/external/eigen/unsupported/test/ |
H A D | cxx11_tensor_simple.cpp | 159 Tensor<int, 3> epsilon(3,3,3); 160 epsilon.setZero(); 161 epsilon(0,1,2) = epsilon(2,0,1) = epsilon(1,2,0) = 1; 162 epsilon(2,1,0) = epsilon(0,2,1) = epsilon(1,0,2) = -1; 164 VERIFY_IS_EQUAL((epsilon.size()), 27); 165 VERIFY_IS_EQUAL((epsilon 297 Tensor<int, 3> epsilon; local [all...] |
/external/vulkan-validation-layers/libs/glm/gtc/ |
H A D | epsilon.hpp | 24 /// @file glm/gtc/epsilon.hpp 35 /// @brief Comparison functions for a user defined epsilon values. 37 /// <glm/gtc/epsilon.hpp> need to be included to use these functionalities. 56 /// Returns the component-wise comparison of |x - y| < epsilon. 64 T const & epsilon); 66 /// Returns the component-wise comparison of |x - y| < epsilon. 74 genType const & epsilon); 76 /// Returns the component-wise comparison of |x - y| < epsilon. 84 typename genType::value_type const & epsilon); 86 /// Returns the component-wise comparison of |x - y| >= epsilon [all...] |
/external/skia/src/pathops/ |
H A D | SkPathOpsTypes.cpp | 12 static bool arguments_denormalized(float a, float b, int epsilon) { argument 13 float denormalizedCheck = FLT_EPSILON * epsilon / 2; 19 static bool equal_ulps(float a, float b, int epsilon, int depsilon) { argument 26 return aBits < bBits + epsilon && bBits < aBits + epsilon; 29 static bool equal_ulps_no_normal_check(float a, float b, int epsilon, int depsilon) { argument 33 return aBits < bBits + epsilon && bBits < aBits + epsilon; 36 static bool equal_ulps_pin(float a, float b, int epsilon, int depsilon) { argument 46 return aBits < bBits + epsilon 49 d_equal_ulps(float a, float b, int epsilon) argument 56 not_equal_ulps(float a, float b, int epsilon) argument 66 not_equal_ulps_pin(float a, float b, int epsilon) argument 79 d_not_equal_ulps(float a, float b, int epsilon) argument 86 less_ulps(float a, float b, int epsilon) argument 96 less_or_equal_ulps(float a, float b, int epsilon) argument [all...] |
/external/vulkan-validation-layers/libs/glm/gtx/ |
H A D | matrix_query.hpp | 59 GLM_FUNC_DECL bool isNull(detail::tmat2x2<T, P> const & m, T const & epsilon); 64 GLM_FUNC_DECL bool isNull(detail::tmat3x3<T, P> const & m, T const & epsilon); 69 GLM_FUNC_DECL bool isNull(detail::tmat4x4<T, P> const & m, T const & epsilon); 74 GLM_FUNC_DECL bool isIdentity(matType<T, P> const & m, T const & epsilon); 79 GLM_FUNC_DECL bool isNormalized(detail::tmat2x2<T, P> const & m, T const & epsilon); 84 GLM_FUNC_DECL bool isNormalized(detail::tmat3x3<T, P> const & m, T const & epsilon); 89 GLM_FUNC_DECL bool isNormalized(detail::tmat4x4<T, P> const & m, T const & epsilon); 94 GLM_FUNC_DECL bool isOrthogonal(matType<T, P> const & m, T const & epsilon);
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H A D | vector_query.hpp | 58 GLM_FUNC_DECL bool areCollinear(vecType<T, P> const & v0, vecType<T, P> const & v1, T const & epsilon); 63 GLM_FUNC_DECL bool areOrthogonal(vecType<T, P> const & v0, vecType<T, P> const & v1, T const & epsilon); 68 GLM_FUNC_DECL bool isNormalized(vecType<T, P> const & v, T const & epsilon); 73 GLM_FUNC_DECL bool isNull(vecType<T, P> const & v, T const & epsilon); 78 GLM_FUNC_DECL vecType<bool, P> isCompNull(vecType<T, P> const & v, T const & epsilon); 83 GLM_FUNC_DECL bool areOrthonormal(vecType<T, P> const & v0, vecType<T, P> const & v1, T const & epsilon);
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/external/libcxx/test/std/language.support/support.limits/limits/numeric.limits.members/ |
H A D | epsilon.pass.cpp | 12 // epsilon() 22 assert(std::numeric_limits<T>::epsilon() == expected); 23 assert(std::numeric_limits<const T>::epsilon() == expected); 24 assert(std::numeric_limits<volatile T>::epsilon() == expected); 25 assert(std::numeric_limits<const volatile T>::epsilon() == expected);
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/external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
H A D | PoissonDistributionImpl.java | 70 private double epsilon = DEFAULT_EPSILON; field in class:PoissonDistributionImpl 88 * @param epsilon the convergence criteria for cumulative probabilites 92 public PoissonDistributionImpl(double p, double epsilon, int maxIterations) { argument 94 this.epsilon = epsilon; 102 * @param epsilon the convergence criteria for cumulative probabilites 105 public PoissonDistributionImpl(double p, double epsilon) { argument 107 this.epsilon = epsilon; 219 return Gamma.regularizedGammaQ((double) x + 1, mean, epsilon, maxIteration [all...] |
/external/eigen/test/ |
H A D | bicgstab.cpp | 20 bicgstab_colmajor_diag.setTolerance(NumTraits<T>::epsilon()*4); 21 bicgstab_colmajor_ilut.setTolerance(NumTraits<T>::epsilon()*4);
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H A D | prec_inverse_4x4.cpp | 22 double error = double( (m*inv-MatrixType::Identity()).norm() / NumTraits<Scalar>::epsilon() ); 42 } while(absdet < NumTraits<Scalar>::epsilon()); 44 double error = double( (m*inv-MatrixType::Identity()).norm() * absdet / NumTraits<Scalar>::epsilon() );
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/external/libcups/cups/ |
H A D | pwg-private.h | 48 extern pwg_media_t *_pwgMediaNearSize(int width, int length, int epsilon);
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/external/apache-commons-math/src/main/java/org/apache/commons/math/special/ |
H A D | Beta.java | 66 * @param epsilon When the absolute value of the nth item in the 67 * series is less than epsilon the approximation ceases 73 double epsilon) throws MathException 75 return regularizedBeta(x, a, b, epsilon, Integer.MAX_VALUE); 110 * @param epsilon When the absolute value of the nth item in the 111 * series is less than epsilon the approximation ceases 118 final double b, double epsilon, int maxIterations) throws MathException 127 ret = 1.0 - regularizedBeta(1.0 - x, b, a, epsilon, maxIterations); 153 FastMath.log(a) - logBeta(a, b, epsilon, maxIterations)) * 154 1.0 / fraction.evaluate(x, epsilon, maxIteration 72 regularizedBeta(double x, double a, double b, double epsilon) argument 117 regularizedBeta(double x, final double a, final double b, double epsilon, int maxIterations) argument 188 logBeta(double a, double b, double epsilon, int maxIterations) argument [all...] |
H A D | Gamma.java | 151 * @param epsilon When the absolute value of the nth item in the 152 * series is less than epsilon the approximation ceases 160 double epsilon, 173 ret = 1.0 - regularizedGammaQ(a, x, epsilon, maxIterations); 179 while (FastMath.abs(an/sum) > epsilon && n < maxIterations && sum < Double.POSITIVE_INFINITY) { 228 * @param epsilon When the absolute value of the nth item in the 229 * series is less than epsilon the approximation ceases 237 double epsilon, 250 ret = 1.0 - regularizedGammaP(a, x, epsilon, maxIterations); 266 ret = 1.0 / cf.evaluate(x, epsilon, maxIteration 158 regularizedGammaP(double a, double x, double epsilon, int maxIterations) argument 235 regularizedGammaQ(final double a, double x, double epsilon, int maxIterations) argument [all...] |
/external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/linear/ |
H A D | SimplexSolver.java | 39 protected final double epsilon; field in class:SimplexSolver 50 * @param epsilon the amount of error to accept in floating point comparisons 52 public SimplexSolver(final double epsilon) { argument 53 this.epsilon = epsilon; 65 if (MathUtils.compareTo(tableau.getEntry(0, i), minValue, epsilon) < 0) { 86 if (MathUtils.compareTo(entry, 0, epsilon) > 0) { 88 if (MathUtils.equals(ratio, minRatio, epsilon)) { 106 if (MathUtils.equals(tableau.getEntry(row, column), 1, epsilon) && 165 if (!MathUtils.equals(tableau.getEntry(0, tableau.getRhsOffset()), 0, epsilon)) { [all...] |
H A D | SimplexTableau.java | 96 private final double epsilon; field in class:SimplexTableau 105 * @param epsilon amount of error to accept in floating point comparisons 110 final double epsilon) { 114 this.epsilon = epsilon; 288 if (MathUtils.equals(getEntry(i, col), 1.0, epsilon) && (row == null)) { 290 } else if (!MathUtils.equals(getEntry(i, col), 0.0, epsilon)) { 311 if (MathUtils.compareTo(tableau.getEntry(0, i), 0, epsilon) > 0) { 356 if (MathUtils.compareTo(tableau.getEntry(0, i), 0, epsilon) < 0) { 547 (epsilon 107 SimplexTableau(final LinearObjectiveFunction f, final Collection<LinearConstraint> constraints, final GoalType goalType, final boolean restrictToNonNegative, final double epsilon) argument [all...] |
/external/replicaisland/src/com/replica/replicaisland/ |
H A D | Utils.java | 27 public final static boolean close(float a, float b, float epsilon) { argument 28 return Math.abs(a - b) < epsilon;
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/external/protobuf/js/binary/ |
H A D | decoder_test.js | 54 * @param {number} epsilon 60 writeValue, epsilon, upperLimit, filter) { 65 writeValue.call(encoder, filter(epsilon)); 69 for (var cursor = epsilon; cursor < upperLimit; cursor *= 1.1) { 77 assertEquals(filter(epsilon), readValue.call(decoder)); 81 for (var cursor = epsilon; cursor < upperLimit; cursor *= 1.1) { 95 * @param {number} epsilon 102 writeValue, epsilon, lowerLimit, upperLimit, filter) { 107 writeValue.call(encoder, filter(-epsilon)); 109 writeValue.call(encoder, filter(epsilon)); [all...] |
/external/apache-commons-math/src/main/java/org/apache/commons/math/util/ |
H A D | ContinuedFraction.java | 81 * @param epsilon maximum error allowed. 85 public double evaluate(double x, double epsilon) throws MathException { argument 86 return evaluate(x, epsilon, Integer.MAX_VALUE); 121 * @param epsilon maximum error allowed. 126 public double evaluate(double x, double epsilon, int maxIterations) argument 136 while (n < maxIterations && relativeError > epsilon) {
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/external/eigen/Eigen/src/SparseCore/ |
H A D | SparseView.h | 38 * entries smaller than \c reference * \c epsilon are removed. 55 const RealScalar &epsilon = NumTraits<Scalar>::dummy_precision()) 56 : m_matrix(mat), m_reference(reference), m_epsilon(epsilon) {} 69 RealScalar epsilon() const { return m_epsilon; } function in class:Eigen::SparseView 117 while((bool(*this)) && internal::isMuchSmallerThan(value(), m_view.reference(), m_view.epsilon())) 186 while((bool(*this)) && internal::isMuchSmallerThan(value(), m_sve.m_view.reference(), m_sve.m_view.epsilon())) 210 * \a reference * \a epsilon removed. 218 * S = D.sparseView(reference,epsilon); 221 * and \a epsilon is a tolerance factor defaulting to NumTraits<Scalar>::dummy_precision(). 226 const typename NumTraits<Scalar>::Real& epsilon) cons [all...] |
/external/eigen/Eigen/src/Core/ |
H A D | NumTraits.h | 18 // 0 for integer types, and log10(epsilon()) otherwise. 34 return int(ceil(-log10(NumTraits<Real>::epsilon()))); 78 * \li An epsilon() function which, unlike <a href="http://en.cppreference.com/w/cpp/types/numeric_limits/epsilon">std::numeric_limits::epsilon()</a>, 80 * \li A dummy_precision() function returning a weak epsilon value. It is mainly used as a default 110 static inline Real epsilon() 112 return numext::numeric_limits<T>::epsilon(); 186 static inline Real epsilon() { return NumTraits<Real>::epsilon(); } [all...] |
/external/eigen/unsupported/Eigen/src/NonLinearOptimization/ |
H A D | chkder.h | 25 const Scalar eps = sqrt(NumTraits<Scalar>::epsilon()); 26 const Scalar epsf = chkder_factor * NumTraits<Scalar>::epsilon(); 56 if (temp > NumTraits<Scalar>::epsilon() && temp < eps)
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/external/libvorbis/lib/ |
H A D | lpc.c | 65 double epsilon; local 80 epsilon=1e-9*aut[0]+1e-10; 85 if(error<epsilon){
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/external/deqp/framework/delibs/decpp/ |
H A D | deRandom.cpp | 91 const float epsilon = 0.01f; local 94 DE_TEST_ASSERT(de::abs(expected[i] - rnd.getFloat()) < epsilon); 101 const float epsilon = 0.01f; 104 DE_TEST_ASSERT(de::abs(expected[i] - rnd.getFloat(-542.2f, 1248.7f)) < epsilon);
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/external/google-benchmark/src/ |
H A D | benchmark_api_internal.h | 40 return std::abs(n) < std::numeric_limits<double>::epsilon();
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/external/libcxx/utils/google-benchmark/src/ |
H A D | benchmark_api_internal.h | 40 return std::abs(n) < std::numeric_limits<double>::epsilon();
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/external/apache-commons-math/src/main/java/org/apache/commons/math/linear/ |
H A D | OpenMapRealVector.java | 47 private final double epsilon; field in class:OpenMapRealVector 73 * @param epsilon The tolerance for having a value considered zero 75 public OpenMapRealVector(int dimension, double epsilon) { argument 78 this.epsilon = epsilon; 89 epsilon = v.epsilon; 105 * @param epsilon The tolerance for having a value considered zero 107 public OpenMapRealVector(int dimension, int expectedSize, double epsilon) { argument 110 this.epsilon 128 OpenMapRealVector(double[] values, double epsilon) argument 155 OpenMapRealVector(Double[] values, double epsilon) argument [all...] |