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mXparser is a super easy, rich, fast and highly flexible math expression parser library (parser and evaluator of mathematical expressions / formulas provided as plain text / string). Software delivers easy to use API for JAVA, Android and C# .NET/MONO (Common Language Specification compliant: F#, Visual Basic, C++/CLI). *** If you find the software useful donation is something you might consider: https://mathparser.org/donate/ *** Scalar Scientific Calculator, Charts and Scripts, Scalar Lite: https://play.google.com/store/apps/details?id=org.mathparser.scalar.lite *** Scalar Pro: https://play.google.com/store/apps/details?id=org.mathparser.scalar.pro *** ScalarMath.org: https://scalarmath.org/ *** MathSpace.pl: https://mathspace.pl/ ***
/*
* @(#)Statistics.java 5.0.4 2022-05-22
*
* MathParser.org-mXparser DUAL LICENSE AGREEMENT as of date 2022-05-22
* The most up-to-date license is available at the below link:
* - https://mathparser.org/mxparser-license
*
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* PRODUCT: MathParser.org-mXparser SOFTWARE
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package org.mariuszgromada.math.mxparser.mathcollection;
import org.mariuszgromada.math.mxparser.Argument;
import org.mariuszgromada.math.mxparser.Expression;
import org.mariuszgromada.math.mxparser.mXparser;
/**
* Statistics - i.e.: mean, variance, standard deviation, etc.
*
* @author Mariusz Gromada
* MathParser.org - mXparser project page
* mXparser on GitHub
* INFIMA place to purchase a commercial MathParser.org-mXparser software license
* [email protected]
* ScalarMath.org - a powerful math engine and math scripting language
* Scalar Lite
* Scalar Pro
* MathSpace.pl
*
* @version 5.0.0
*/
public final class Statistics {
/**
* Average from sample function values - iterative operator.
*
* @param f the expression
* @param index the name of index argument
* @param from FROM index = form
* @param to TO index = to
* @param delta BY delta
*
* @return product operation (for empty product operations returns 1).
*
* @see Expression
* @see Argument
*/
public static double avg(Expression f, Argument index, double from, double to, double delta) {
if ( (Double.isNaN(delta) ) || (Double.isNaN(from) ) || (Double.isNaN(to) ) || (delta == 0) )
return Double.NaN;
double sum = 0;
int n = 0;
if ( (to >= from) && (delta > 0) ) {
double i;
for (i = from; i < to; i+=delta) {
if (mXparser.isCurrentCalculationCancelled()) return Double.NaN;
sum += mXparser.getFunctionValue(f, index, i);
n++;
}
if ( delta - (i - to) > 0.5 * delta) {
if (mXparser.isCurrentCalculationCancelled()) return Double.NaN;
sum += mXparser.getFunctionValue(f, index, to);
n++;
}
} else if ( (to <= from) && (delta < 0) ) {
double i;
for (i = from; i > to; i+=delta) {
if (mXparser.isCurrentCalculationCancelled()) return Double.NaN;
sum += mXparser.getFunctionValue(f, index, i);
n++;
}
if ( -delta - (to - i) > -0.5 * delta) {
if (mXparser.isCurrentCalculationCancelled()) return Double.NaN;
sum += mXparser.getFunctionValue(f, index, to);
n++;
}
} else if (from == to)
return mXparser.getFunctionValue(f, index, from);
return sum / n;
}
/**
* Bias-corrected variance from sample function values - iterative operator.
*
* @param f the expression
* @param index the name of index argument
* @param from FROM index = form
* @param to TO index = to
* @param delta BY delta
*
* @return product operation (for empty product operations returns 1).
*
* @see Expression
* @see Argument
*/
public static double var(Expression f, Argument index, double from, double to, double delta) {
if ( (Double.isNaN(delta) ) || (Double.isNaN(from) ) || (Double.isNaN(to) ) || (delta == 0) )
return Double.NaN;
return var( mXparser.getFunctionValues(f, index, from, to, delta) );
}
/**
* Bias-corrected standard deviation from sample function values - iterative operator.
*
* @param f the expression
* @param index the name of index argument
* @param from FROM index = form
* @param to TO index = to
* @param delta BY delta
*
* @return product operation (for empty product operations returns 1).
*
* @see Expression
* @see Argument
*/
public static final double std(Expression f, Argument index, double from, double to, double delta) {
if ( (Double.isNaN(delta) ) || (Double.isNaN(from) ) || (Double.isNaN(to) ) || (delta == 0) )
return Double.NaN;
return std( mXparser.getFunctionValues(f, index, from, to, delta) );
}
/**
* Sample average.
*
* @param numbers the numbers
*
* @return if each number from numbers <> Double.NaN returns
* avg(a_1,...,a_n) a_1,...,a_n in numbers,
* otherwise returns Double.NaN.
*/
public static double avg(double... numbers) {
if (numbers == null) return Double.NaN;
if (numbers.length == 0) return Double.NaN;
if (numbers.length == 1) return numbers[0];
double sum = 0;
for (double xi : numbers) {
if (mXparser.isCurrentCalculationCancelled()) return Double.NaN;
if ( Double.isNaN(xi) )
return Double.NaN;
sum+=xi;
}
return sum / numbers.length;
}
/**
* Sample variance (biased-corrected).
*
* @param numbers the numbers
*
* @return if each number from numbers <> Double.NaN returns
* Var(a_1,...,a_n) a_1,...,a_n in numbers,
* otherwise returns Double.NaN.
*/
public static double var(double... numbers) {
if (numbers == null) return Double.NaN;
if (numbers.length == 0) return Double.NaN;
if (numbers.length == 1) {
if (Double.isNaN(numbers[0])) return Double.NaN;
return 0;
}
double m = avg(numbers);
double sum = 0;
for (double xi : numbers) {
if (mXparser.isCurrentCalculationCancelled()) return Double.NaN;
if ( Double.isNaN(xi) )
return Double.NaN;
sum+=(xi-m)*(xi-m);
}
return sum / (numbers.length - 1);
}
/**
* Sample standard deviation (biased-corrected).
*
* @param numbers the numbers
*
* @return if each number from numbers <> Double.NaN returns
* Std(a_1,...,a_n) a_1,...,a_n in numbers,
* otherwise returns Double.NaN.
*/
public static double std(double... numbers) {
if (numbers == null) return Double.NaN;
if (numbers.length == 0) return Double.NaN;
if (numbers.length == 1) {
if (Double.isNaN(numbers[0])) return Double.NaN;
return 0;
}
return MathFunctions.sqrt( var(numbers) );
}
/**
* Sample median
* @param numbers List of number
* @return Sample median, if table was empty or null then Double.NaN is returned.
*/
public static double median(double... numbers) {
if (numbers == null) return Double.NaN;
if (numbers.length == 0) return Double.NaN;
if (numbers.length == 1) return numbers[0];
if (numbers.length == 2) return (numbers[0] + numbers[1]) / 2.0;
for (double v : numbers) {
if (mXparser.isCurrentCalculationCancelled()) return Double.NaN;
if (Double.isNaN(v)) return Double.NaN;
}
NumberTheory.sortAsc(numbers);
if ((numbers.length % 2) == 1) {
int i = (numbers.length-1) / 2;
return numbers[i];
} else {
int i = ( numbers.length / 2 ) - 1;
return (numbers[i] + numbers[i+1]) / 2.0;
}
}
/**
* Sample mode
* @param numbers List of number
* @return Sample median, if table was empty or null then Double.NaN is returned.
*/
public static double mode(double... numbers) {
if (numbers == null) return Double.NaN;
if (numbers.length == 0) return Double.NaN;
if (numbers.length == 1) return numbers[0];
for (double v : numbers) {
if (mXparser.isCurrentCalculationCancelled()) return Double.NaN;
if (Double.isNaN(v)) return Double.NaN;
}
double[][] dist = NumberTheory.getDistValues(numbers, true);
return dist[0][0];
}
}
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