Math::NumberCruncher - Very useful, commonly needed math/statistics/geometric functions.
use Math::NumberCruncher;
($high, $low) = Math::NumberCruncher::Range(\@array);
$mean = Math::NumberCruncher::Mean(\@array);
$median = Math::NumberCruncher::Median(\@array);
$odd_median = Math::NumberCruncher::OddMedian(\@array);
$mode = Math::NumberCruncher::Mode(\@array);
$covariance = Math::NumberCruncher::Covariance(\@array1, \@array2);
$correlation = Math::NumberCruncher::Correlation(\@array1, \@array2);
($slope, $y_intercept) = Math::NumberCruncher::BestFit(\@array1, \@array2);
$distance = Math::NumberCruncher::Distance($x1,$y1,$z1,$x2,$y2,$z2);
$distance = Math::NumberCruncher::Distance($x1,$y1,$x1,$x2);
$distance = Math::NumberCruncher::ManhattanDistance($x1,$y1,$x2,$y2);
$probAll = Math::NumberCruncher::AllOf('0.3','0.25','0.91','0.002');
$probNone = Math::NumberCruncher::NoneOf('0.4','0.5772','0.212');
$probSome = Math::NumberCruncher::SomeOf('0.11','0.56','0.3275');
$factorial = Math::NumberCruncher::Factorial($some_number);
$permutations = Math::NumberCruncher::Permutation($n);
$permutations = Math::NumberCruncher::Permutation($n,$k);
$roll = Math::NumberCruncher::Dice(3,12,4);
$randInt = Math::NumberCruncher::RandInt(10,50);
$randomElement = Math::NumberCruncher::RandomElement(\@array);
@shuffled = Math::NumberCruncher::ShuffleArray(\@array);
@unique = Math::NumberCruncher::Unique(\@array);
@a_only = Math::NumberCruncher::Compare(\@a,\@b);
@union = Math::NumberCruncher::Union(\@a,\@b);
@intersection = Math::NumberCruncher::Intersection(\@a,\@b);
@difference = Math::NumberCruncher::Difference(\@a,\@b);
$gaussianRand = Math::NumberCruncher::GaussianRand();
$prob = Math::NumberCruncher::Choose($n,$k);
$binomial = Math::NumberCruncher::Binomial($attempts,$successes,$probability);
$gaussianDist = Math::NumberCruncher::GaussianDist($x,$mean,$variance);
$StdDev = Math::NumberCruncher::StandardDeviation(\@array);
$variance = Math::NumberCruncher::Variance(\@array);
@scores = Math::NumberCruncher::StandardScores(\@array);
$confidence = Math::NumberCruncher::SignSignificance($trials,$hits,$probability);
$e = Math::Numbercruncher::EMC2( "m512" [, 1] );
$m = Math::NumberCruncher::EMC2( "e987432" [, 1] );
$force = Math::NumberCruncher::FMA( "m12", "a73.5" );
$mass = Math::NumberCruncher::FMA( "a43", "f1324" );
$acceleration = Math::NumberCruncher::FMA( "f53512", "m356" );
$predicted_value = Math::NubmerCruncher::Predict( $slope, $y_intercept, $proposed_x );
This module is a collection of commonly needed number-related functions, including numerous standard statistical, geometric, and probability functions. Some of these functions are taken directly from _Mastering Algorithms with Perl_, by Jon Orwant, Jarkko Hietaniemi, and John Macdonald, and others are adapted heavily from same. The remainder are either original functions written by the author, or original adaptations of standard algorithms. Some of the functions are fairly obvious, others are explained in greater detail below.
Returns the largest and smallest elements in an array.
Returns the mean, or average, of an array.
Returns the median, or the middle, of an array. The median may or may not be an element of the array itself.
Returns the odd median, which, unlike the median, *is* an element of the array. In all other respects it is similar to the median.
Returns the mode, or most frequently occurring item, of @array.
Returns the covariance, which is a measurement of the correlation of two variables.
Returns the correlation of two variables. Correlation ranges from 1 to -1, with a correlation of zero meaning no correlation exists between the two variables.
Returns the slope and y-intercept of the line of best fit for the data in question.
Returns the Euclidian distance between two points. The above example demonstrates the use in two dimensions. For three dimensions, use would be $distance = Math::NumberCruncher::Distance($x1,$y1,$z1,$x2,$y2,$z2);
Modified two-dimensional distance between two points. As stated in _Mastering Algorithms with Perl_, "Helicopter pilots tend to think in Euclidian distance, good New York cabbies tend to think in Manhattan distance." Rather than distance "as the crow flies," this is distance based on a rigid grid, or network of streets, like those found in Manhattan.
The probability that all of the probabilities in question will be satisfied. (i.e., the probability that the Steelers will win the SuperBowl and that David Tua will win the World Heavyweight Title in boxing.)
The probability that none of the probabilities in question will be satisfied. (i.e., the probability that the Steelers will not win the SuperBowl and that David Tua will not win the World Heavyweight Title in boxing.)
The probability that at least one of the probabilities in question will be satisfied. (i.e., the probability that either the Steelers will win the SuperBowl or David Tua will win the World Heavyweight Title in boxing.)
The number of possible orderings of $factorial items. The factorial n! gives the number of ways in which n objects can be permuted.
The number of permutations of $n elements.
The number of permutations of $k elements drawn from a set of $n elements.
The obligatory dice rolling routine. Returns the result after passing the number of rolls of the die, the number of sides of the die, and any additional points to be added to the roll. As commonly seen in role playing games, 4d12+5 would be expressed as Dice(4,12,5). The function defaults to a single 6-sided die rolled once without any points added.
Returns a random integer between the two number passed to the function, inclusive. With no parameters passed, the function returns either 0 or 1.
Returns a randome element from @array.
Shuffles the elements of @array and returns them.
Returns an array of the unique items in an array.
Returns an array of elements that appear only in the first array passed. Any elements that appear in both arrays, or appear only in the second array, are discarded.
Returns an array of the unique elements produced from the joining of the two arrays.
Returns an array of the elements that appear in both arrays.
Returns an array of the symmetric difference of the two arrays. For example, in the words of _Mastering Algorithms in Perl_, "show me the web documents that talk about Perl or about sets but not those that talk about both.
Returns one or two floating point numbers based on the Gaussian Distribution, based upon the call wants an array or a scalar value.
Returns the probability of $k successes in $n tries.
Returns the probability of $k successes in $n tries, given a probability of $p. (i.e., if the probability of being struck by lightning is 1 in 75,000, in 100 days, the probability of being struck by lightning exactly twice would be expressed as Binomial('100','2','0.0000133'))
Returns the probability, based on Gaussian Distribution, of our random variable, $x, given the $mean and $variance.
Returns the Standard Deviation of @array, which is a measurement of how diverse your data is.
Returns the variance for @array, which is the square of the standard deviation. Or think of standard deviation as the square root of the variance. Variance is another indicator of the diversity of your data.
Returns an array of the number of standard deviations above the mean for @array.
Returns the probability of how likely it is that your data is due to chance. The lower the confidence, the less likely your data is due to chance.
Implementation of Einstein's E=MC**2. Given either energy or mass, the function returns the other. When passing mass, the value must be preceeded by a "m," which may be either upper or lower case. When passing energy, the value must be preceeded by a "e," which may be either upper or lower case. The function defaults to using kilometers per second for the speed of light. To make the function use miles per second for the speed of light, simply pass any non-zero value as the second value.
Implementation of the stadard force = mass * acceleration formula. Given two of the three variables (i.e., mass and force, mass and acceleration, or acceleration and force), the function returns the third. When passing the values, mass must be preceeded by a "m," force must be preceeded by a "f," and acceleration must be preceeded by an "a." Case is irrelevant.
Useful for predicting values based on data trends, as calculated by BestFit(). Given the slope and y-intercept, and a proposed value of x, returns corresponding y.
Kurt Kincaid, sifukurt@yahoo.com Jon Orwant Jarkko Hietaniemi John Macdonald
perl(1).
2 POD Errors
The following errors were encountered while parsing the POD:
'=item' outside of any '=over'
You forgot a '=back' before '=head1'
To install Math::NumberCruncher, copy and paste the appropriate command in to your terminal.
cpanm
cpanm Math::NumberCruncher
CPAN shell
perl -MCPAN -e shell install Math::NumberCruncher
For more information on module installation, please visit the detailed CPAN module installation guide.