| /external/eigen/unsupported/Eigen/src/NonLinearOptimization/ |
| D | lmpar.h | 36 Matrix< Scalar, Dynamic, 1 > wa1, wa2; in lmpar() local
41 wa1 = qtb; in lmpar()
46 wa1[j] = 0.; in lmpar()
49 wa1[j] /= r(j,j); in lmpar()
50 temp = wa1[j]; in lmpar()
52 wa1[i] -= r(i,j) * temp; in lmpar()
56 x[ipvt[j]] = wa1[j]; in lmpar()
77 wa1[j] = diag[l] * (wa2[l] / dxnorm); in lmpar()
84 sum += r(i,j) * wa1[i]; in lmpar()
85 wa1[j] = (wa1[j] - sum) / r(j,j); in lmpar()
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| D | HybridNonLinearSolver.h | 113 FVectorType wa1, wa2, wa3, wa4; variable
147 wa1.resize(n); wa2.resize(n); wa3.resize(n); wa4.resize(n); in solveInit()
237 internal::dogleg<Scalar>(R, diag, qtf, delta, wa1); in solveOneStep()
240 wa1 = -wa1; in solveOneStep()
241 wa2 = x + wa1; in solveOneStep()
242 pnorm = diag.cwiseProduct(wa1).stableNorm(); in solveOneStep()
260 wa3 = R.template triangularView<Upper>()*wa1 + qtf; in solveOneStep()
326 wa1 = diag.cwiseProduct( diag.cwiseProduct(wa1)/pnorm ); in solveOneStep()
333 internal::r1updt<Scalar>(R, wa1, v_givens, w_givens, wa2, wa3, &sing); in solveOneStep()
387 wa1.resize(n); wa2.resize(n); wa3.resize(n); wa4.resize(n); in solveNumericalDiffInit()
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| D | dogleg.h | 30 Matrix< Scalar, Dynamic, 1 > wa1(n), wa2(n); in dogleg()
56 wa1.fill(0.); in dogleg()
58 wa1.tail(n-j) += qrfac.row(j).tail(n-j) * qtb[j]; in dogleg()
59 wa1[j] /= diag[j]; in dogleg()
64 gnorm = wa1.stableNorm(); in dogleg()
72 wa1.array() /= (diag*gnorm).array(); in dogleg()
78 sum += qrfac(j,i) * wa1[i]; in dogleg()
102 x = temp * wa1 + alpha * x; in dogleg()
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| D | LevenbergMarquardt.h | 122 FVectorType wa1, wa2, wa3, wa4; variable
176 wa1.resize(n); wa2.resize(n); wa3.resize(n); in minimizeInit()
275 internal::lmpar2<Scalar>(qrfac, diag, qtf, delta, par, wa1); in minimizeOneStep()
278 wa1 = -wa1; in minimizeOneStep()
279 wa2 = x + wa1; in minimizeOneStep()
280 pnorm = diag.cwiseProduct(wa1).stableNorm(); in minimizeOneStep()
299 wa3 = fjac.template triangularView<Upper>() * (qrfac.colsPermutation().inverse() *wa1); in minimizeOneStep()
390 wa1.resize(n); wa2.resize(n); wa3.resize(n); in minimizeOptimumStorageInit()
473 wa1 = fjac.diagonal(); in minimizeOptimumStorageOneStep()
488 fjac(j,j) = wa1[j]; in minimizeOptimumStorageOneStep()
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| D | fdjac1.h | 31 Matrix< Scalar, Dynamic, 1 > wa1(n); in fdjac1()
44 iflag = Functor(x, wa1); in fdjac1()
48 fjac.col(j) = (wa1-fvec)/h; in fdjac1()
60 iflag = Functor(x, wa1); in fdjac1()
70 … fjac.col(j).segment(start, length) = ( wa1.segment(start, length)-fvec.segment(start, length))/h; in fdjac1()
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| /external/eigen/unsupported/Eigen/src/LevenbergMarquardt/ |
| D | LMpar.h | 55 VectorType wa1, wa2; in lmpar2() local
62 wa1 = qtb; in lmpar2()
63 wa1.tail(n-rank).setZero(); in lmpar2()
65 …wa1.head(rank) = s.topLeftCorner(rank,rank).template triangularView<Upper>().solve(qtb.head(rank)); in lmpar2()
67 x = qr.colsPermutation()*wa1; in lmpar2()
86 wa1 = qr.colsPermutation().inverse() * diag.cwiseProduct(wa2)/dxnorm; in lmpar2()
87 s.topLeftCorner(n,n).transpose().template triangularView<Lower>().solveInPlace(wa1); in lmpar2()
88 temp = wa1.blueNorm(); in lmpar2()
94 wa1[j] = s.col(j).head(j+1).dot(qtb.head(j+1)) / diag[qr.colsPermutation().indices()(j)]; in lmpar2()
96 gnorm = wa1.stableNorm(); in lmpar2()
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| /external/speex/libspeex/ |
| D | smallft.c | 116 static void dradf2(int ido,int l1,float *cc,float *ch,float *wa1){ in dradf2() argument
146 tr2=wa1[i-2]*cc[t3-1]+wa1[i-1]*cc[t3]; in dradf2()
147 ti2=wa1[i-2]*cc[t3]-wa1[i-1]*cc[t3-1]; in dradf2()
171 static void dradf4(int ido,int l1,float *cc,float *ch,float *wa1, in dradf4() argument
213 cr2=wa1[i-2]*cc[t3-1]+wa1[i-1]*cc[t3]; in dradf4()
214 ci2=wa1[i-2]*cc[t3]-wa1[i-1]*cc[t3-1]; in dradf4()
636 static void dradb2(int ido,int l1,float *cc,float *ch,float *wa1){ in dradb2() argument
669 ch[t6-1]=wa1[i-2]*tr2-wa1[i-1]*ti2; in dradb2()
670 ch[t6]=wa1[i-2]*ti2+wa1[i-1]*tr2; in dradb2()
688 static void dradb3(int ido,int l1,float *cc,float *ch,float *wa1, in dradb3() argument
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| /external/webp/src/dsp/ |
| D | ssim_sse2.c | 113 const __m128i wa1 = _mm_mullo_epi16(a1, W); \
116 xm = _mm_add_epi16(xm, wa1); \
118 xxm = _mm_add_epi32(xxm, _mm_madd_epi16(a1, wa1)); \
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| /external/lmfit/lib/ |
| D | lmmin.c | 213 double* wa1 = (double*)pws; in lmmin() local
304 lm_qrfac(m, n, fjac, Pivot, wa1, wa2, wa3); in lmmin()
321 fjac[j*m+j] = wa1[j]; in lmmin()
390 wa1, wa2, wf, wa3); in lmmin()
403 wa3[i] -= fjac[j*m+i] * wa1[Pivot[j]]; in lmmin()
419 wa2[j] = x[j] - wa1[j]; in lmmin()
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| /external/lmfit/ |
| D | CHANGELOG | 130 - eliminate unncessary wa1 = -wa1 computation
131 - avoid passing wa3 to wa1, choose better names for work arrays in lm_par
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| /external/icu/icu4c/source/data/translit/ |
| D | Latn_Bopo.txt | 1300 wa1 ← ㄨㄚ;
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