| /external/boringssl/src/crypto/fipsmodule/ec/ |
| ec_montgomery.c | 334 EC_FELEM delta, gamma, beta, ftmp, ftmp2, tmptmp, alpha, fourbeta; local
337 // gamma = y^2
338 ec_GFp_mont_felem_sqr(group, &gamma, &a->Y);
339 // beta = x*gamma
340 ec_GFp_mont_felem_mul(group, &beta, &a->X, &gamma);
357 // z' = (y + z)^2 - gamma - delta
358 ec_felem_add(group, &delta, &gamma, &delta);
363 // y' = alpha*(4*beta - x') - 8*gamma^2
365 ec_felem_add(group, &gamma, &gamma, &gamma)
[all...] |
| /external/libxaac/decoder/drc_src/ |
| impd_drc_fiilter_bank.c | 36 FLOAT32 gamma = normal_cross_freq[crossover_freq_idx].gamma; local
41 pstr_lp_filt_coeff->a1 = 2.0f * (gamma - delta);
42 pstr_lp_filt_coeff->a2 = 2.0f * (gamma + delta) - 1.0f;
43 pstr_lp_filt_coeff->b0 = gamma;
44 pstr_lp_filt_coeff->b1 = 2.0f * gamma;
45 pstr_lp_filt_coeff->b2 = gamma;
57 pstr_ap_filt_coeff->a1 = 2.0f * (gamma - delta);
59 pstr_ap_filt_coeff->a2 = 2.0f * (gamma + delta) - 1.0f;
|
| impd_drc_filter_bank.c | 36 FLOAT32 gamma = normal_cross_freq[crossover_freq_idx].gamma; local
41 pstr_lp_filt_coeff->a1 = 2.0f * (gamma - delta);
42 pstr_lp_filt_coeff->a2 = 2.0f * (gamma + delta) - 1.0f;
43 pstr_lp_filt_coeff->b0 = gamma;
44 pstr_lp_filt_coeff->b1 = 2.0f * gamma;
45 pstr_lp_filt_coeff->b2 = gamma;
57 pstr_ap_filt_coeff->a1 = 2.0f * (gamma - delta);
59 pstr_ap_filt_coeff->a2 = 2.0f * (gamma + delta) - 1.0f;
|
| /external/pdfium/core/fxcodec/codec/ |
| ccodec_pngmodule.cpp | 132 double gamma = 1.0; local
134 &color_type, &gamma)) {
139 png_set_gamma(png_ptr, gamma, 0.45455);
143 png_set_gamma(png_ptr, gamma, image_gamma);
145 png_set_gamma(png_ptr, gamma, 0.45455);
|
| /external/ImageMagick/MagickCore/ |
| pixel.c | 4429 gamma; local
4493 gamma, local
4920 gamma, local
5485 gamma; local
[all...] |
| composite.c | 153 Da' in in the follow formula as 'gamma' The resulting alpla value.
157 gamma = Sa+Da-Sa*Da;
158 gamma = 1 - QuantumScale*alpha * QuantumScale*beta;
159 opacity = QuantumScale*alpha*beta; // over blend, optimized 1-Gamma
385 gamma;
499 gamma=PerceptibleReciprocal(alpha);
500 pixel=QuantumRange*gamma*(Sca+Dca*(1.0-Sa));
383 gamma; local
1291 gamma; local
[all...] |
| channel.c | 533 if (fabs(image->gamma-1.0) <= MagickEpsilon)
753 separate_image->gamma=image->gamma;
924 gamma,
935 gamma=Sa*(-Da)+Sa+Da;
936 gamma=PerceptibleReciprocal(gamma);
947 composite[i]=ClampToQuantum(gamma*MagickOver_((double) q[i],beta,
953 composite[i]=ClampToQuantum(gamma*MagickOver_((double) q[i],beta,
959 composite[i]=ClampToQuantum(gamma*MagickOver_((double) q[i],beta
918 gamma, local
1031 gamma; local
1151 gamma, local
[all...] |
| gem.c | 1485 gamma, local
1600 gamma, local
1641 gamma, local
[all...] |
| effect.c | 312 gamma,
348 gamma=0.0;
359 gamma+=(*k);
364 gamma=PerceptibleReciprocal(gamma);
365 SetPixelChannel(blur_image,channel,ClampToQuantum(gamma*pixel),q);
377 gamma+=(*k)*alpha;
382 gamma=PerceptibleReciprocal(gamma);
383 SetPixelChannel(blur_image,channel,ClampToQuantum(gamma*pixel),q)
310 gamma, local
631 gamma, local
1269 gamma, local
2133 gamma, local
2273 gamma, local
2942 gamma, local
3251 gamma, local
3661 gamma, local
[all...] |
| accelerate-kernels-private.h | 757 gamma,
763 gamma=sqrt(-2.0f*log(alpha));
764 sigma=gamma*cospi((2.0f*beta));
765 tau=gamma*sinpi((2.0f*beta));
[all...] |
| /external/libpng/contrib/gregbook/ |
| readpng.c | 210 double gamma; local
252 * this file may have come from--so if it doesn't have a file gamma, don't
255 if (png_get_gAMA(png_ptr, info_ptr, &gamma))
256 png_set_gamma(png_ptr, display_exponent, gamma);
|
| writepng.h | 91 double gamma; member in struct:_mainprog_info
|
| /external/adhd/cras/src/dsp/ |
| biquad.c | 58 double gamma = (0.5 + beta) * cos(theta); local
59 double alpha = 0.25 * (0.5 + beta - gamma);
64 double a1 = 2 * -gamma;
93 double gamma = (0.5 + beta) * cos(theta); local
94 double alpha = 0.25 * (0.5 + beta + gamma);
99 double a1 = 2 * -gamma;
|
| /external/libaom/libaom/av1/common/ |
| warped_motion.c | 338 static int is_affine_shear_allowed(int16_t alpha, int16_t beta, int16_t gamma,
341 (4 * abs(gamma) + 4 * abs(delta) >= (1 << WARPEDMODEL_PREC_BITS)))
357 wm->gamma =
368 wm->gamma = ROUND_POWER_OF_TWO_SIGNED(wm->gamma, WARP_PARAM_REDUCE_BITS) *
373 if (!is_affine_shear_allowed(wm->alpha, wm->beta, wm->gamma, wm->delta))
399 int16_t beta, int16_t gamma, int16_t delta) {
435 sy4 += gamma * (-4) + delta * (-4);
510 sy += gamma;
531 const int16_t gamma = wm->gamma local
817 const int16_t gamma = wm->gamma; local
[all...] |
| /external/skia/tests/ |
| ParametricStageTest.cpp | 43 static void check_error(skiatest::Reporter* r, float limit, float gamma) {
45 fn.g = gamma;
|
| /external/skqp/tests/ |
| ParametricStageTest.cpp | 43 static void check_error(skiatest::Reporter* r, float limit, float gamma) {
45 fn.g = gamma;
|
| /external/syzkaller/vendor/google.golang.org/grpc/transport/ |
| bdp_estimator.go | 36 // increase our bbp estimate by a factor of gamma.
41 gamma = 2
130 b.bdp = uint32(gamma * sampleFloat)
37 gamma = 2 const
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| chi2.py | 27 from tensorflow.python.ops.distributions import gamma
37 class Chi2(gamma.Gamma):
49 Z = 2**(0.5 df) Gamma(0.5 df)
56 * `Gamma` is the [gamma function](
59 The Chi2 distribution is a special case of the Gamma distribution, i.e.,
62 Chi2(df) = Gamma(concentration=0.5 * df, rate=0.5)
97 # not true in the parent class "gamma." therefore, passing
|
| /external/tensorflow/tensorflow/python/layers/ |
| normalization_test.py | 328 np_gamma, np_beta = self.evaluate([bn.gamma, bn.beta])
370 np_gamma, np_beta = self.evaluate([bn.gamma, bn.beta])
412 np_gamma, np_beta = self.evaluate([bn.gamma, bn.beta])
453 np_gamma, np_beta = self.evaluate([bn.gamma, bn.beta])
494 np_gamma, np_beta = self.evaluate([bn.gamma, bn.beta])
535 np_gamma, np_beta = self.evaluate([bn.gamma, bn.beta])
577 np_gamma, np_beta = self.evaluate([bn.gamma, bn.beta])
618 np_gamma, np_beta = self.evaluate([bn.gamma, bn.beta])
660 np_gamma, np_beta = self.evaluate([bn.gamma, bn.beta])
706 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/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| batch_normalization.py | 61 scale: A scale `Tensor`, often denoted `gamma` in equations, or
237 gamma = broadcast_fn(self.batchnorm.gamma) if self.batchnorm.scale else None
239 x, mean, variance, beta, gamma, self.batchnorm.epsilon)
272 # `gamma` and `log Var(y)` reductions over event_dims.
273 # Log(total change in area from gamma term).
274 log_total_gamma = math_ops.reduce_sum(math_ops.log(self.batchnorm.gamma))
|
| /external/ImageMagick/coders/ |
| pango.c | 447 gamma;
456 gamma=QuantumScale*fill_color.alpha;
457 gamma=PerceptibleReciprocal(gamma);
458 fill_color.blue*=gamma;
459 fill_color.green*=gamma;
460 fill_color.red*=gamma;
444 gamma; local
|
| /external/tensorflow/tensorflow/python/keras/layers/ |
| normalization_test.py | 86 self.assertEqual(layer.gamma.constraint, max_norm)
106 out /= np.reshape(keras.backend.eval(norm.gamma), (1, 3, 1, 1))
126 out /= np.reshape(keras.backend.eval(norm.gamma), (1, 1, 1, 3))
156 self.assertEqual(norm.gamma.dtype.base_dtype, 'float32')
267 out /= keras.backend.eval(norm.gamma)
401 out /= keras.backend.eval(norm.gamma)
453 self.assertEqual(layer.gamma.constraint, max_norm)
473 out /= np.reshape(keras.backend.eval(norm.gamma), (1, 3, 1, 1))
492 out /= np.reshape(keras.backend.eval(norm.gamma), (1, 1, 1, 3))
544 gamma = layer.gamm
[all...] |
