Searched defs:weights (Results 1 - 25 of 47) sorted by relevance

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/external/libopus/src/
H A Dmlp_data.c2 It contains multi-layer perceptron (MLP) weights. */
8 static const float weights[422] = { variable
104 weights
H A Dmlp.h36 const float *weights; member in struct:__anon9031
/external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/
H A DLeastSquaresConverter.java49 * This class support combination of residuals with or without weights and correlations.
66 /** Optional weights for the residuals. */
67 private final double[] weights; field in class:LeastSquaresConverter
80 this.weights = null;
84 /** Build a simple converter for uncorrelated residuals with the specific weights.
96 * In this case, the weights array should be initialized with value
102 * weights array must have consistent sizes or a {@link FunctionEvaluationException} will be
107 * @param weights weights to apply to the residuals
108 * @exception IllegalArgumentException if the observations vector and the weights
112 LeastSquaresConverter(final MultivariateVectorialFunction function, final double[] observations, final double[] weights) argument
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H A DDifferentiableMultivariateVectorialOptimizer.java101 * @param weights weight for the least squares cost computation
110 double[] target, double[] weights,
109 optimize(DifferentiableMultivariateVectorialFunction f, double[] target, double[] weights, double[] startPoint) argument
H A DMultiStartDifferentiableMultivariateVectorialOptimizer.java177 final double[] target, final double[] weights,
192 optima[i] = optimizer.optimize(f, target, weights,
221 sum += weights[i] * ri * ri;
176 optimize(final DifferentiableMultivariateVectorialFunction f, final double[] target, final double[] weights, final double[] startPoint) argument
/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/
H A DWeightedEvaluation.java29 * using the supplied weights.
32 * @param weights array of weights
35 double evaluate(double[] values, double[] weights); argument
39 * in the input array, using corresponding entries in the supplied weights array.
42 * @param weights array of weights
47 double evaluate(double[] values, double[] weights, int begin, int length); argument
H A DAbstractUnivariateStatistic.java165 * and the weights are all non-negative, non-NaN, finite, and not all zero.
169 * positive length and the weights array contains legitimate values.</li>
172 * <li>the weights array is null</li>
173 * <li>the weights array does not have the same length as the values array</li>
174 * <li>the weights array contains one or more infinite values</li>
175 * <li>the weights array contains one or more NaN values</li>
176 * <li>the weights array contains negative values</li>
184 * @param weights the weights array
193 final double[] weights,
191 test( final double[] values, final double[] weights, final int begin, final int length) argument
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/external/clang/test/Profile/
H A Dc-general.c123 // Never reached -> no weights
140 // Never reached -> no weights
199 // never reached -> no weights
216 static int weights[] = {1, 2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 5}; local
218 // No cases -> no weights
219 switch (weights[0]) {
228 for (int i = 0, len = sizeof(weights) / sizeof(weights[0]); i < len; ++i) {
231 switch (i[weights]) {
278 // Never reached -> no weights
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/external/apache-commons-math/src/main/java/org/apache/commons/math/analysis/integration/
H A DLegendreGaussIntegrator.java45 * Legendre polynomial. The weights a<sub>i</sub> of the quadrature formula
120 private final double[] weights; field in class:LegendreGaussIntegrator
135 weights = WEIGHTS_2;
139 weights = WEIGHTS_3;
143 weights = WEIGHTS_4;
147 weights = WEIGHTS_5;
227 sum += weights[j] * f.value(midPoint + halfStep * abscissas[j]);
/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/moment/
H A DMean.java180 * described above is used here, with weights applied in computing both the original
185 * <li>the weights array is null</li>
186 * <li>the weights array does not have the same length as the values array</li>
187 * <li>the weights array contains one or more infinite values</li>
188 * <li>the weights array contains one or more NaN values</li>
189 * <li>the weights array contains negative values</li>
194 * @param weights the weights array
201 public double evaluate(final double[] values, final double[] weights, argument
203 if (test(values, weights, begi
244 evaluate(final double[] values, final double[] weights) argument
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H A DVariance.java266 * &Sigma;(weights[i]*(values[i] - weightedMean)<sup>2</sup>)/(&Sigma;(weights[i]) - 1)
271 * weights are equal, unless all weights are equal to 1. The formula assumes that
272 * weights are to be treated as "expansion values," as will be the case if for example
273 * the weights represent frequency counts. To normalize weights so that the denominator
275 * <code>evaluate(values, MathUtils.normalizeArray(weights, values.length)); </code>
282 * <li>the weights array is null</li>
283 * <li>the weights arra
302 evaluate(final double[] values, final double[] weights, final int begin, final int length) argument
358 evaluate(final double[] values, final double[] weights) argument
490 evaluate(final double[] values, final double[] weights, final double mean, final int begin, final int length) argument
564 evaluate(final double[] values, final double[] weights, final double mean) argument
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/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/summary/
H A DProduct.java139 * <li>the weights array is null</li>
140 * <li>the weights array does not have the same length as the values array</li>
141 * <li>the weights array contains one or more infinite values</li>
142 * <li>the weights array contains one or more NaN values</li>
143 * <li>the weights array contains negative values</li>
148 * weighted product = &prod;values[i]<sup>weights[i]</sup>
150 * that is, the weights are applied as exponents when computing the weighted product.</p>
153 * @param weights the weights array
160 public double evaluate(final double[] values, final double[] weights, argument
195 evaluate(final double[] values, final double[] weights) argument
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H A DSum.java138 * <li>the weights array is null</li>
139 * <li>the weights array does not have the same length as the values array</li>
140 * <li>the weights array contains one or more infinite values</li>
141 * <li>the weights array contains one or more NaN values</li>
142 * <li>the weights array contains negative values</li>
147 * weighted sum = &Sigma;(values[i] * weights[i])
151 * @param weights the weights array
158 public double evaluate(final double[] values, final double[] weights, argument
161 if (test(values, weights, begi
192 evaluate(final double[] values, final double[] weights) argument
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/external/freetype/src/base/
H A Dftlcdfil.c38 FT_Byte* weights = library->lcd_weights; local
54 /* the values in `weights' can exceed 0xFF */
63 fir[0] = weights[2] * val1;
64 fir[1] = weights[3] * val1;
65 fir[2] = weights[4] * val1;
69 fir[0] += weights[1] * val1;
70 fir[1] += weights[2] * val1;
71 fir[2] += weights[3] * val1;
72 fir[3] += weights[4] * val1;
80 pix = fir[0] + weights[
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/external/jmonkeyengine/engine/src/core/com/jme3/animation/
H A DPoseTrack.java56 float[] weights; field in class:PoseTrack.PoseFrame
58 public PoseFrame(Pose[] poses, float[] weights) { argument
60 this.weights = weights;
71 result.weights = this.weights.clone();
87 out.write(weights, "weights", null);
93 weights = in.readFloatArray("weights", nul
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/external/openfst/src/include/fst/script/
H A Dshortest-path.h65 vector<typename Arc::Weight> weights; local
73 ArcFilter>::Construct(ifst, &weights);
78 ShortestPath(ifst, ofst, &weights, spopts);
85 ArcFilter>::Construct(ifst, &weights);
90 ShortestPath(ifst, ofst, &weights, spopts);
97 ArcFilter >::Construct(ifst, &weights);
102 ShortestPath(ifst, ofst, &weights, spopts);
109 ArcFilter>::Construct(ifst, &weights);
114 ShortestPath(ifst, ofst, &weights, spopts);
121 ArcFilter>::Construct(ifst, &weights);
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H A Drmepsilon.h174 vector<typename Arc::Weight> weights; local
176 RmEpsilonHelper(fst, &weights, opts);
178 // Copy the weights back
179 args->arg2->resize(weights.size());
180 for (unsigned i = 0; i < weights.size(); ++i) {
181 (*args->arg2)[i] = WeightClass(weights[i]);
H A Dshortest-distance.h95 const Fst<Arc> &fst, const vector<typename Arc::Weight> *weights) {
106 vector<typename Arc::Weight> weights; local
112 fst, &weights);
115 ShortestDistance(fst, &weights, sdopts);
122 fst, &weights);
126 ShortestDistance(fst, &weights, sdopts);
133 fst, &weights);
137 ShortestDistance(fst, &weights, sdopts);
145 fst, &weights);
149 ShortestDistance(fst, &weights, sdopt
94 Construct( const Fst<Arc> &fst, const vector<typename Arc::Weight> *weights) argument
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/external/pdfium/third_party/freetype/src/base/
H A Dftlcdfil.c38 FT_Byte* weights = library->lcd_weights; local
54 /* the values in `weights' can exceed 0xFF */
63 fir[0] = weights[2] * val1;
64 fir[1] = weights[3] * val1;
65 fir[2] = weights[4] * val1;
69 fir[0] += weights[1] * val1;
70 fir[1] += weights[2] * val1;
71 fir[2] += weights[3] * val1;
72 fir[3] += weights[4] * val1;
80 pix = fir[0] + weights[
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/external/apache-commons-math/src/main/java/org/apache/commons/math/analysis/interpolation/
H A DLoessInterpolator.java189 * @param weights point weights: coefficients by which the robustness weight of a point is multiplied
199 public final double[] smooth(final double[] xval, final double[] yval, final double[] weights) argument
214 checkAllFiniteReal(weights, LocalizedFormats.NON_REAL_FINITE_WEIGHT);
242 // starting with all robustness weights set to 1.
254 updateBandwidthInterval(xval, weights, i, bandwidthInterval);
270 // the product of robustness weights and the tricube
286 final double w = tricube(dist * denom) * robustnessWeights[k] * weights[k];
313 // No need to recompute the robustness weights at the last
319 // Recompute the robustness weights
386 updateBandwidthInterval(final double[] xval, final double[] weights, final int i, final int[] bandwidthInterval) argument
408 nextNonzero(final double[] weights, final int i) argument
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/external/opencv/cv/src/
H A Dcvlinefit.cpp46 icvFitLine2D_wods( CvPoint2D32f * points, int _count, float *weights, float *line ) argument
56 if( weights == 0 )
72 x += weights[i] * points[i].x;
73 y += weights[i] * points[i].y;
74 x2 += weights[i] * points[i].x * points[i].x;
75 y2 += weights[i] * points[i].y * points[i].y;
76 xy += weights[i] * points[i].x * points[i].y;
77 w += weights[i];
102 icvFitLine3D_wods( CvPoint3D32f * points, int count, float *weights, float *line ) argument
116 if( weights )
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/external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/general/
H A DAbstractLeastSquaresOptimizer.java255 * the reciprocal of the weights.
327 final double[] target, final double[] weights,
331 if (target.length != weights.length) {
333 target.length, weights.length);
345 residualsWeights = weights.clone();
326 optimize(final DifferentiableMultivariateVectorialFunction f, final double[] target, final double[] weights, final double[] startPoint) argument
/external/eigen/unsupported/Eigen/src/MatrixFunctions/
H A DMatrixLogarithm.h238 const RealScalar weights[] = { 0.2777777777777777777777777777777778L, 0.4444444444444444444444444444444444L, local
244 result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
254 const RealScalar weights[] = { 0.1739274225687269286865319746109997L, 0.3260725774312730713134680253890003L, local
260 result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
271 const RealScalar weights[] = { 0.1184634425280945437571320203599587L, 0.2393143352496832340206457574178191L, local
278 result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
289 const RealScalar weights[] = { 0.0856622461895851725201480710863665L, 0.1803807865240693037849167569188581L, local
296 result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
308 const RealScalar weights[] = { 0.0647424830844348466353057163395410L, 0.1398526957446383339507338857118898L, local
316 result += weights[
328 const RealScalar weights[] = { 0.0506142681451881295762656771549811L, 0.1111905172266872352721779972131204L, local
349 const RealScalar weights[] = { 0.0406371941807872059859460790552618L, 0.0903240803474287020292360156214564L, local
371 const RealScalar weights[] = { 0.0333356721543440687967844049466659L, 0.0747256745752902965728881698288487L, local
394 const RealScalar weights[] = { 0.0278342835580868332413768602212743L, 0.0627901847324523123173471496119701L, local
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/external/jmonkeyengine/engine/src/core/com/jme3/math/
H A DSpline.java28 private float[] weights; //weights of NURBS spline field in class:Spline
57 throw new IllegalArgumentException("To create NURBS spline use: 'public Spline(Vector3f[] controlPoints, float[] weights, float[] nurbKnots)' constructor!");
86 throw new IllegalArgumentException("To create NURBS spline use: 'public Spline(Vector3f[] controlPoints, float[] weights, float[] nurbKnots)' constructor!");
111 this.weights = new float[controlPoints.size()];
113 this.basisFunctionDegree = nurbKnots.size() - weights.length;
117 this.weights[i] = controlPoint.w;
379 return knots.get(weights.length);
391 * This method returns NURBS' spline weights.
392 * @return NURBS' spline weights
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/external/skia/src/core/
H A DSkPathRef.cpp287 SkScalar** weights) {
356 SkASSERT(weights);
357 *weights = fConicWeights.append(numVbs);
285 growForRepeatedVerb(int verb, int numVbs, SkScalar** weights) argument

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