/* ------------------------------------------------------------------------- * This program is based on a one-pass algorithm for the calculation of an * array of autocorrelations r[1], r[2], ... r[K].  The key feature of this * algorithm is the circular array 'hold' which stores the (K + 1) most * recent data points and the associated index 'p' which points to the * (rotating) head of the array. * * Data is read from a text file in the format 1-data-point-per-line (with * no blank lines).  Similar to programs UVS and BVS, this program is * designed to be used with OS redirection. * * NOTE: the constant K (maximum lag) MUST be smaller than the # of data * points in the text file, n.  Moreover, if the autocorrelations are to be * statistically meaningful, K should be MUCH smaller than n. * * Name              : Acs.java (AutoCorrelation Statistics) * Authors           : Steve Park & Dave Geyer   * Translation by    : Jun Wang * Language          : Java * Latest Revision   : 6-16-06 * ------------------------------------------------------------------------- */import java.io.*;import java.util.*;import java.text.*;class Acs {  static int K    = 50;               /* K is the maximum lag          */  static int SIZE = K + 1;  public static void main(String[] args) throws IOException {    int    i = 0;                   /* data point index              */    int    j;                       /* lag index                     */    int    p = 0;                   /* points to the head of 'hold'  */    double x;                       /* current x[i] data point       */    double sum = 0.0;               /* sums x[i]                     */    long   n;                       /* number of data points         */    double mean;    double hold[]  = new double [SIZE]; /* K + 1 most recent data points */    double cosum[] = new double [SIZE]; /* cosum[j] sums x[i] * x[i+j]   */    for (j = 0; j < SIZE; j++)      cosum[j] = 0.0;    String line;    InputStreamReader r = new InputStreamReader(System.in);    BufferedReader ReadThis = new BufferedReader(r);    try {                         /* the first K + 1 data values    */      while (i < SIZE) {              /* initialize the hold array with */        if ( (line = ReadThis.readLine()) != null) {          x        = Double.parseDouble(line);          sum     += x;          hold[i]  = x;          i++;        }      }      while ( (line = ReadThis.readLine()) != null ) {        for (j = 0; j < SIZE; j++)          cosum[j] += hold[p] * hold[(p + j) % SIZE];        x       = Double.parseDouble(line);        sum    += x;        hold[p] = x;        p       = (p + 1) % SIZE;        i++;      }    } catch (EOFException e) {      System.out.println("Acs: " + e);    } catch (NumberFormatException nfe) {//      System.out.println("Acs: " + nfe);    }    n = i;    while (i < n + SIZE) {        /* empty the circular array       */      for (j = 0; j < SIZE; j++)        cosum[j] += hold[p] * hold[(p + j) % SIZE];      hold[p] = 0.0;      p       = (p + 1) % SIZE;      i++;    }    mean = sum / n;    for (j = 0; j <= K; j++)      cosum[j] = (cosum[j] / (n - j)) - (mean * mean);    DecimalFormat f = new DecimalFormat("###0.00");    DecimalFormat g = new DecimalFormat("###0.000");    System.out.println("for " + n + " data points");    System.out.println("the mean is ... " + f.format(mean));    System.out.println("the stdev is .. " + f.format(Math.sqrt(cosum[0])) +"\n");    System.out.println("  j (lag)   r[j] (autocorrelation)");    for (j = 1; j < SIZE; j++)      System.out.println("  " + j + "          " + g.format(cosum[j] / cosum[0]));  }}