http://git-wip-us.apache.org/repos/asf/incubator-samoa/blob/23a35dbe/samoa-api/src/main/java/com/yahoo/labs/samoa/moa/core/Statistics.java ---------------------------------------------------------------------- diff --git a/samoa-api/src/main/java/com/yahoo/labs/samoa/moa/core/Statistics.java b/samoa-api/src/main/java/com/yahoo/labs/samoa/moa/core/Statistics.java index 65536db..c270de9 100644 --- a/samoa-api/src/main/java/com/yahoo/labs/samoa/moa/core/Statistics.java +++ b/samoa-api/src/main/java/com/yahoo/labs/samoa/moa/core/Statistics.java @@ -23,140 +23,150 @@ package com.yahoo.labs.samoa.moa.core; public class Statistics { /** Some constants */ - protected static final double MACHEP = 1.11022302462515654042E-16; - protected static final double MAXLOG = 7.09782712893383996732E2; + protected static final double MACHEP = 1.11022302462515654042E-16; + protected static final double MAXLOG = 7.09782712893383996732E2; protected static final double MINLOG = -7.451332191019412076235E2; protected static final double MAXGAM = 171.624376956302725; - protected static final double SQTPI = 2.50662827463100050242E0; - protected static final double SQRTH = 7.07106781186547524401E-1; - protected static final double LOGPI = 1.14472988584940017414; - - protected static final double big = 4.503599627370496e15; - protected static final double biginv = 2.22044604925031308085e-16; + protected static final double SQTPI = 2.50662827463100050242E0; + protected static final double SQRTH = 7.07106781186547524401E-1; + protected static final double LOGPI = 1.14472988584940017414; + + protected static final double big = 4.503599627370496e15; + protected static final double biginv = 2.22044604925031308085e-16; /************************************************* - * COEFFICIENTS FOR METHOD normalInverse() * + * COEFFICIENTS FOR METHOD normalInverse() * *************************************************/ /* approximation for 0 <= |y - 0.5| <= 3/8 */ protected static final double P0[] = { - -5.99633501014107895267E1, - 9.80010754185999661536E1, - -5.66762857469070293439E1, - 1.39312609387279679503E1, - -1.23916583867381258016E0, + -5.99633501014107895267E1, + 9.80010754185999661536E1, + -5.66762857469070293439E1, + 1.39312609387279679503E1, + -1.23916583867381258016E0, }; protected static final double Q0[] = { - /* 1.00000000000000000000E0,*/ - 1.95448858338141759834E0, - 4.67627912898881538453E0, - 8.63602421390890590575E1, - -2.25462687854119370527E2, - 2.00260212380060660359E2, - -8.20372256168333339912E1, - 1.59056225126211695515E1, - -1.18331621121330003142E0, + /* 1.00000000000000000000E0, */ + 1.95448858338141759834E0, + 4.67627912898881538453E0, + 8.63602421390890590575E1, + -2.25462687854119370527E2, + 2.00260212380060660359E2, + -8.20372256168333339912E1, + 1.59056225126211695515E1, + -1.18331621121330003142E0, }; - - /* Approximation for interval z = sqrt(-2 log y ) between 2 and 8 - * i.e., y between exp(-2) = .135 and exp(-32) = 1.27e-14. + + /* + * Approximation for interval z = sqrt(-2 log y ) between 2 and 8 i.e., y + * between exp(-2) = .135 and exp(-32) = 1.27e-14. */ protected static final double P1[] = { - 4.05544892305962419923E0, - 3.15251094599893866154E1, - 5.71628192246421288162E1, - 4.40805073893200834700E1, - 1.46849561928858024014E1, - 2.18663306850790267539E0, - -1.40256079171354495875E-1, - -3.50424626827848203418E-2, - -8.57456785154685413611E-4, + 4.05544892305962419923E0, + 3.15251094599893866154E1, + 5.71628192246421288162E1, + 4.40805073893200834700E1, + 1.46849561928858024014E1, + 2.18663306850790267539E0, + -1.40256079171354495875E-1, + -3.50424626827848203418E-2, + -8.57456785154685413611E-4, }; protected static final double Q1[] = { - /* 1.00000000000000000000E0,*/ - 1.57799883256466749731E1, - 4.53907635128879210584E1, - 4.13172038254672030440E1, - 1.50425385692907503408E1, - 2.50464946208309415979E0, - -1.42182922854787788574E-1, - -3.80806407691578277194E-2, - -9.33259480895457427372E-4, + /* 1.00000000000000000000E0, */ + 1.57799883256466749731E1, + 4.53907635128879210584E1, + 4.13172038254672030440E1, + 1.50425385692907503408E1, + 2.50464946208309415979E0, + -1.42182922854787788574E-1, + -3.80806407691578277194E-2, + -9.33259480895457427372E-4, }; - - /* Approximation for interval z = sqrt(-2 log y ) between 8 and 64 - * i.e., y between exp(-32) = 1.27e-14 and exp(-2048) = 3.67e-890. + + /* + * Approximation for interval z = sqrt(-2 log y ) between 8 and 64 i.e., y + * between exp(-32) = 1.27e-14 and exp(-2048) = 3.67e-890. */ - protected static final double P2[] = { - 3.23774891776946035970E0, - 6.91522889068984211695E0, - 3.93881025292474443415E0, - 1.33303460815807542389E0, - 2.01485389549179081538E-1, - 1.23716634817820021358E-2, - 3.01581553508235416007E-4, - 2.65806974686737550832E-6, - 6.23974539184983293730E-9, + protected static final double P2[] = { + 3.23774891776946035970E0, + 6.91522889068984211695E0, + 3.93881025292474443415E0, + 1.33303460815807542389E0, + 2.01485389549179081538E-1, + 1.23716634817820021358E-2, + 3.01581553508235416007E-4, + 2.65806974686737550832E-6, + 6.23974539184983293730E-9, }; - protected static final double Q2[] = { - /* 1.00000000000000000000E0,*/ - 6.02427039364742014255E0, - 3.67983563856160859403E0, - 1.37702099489081330271E0, - 2.16236993594496635890E-1, - 1.34204006088543189037E-2, - 3.28014464682127739104E-4, - 2.89247864745380683936E-6, - 6.79019408009981274425E-9, + protected static final double Q2[] = { + /* 1.00000000000000000000E0, */ + 6.02427039364742014255E0, + 3.67983563856160859403E0, + 1.37702099489081330271E0, + 2.16236993594496635890E-1, + 1.34204006088543189037E-2, + 3.28014464682127739104E-4, + 2.89247864745380683936E-6, + 6.79019408009981274425E-9, }; - + /** - * Computes standard error for observed values of a binomial - * random variable. - * - * @param p the probability of success - * @param n the size of the sample + * Computes standard error for observed values of a binomial random variable. + * + * @param p + * the probability of success + * @param n + * the size of the sample * @return the standard error */ public static double binomialStandardError(double p, int n) { - + if (n == 0) { - return 0; + return 0; } - return Math.sqrt((p*(1-p))/(double) n); + return Math.sqrt((p * (1 - p)) / (double) n); } - + /** - * Returns chi-squared probability for given value and degrees - * of freedom. (The probability that the chi-squared variate - * will be greater than x for the given degrees of freedom.) - * - * @param x the value - * @param v the number of degrees of freedom + * Returns chi-squared probability for given value and degrees of freedom. + * (The probability that the chi-squared variate will be greater than x for + * the given degrees of freedom.) + * + * @param x + * the value + * @param v + * the number of degrees of freedom * @return the chi-squared probability */ - public static double chiSquaredProbability(double x, double v) { + public static double chiSquaredProbability(double x, double v) { - if( x < 0.0 || v < 1.0 ) return 0.0; - return incompleteGammaComplement( v/2.0, x/2.0 ); + if (x < 0.0 || v < 1.0) + return 0.0; + return incompleteGammaComplement(v / 2.0, x / 2.0); } /** * Computes probability of F-ratio. - * - * @param F the F-ratio - * @param df1 the first number of degrees of freedom - * @param df2 the second number of degrees of freedom + * + * @param F + * the F-ratio + * @param df1 + * the first number of degrees of freedom + * @param df2 + * the second number of degrees of freedom * @return the probability of the F-ratio. */ public static double FProbability(double F, int df1, int df2) { - - return incompleteBeta( df2/2.0, df1/2.0, df2/(df2+df1*F) ); + + return incompleteBeta(df2 / 2.0, df1 / 2.0, df2 / (df2 + df1 * F)); } /** - * Returns the area under the Normal (Gaussian) probability density - * function, integrated from minus infinity to <tt>x</tt> - * (assumes mean is zero, variance is one). + * Returns the area under the Normal (Gaussian) probability density function, + * integrated from minus infinity to <tt>x</tt> (assumes mean is zero, + * variance is one). + * * <pre> * x * - @@ -165,176 +175,188 @@ public class Statistics { * sqrt(2pi) | | * - * -inf. - * + * * = ( 1 + erf(z) ) / 2 * = erfc(z) / 2 * </pre> - * where <tt>z = x/sqrt(2)</tt>. - * Computation is via the functions <tt>errorFunction</tt> and <tt>errorFunctionComplement</tt>. - * - * @param a the z-value + * + * where <tt>z = x/sqrt(2)</tt>. Computation is via the functions + * <tt>errorFunction</tt> and <tt>errorFunctionComplement</tt>. + * + * @param a + * the z-value * @return the probability of the z value according to the normal pdf */ - public static double normalProbability(double a) { + public static double normalProbability(double a) { double x, y, z; - + x = a * SQRTH; z = Math.abs(x); - - if( z < SQRTH ) y = 0.5 + 0.5 * errorFunction(x); + + if (z < SQRTH) + y = 0.5 + 0.5 * errorFunction(x); else { y = 0.5 * errorFunctionComplemented(z); - if( x > 0 ) y = 1.0 - y; - } + if (x > 0) + y = 1.0 - y; + } return y; } /** - * Returns the value, <tt>x</tt>, for which the area under the - * Normal (Gaussian) probability density function (integrated from - * minus infinity to <tt>x</tt>) is equal to the argument <tt>y</tt> - * (assumes mean is zero, variance is one). + * Returns the value, <tt>x</tt>, for which the area under the Normal + * (Gaussian) probability density function (integrated from minus infinity to + * <tt>x</tt>) is equal to the argument <tt>y</tt> (assumes mean is zero, + * variance is one). * <p> * For small arguments <tt>0 < y < exp(-2)</tt>, the program computes - * <tt>z = sqrt( -2.0 * log(y) )</tt>; then the approximation is - * <tt>x = z - log(z)/z - (1/z) P(1/z) / Q(1/z)</tt>. - * There are two rational functions P/Q, one for <tt>0 < y < exp(-32)</tt> - * and the other for <tt>y</tt> up to <tt>exp(-2)</tt>. - * For larger arguments, - * <tt>w = y - 0.5</tt>, and <tt>x/sqrt(2pi) = w + w**3 R(w**2)/S(w**2))</tt>. - * - * @param y0 the area under the normal pdf + * <tt>z = sqrt( -2.0 * log(y) )</tt>; then the approximation is + * <tt>x = z - log(z)/z - (1/z) P(1/z) / Q(1/z)</tt>. There are two rational + * functions P/Q, one for <tt>0 < y < exp(-32)</tt> and the other for + * <tt>y</tt> up to <tt>exp(-2)</tt>. For larger arguments, + * <tt>w = y - 0.5</tt>, and <tt>x/sqrt(2pi) = w + w**3 R(w**2)/S(w**2))</tt>. + * + * @param y0 + * the area under the normal pdf * @return the z-value */ - public static double normalInverse(double y0) { + public static double normalInverse(double y0) { double x, y, z, y2, x0, x1; int code; - final double s2pi = Math.sqrt(2.0*Math.PI); + final double s2pi = Math.sqrt(2.0 * Math.PI); - if( y0 <= 0.0 ) throw new IllegalArgumentException(); - if( y0 >= 1.0 ) throw new IllegalArgumentException(); + if (y0 <= 0.0) + throw new IllegalArgumentException(); + if (y0 >= 1.0) + throw new IllegalArgumentException(); code = 1; y = y0; - if( y > (1.0 - 0.13533528323661269189) ) { /* 0.135... = exp(-2) */ + if (y > (1.0 - 0.13533528323661269189)) { /* 0.135... = exp(-2) */ y = 1.0 - y; code = 0; } - if( y > 0.13533528323661269189 ) { + if (y > 0.13533528323661269189) { y = y - 0.5; y2 = y * y; - x = y + y * (y2 * polevl( y2, P0, 4)/p1evl( y2, Q0, 8 )); - x = x * s2pi; - return(x); + x = y + y * (y2 * polevl(y2, P0, 4) / p1evl(y2, Q0, 8)); + x = x * s2pi; + return (x); } - x = Math.sqrt( -2.0 * Math.log(y) ); - x0 = x - Math.log(x)/x; + x = Math.sqrt(-2.0 * Math.log(y)); + x0 = x - Math.log(x) / x; - z = 1.0/x; - if( x < 8.0 ) /* y > exp(-32) = 1.2664165549e-14 */ - x1 = z * polevl( z, P1, 8 )/p1evl( z, Q1, 8 ); + z = 1.0 / x; + if (x < 8.0) /* y > exp(-32) = 1.2664165549e-14 */ + x1 = z * polevl(z, P1, 8) / p1evl(z, Q1, 8); else - x1 = z * polevl( z, P2, 8 )/p1evl( z, Q2, 8 ); + x1 = z * polevl(z, P2, 8) / p1evl(z, Q2, 8); x = x0 - x1; - if( code != 0 ) + if (code != 0) x = -x; - return( x ); + return (x); } /** * Returns natural logarithm of gamma function. - * - * @param x the value + * + * @param x + * the value * @return natural logarithm of gamma function */ public static double lnGamma(double x) { double p, q, w, z; - + double A[] = { - 8.11614167470508450300E-4, - -5.95061904284301438324E-4, - 7.93650340457716943945E-4, - -2.77777777730099687205E-3, - 8.33333333333331927722E-2 + 8.11614167470508450300E-4, + -5.95061904284301438324E-4, + 7.93650340457716943945E-4, + -2.77777777730099687205E-3, + 8.33333333333331927722E-2 }; double B[] = { - -1.37825152569120859100E3, - -3.88016315134637840924E4, - -3.31612992738871184744E5, - -1.16237097492762307383E6, - -1.72173700820839662146E6, - -8.53555664245765465627E5 + -1.37825152569120859100E3, + -3.88016315134637840924E4, + -3.31612992738871184744E5, + -1.16237097492762307383E6, + -1.72173700820839662146E6, + -8.53555664245765465627E5 }; double C[] = { - /* 1.00000000000000000000E0, */ - -3.51815701436523470549E2, - -1.70642106651881159223E4, - -2.20528590553854454839E5, - -1.13933444367982507207E6, - -2.53252307177582951285E6, - -2.01889141433532773231E6 + /* 1.00000000000000000000E0, */ + -3.51815701436523470549E2, + -1.70642106651881159223E4, + -2.20528590553854454839E5, + -1.13933444367982507207E6, + -2.53252307177582951285E6, + -2.01889141433532773231E6 }; - - if( x < -34.0 ) { + + if (x < -34.0) { q = -x; w = lnGamma(q); p = Math.floor(q); - if( p == q ) throw new ArithmeticException("lnGamma: Overflow"); + if (p == q) + throw new ArithmeticException("lnGamma: Overflow"); z = q - p; - if( z > 0.5 ) { - p += 1.0; - z = p - q; + if (z > 0.5) { + p += 1.0; + z = p - q; } - z = q * Math.sin( Math.PI * z ); - if( z == 0.0 ) throw new - ArithmeticException("lnGamma: Overflow"); - z = LOGPI - Math.log( z ) - w; + z = q * Math.sin(Math.PI * z); + if (z == 0.0) + throw new ArithmeticException("lnGamma: Overflow"); + z = LOGPI - Math.log(z) - w; return z; } - - if( x < 13.0 ) { + + if (x < 13.0) { z = 1.0; - while( x >= 3.0 ) { - x -= 1.0; - z *= x; + while (x >= 3.0) { + x -= 1.0; + z *= x; } - while( x < 2.0 ) { - if( x == 0.0 ) throw new - ArithmeticException("lnGamma: Overflow"); - z /= x; - x += 1.0; + while (x < 2.0) { + if (x == 0.0) + throw new ArithmeticException("lnGamma: Overflow"); + z /= x; + x += 1.0; } - if( z < 0.0 ) z = -z; - if( x == 2.0 ) return Math.log(z); + if (z < 0.0) + z = -z; + if (x == 2.0) + return Math.log(z); x -= 2.0; - p = x * polevl( x, B, 5 ) / p1evl( x, C, 6); - return( Math.log(z) + p ); + p = x * polevl(x, B, 5) / p1evl(x, C, 6); + return (Math.log(z) + p); } - - if( x > 2.556348e305 ) throw new ArithmeticException("lnGamma: Overflow"); - - q = ( x - 0.5 ) * Math.log(x) - x + 0.91893853320467274178; - - if( x > 1.0e8 ) return( q ); - - p = 1.0/(x*x); - if( x >= 1000.0 ) - q += (( 7.9365079365079365079365e-4 * p - - 2.7777777777777777777778e-3) *p - + 0.0833333333333333333333) / x; + + if (x > 2.556348e305) + throw new ArithmeticException("lnGamma: Overflow"); + + q = (x - 0.5) * Math.log(x) - x + 0.91893853320467274178; + + if (x > 1.0e8) + return (q); + + p = 1.0 / (x * x); + if (x >= 1000.0) + q += ((7.9365079365079365079365e-4 * p + - 2.7777777777777777777778e-3) * p + + 0.0833333333333333333333) / x; else - q += polevl( p, A, 4 ) / x; + q += polevl(p, A, 4) / x; return q; } /** - * Returns the error function of the normal distribution. - * The integral is + * Returns the error function of the normal distribution. The integral is + * * <pre> * x * - @@ -344,47 +366,51 @@ public class Statistics { * - * 0 * </pre> - * <b>Implementation:</b> - * For <tt>0 <= |x| < 1, erf(x) = x * P4(x**2)/Q5(x**2)</tt>; otherwise + * + * <b>Implementation:</b> For + * <tt>0 <= |x| < 1, erf(x) = x * P4(x**2)/Q5(x**2)</tt>; otherwise * <tt>erf(x) = 1 - erfc(x)</tt>. * <p> - * Code adapted from the <A HREF="http://www.sci.usq.edu.au/staff/leighb/graph/Top.html";> - * Java 2D Graph Package 2.4</A>, - * which in turn is a port from the - * <A HREF="http://people.ne.mediaone.net/moshier/index.html#Cephes";>Cephes 2.2</A> - * Math Library (C). - * - * @param a the argument to the function. + * Code adapted from the <A + * HREF="http://www.sci.usq.edu.au/staff/leighb/graph/Top.html";> Java 2D Graph + * Package 2.4</A>, which in turn is a port from the <A + * HREF="http://people.ne.mediaone.net/moshier/index.html#Cephes";>Cephes + * 2.2</A> Math Library (C). + * + * @param a + * the argument to the function. */ - public static double errorFunction(double x) { + public static double errorFunction(double x) { double y, z; final double T[] = { - 9.60497373987051638749E0, - 9.00260197203842689217E1, - 2.23200534594684319226E3, - 7.00332514112805075473E3, - 5.55923013010394962768E4 + 9.60497373987051638749E0, + 9.00260197203842689217E1, + 2.23200534594684319226E3, + 7.00332514112805075473E3, + 5.55923013010394962768E4 }; final double U[] = { - //1.00000000000000000000E0, - 3.35617141647503099647E1, - 5.21357949780152679795E2, - 4.59432382970980127987E3, - 2.26290000613890934246E4, - 4.92673942608635921086E4 + // 1.00000000000000000000E0, + 3.35617141647503099647E1, + 5.21357949780152679795E2, + 4.59432382970980127987E3, + 2.26290000613890934246E4, + 4.92673942608635921086E4 }; - - if( Math.abs(x) > 1.0 ) return( 1.0 - errorFunctionComplemented(x) ); + + if (Math.abs(x) > 1.0) + return (1.0 - errorFunctionComplemented(x)); z = x * x; - y = x * polevl( z, T, 4 ) / p1evl( z, U, 5 ); + y = x * polevl(z, T, 4) / p1evl(z, U, 5); return y; } /** * Returns the complementary Error function of the normal distribution. + * * <pre> * 1 - erf(x) = - * + * * inf. * - * 2 | | 2 @@ -393,174 +419,201 @@ public class Statistics { * - * x * </pre> - * <b>Implementation:</b> - * For small x, <tt>erfc(x) = 1 - erf(x)</tt>; otherwise rational - * approximations are computed. + * + * <b>Implementation:</b> For small x, <tt>erfc(x) = 1 - erf(x)</tt>; + * otherwise rational approximations are computed. * <p> - * Code adapted from the <A HREF="http://www.sci.usq.edu.au/staff/leighb/graph/Top.html";> - * Java 2D Graph Package 2.4</A>, - * which in turn is a port from the - * <A HREF="http://people.ne.mediaone.net/moshier/index.html#Cephes";>Cephes 2.2</A> - * Math Library (C). - * - * @param a the argument to the function. + * Code adapted from the <A + * HREF="http://www.sci.usq.edu.au/staff/leighb/graph/Top.html";> Java 2D Graph + * Package 2.4</A>, which in turn is a port from the <A + * HREF="http://people.ne.mediaone.net/moshier/index.html#Cephes";>Cephes + * 2.2</A> Math Library (C). + * + * @param a + * the argument to the function. */ - public static double errorFunctionComplemented(double a) { - double x,y,z,p,q; - + public static double errorFunctionComplemented(double a) { + double x, y, z, p, q; + double P[] = { - 2.46196981473530512524E-10, - 5.64189564831068821977E-1, - 7.46321056442269912687E0, - 4.86371970985681366614E1, - 1.96520832956077098242E2, - 5.26445194995477358631E2, - 9.34528527171957607540E2, - 1.02755188689515710272E3, - 5.57535335369399327526E2 + 2.46196981473530512524E-10, + 5.64189564831068821977E-1, + 7.46321056442269912687E0, + 4.86371970985681366614E1, + 1.96520832956077098242E2, + 5.26445194995477358631E2, + 9.34528527171957607540E2, + 1.02755188689515710272E3, + 5.57535335369399327526E2 }; double Q[] = { - //1.0 - 1.32281951154744992508E1, - 8.67072140885989742329E1, - 3.54937778887819891062E2, - 9.75708501743205489753E2, - 1.82390916687909736289E3, - 2.24633760818710981792E3, - 1.65666309194161350182E3, - 5.57535340817727675546E2 + // 1.0 + 1.32281951154744992508E1, + 8.67072140885989742329E1, + 3.54937778887819891062E2, + 9.75708501743205489753E2, + 1.82390916687909736289E3, + 2.24633760818710981792E3, + 1.65666309194161350182E3, + 5.57535340817727675546E2 }; - + double R[] = { - 5.64189583547755073984E-1, - 1.27536670759978104416E0, - 5.01905042251180477414E0, - 6.16021097993053585195E0, - 7.40974269950448939160E0, - 2.97886665372100240670E0 + 5.64189583547755073984E-1, + 1.27536670759978104416E0, + 5.01905042251180477414E0, + 6.16021097993053585195E0, + 7.40974269950448939160E0, + 2.97886665372100240670E0 }; double S[] = { - //1.00000000000000000000E0, - 2.26052863220117276590E0, - 9.39603524938001434673E0, - 1.20489539808096656605E1, - 1.70814450747565897222E1, - 9.60896809063285878198E0, - 3.36907645100081516050E0 + // 1.00000000000000000000E0, + 2.26052863220117276590E0, + 9.39603524938001434673E0, + 1.20489539808096656605E1, + 1.70814450747565897222E1, + 9.60896809063285878198E0, + 3.36907645100081516050E0 }; - - if( a < 0.0 ) x = -a; - else x = a; - - if( x < 1.0 ) return 1.0 - errorFunction(a); - + + if (a < 0.0) + x = -a; + else + x = a; + + if (x < 1.0) + return 1.0 - errorFunction(a); + z = -a * a; - - if( z < -MAXLOG ) { - if( a < 0 ) return( 2.0 ); - else return( 0.0 ); + + if (z < -MAXLOG) { + if (a < 0) + return (2.0); + else + return (0.0); } - + z = Math.exp(z); - - if( x < 8.0 ) { - p = polevl( x, P, 8 ); - q = p1evl( x, Q, 8 ); + + if (x < 8.0) { + p = polevl(x, P, 8); + q = p1evl(x, Q, 8); } else { - p = polevl( x, R, 5 ); - q = p1evl( x, S, 6 ); + p = polevl(x, R, 5); + q = p1evl(x, S, 6); } - - y = (z * p)/q; - - if( a < 0 ) y = 2.0 - y; - - if( y == 0.0 ) { - if( a < 0 ) return 2.0; - else return( 0.0 ); + + y = (z * p) / q; + + if (a < 0) + y = 2.0 - y; + + if (y == 0.0) { + if (a < 0) + return 2.0; + else + return (0.0); } return y; } - + /** * Evaluates the given polynomial of degree <tt>N</tt> at <tt>x</tt>. - * Evaluates polynomial when coefficient of N is 1.0. - * Otherwise same as <tt>polevl()</tt>. + * Evaluates polynomial when coefficient of N is 1.0. Otherwise same as + * <tt>polevl()</tt>. + * * <pre> * 2 N * y = C + C x + C x +...+ C x * 0 1 2 N - * + * * Coefficients are stored in reverse order: - * + * * coef[0] = C , ..., coef[N] = C . * N 0 * </pre> + * * The function <tt>p1evl()</tt> assumes that <tt>coef[N] = 1.0</tt> and is - * omitted from the array. Its calling arguments are - * otherwise the same as <tt>polevl()</tt>. + * omitted from the array. Its calling arguments are otherwise the same as + * <tt>polevl()</tt>. * <p> * In the interest of speed, there are no checks for out of bounds arithmetic. - * - * @param x argument to the polynomial. - * @param coef the coefficients of the polynomial. - * @param N the degree of the polynomial. + * + * @param x + * argument to the polynomial. + * @param coef + * the coefficients of the polynomial. + * @param N + * the degree of the polynomial. */ - public static double p1evl( double x, double coef[], int N ) { - + public static double p1evl(double x, double coef[], int N) { + double ans; ans = x + coef[0]; - - for(int i=1; i<N; i++) ans = ans*x+coef[i]; - + + for (int i = 1; i < N; i++) + ans = ans * x + coef[i]; + return ans; } /** * Evaluates the given polynomial of degree <tt>N</tt> at <tt>x</tt>. + * * <pre> * 2 N * y = C + C x + C x +...+ C x * 0 1 2 N - * + * * Coefficients are stored in reverse order: - * + * * coef[0] = C , ..., coef[N] = C . * N 0 * </pre> + * * In the interest of speed, there are no checks for out of bounds arithmetic. - * - * @param x argument to the polynomial. - * @param coef the coefficients of the polynomial. - * @param N the degree of the polynomial. + * + * @param x + * argument to the polynomial. + * @param coef + * the coefficients of the polynomial. + * @param N + * the degree of the polynomial. */ - public static double polevl( double x, double coef[], int N ) { + public static double polevl(double x, double coef[], int N) { double ans; ans = coef[0]; - - for(int i=1; i<=N; i++) ans = ans*x+coef[i]; - + + for (int i = 1; i <= N; i++) + ans = ans * x + coef[i]; + return ans; } /** * Returns the Incomplete Gamma function. - * @param a the parameter of the gamma distribution. - * @param x the integration end point. + * + * @param a + * the parameter of the gamma distribution. + * @param x + * the integration end point. */ - public static double incompleteGamma(double a, double x) - { - + public static double incompleteGamma(double a, double x) + { + double ans, ax, c, r; - - if( x <= 0 || a <= 0 ) return 0.0; - - if( x > 1.0 && x > a ) return 1.0 - incompleteGammaComplement(a,x); - /* Compute x**a * exp(-x) / gamma(a) */ + if (x <= 0 || a <= 0) + return 0.0; + + if (x > 1.0 && x > a) + return 1.0 - incompleteGammaComplement(a, x); + + /* Compute x**a * exp(-x) / gamma(a) */ ax = a * Math.log(x) - x - lnGamma(a); - if( ax < -MAXLOG ) return( 0.0 ); + if (ax < -MAXLOG) + return (0.0); ax = Math.exp(ax); @@ -571,33 +624,38 @@ public class Statistics { do { r += 1.0; - c *= x/r; + c *= x / r; ans += c; - } - while( c/ans > MACHEP ); - - return( ans * ax/a ); + } while (c / ans > MACHEP); + + return (ans * ax / a); } /** * Returns the Complemented Incomplete Gamma function. - * @param a the parameter of the gamma distribution. - * @param x the integration start point. + * + * @param a + * the parameter of the gamma distribution. + * @param x + * the integration start point. */ - public static double incompleteGammaComplement( double a, double x ) { + public static double incompleteGammaComplement(double a, double x) { double ans, ax, c, yc, r, t, y, z; double pk, pkm1, pkm2, qk, qkm1, qkm2; - if( x <= 0 || a <= 0 ) return 1.0; - - if( x < 1.0 || x < a ) return 1.0 - incompleteGamma(a,x); - + if (x <= 0 || a <= 0) + return 1.0; + + if (x < 1.0 || x < a) + return 1.0 - incompleteGamma(a, x); + ax = a * Math.log(x) - x - lnGamma(a); - if( ax < -MAXLOG ) return 0.0; - + if (ax < -MAXLOG) + return 0.0; + ax = Math.exp(ax); - + /* continued fraction */ y = 1.0 - a; z = x + y + 1.0; @@ -606,34 +664,34 @@ public class Statistics { qkm2 = x; pkm1 = x + 1.0; qkm1 = z * x; - ans = pkm1/qkm1; - + ans = pkm1 / qkm1; + do { c += 1.0; y += 1.0; z += 2.0; yc = y * c; - pk = pkm1 * z - pkm2 * yc; - qk = qkm1 * z - qkm2 * yc; - if( qk != 0 ) { - r = pk/qk; - t = Math.abs( (ans - r)/r ); - ans = r; + pk = pkm1 * z - pkm2 * yc; + qk = qkm1 * z - qkm2 * yc; + if (qk != 0) { + r = pk / qk; + t = Math.abs((ans - r) / r); + ans = r; } else - t = 1.0; + t = 1.0; pkm2 = pkm1; pkm1 = pk; qkm2 = qkm1; qkm1 = qk; - if( Math.abs(pk) > big ) { - pkm2 *= biginv; + if (Math.abs(pk) > big) { + pkm2 *= biginv; pkm1 *= biginv; - qkm2 *= biginv; - qkm1 *= biginv; + qkm2 *= biginv; + qkm1 *= biginv; } - } while( t > MACHEP ); - + } while (t > MACHEP); + return ans * ax; } @@ -643,23 +701,23 @@ public class Statistics { public static double gamma(double x) { double P[] = { - 1.60119522476751861407E-4, - 1.19135147006586384913E-3, - 1.04213797561761569935E-2, - 4.76367800457137231464E-2, - 2.07448227648435975150E-1, - 4.94214826801497100753E-1, - 9.99999999999999996796E-1 + 1.60119522476751861407E-4, + 1.19135147006586384913E-3, + 1.04213797561761569935E-2, + 4.76367800457137231464E-2, + 2.07448227648435975150E-1, + 4.94214826801497100753E-1, + 9.99999999999999996796E-1 }; double Q[] = { - -2.31581873324120129819E-5, - 5.39605580493303397842E-4, - -4.45641913851797240494E-3, - 1.18139785222060435552E-2, - 3.58236398605498653373E-2, - -2.34591795718243348568E-1, - 7.14304917030273074085E-2, - 1.00000000000000000320E0 + -2.31581873324120129819E-5, + 5.39605580493303397842E-4, + -4.45641913851797240494E-3, + 1.18139785222060435552E-2, + 3.58236398605498653373E-2, + -2.34591795718243348568E-1, + 7.14304917030273074085E-2, + 1.00000000000000000320E0 }; double p, z; @@ -667,89 +725,90 @@ public class Statistics { double q = Math.abs(x); - if( q > 33.0 ) { - if( x < 0.0 ) { - p = Math.floor(q); - if( p == q ) throw new ArithmeticException("gamma: overflow"); - i = (int)p; - z = q - p; - if( z > 0.5 ) { - p += 1.0; - z = q - p; - } - z = q * Math.sin( Math.PI * z ); - if( z == 0.0 ) throw new ArithmeticException("gamma: overflow"); - z = Math.abs(z); - z = Math.PI/(z * stirlingFormula(q) ); - - return -z; + if (q > 33.0) { + if (x < 0.0) { + p = Math.floor(q); + if (p == q) + throw new ArithmeticException("gamma: overflow"); + i = (int) p; + z = q - p; + if (z > 0.5) { + p += 1.0; + z = q - p; + } + z = q * Math.sin(Math.PI * z); + if (z == 0.0) + throw new ArithmeticException("gamma: overflow"); + z = Math.abs(z); + z = Math.PI / (z * stirlingFormula(q)); + + return -z; } else { - return stirlingFormula(x); + return stirlingFormula(x); } } z = 1.0; - while( x >= 3.0 ) { + while (x >= 3.0) { x -= 1.0; z *= x; } - while( x < 0.0 ) { - if( x == 0.0 ) { - throw new ArithmeticException("gamma: singular"); - } else - if( x > -1.E-9 ) { - return( z/((1.0 + 0.5772156649015329 * x) * x) ); - } + while (x < 0.0) { + if (x == 0.0) { + throw new ArithmeticException("gamma: singular"); + } else if (x > -1.E-9) { + return (z / ((1.0 + 0.5772156649015329 * x) * x)); + } z /= x; x += 1.0; } - while( x < 2.0 ) { - if( x == 0.0 ) { - throw new ArithmeticException("gamma: singular"); - } else - if( x < 1.e-9 ) { - return( z/((1.0 + 0.5772156649015329 * x) * x) ); - } + while (x < 2.0) { + if (x == 0.0) { + throw new ArithmeticException("gamma: singular"); + } else if (x < 1.e-9) { + return (z / ((1.0 + 0.5772156649015329 * x) * x)); + } z /= x; x += 1.0; } - if( (x == 2.0) || (x == 3.0) ) return z; + if ((x == 2.0) || (x == 3.0)) + return z; x -= 2.0; - p = polevl( x, P, 6 ); - q = polevl( x, Q, 7 ); - return z * p / q; + p = polevl(x, P, 6); + q = polevl(x, Q, 7); + return z * p / q; } /** - * Returns the Gamma function computed by Stirling's formula. - * The polynomial STIR is valid for 33 <= x <= 172. + * Returns the Gamma function computed by Stirling's formula. The polynomial + * STIR is valid for 33 <= x <= 172. */ public static double stirlingFormula(double x) { double STIR[] = { - 7.87311395793093628397E-4, - -2.29549961613378126380E-4, - -2.68132617805781232825E-3, - 3.47222221605458667310E-3, - 8.33333333333482257126E-2, + 7.87311395793093628397E-4, + -2.29549961613378126380E-4, + -2.68132617805781232825E-3, + 3.47222221605458667310E-3, + 8.33333333333482257126E-2, }; double MAXSTIR = 143.01608; - double w = 1.0/x; - double y = Math.exp(x); + double w = 1.0 / x; + double y = Math.exp(x); - w = 1.0 + w * polevl( w, STIR, 4 ); + w = 1.0 + w * polevl(w, STIR, 4); - if( x > MAXSTIR ) { + if (x > MAXSTIR) { /* Avoid overflow in Math.pow() */ - double v = Math.pow( x, 0.5 * x - 0.25 ); + double v = Math.pow(x, 0.5 * x - 0.25); y = v * (v / y); } else { - y = Math.pow( x, x - 0.5 ) / y; + y = Math.pow(x, x - 0.5) / y; } y = SQTPI * y * w; return y; @@ -757,27 +816,32 @@ public class Statistics { /** * Returns the Incomplete Beta Function evaluated from zero to <tt>xx</tt>. - * - * @param aa the alpha parameter of the beta distribution. - * @param bb the beta parameter of the beta distribution. - * @param xx the integration end point. + * + * @param aa + * the alpha parameter of the beta distribution. + * @param bb + * the beta parameter of the beta distribution. + * @param xx + * the integration end point. */ - public static double incompleteBeta( double aa, double bb, double xx ) { + public static double incompleteBeta(double aa, double bb, double xx) { double a, b, t, x, xc, w, y; boolean flag; - if( aa <= 0.0 || bb <= 0.0 ) throw new - ArithmeticException("ibeta: Domain error!"); + if (aa <= 0.0 || bb <= 0.0) + throw new ArithmeticException("ibeta: Domain error!"); - if( (xx <= 0.0) || ( xx >= 1.0) ) { - if( xx == 0.0 ) return 0.0; - if( xx == 1.0 ) return 1.0; + if ((xx <= 0.0) || (xx >= 1.0)) { + if (xx == 0.0) + return 0.0; + if (xx == 1.0) + return 1.0; throw new ArithmeticException("ibeta: Domain error!"); } flag = false; - if( (bb * xx) <= 1.0 && xx <= 0.95) { + if ((bb * xx) <= 1.0 && xx <= 0.95) { t = powerSeries(aa, bb, xx); return t; } @@ -785,7 +849,7 @@ public class Statistics { w = 1.0 - xx; /* Reverse a and b if x is greater than the mean. */ - if( xx > (aa/(aa+bb)) ) { + if (xx > (aa / (aa + bb))) { flag = true; a = bb; b = aa; @@ -798,57 +862,63 @@ public class Statistics { x = xx; } - if( flag && (b * x) <= 1.0 && x <= 0.95) { + if (flag && (b * x) <= 1.0 && x <= 0.95) { t = powerSeries(a, b, x); - if( t <= MACHEP ) t = 1.0 - MACHEP; - else t = 1.0 - t; + if (t <= MACHEP) + t = 1.0 - MACHEP; + else + t = 1.0 - t; return t; } /* Choose expansion for better convergence. */ - y = x * (a+b-2.0) - (a-1.0); - if( y < 0.0 ) - w = incompleteBetaFraction1( a, b, x ); + y = x * (a + b - 2.0) - (a - 1.0); + if (y < 0.0) + w = incompleteBetaFraction1(a, b, x); else - w = incompleteBetaFraction2( a, b, x ) / xc; + w = incompleteBetaFraction2(a, b, x) / xc; - /* Multiply w by the factor - a b _ _ _ - x (1-x) | (a+b) / ( a | (a) | (b) ) . */ + /* + * Multiply w by the factor a b _ _ _ x (1-x) | (a+b) / ( a | (a) | (b) ) . + */ y = a * Math.log(x); t = b * Math.log(xc); - if( (a+b) < MAXGAM && Math.abs(y) < MAXLOG && Math.abs(t) < MAXLOG ) { - t = Math.pow(xc,b); - t *= Math.pow(x,a); + if ((a + b) < MAXGAM && Math.abs(y) < MAXLOG && Math.abs(t) < MAXLOG) { + t = Math.pow(xc, b); + t *= Math.pow(x, a); t /= a; t *= w; - t *= gamma(a+b) / (gamma(a) * gamma(b)); - if( flag ) { - if( t <= MACHEP ) t = 1.0 - MACHEP; - else t = 1.0 - t; + t *= gamma(a + b) / (gamma(a) * gamma(b)); + if (flag) { + if (t <= MACHEP) + t = 1.0 - MACHEP; + else + t = 1.0 - t; } return t; } - /* Resort to logarithms. */ - y += t + lnGamma(a+b) - lnGamma(a) - lnGamma(b); - y += Math.log(w/a); - if( y < MINLOG ) + /* Resort to logarithms. */ + y += t + lnGamma(a + b) - lnGamma(a) - lnGamma(b); + y += Math.log(w / a); + if (y < MINLOG) t = 0.0; else t = Math.exp(y); - if( flag ) { - if( t <= MACHEP ) t = 1.0 - MACHEP; - else t = 1.0 - t; + if (flag) { + if (t <= MACHEP) + t = 1.0 - MACHEP; + else + t = 1.0 - t; } return t; - } + } /** * Continued fraction expansion #1 for incomplete beta integral. */ - public static double incompleteBetaFraction1( double a, double b, double x ) { + public static double incompleteBetaFraction1(double a, double b, double x) { double xk, pk, pkm1, pkm2, qk, qkm1, qkm2; double k1, k2, k3, k4, k5, k6, k7, k8; @@ -873,30 +943,32 @@ public class Statistics { n = 0; thresh = 3.0 * MACHEP; do { - xk = -( x * k1 * k2 )/( k3 * k4 ); - pk = pkm1 + pkm2 * xk; - qk = qkm1 + qkm2 * xk; + xk = -(x * k1 * k2) / (k3 * k4); + pk = pkm1 + pkm2 * xk; + qk = qkm1 + qkm2 * xk; pkm2 = pkm1; pkm1 = pk; qkm2 = qkm1; qkm1 = qk; - xk = ( x * k5 * k6 )/( k7 * k8 ); - pk = pkm1 + pkm2 * xk; - qk = qkm1 + qkm2 * xk; + xk = (x * k5 * k6) / (k7 * k8); + pk = pkm1 + pkm2 * xk; + qk = qkm1 + qkm2 * xk; pkm2 = pkm1; pkm1 = pk; qkm2 = qkm1; qkm1 = qk; - if( qk != 0 ) r = pk/qk; - if( r != 0 ) { - t = Math.abs( (ans - r)/r ); - ans = r; - } else - t = 1.0; + if (qk != 0) + r = pk / qk; + if (r != 0) { + t = Math.abs((ans - r) / r); + ans = r; + } else + t = 1.0; - if( t < thresh ) return ans; + if (t < thresh) + return ans; k1 += 1.0; k2 += 1.0; @@ -907,27 +979,27 @@ public class Statistics { k7 += 2.0; k8 += 2.0; - if( (Math.abs(qk) + Math.abs(pk)) > big ) { - pkm2 *= biginv; - pkm1 *= biginv; - qkm2 *= biginv; - qkm1 *= biginv; + if ((Math.abs(qk) + Math.abs(pk)) > big) { + pkm2 *= biginv; + pkm1 *= biginv; + qkm2 *= biginv; + qkm1 *= biginv; } - if( (Math.abs(qk) < biginv) || (Math.abs(pk) < biginv) ) { - pkm2 *= big; - pkm1 *= big; - qkm2 *= big; - qkm1 *= big; + if ((Math.abs(qk) < biginv) || (Math.abs(pk) < biginv)) { + pkm2 *= big; + pkm1 *= big; + qkm2 *= big; + qkm1 *= big; } - } while( ++n < 300 ); + } while (++n < 300); return ans; - } + } /** * Continued fraction expansion #2 for incomplete beta integral. */ - public static double incompleteBetaFraction2( double a, double b, double x ) { + public static double incompleteBetaFraction2(double a, double b, double x) { double xk, pk, pkm1, pkm2, qk, qkm1, qkm2; double k1, k2, k3, k4, k5, k6, k7, k8; @@ -940,43 +1012,46 @@ public class Statistics { k4 = a + 1.0; k5 = 1.0; k6 = a + b; - k7 = a + 1.0;; + k7 = a + 1.0; + ; k8 = a + 2.0; pkm2 = 0.0; qkm2 = 1.0; pkm1 = 1.0; qkm1 = 1.0; - z = x / (1.0-x); + z = x / (1.0 - x); ans = 1.0; r = 1.0; n = 0; thresh = 3.0 * MACHEP; do { - xk = -( z * k1 * k2 )/( k3 * k4 ); - pk = pkm1 + pkm2 * xk; - qk = qkm1 + qkm2 * xk; + xk = -(z * k1 * k2) / (k3 * k4); + pk = pkm1 + pkm2 * xk; + qk = qkm1 + qkm2 * xk; pkm2 = pkm1; pkm1 = pk; qkm2 = qkm1; qkm1 = qk; - xk = ( z * k5 * k6 )/( k7 * k8 ); - pk = pkm1 + pkm2 * xk; - qk = qkm1 + qkm2 * xk; + xk = (z * k5 * k6) / (k7 * k8); + pk = pkm1 + pkm2 * xk; + qk = qkm1 + qkm2 * xk; pkm2 = pkm1; pkm1 = pk; qkm2 = qkm1; qkm1 = qk; - if( qk != 0 ) r = pk/qk; - if( r != 0 ) { - t = Math.abs( (ans - r)/r ); - ans = r; + if (qk != 0) + r = pk / qk; + if (r != 0) { + t = Math.abs((ans - r) / r); + ans = r; } else - t = 1.0; + t = 1.0; - if( t < thresh ) return ans; + if (t < thresh) + return ans; k1 += 1.0; k2 -= 1.0; @@ -987,31 +1062,31 @@ public class Statistics { k7 += 2.0; k8 += 2.0; - if( (Math.abs(qk) + Math.abs(pk)) > big ) { - pkm2 *= biginv; - pkm1 *= biginv; - qkm2 *= biginv; - qkm1 *= biginv; + if ((Math.abs(qk) + Math.abs(pk)) > big) { + pkm2 *= biginv; + pkm1 *= biginv; + qkm2 *= biginv; + qkm1 *= biginv; } - if( (Math.abs(qk) < biginv) || (Math.abs(pk) < biginv) ) { - pkm2 *= big; - pkm1 *= big; - qkm2 *= big; - qkm1 *= big; + if ((Math.abs(qk) < biginv) || (Math.abs(pk) < biginv)) { + pkm2 *= big; + pkm1 *= big; + qkm2 *= big; + qkm1 *= big; } - } while( ++n < 300 ); + } while (++n < 300); return ans; } /** - * Power series for incomplete beta integral. - * Use when b*x is small and x not too close to 1. + * Power series for incomplete beta integral. Use when b*x is small and x not + * too close to 1. */ - public static double powerSeries( double a, double b, double x ) { + public static double powerSeries(double a, double b, double x) { double s, t, u, v, n, t1, z, ai; - + ai = 1.0 / a; u = (1.0 - b) * x; v = u / (a + 1.0); @@ -1020,27 +1095,28 @@ public class Statistics { n = 2.0; s = 0.0; z = MACHEP * ai; - while( Math.abs(v) > z ) { + while (Math.abs(v) > z) { u = (n - b) * x / n; t *= u; v = t / (a + n); - s += v; + s += v; n += 1.0; } s += t1; s += ai; u = a * Math.log(x); - if( (a+b) < MAXGAM && Math.abs(u) < MAXLOG ) { - t = gamma(a+b)/(gamma(a)*gamma(b)); - s = s * t * Math.pow(x,a); + if ((a + b) < MAXGAM && Math.abs(u) < MAXLOG) { + t = gamma(a + b) / (gamma(a) * gamma(b)); + s = s * t * Math.pow(x, a); } else { - t = lnGamma(a+b) - lnGamma(a) - lnGamma(b) + u + Math.log(s); - if( t < MINLOG ) s = 0.0; - else s = Math.exp(t); + t = lnGamma(a + b) - lnGamma(a) - lnGamma(b) + u + Math.log(s); + if (t < MINLOG) + s = 0.0; + else + s = Math.exp(t); } return s; } - }
http://git-wip-us.apache.org/repos/asf/incubator-samoa/blob/23a35dbe/samoa-api/src/main/java/com/yahoo/labs/samoa/moa/core/StringUtils.java ---------------------------------------------------------------------- diff --git a/samoa-api/src/main/java/com/yahoo/labs/samoa/moa/core/StringUtils.java b/samoa-api/src/main/java/com/yahoo/labs/samoa/moa/core/StringUtils.java index 6a27206..a14e21e 100644 --- a/samoa-api/src/main/java/com/yahoo/labs/samoa/moa/core/StringUtils.java +++ b/samoa-api/src/main/java/com/yahoo/labs/samoa/moa/core/StringUtils.java @@ -24,73 +24,73 @@ import java.text.DecimalFormat; /** * Class implementing some string utility methods. - * + * * @author Richard Kirkby ([email protected]) * @version $Revision: 7 $ */ public class StringUtils { - public static final String newline = System.getProperty("line.separator"); + public static final String newline = System.getProperty("line.separator"); - public static String doubleToString(double value, int fractionDigits) { - return doubleToString(value, 0, fractionDigits); - } + public static String doubleToString(double value, int fractionDigits) { + return doubleToString(value, 0, fractionDigits); + } - public static String doubleToString(double value, int minFractionDigits, - int maxFractionDigits) { - DecimalFormat numberFormat = new DecimalFormat(); - numberFormat.setMinimumFractionDigits(minFractionDigits); - numberFormat.setMaximumFractionDigits(maxFractionDigits); - return numberFormat.format(value); - } + public static String doubleToString(double value, int minFractionDigits, + int maxFractionDigits) { + DecimalFormat numberFormat = new DecimalFormat(); + numberFormat.setMinimumFractionDigits(minFractionDigits); + numberFormat.setMaximumFractionDigits(maxFractionDigits); + return numberFormat.format(value); + } - public static void appendNewline(StringBuilder out) { - out.append(newline); - } + public static void appendNewline(StringBuilder out) { + out.append(newline); + } - public static void appendIndent(StringBuilder out, int indent) { - for (int i = 0; i < indent; i++) { - out.append(' '); - } + public static void appendIndent(StringBuilder out, int indent) { + for (int i = 0; i < indent; i++) { + out.append(' '); } + } - public static void appendIndented(StringBuilder out, int indent, String s) { - appendIndent(out, indent); - out.append(s); - } + public static void appendIndented(StringBuilder out, int indent, String s) { + appendIndent(out, indent); + out.append(s); + } - public static void appendNewlineIndented(StringBuilder out, int indent, - String s) { - appendNewline(out); - appendIndented(out, indent, s); - } + public static void appendNewlineIndented(StringBuilder out, int indent, + String s) { + appendNewline(out); + appendIndented(out, indent, s); + } - public static String secondsToDHMSString(double seconds) { - if (seconds < 60) { - return doubleToString(seconds, 2, 2) + 's'; - } - long secs = (int) (seconds); - long mins = secs / 60; - long hours = mins / 60; - long days = hours / 24; - secs %= 60; - mins %= 60; - hours %= 24; - StringBuilder result = new StringBuilder(); - if (days > 0) { - result.append(days); - result.append('d'); - } - if ((hours > 0) || (days > 0)) { - result.append(hours); - result.append('h'); - } - if ((hours > 0) || (days > 0) || (mins > 0)) { - result.append(mins); - result.append('m'); - } - result.append(secs); - result.append('s'); - return result.toString(); + public static String secondsToDHMSString(double seconds) { + if (seconds < 60) { + return doubleToString(seconds, 2, 2) + 's'; + } + long secs = (int) (seconds); + long mins = secs / 60; + long hours = mins / 60; + long days = hours / 24; + secs %= 60; + mins %= 60; + hours %= 24; + StringBuilder result = new StringBuilder(); + if (days > 0) { + result.append(days); + result.append('d'); + } + if ((hours > 0) || (days > 0)) { + result.append(hours); + result.append('h'); + } + if ((hours > 0) || (days > 0) || (mins > 0)) { + result.append(mins); + result.append('m'); } + result.append(secs); + result.append('s'); + return result.toString(); + } }
