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/external/eigen/doc/
DLeastSquares.dox3 /** \eigenManualPage LeastSquares Solving linear least squares systems
5 This page describes how to solve linear least squares systems using %Eigen. An overdetermined system
20 solve linear squares systems. It is not enough to compute only the singular values (the default for
22 computing least squares solutions:
37 The solve() method in QR decomposition classes also computes the least squares solution. There are
53 Finding the least squares solution of \a Ax = \a b is equivalent to solving the normal equation
DTutorialLinearAlgebra.dox184 \section TutorialLinAlgLeastsquares Least squares solving
186 The most accurate method to do least squares solving is with a SVD decomposition. Eigen provides one
187 as the JacobiSVD class, and its solve() is doing least-squares solving.
199 normal matrix or a QR decomposition. Our page on \link LeastSquares least squares solving \endlink
/external/skia/gm/
Dthinrects.cpp100 constexpr SkRect squares[] = { in DrawSquares() local
110 for (size_t j = 0; j < SK_ARRAY_COUNT(squares); ++j) { in DrawSquares()
111 canvas->drawRect(squares[j], p); in DrawSquares()
/external/skqp/gm/
Dthinrects.cpp100 constexpr SkRect squares[] = { in DrawSquares() local
110 for (size_t j = 0; j < SK_ARRAY_COUNT(squares); ++j) { in DrawSquares()
111 canvas->drawRect(squares[j], p); in DrawSquares()
/external/python/cpython2/Lib/test/
Dtest_generators.py1127 squares = [" " for j in range(n)]
1128 squares[row2col[i]] = "Q"
1129 print "|" + "|".join(squares) + "|"
1314 squares = [[None] * n for i in range(m)]
1318 squares[i1][j1] = format % k
1324 row = squares[i]
/external/tensorflow/tensorflow/core/graph/
Dgraph_partition_test.cc575 std::vector<ops::Square> squares; in TEST() local
577 squares.emplace_back(root.WithOpName(strings::StrCat("s", i)), in TEST()
579 squares.back().node()->AddAttr("_start_time", 50 - (i + 1)); in TEST()
584 for (const auto& s : squares) inputs.push_back(s); in TEST()
598 ASSERT_EQ(1 + squares.size() + placeholders.size(), nodes.size()); in TEST()
605 for (int i = 0; i < squares.size(); ++i) { in TEST()
670 std::vector<Square> squares; in TEST() local
671 squares.reserve(indexes.size()); in TEST()
673 squares.emplace_back(root.WithOpName(strings::StrCat("s", i)), in TEST()
675 squares.back().node()->AddAttr("_start_time", 500 - (i + 1)); in TEST()
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/external/tensorflow/tensorflow/core/api_def/base_api/
Dapi_def_MatrixSolveLs.pbtxt31 summary: "Solves one or more linear least-squares problems."
39 in the least squares sense.
51 \\(X = (A^H A + \lambda I)^{-1} A^H B\\), which solves the least-squares
64 least-squares solution, even when \\(A\\) is rank deficient. This path is
/external/ImageMagick/MagickCore/
Dsegment.c282 *squares; in Classify() local
509 squares=(double *) AcquireQuantumMemory(513UL,sizeof(*squares)); in Classify()
510 if (squares == (double *) NULL) in Classify()
513 squares+=255; in Classify()
515 squares[i]=(double) i*(double) i; in Classify()
609 distance_squared=squares[(ssize_t) ScaleQuantumToChar( in Classify()
611 ScaleQuantumToChar(ClampToQuantum(p->red))]+squares[(ssize_t) in Classify()
613 ScaleQuantumToChar(ClampToQuantum(p->green))]+squares[(ssize_t) in Classify()
620 distance_squared=squares[(ssize_t) ScaleQuantumToChar( in Classify()
622 ScaleQuantumToChar(ClampToQuantum(p->red))]+squares[ in Classify()
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/external/tensorflow/tensorflow/examples/android/jni/object_tracking/
Dobject_detector.h59 std::vector<BoundingSquare>* const squares) { in FillWithSquares() argument
68 squares->push_back(descriptor_area); in FillWithSquares()
74 squares->size(), starting_square_size, smallest_square_size, in FillWithSquares()
/external/python/cpython3/Lib/test/
Dtest_generators.py1423 squares = [" " for j in range(n)]
1424 squares[row2col[i]] = "Q"
1425 print("|" + "|".join(squares) + "|")
1610 squares = [[None] * n for i in range(m)]
1614 squares[i1][j1] = format % k
1620 row = squares[i]
/external/lmfit/man/
Dlmfit.pod11 lmfit - Levenberg-Marquardt least-squares minimization
16 B<lmfit> is a C library for Levenberg-Marquardt least-squares minimization and curve fitting. It is…
/external/fec/
Dsumsq_mmx_assist.s7 # Evaluate sum of squares of signed 16-bit input samples
49 # Evaluate sum of squares of signed 16-bit input samples
Dsumsq_sse2_assist.s6 # Evaluate sum of squares of signed 16-bit input samples
/external/tensorflow/tensorflow/contrib/tensor_forest/kernels/
Dtree_utils_test.cc44 Tensor squares = test::AsTensor<float>({29, 12}, {2}); in TEST() local
47 squares.unaligned_flat<float>(), 3), in TEST()
Dtree_utils.h98 float WeightedVariance(const T1& sums, const T2& squares, float count) { in WeightedVariance() argument
100 const auto e_x2 = squares / count; in WeightedVariance()
/external/lmfit/
Dlmfit.pc.in7 Description: Levenberg-Marquardt mean-squares minimization and curve fitting
Dconfigure.ac2 # Levenberg-Marquardt least squares fitting
/external/libvpx/libvpx/vp9/encoder/x86/
Dvp9_error_sse2.asm36 ; individual errors are max. 15bit+sign, so squares are 30bit, and
92 ; individual errors are max. 15bit+sign, so squares are 30bit, and
/external/python/cpython3/Doc/tutorial/
Dintroduction.rst382 >>> squares = [1, 4, 9, 16, 25]
383 >>> squares
389 >>> squares[0] # indexing returns the item
391 >>> squares[-1]
393 >>> squares[-3:] # slicing returns a new list
399 >>> squares[:]
404 >>> squares + [36, 49, 64, 81, 100]
Ddatastructures.rst197 For example, assume we want to create a list of squares, like::
199 >>> squares = []
201 ... squares.append(x**2)
203 >>> squares
207 after the loop completes. We can calculate the list of squares without any
210 squares = list(map(lambda x: x**2, range(10)))
214 squares = [x**2 for x in range(10)]
/external/python/cpython2/Doc/tutorial/
Dintroduction.rst476 >>> squares = [1, 4, 9, 16, 25]
477 >>> squares
483 >>> squares[0] # indexing returns the item
485 >>> squares[-1]
487 >>> squares[-3:] # slicing returns a new list
493 >>> squares[:]
498 >>> squares + [36, 49, 64, 81, 100]
Ddatastructures.rst252 For example, assume we want to create a list of squares, like::
254 >>> squares = []
256 ... squares.append(x**2)
258 >>> squares
263 squares = [x**2 for x in range(10)]
265 This is also equivalent to ``squares = map(lambda x: x**2, range(10))``,
/external/tensorflow/tensorflow/contrib/solvers/
DBUILD2 # Contains ops for iterative solvers for linear systems, linear least-squares
/external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/
Dgrow_stats.cc819 const auto& squares = cand.left_stats().regression().mean_output_squares(); in ExtractFromProto() local
822 left_square(split_num, i) = squares.value(i).float_value(); in ExtractFromProto()
851 auto* squares = cand->mutable_left_stats() in PackToProto() local
856 squares->add_value()->set_float_value(left_square(split_num, i)); in PackToProto()
/external/libaom/libaom/av1/encoder/x86/
Derror_sse2.asm38 ; individual errors are max. 15bit+sign, so squares are 30bit, and

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