp | 83 uint32_t radius, float sigma)
84 : CLGaussImageKernel (context, radius, sigma)
293 uint32_t radius, float sigma)
301 kernel = new CLRetinexGaussImageKernel (context, handler, index, radius, sigma);
|
| /external/opencv/cv/src/ |
| cvthresh.cpp | 258 double p_i, q2, mu2, val_i, sigma; local
275 sigma = q1*q2*(mu1 - mu2)*(mu1 - mu2);
276 if( sigma > max_sigma )
278 max_sigma = sigma;
|
| /external/ImageMagick/PerlMagick/ |
| Magick.xs | 222 {"sigma", RealReference}, {"channel", MagickChannelOptions} } },
233 {"sigma", RealReference} } },
248 { "OilPaint", { {"radius", RealReference}, {"sigma", RealReference} } },
263 {"sigma", RealReference}, {"channel", MagickChannelOptions} } },
376 {"sigma", RealReference} } },
388 {"radius", RealReference}, {"sigma", RealReference},
397 {"radius", RealReference}, {"sigma", RealReference},
401 {"radius", RealReference}, {"sigma", RealReference},
441 {"sigma", RealReference}, {"x", IntegerReference},
454 {"sigma", RealReference}, {"x", IntegerReference}
[all...] |
| /external/ImageMagick/PerlMagick/quantum/ |
| quantum.xs.in | 222 {"sigma", RealReference}, {"channel", MagickChannelOptions} } },
233 {"sigma", RealReference} } },
248 { "OilPaint", { {"radius", RealReference}, {"sigma", RealReference} } },
263 {"sigma", RealReference}, {"channel", MagickChannelOptions} } },
376 {"sigma", RealReference} } },
388 {"radius", RealReference}, {"sigma", RealReference},
397 {"radius", RealReference}, {"sigma", RealReference},
401 {"radius", RealReference}, {"sigma", RealReference},
441 {"sigma", RealReference}, {"x", IntegerReference},
454 {"sigma", RealReference}, {"x", IntegerReference}
[all...] |
| /external/ImageMagick/coders/ |
| msl.c | 950 geometry_info.sigma=1.0;
952 affine.sy=geometry_info.sigma;
1445 sigma = 1.0; local
6361 sigma = 1.0; local
[all...] |
