| /external/skia/include/core/ |
| SkColorSpace.h | 88 * Colorspace with the sRGB primaries, but a linear (1.0) gamma. Commonly used for
116 static sk_sp<SkColorSpace> MakeRGB(RenderTargetGamma gamma, Gamut gamut);
117 static sk_sp<SkColorSpace> MakeRGB(RenderTargetGamma gamma, const SkMatrix44& toXYZD50);
142 * Returns true if the color space gamma is near enough to be approximated as sRGB.
149 * Returns true if the color space gamma is linear.
187 * Returns a color space with the same gamut as this one, but with a linear gamma.
|
| /external/skia/tests/ |
| ParametricStageTest.cpp | 44 static void check_error(skiatest::Reporter* r, float limit, float gamma) {
46 fn.fG = gamma;
|
| /external/skqp/include/core/ |
| SkColorSpace.h | 88 * Colorspace with the sRGB primaries, but a linear (1.0) gamma. Commonly used for
116 static sk_sp<SkColorSpace> MakeRGB(RenderTargetGamma gamma, Gamut gamut);
117 static sk_sp<SkColorSpace> MakeRGB(RenderTargetGamma gamma, const SkMatrix44& toXYZD50);
142 * Returns true if the color space gamma is near enough to be approximated as sRGB.
149 * Returns true if the color space gamma is linear.
187 * Returns a color space with the same gamut as this one, but with a linear gamma.
|
| /external/skqp/tests/ |
| ParametricStageTest.cpp | 44 static void check_error(skiatest::Reporter* r, float limit, float gamma) {
46 fn.fG = gamma;
|
| /external/tensorflow/tensorflow/python/ops/distributions/ |
| exponential.py | 29 from tensorflow.python.ops.distributions import gamma
40 class Exponential(gamma.Gamma):
56 The Exponential distribution is a special case of the Gamma distribution,
60 Exponential(rate) = Gamma(concentration=1., rate)
95 # true in the parent class "Gamma." Therefore, passing
106 # While the Gamma distribution is not reparameterizable, the exponential
|
| /frameworks/base/core/jni/android/graphics/ |
| MaskFilter.cpp | 58 static jlong createGammaTable(JNIEnv* env, jobject, jfloat gamma) {
59 SkMaskFilter* filter = SkTableMaskFilter::CreateGamma(gamma);
|
| /external/ImageMagick/MagickCore/ |
| gem.c | 1485 gamma, local
1600 gamma, local
1641 gamma, local
[all...] |
| effect.c | 312 gamma,
349 gamma=0.0;
360 gamma+=(*k);
365 gamma=PerceptibleReciprocal(gamma);
366 SetPixelChannel(blur_image,channel,ClampToQuantum(gamma*pixel),q);
378 gamma+=(*k)*alpha;
383 gamma=PerceptibleReciprocal(gamma);
384 SetPixelChannel(blur_image,channel,ClampToQuantum(gamma*pixel),q)
310 gamma, local
631 gamma, local
1269 gamma, local
2113 gamma, local
2253 gamma, local
2915 gamma, local
3222 gamma, local
3630 gamma, local
[all...] |
| channel.c | 872 gamma, local
883 gamma=Sa*(-Da)+Sa+Da;
884 gamma=PerceptibleReciprocal(gamma);
895 composite[i]=ClampToQuantum(gamma*MagickOver_((double) q[i],beta,
901 composite[i]=ClampToQuantum(gamma*MagickOver_((double) q[i],beta,
907 composite[i]=ClampToQuantum(gamma*MagickOver_((double) q[i],beta,
913 composite[i]=ClampToQuantum(gamma*MagickOver_((double) q[i],beta,
985 gamma; local
995 gamma=QuantumScale*GetPixelAlpha(image,q)
1117 gamma, local
[all...] |
| accelerate-kernels-private.h | 760 gamma,
766 gamma=sqrt(-2.0f*log(alpha));
767 sigma=gamma*cospi((2.0f*beta));
768 tau=gamma*sinpi((2.0f*beta));
[all...] |
| /external/tensorflow/tensorflow/python/layers/ |
| normalization_test.py | 326 np_gamma, np_beta = sess.run([bn.gamma, bn.beta])
367 np_gamma, np_beta = sess.run([bn.gamma, bn.beta])
408 np_gamma, np_beta = sess.run([bn.gamma, bn.beta])
448 np_gamma, np_beta = sess.run([bn.gamma, bn.beta])
488 np_gamma, np_beta = sess.run([bn.gamma, bn.beta])
528 np_gamma, np_beta = sess.run([bn.gamma, bn.beta])
569 np_gamma, np_beta = sess.run([bn.gamma, bn.beta])
609 np_gamma, np_beta = sess.run([bn.gamma, bn.beta])
650 np_gamma, np_beta = sess.run([bn.gamma, bn.beta])
695 gamma = all_vars['bn/gamma:0'
[all...] |
| /external/apache-commons-math/src/main/java/org/apache/commons/math/linear/ |
| TriDiagonalTransformer.java | 243 // compute gamma = beta vT z / 2
244 double gamma = 0; local
246 gamma += z[i] * hK[i];
248 gamma *= beta / 2;
250 // compute z = z - gamma v
252 z[i] -= gamma * hK[i];
|
| /external/eigen/unsupported/Eigen/src/EulerAngles/ |
| EulerSystem.h | 143 IsGammaOpposite = (GammaAxis < 0) ? 1 : 0, /*!< weather gamma axis is negative */
289 res.gamma() = -res.gamma();
298 if (PositiveRangeGamma && (res.gamma() < 0))
299 res.gamma() += Scalar(2 * EIGEN_PI);
|
| /external/eigen/unsupported/Eigen/src/IterativeSolvers/ |
| ConstrainedConjGrad.h | 114 Scalar rho = 1.0, rho_1, lambda, gamma; local
163 if (transition || iter.first()) gamma = 0.0;
164 else gamma = (std::max)(0.0, (rho - old_z.dot(z)) / rho_1);
165 p = z + gamma*p;
|
| /external/google-tv-pairing-protocol/cpp/src/polo/pairing/ |
| pairingsession.cc | 90 bool PairingSession::SetSecret(const Gamma& secret) {
91 secret_ = new Gamma(secret);
162 const Gamma* gamma = challenge().GetGamma(*nonce_); local
163 if (!gamma) {
164 LOG(ERROR) << "Failed to get gamma";
170 listener_->OnPerformOutputDeviceRole(*gamma);
171 delete gamma;
|
| /external/libpng/contrib/gregbook/ |
| writepng.h | 91 double gamma; member in struct:_mainprog_info
|
| /external/ImageMagick/coders/ |
| pango.c | 431 gamma;
440 gamma=QuantumScale*fill_color.alpha;
441 gamma=PerceptibleReciprocal(gamma);
442 fill_color.blue*=gamma;
443 fill_color.green*=gamma;
444 fill_color.red*=gamma;
429 gamma; local
|
| /frameworks/base/core/java/android/os/ |
| VibrationEffect.java | 316 protected static int scale(int amplitude, float gamma, int maxAmplitude) {
317 float val = MathUtils.pow(amplitude / (float) MAX_AMPLITUDE, gamma);
348 * @param gamma the gamma adjustment to apply
353 public VibrationEffect scale(float gamma, int maxAmplitude) {
354 int newAmplitude = scale(mAmplitude, gamma, maxAmplitude);
478 * Scale the Waveform with the given gamma and new max amplitude.
480 * @param gamma the gamma adjustment to apply
486 public VibrationEffect scale(float gamma, int maxAmplitude)
[all...] |
| /frameworks/base/services/core/java/com/android/server/display/ |
| BrightnessMappingStrategy.java | 187 * {@code config_autoBrightnessAdjustmentMaxGamma<sup>-adjustment</sup>} is used to gamma
340 float gamma = Float.NaN; local
341 // Extreme edge cases: use a simpler heuristic, as proper gamma correction around the edges
352 // current^gamma = desired => gamma = log[current](desired)
353 gamma = MathUtils.log(desiredBrightness) / MathUtils.log(currentBrightness);
354 // max^-adjustment = gamma => adjustment = -log[max](gamma)
355 adjustment = -MathUtils.log(gamma) / MathUtils.log(maxGamma);
360 MathUtils.pow(maxGamma, -adjustment) + " == " + gamma);
375 float gamma = MathUtils.pow(maxGamma, -adjustment); local
[all...] |
| /prebuilts/go/darwin-x86/src/crypto/elliptic/ |
| elliptic.go | 197 gamma := new(big.Int).Mul(y, y)
198 gamma.Mod(gamma, curve.P)
209 beta := alpha2.Mul(x, gamma)
221 z3.Sub(z3, gamma)
238 gamma.Mul(gamma, gamma)
239 gamma.Lsh(gamma, 3
[all...] |
| /prebuilts/go/linux-x86/src/crypto/elliptic/ |
| elliptic.go | 197 gamma := new(big.Int).Mul(y, y)
198 gamma.Mod(gamma, curve.P)
209 beta := alpha2.Mul(x, gamma)
221 z3.Sub(z3, gamma)
238 gamma.Mul(gamma, gamma)
239 gamma.Lsh(gamma, 3
[all...] |
| /external/opencv/cv/src/ |
| cvsnakes.cpp | 60 // gamma - pointer to coefficient of image energy,
61 // coeffUsage - if CV_VALUE - alpha, beta, gamma point to single value
78 float *gamma,
133 if( gamma == NULL )
351 _gamma = *gamma;
357 _gamma = gamma[i];
411 float *beta, float *gamma,
433 alpha, beta, gamma, coeffUsage, win, criteria,
|
| /libcore/ojluni/src/main/java/java/util/ |
| SplittableRandom.java | 102 * constant ("gamma") to the current (64 bit) seed, forming a
103 * simple sequence. The seed and the gamma values for any two
118 * and gamma for another SplittableRandom. To conservatively
120 * gamma selection (method mixGamma) uses different
126 * most 4 to any given gamma value). This reduces the effective
127 * set of 64bit odd gamma values by about 2%, and serves as an
158 * The golden ratio scaled to 64bits, used as the initial gamma
177 private final long gamma; field in class:SplittableRandom
182 private SplittableRandom(long seed, long gamma) {
184 this.gamma = gamma
[all...] |
| /external/opencv/ml/src/ |
| mlsvm.cpp | 132 else if( param_id == CvSVM::GAMMA )
164 "(use one of CvSVM::C, CvSVM::GAMMA et al.)", __FILE__, __LINE__ );
171 gamma(1), coef0(0), C(1), nu(0), p(0), class_weights(0)
182 degree(_degree), gamma(_gamma), coef0(_coef0),
261 calc_non_rbf_base( vcount, var_count, vecs, another, results, params->gamma, params->coef0 );
271 -2*params->gamma, -2*params->coef0 );
289 double gamma = -params->gamma; local
315 results[j] = (Qfloat)(s*gamma);
1613 double gamma = 0, C = 0, degree = 0, coef = 0, p = 0, nu = 0; local
[all...] |
| /external/apache-commons-math/src/main/java/org/apache/commons/math/estimation/ |
| LevenbergMarquardtEstimator.java | 857 double gamma = 0; local
859 gamma += jacobian[index] * jacobian[index + dkp];
861 gamma *= betak;
863 jacobian[index + dkp] -= gamma * jacobian[index];
882 double gamma = 0; local
885 gamma += jacobian[index] * y[i];
888 gamma *= beta[pk];
891 y[i] -= gamma * jacobian[index];
|
