oms3.util
Class Stats

java.lang.Object
  oms3.util.Stats

public class Stats
extends java.lang.Object

Author:

Olaf David

Method Summary

static double	bias(double[] pred, double[] valid)
static double	err_sum(double[] validation, double[] prediction)
static double	gradient(double[] xData, double[] yData)
static double	intercept(double[] xData, double[] yData)
static double	ioa(double[] prediction, double[] validation, double pow) Calculates the index of agreement (ioa) between a test data set and a verification data set after Willmot & Wicks (1980).
static double	lag1(double[] vals) Returns the lag-1 autocorrelation of a dataset;
static int	length(double[] vals)
static double	max(double[] vals)
static double	mean(double[] vals)
static double	meandev(double[] vals)
static double	median(double[] vals)
static double	min(double[] vals)
static double	nashsut_log(double[] prediction, double[] validation, double pow) Calculates the efficiency between the log values of a test data set and a verification data set after Nash & Sutcliffe (1970).
static double	nashsut(double[] prediction, double[] validation, double pow) Calculates the efficiency between a test data set and a verification data set after Nash & Sutcliffe (1970).
static double	norm_vec(double x, double y, double z) Normalized Vector.
static double	product(double[] vals)
static double	quantile(double[] vals, double phi)
static double	r2(double[] xData, double[] yData)
static double	random(double min, double max) Generate a random number in a range.
static double	range(double[] vals)
static double	rmse(double[] pred, double[] valid)
static double	round(double val, int places) Round a double value to a specified number of decimal places.
static float	round(float val, int places) Round a float value to a specified number of decimal places.
static double	stddev(double[] vals)
static double	stderr(double[] vals)
static double	sum(double[] vals)
static double	variance(double[] vals)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

norm_vec

public static double norm_vec(double x,
                              double y,
                              double z)

Normalized Vector.

max

public static double max(double[] vals)

min

public static double min(double[] vals)

range

public static double range(double[] vals)

length

public static int length(double[] vals)

median

public static double median(double[] vals)

mean

public static double mean(double[] vals)

stddev

public static double stddev(double[] vals)

stderr

public static double stderr(double[] vals)

variance

public static double variance(double[] vals)

meandev

public static double meandev(double[] vals)

sum

public static double sum(double[] vals)

product

public static double product(double[] vals)

quantile

public static double quantile(double[] vals,
                              double phi)

lag1

public static double lag1(double[] vals)

Returns the lag-1 autocorrelation of a dataset;

rmse

public static double rmse(double[] pred,
                          double[] valid)

bias

public static double bias(double[] pred,
                          double[] valid)

nashsut

public static double nashsut(double[] prediction,
                             double[] validation,
                             double pow)

Calculates the efficiency between a test data set and a verification data set after Nash & Sutcliffe (1970). The efficiency is described as the proportion of the cumulated cubic deviation between both data sets and the cumulated cubic deviation between the verification data set and its mean value.

Parameters:

prediction - the simulation data set

validation - the validation (observed) data set

pow - the power for the deviation terms

Returns:

the calculated efficiency or -9999 if an error occurs

nashsut_log

public static double nashsut_log(double[] prediction,
                                 double[] validation,
                                 double pow)

Calculates the efficiency between the log values of a test data set and a verification data set after Nash & Sutcliffe (1970). The efficiency is described as the proportion of the cumulated cubic deviation between both data sets and the cumulated cubic deviation between the verification data set and its mean value.

Parameters:

prediction - the simulation data set

validation - the validation (observed) data set

pow - the power for the deviation terms

Returns:

the calculated log_efficiency or -9999 if an error occurs

err_sum

public static double err_sum(double[] validation,
                             double[] prediction)

ioa

public static double ioa(double[] prediction,
                         double[] validation,
                         double pow)

Calculates the index of agreement (ioa) between a test data set and a verification data set after Willmot & Wicks (1980). The ioa is described as the proportion of the cumulated cubic deviation between both data sets and the squared sum of the absolute deviations between the verification data set and the test mean value and the test data set and its mean value.

Parameters:

prediction - the test Data set

validation - the verification data set

pow - the power

Returns:

the calculated ioa or -9999 if an error occurs

intercept

public static double intercept(double[] xData,
                               double[] yData)

gradient

public static double gradient(double[] xData,
                              double[] yData)

r2

public static double r2(double[] xData,
                        double[] yData)

round

public static double round(double val,
                           int places)

Round a double value to a specified number of decimal places.

Parameters:

val - the value to be rounded.

places - the number of decimal places to round to.

Returns:

val rounded to places decimal places.

round

public static float round(float val,
                          int places)

Round a float value to a specified number of decimal places.

Parameters:

val - the value to be rounded.

places - the number of decimal places to round to.

Returns:

val rounded to places decimal places.

random

public static double random(double min,
                            double max)

Generate a random number in a range.

Parameters:

min -

max -

Returns:

the random value in the min/max range