/external/ImageMagick/MagickCore/ |
H A D | morphology.h | 116 *values; member in struct:_KernelInfo
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H A D | thread.c | 57 **values, 106 (*keys)->values=AcquireQuantumMemory((*keys)->number_threads, 108 if ((*keys)->values == (void *) NULL) 111 (void) memset((*keys)->values,0,(*keys)->number_threads* 160 (keys->values[i] != (void *) NULL)) 162 keys->destructor(keys->values[i]); 163 keys->values[i]=(void *) NULL; 207 return(keys->values[GetOpenMPThreadId()]); 252 keys->values[GetOpenMPThreadId()]=(void *) value; 55 **values, member in struct:_MagickThreadValue
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/external/aac/libAACenc/src/ |
H A D | bit_cnt.cpp | 109 static void FDKaacEnc_count1_2_3_4_5_6_7_8_9_10_11(const SHORT *RESTRICT values, argument 127 t0= values[i+0]; 128 t1= values[i+1]; 129 t2= values[i+2]; 130 t3= values[i+3]; 185 static void FDKaacEnc_count3_4_5_6_7_8_9_10_11(const SHORT *RESTRICT values, argument 203 t0= values[i+0]; 204 t1= values[i+1]; 205 t2= values[i+2]; 206 t3= values[ 256 FDKaacEnc_count5_6_7_8_9_10_11(const SHORT *RESTRICT values, const INT width, INT *bitCount) argument 311 FDKaacEnc_count7_8_9_10_11(const SHORT *RESTRICT values, const INT width, INT *bitCount) argument 361 FDKaacEnc_count9_10_11(const SHORT *RESTRICT values, const INT width, INT *bitCount) argument 408 FDKaacEnc_count11(const SHORT *RESTRICT values, const INT width, INT *bitCount) argument 449 FDKaacEnc_countEsc(const SHORT *RESTRICT values, const INT width, INT *RESTRICT bitCount) argument 519 FDKaacEnc_bitCount(const SHORT *values, const INT width, INT maxVal, INT *bitCount) argument 545 FDKaacEnc_countValues(SHORT *RESTRICT values, INT width, INT codeBook) argument 779 FDKaacEnc_codeValues(SHORT *RESTRICT values, INT width, INT codeBook, HANDLE_FDK_BITSTREAM hBitstream) argument [all...] |
/external/androidplot/AndroidPlot-Core/src/main/java/com/androidplot/pie/ |
H A D | PieRenderer.java | 57 double[] values = getValues(); 58 double scale = calculateScale(values); 69 float sweep = (float) (scale * (values[i]) * 360); 176 private double calculateScale(double[] values) { argument 178 for (int i = 0; i < values.length; i++) { 179 total += values[i];
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/external/antlr/antlr-3.4/lib/ |
H A D | antlr-3.4-complete.jar | META-INF/ META-INF/MANIFEST.MF org/ org/antlr/ org/antlr/analysis/ org/antlr/codegen/ org/ ... |
/external/antlr/antlr-3.4/runtime/ActionScript/project/lib/ |
H A D | FlexAntTasks.jar | META-INF/ META-INF/MANIFEST.MF com/ com/adobe/ com/adobe/ac/ com/adobe/ac/ant/ ... |
/external/antlr/antlr-3.4/runtime/Java/src/main/java/org/antlr/runtime/misc/ |
H A D | DoubleKeyMap.java | 34 /** Get all values associated with primary key */ 35 public Collection<Value> values(Key1 k1) { method in class:DoubleKeyMap 38 return data2.values(); 53 public Collection<Value> values() { method in class:DoubleKeyMap 55 for (Map<Key2, Value> k2 : data.values()) { 56 for (Value v : k2.values()) {
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/external/apache-commons-math/src/main/java/org/apache/commons/math/analysis/interpolation/ |
H A D | LoessInterpolator.java | 170 * @param yval the values for the interpolation points 174 * <li> Arguments and values are of the same size that is greater than zero</li> 176 * <li> All arguments and values are finite real numbers</li> 188 * @param yval the values for the interpolation points 190 * @return values of the loess fit at corresponding original abscissae 193 * <li> Arguments and values are of the same size that is greater than zero</li> 195 * <li> All arguments and values are finite real numbers</li> 350 * @param yval the values for the interpolation points 351 * @return values of the loess fit at corresponding original abscissae 354 * <li> Arguments and values ar 436 checkAllFiniteReal(final double[] values, final Localizable pattern) argument [all...] |
/external/apache-commons-math/src/main/java/org/apache/commons/math/linear/ |
H A D | OpenMapRealVector.java | 116 * @param values The set of values to create from 118 public OpenMapRealVector(double[] values) { argument 119 this(values, DEFAULT_ZERO_TOLERANCE); 125 * @param values The set of values to create from 128 public OpenMapRealVector(double[] values, double epsilon) { argument 129 virtualSize = values.length; 132 for (int key = 0; key < values.length; key++) { 133 double value = values[ke 145 OpenMapRealVector(Double[] values) argument 155 OpenMapRealVector(Double[] values, double epsilon) argument [all...] |
H A D | SparseFieldVector.java | 101 * @param values The set of values to create from 103 public SparseFieldVector(Field<T> field, T[] values) { argument 105 virtualSize = values.length; 107 for (int key = 0; key < values.length; key++) { 108 T value = values[key];
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/external/apache-commons-math/src/main/java/org/apache/commons/math/random/ |
H A D | ValueServer.java | 29 * Generates values for use in simulation applications. 31 * How values are generated is determined by the <code>mode</code> 34 * Supported <code>mode</code> values are: <ul> 37 * <li> UNIFORM_MODE -- generates uniformly distributed random values with 39 * <li> EXPONENTIAL_MODE -- generates exponentially distributed random values 41 * <li> GAUSSIAN_MODE -- generates Gaussian distributed random values with 69 /** mode determines how values are generated. */ 72 /** URI to raw data values. */ 133 * Fills the input array with values generated using getNext() repeatedly. 135 * @param values arra 138 fill(double[] values) argument [all...] |
/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/ |
H A D | StatUtils.java | 79 * Returns the sum of the values in the input array, or 85 * @param values array of values to sum 86 * @return the sum of the values or <code>Double.NaN</code> if the array 90 public static double sum(final double[] values) { argument 91 return SUM.evaluate(values); 101 * @param values the input array 104 * @return the sum of the values or Double.NaN if length = 0 108 public static double sum(final double[] values, final int begin, argument 110 return SUM.evaluate(values, begi 124 sumSq(final double[] values) argument 142 sumSq(final double[] values, final int begin, final int length) argument 157 product(final double[] values) argument 175 product(final double[] values, final int begin, final int length) argument 194 sumLog(final double[] values) argument 216 sumLog(final double[] values, final int begin, final int length) argument 234 mean(final double[] values) argument 255 mean(final double[] values, final int begin, final int length) argument 273 geometricMean(final double[] values) argument 294 geometricMean(final double[] values, final int begin, final int length) argument 315 variance(final double[] values) argument 339 variance(final double[] values, final int begin, final int length) argument 370 variance(final double[] values, final double mean, final int begin, final int length) argument 397 variance(final double[] values, final double mean) argument 418 max(final double[] values) argument 444 max(final double[] values, final int begin, final int length) argument 466 min(final double[] values) argument 492 min(final double[] values, final int begin, final int length) argument 520 percentile(final double[] values, final double p) argument 551 percentile(final double[] values, final int begin, final int length, final double p) argument [all...] |
/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/ |
H A D | AbstractStorelessUnivariateStatistic.java | 52 * @param values input array 57 public double evaluate(final double[] values) { argument 58 if (values == null) { 61 return evaluate(values, 0, values.length); 79 * @param values the input array 86 public double evaluate(final double[] values, final int begin, final int length) { argument 87 if (test(values, begin, length)) { 89 incrementAll(values, begin, length); 119 * Throws IllegalArgumentException if the input values arra 125 incrementAll(double[] values) argument 144 incrementAll(double[] values, int begin, int length) argument [all...] |
H A D | AbstractUnivariateStatistic.java | 49 * @param values data array to store (may be null to remove stored data) 52 public void setData(final double[] values) { argument 53 storedData = (values == null) ? null : values.clone(); 74 * @param values data array to store 79 public void setData(final double[] values, final int begin, final int length) { argument 81 System.arraycopy(values, begin, storedData, 0, length); 98 public double evaluate(final double[] values) { argument 99 test(values, 0, 0); 100 return evaluate(values, 106 evaluate(final double[] values, final int begin, final int length) argument 132 test( final double[] values, final int begin, final int length) argument 191 test( final double[] values, final double[] weights, final int begin, final int length) argument [all...] |
H A D | StorelessUnivariateStatistic.java | 22 * values and updating internal state. 26 * sample values.</p> 40 * all values in the values array. Does not clear the statistic first -- 41 * i.e., the values are added <strong>incrementally</strong> to the dataset. 43 * @param values array holding the new values to add 46 void incrementAll(double[] values); argument 50 * the values in the designated portion of the values arra 59 incrementAll(double[] values, int start, int length) argument [all...] |
H A D | UnivariateStatistic.java | 30 * @param values input array 33 double evaluate(double[] values); argument 39 * @param values the input array 44 double evaluate(double[] values, int begin, int length); argument
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H A D | WeightedEvaluation.java | 31 * @param values input array 35 double evaluate(double[] values, double[] weights); argument 41 * @param values the input array 47 double evaluate(double[] values, double[] weights, int begin, int length); argument
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/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/moment/ |
H A D | GeometricMean.java | 30 * geometric mean </a> of the available values. 35 * <li>If any of values are < 0, the result is <code>NaN.</code></li> 36 * <li>If all values are non-negative and less than 40 * <code>Double.NEGATIVE_INFINITY</code> are among the values, the result is 132 * @param values input array containing the values 136 * any of the values are <= 0. 142 final double[] values, final int begin, final int length) { 144 sumOfLogs.evaluate(values, begin, length) / length); 141 evaluate( final double[] values, final int begin, final int length) argument
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H A D | Kurtosis.java | 28 * Computes the Kurtosis of the available values. 34 * where n is the number of values, mean is the {@link Mean} and std is the 155 * @param values the input array 158 * @return the kurtosis of the values or Double.NaN if length is less than 164 public double evaluate(final double[] values,final int begin, final int length) { argument 168 if (test(values, begin, length) && length > 3) { 172 variance.incrementAll(values, begin, length); 180 accum3 += FastMath.pow(values[i] - mean, 4.0);
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H A D | Mean.java | 26 * <p>Computes the arithmetic mean of a set of values. Uses the definitional 34 * stream of (unstored) values, the value of the statistic that 43 * of stored values, a two-pass, corrected algorithm is used, starting with 44 * the definitional formula computed using the array of stored values and then 45 * correcting this by adding the mean deviation of the data values from the 146 * @param values the input array 149 * @return the mean of the values or Double.NaN if length = 0 154 public double evaluate(final double[] values,final int begin, final int length) { argument 155 if (test(values, begin, length)) { 160 double xbar = sum.evaluate(values, begi 201 evaluate(final double[] values, final double[] weights, final int begin, final int length) argument 244 evaluate(final double[] values, final double[] weights) argument [all...] |
H A D | SemiVariance.java | 26 * <p>Computes the semivariance of a set of values with respect to a given cutoff value. 27 * We define the <i>downside semivariance</i> of a set of values <code>x</code> 33 * is defined similarly, with the sum taken over values of <code>x</code> that 38 * and bias correction may be set using property setters or their values can provided as 172 * @param values the input array 174 * @throws IllegalArgumentException if values is null 178 public double evaluate(final double[] values) { argument 179 if (values == null) { 182 return evaluate(values, 0, values 201 evaluate(final double[] values, final int start, final int length) argument 217 evaluate(final double[] values, Direction direction) argument 234 evaluate(final double[] values, final double cutoff) argument 251 evaluate(final double[] values, final double cutoff, final Direction direction) argument 273 evaluate(final double[] values, final double cutoff, final Direction direction, final boolean corrected, final int start, final int length) argument [all...] |
H A D | Skewness.java | 25 * Computes the skewness of the available values. 31 * where n is the number of values, mean is the {@link Mean} and std is the 95 * Returns the value of the statistic based on the values that have been added. 99 * @return the skewness of the available values. 142 * @param values the input array 145 * @return the skewness of the values or Double.NaN if length is less than 151 public double evaluate(final double[] values,final int begin, argument 157 if (test(values, begin, length) && length > 2 ){ 160 double m = mean.evaluate(values, begin, length); 168 final double d = values[ [all...] |
H A D | StandardDeviation.java | 147 * @param values the input array 148 * @return the standard deviation of the values or Double.NaN if length = 0 152 public double evaluate(final double[] values) { argument 153 return FastMath.sqrt(variance.evaluate(values)); 167 * @param values the input array 170 * @return the standard deviation of the values or Double.NaN if length = 0 175 public double evaluate(final double[] values, final int begin, final int length) { argument 176 return FastMath.sqrt(variance.evaluate(values, begin, length)); 195 * @param values the input array 199 * @return the standard deviation of the values o 203 evaluate(final double[] values, final double mean, final int begin, final int length) argument 229 evaluate(final double[] values, final double mean) argument [all...] |
H A D | Variance.java | 27 * Computes the variance of the available values. By default, the unbiased 44 * full array of values in memory to execute a two-pass algorithm. 48 * Note that adding values using <code>increment</code> or 51 * <code>evaluate</code> with the full array of values. The former approach 52 * should only be used when the full array of values is not available.</p> 149 * <p>If all values are available, it is more accurate to use 150 * {@link #evaluate(double[])} rather than adding values one at a time 153 * list of values together to execute a two-pass algorithm. 210 * @param values the input array 211 * @return the variance of the values o 215 evaluate(final double[] values) argument 243 evaluate(final double[] values, final int begin, final int length) argument 302 evaluate(final double[] values, final double[] weights, final int begin, final int length) argument 358 evaluate(final double[] values, final double[] weights) argument 388 evaluate(final double[] values, final double mean, final int begin, final int length) argument 441 evaluate(final double[] values, final double mean) 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 [all...] |
/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/rank/ |
H A D | Max.java | 24 * Returns the maximum of the available values. 27 * <li>The result is <code>NaN</code> iff all values are <code>NaN</code> 28 * (i.e. <code>NaN</code> values have no impact on the value of the statistic).</li> 29 * <li>If any of the values equals <code>Double.POSITIVE_INFINITY</code>, 45 /** Number of values that have been added */ 113 * <li>The result is <code>NaN</code> iff all values are <code>NaN</code> 114 * (i.e. <code>NaN</code> values have no impact on the value of the statistic).</li> 115 * <li>If any of the values equals <code>Double.POSITIVE_INFINITY</code>, 119 * @param values the input array 122 * @return the maximum of the values o 127 evaluate(final double[] values, final int begin, final int length) argument [all...] |