Searched refs:epsilon (Results 1 - 25 of 159) sorted by relevance

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/external/eigen/unsupported/test/
H A Dcxx11_tensor_simple.cpp159 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
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/external/vulkan-validation-layers/libs/glm/gtc/
H A Depsilon.hpp24 /// @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
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/external/skia/src/pathops/
H A DSkPathOpsTypes.cpp12 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
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/external/vulkan-validation-layers/libs/glm/gtx/
H A Dmatrix_query.hpp59 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);
H A Dvector_query.hpp58 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);
/external/libcxx/test/std/language.support/support.limits/limits/numeric.limits.members/
H A Depsilon.pass.cpp12 // 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);
/external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/
H A DPoissonDistributionImpl.java70 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
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/external/eigen/test/
H A Dbicgstab.cpp20 bicgstab_colmajor_diag.setTolerance(NumTraits<T>::epsilon()*4);
21 bicgstab_colmajor_ilut.setTolerance(NumTraits<T>::epsilon()*4);
H A Dprec_inverse_4x4.cpp22 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() );
/external/libcups/cups/
H A Dpwg-private.h48 extern pwg_media_t *_pwgMediaNearSize(int width, int length, int epsilon);
/external/apache-commons-math/src/main/java/org/apache/commons/math/special/
H A DBeta.java66 * @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
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H A DGamma.java151 * @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
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/external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/linear/
H A DSimplexSolver.java39 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)) {
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H A DSimplexTableau.java96 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
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/external/replicaisland/src/com/replica/replicaisland/
H A DUtils.java27 public final static boolean close(float a, float b, float epsilon) { argument
28 return Math.abs(a - b) < epsilon;
/external/protobuf/js/binary/
H A Ddecoder_test.js54 * @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));
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/external/apache-commons-math/src/main/java/org/apache/commons/math/util/
H A DContinuedFraction.java81 * @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) {
/external/eigen/Eigen/src/SparseCore/
H A DSparseView.h38 * 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
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/external/eigen/Eigen/src/Core/
H A DNumTraits.h18 // 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(); }
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/external/eigen/unsupported/Eigen/src/NonLinearOptimization/
H A Dchkder.h25 const Scalar eps = sqrt(NumTraits<Scalar>::epsilon());
26 const Scalar epsf = chkder_factor * NumTraits<Scalar>::epsilon();
56 if (temp > NumTraits<Scalar>::epsilon() && temp < eps)
/external/libvorbis/lib/
H A Dlpc.c65 double epsilon; local
80 epsilon=1e-9*aut[0]+1e-10;
85 if(error<epsilon){
/external/deqp/framework/delibs/decpp/
H A DdeRandom.cpp91 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);
/external/google-benchmark/src/
H A Dbenchmark_api_internal.h40 return std::abs(n) < std::numeric_limits<double>::epsilon();
/external/libcxx/utils/google-benchmark/src/
H A Dbenchmark_api_internal.h40 return std::abs(n) < std::numeric_limits<double>::epsilon();
/external/apache-commons-math/src/main/java/org/apache/commons/math/linear/
H A DOpenMapRealVector.java47 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
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