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  /external/eigen/Eigen/src/Householder/
Householder.h 28 * \f$ H = I - tau v v^*\f$
35 * \param tau the scaling factor of the Householder transformation
42 void MatrixBase<Derived>::makeHouseholderInPlace(Scalar& tau, RealScalar& beta)
45 makeHouseholder(essentialPart, tau, beta);
51 * \f$ H = I - tau v v^*\f$
57 * \param tau the scaling factor of the Householder transformation
67 Scalar& tau,
82 tau = RealScalar(0);
92 tau = conj((beta - c0) / beta);
97 * \f$ H = I - tau v v^*\f
    [all...]
  /external/u-boot/post/lib_powerpc/fpu/
darwin-ldouble.c 92 double t, tau, u, v, w; local
104 asm("fmsub %0,%1,%2,%3" : "=f"(tau) : "f"(a), "f"(c), "f"(t));
106 tau = fmsub(a, c, t);
110 tau += v + w; /* Add in other second-order terms. */
111 u = t + tau;
117 z.dval[1] = (t - u) + tau;
  /external/compiler-rt/lib/builtins/ppc/
gcc_qmul.c 21 double ab, tmp, tau; local
47 tau = ab + tmp;
49 dst.s.lo = (ab - tau) + tmp;
50 dst.s.hi = tau;
  /external/eigen/bench/btl/libs/BLAS/
blas_interface.hh 32 void ssytrd_(char *uplo, const int *n, float *a, const int *lda, float *d, float *e, float *tau, float *work, int *lwork, int *info );
33 void dsytrd_(char *uplo, const int *n, double *a, const int *lda, double *d, double *e, double *tau, double *work, int *lwork, int *info );
34 void sgehrd_( const int *n, int *ilo, int *ihi, float *a, const int *lda, float *tau, float *work, int *lwork, int *info );
35 void dgehrd_( const int *n, int *ilo, int *ihi, double *a, const int *lda, double *tau, double *work, int *lwork, int *info );
  /external/eigen/unsupported/Eigen/src/IterativeSolvers/
GMRES.h 89 VectorType tau = VectorType::Zero(restart + 1); local
100 r0.makeHouseholder(H0_tail, tau.coeffRef(0), beta);
112 v.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data());
122 v.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data());
131 v.tail(m - k).makeHouseholder(Hk_tail, tau.coeffRef(k), beta);
134 v.tail(m - k).applyHouseholderOnTheLeft(Hk_tail, tau.coeffRef(k), workspace.data());
175 x_new.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data());
195 tau.setZero();
198 r0.makeHouseholder(H0_tail, tau.coeffRef(0), beta);
  /external/clang/test/SemaTemplate/
instantiate-var-template.cpp 5 template <typename T> constexpr T tau = 2 * pi<T>; member in namespace:PR17846
6 constexpr double tau_double = tau<double>;
  /development/samples/ApiDemos/src/com/example/android/apis/view/
GameView.java 358 float tau = (currentStepTime - mLastStepTime) * 0.001f;
364 mShip.accelerate(tau, mMaxShipThrust, mMaxShipSpeed);
365 if (!mShip.step(tau)) {
373 if (!bullet.step(tau)) {
384 if (!obstacle.step(tau)) {
542 public boolean step(float tau) {
543 mPositionX += mVelocityX * tau;
544 mPositionY += mVelocityY * tau;
547 mDestroyAnimProgress += tau / getDestroyAnimDuration();
666 public void accelerate(float tau, float maxThrust, float maxSpeed)
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  /external/eigen/Eigen/src/SparseQR/
SparseQR.h 483 // Then update tval = tval - q * tau
503 Scalar tau = RealScalar(0); local
529 tau = numext::conj((beta-c0) / beta);
549 m_hcoeffs(nonzeroCol) = tau;
625 Scalar tau = Scalar(0); local
626 tau = m_qr.m_Q.col(k).dot(res.col(j));
627 if(tau==Scalar(0)) continue;
628 tau = tau * m_qr.m_hcoeffs(k);
629 res.col(j) -= tau * m_qr.m_Q.col(k)
641 Scalar tau = Scalar(0); local
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  /external/eigen/lapack/
slarfg.f 21 * SUBROUTINE SLARFG( N, ALPHA, X, INCX, TAU )
25 * REAL ALPHA, TAU
46 *> H = I - tau * ( 1 ) * ( 1 v**T ) ,
49 *> where tau is a real scalar and v is a real (n-1)-element
52 *> If the elements of x are all zero, then tau = 0 and H is taken to be
55 *> Otherwise 1 <= tau <= 2.
88 *> \param[out] TAU
90 *> TAU is REAL
91 *> The value tau.
107 SUBROUTINE SLARFG( N, ALPHA, X, INCX, TAU )
    [all...]
clarf.f 21 * SUBROUTINE CLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK )
26 * COMPLEX TAU
42 *> H = I - tau * v * v**H
44 *> where tau is a complex scalar and v is a complex vector.
46 *> If tau = 0, then H is taken to be the unit matrix.
48 *> To apply H**H (the conjugate transpose of H), supply conjg(tau) instead
49 *> tau.
80 *> TAU = 0.
89 *> \param[in] TAU
91 *> TAU is COMPLE
    [all...]
clarfg.f 21 * SUBROUTINE CLARFG( N, ALPHA, X, INCX, TAU )
25 * COMPLEX ALPHA, TAU
46 *> H = I - tau * ( 1 ) * ( 1 v**H ) ,
49 *> where tau is a complex scalar and v is a complex (n-1)-element
52 *> If the elements of x are all zero and alpha is real, then tau = 0
55 *> Otherwise 1 <= real(tau) <= 2 and abs(tau-1) <= 1 .
88 *> \param[out] TAU
90 *> TAU is COMPLEX
91 *> The value tau
    [all...]
zlarf.f 21 * SUBROUTINE ZLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK )
26 * COMPLEX*16 TAU
42 *> H = I - tau * v * v**H
44 *> where tau is a complex scalar and v is a complex vector.
46 *> If tau = 0, then H is taken to be the unit matrix.
48 *> To apply H**H, supply conjg(tau) instead
49 *> tau.
80 *> TAU = 0.
89 *> \param[in] TAU
91 *> TAU is COMPLEX*1
    [all...]
zlarfg.f 21 * SUBROUTINE ZLARFG( N, ALPHA, X, INCX, TAU )
25 * COMPLEX*16 ALPHA, TAU
46 *> H = I - tau * ( 1 ) * ( 1 v**H ) ,
49 *> where tau is a complex scalar and v is a complex (n-1)-element
52 *> If the elements of x are all zero and alpha is real, then tau = 0
55 *> Otherwise 1 <= real(tau) <= 2 and abs(tau-1) <= 1 .
88 *> \param[out] TAU
90 *> TAU is COMPLEX*16
91 *> The value tau
    [all...]
dlarfg.f 21 * SUBROUTINE DLARFG( N, ALPHA, X, INCX, TAU )
25 * DOUBLE PRECISION ALPHA, TAU
46 *> H = I - tau * ( 1 ) * ( 1 v**T ) ,
49 *> where tau is a real scalar and v is a real (n-1)-element
52 *> If the elements of x are all zero, then tau = 0 and H is taken to be
55 *> Otherwise 1 <= tau <= 2.
88 *> \param[out] TAU
90 *> TAU is DOUBLE PRECISION
91 *> The value tau.
107 SUBROUTINE DLARFG( N, ALPHA, X, INCX, TAU )
    [all...]
dlarf.f 21 * SUBROUTINE DLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK )
26 * DOUBLE PRECISION TAU
41 *> H = I - tau * v * v**T
43 *> where tau is a real scalar and v is a real vector.
45 *> If tau = 0, then H is taken to be the unit matrix.
76 *> TAU = 0.
85 *> \param[in] TAU
87 *> TAU is DOUBLE PRECISION
88 *> The value tau in the representation of H.
125 SUBROUTINE DLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK
    [all...]
slarf.f 21 * SUBROUTINE SLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK )
26 * REAL TAU
41 *> H = I - tau * v * v**T
43 *> where tau is a real scalar and v is a real vector.
45 *> If tau = 0, then H is taken to be the unit matrix.
76 *> TAU = 0.
85 *> \param[in] TAU
87 *> TAU is REAL
88 *> The value tau in the representation of H.
125 SUBROUTINE SLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK
    [all...]
  /external/ImageMagick/MagickCore/
segment.c 123 #define Tau 5.2f
158 tau;
176 tau,
155 tau; member in struct:_IntervalTree
173 tau, member in struct:_ZeroCrossing
1523 tau, local
    [all...]
  /development/samples/ControllerSample/src/com/example/controllersample/
GameView.java 322 float tau = (currentStepTime - mLastStepTime) * 0.001f; local
330 currentShip.accelerate(tau);
331 if (!currentShip.step(tau)) {
341 if (!bullet.step(tau)) {
352 if (!obstacle.step(tau)) {
540 * Moves the sprite based on the elapsed time defined by tau.
542 * @param tau the elapsed time in seconds since the last step
545 public boolean step(float tau) {
546 mPositionX += mVelocityX * tau;
547 mPositionY += mVelocityY * tau;
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  /external/eigen/Eigen/src/Eigenvalues/
RealSchur.h 502 Scalar tau, beta; local
504 v.makeHouseholder(ess, tau, beta);
514 m_matT.block(k, k, 3, size-k).applyHouseholderOnTheLeft(ess, tau, workspace);
515 m_matT.block(0, k, (std::min)(iu,k+3) + 1, 3).applyHouseholderOnTheRight(ess, tau, workspace);
517 m_matU.block(0, k, size, 3).applyHouseholderOnTheRight(ess, tau, workspace);
522 Scalar tau, beta; local
524 v.makeHouseholder(ess, tau, beta);
529 m_matT.block(iu-1, iu-1, 2, size-iu+1).applyHouseholderOnTheLeft(ess, tau, workspace);
530 m_matT.block(0, iu-1, iu+1, 2).applyHouseholderOnTheRight(ess, tau, workspace);
532 m_matU.block(0, iu-1, size, 2).applyHouseholderOnTheRight(ess, tau, workspace)
    [all...]
RealQZ.h 478 Scalar tau, beta; local
483 hr.makeHouseholderInPlace(tau, beta);
486 m_S.template middleRows<3>(k).rightCols(dim-fc).applyHouseholderOnTheLeft(essential2, tau, m_workspace.data());
487 m_T.template middleRows<3>(k).rightCols(dim-fc).applyHouseholderOnTheLeft(essential2, tau, m_workspace.data());
489 m_Q.template middleCols<3>(k).applyHouseholderOnTheRight(essential2, tau, m_workspace.data());
495 hr.makeHouseholderInPlace(tau, beta);
503 m_S.col(k+2).head(lr) -= tau*tmp;
504 m_S.template middleCols<2>(k).topRows(lr) -= (tau*tmp) * essential2.adjoint();
508 m_T.col(k+2).head(lr) -= tau*tmp;
509 m_T.template middleCols<2>(k).topRows(lr) -= (tau*tmp) * essential2.adjoint()
    [all...]
  /external/tensorflow/tensorflow/compiler/xla/client/lib/
qr.cc 47 // H = I - tau v v.T.
65 // tau = 0
69 // tau = (beta - alpha) / beta
72 // return (v, tau, beta)
76 const int64 m, XlaOp* v, XlaOp* tau, XlaOp* beta) {
105 *tau = Select(sigma_is_zero, Broadcast(zero, batch_dims),
133 // v, tau, beta = house(a[:, j], j)
137 // a[:, :] -= tau * np.dot(v[:, np.newaxis],
144 // taus[j] = tau
184 XlaOp v, tau, beta
    [all...]
self_adjoint_eig.cc 66 // tau = (A[q, q] - A[p, p]) / (2 * A[p, q])
67 // if tau >= 0:
68 // t = 1.0 / (tau + np.sqrt(1 + tau ** 2))
70 // t = -1.0 / (-tau + np.sqrt(1 + tau ** 2))
91 auto tau = (qs - ps) / (pqs * two); local
92 auto t_pos = one / (tau + Sqrt(one + Square(tau)));
93 auto t_neg = -one / (-tau + Sqrt(one + Square(tau)))
    [all...]
  /external/python/cpython3/Lib/test/test_json/
test_enum.py 18 TAU = 2 * PI
23 tau = TAU variable in class:FloatNum
64 str([E, PI, TAU]))
79 e:"Euler's number", p:'pi', t:'tau',
89 self.assertEqual(nd[repr(TAU)], 'tau')
102 tau=FloatNum.tau,
114 self.assertEqual(nd['tau'], TAU
    [all...]
  /external/tensorflow/tensorflow/contrib/eager/python/examples/l2hmc/
main.py 186 for tau in range(time_steps - t):
187 v_tau = samples_history[tau, :, :] - target_mean
188 v_tau_plus_t = samples_history[tau + t, :, :] - target_mean
  /external/eigen/Eigen/src/misc/
lapacke.h     [all...]

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