asdlei99 / vector-toolkit

A toolkit of useful functions for processing C++ STL vectors

Vector Toolkit

A toolkit of useful functions for processing C++ STL vectors. It contains over 50 functions to help quickly process vectors of numbers.

Author

Vector Toolkit is developed and maintained by Adam Stark.

Usage

Vector Toolkit can be used with the following types:

int
float	
double
long

For each type, there is a shorthand typedef:

• VTi
• VTf
• VTd
• VTl

E.g. For integers:

// create a vector counting from 0 to 99
std::vector<int> x = VTi::range(100);

// calculate the mean
double mean = VTi::mean(x);

// calculate the standard deviation
double std = VTi::standardDeviation(x);

// calculate the maximum index
int maxIndex = VTi::maxIndex(x);

// multiply every element by 4
std::vector<int> y = VTi::multiply(x,4);

// calcualte the Euclidean distance between the two vectors
double distance = VTi::euclideanDistance(x,y);

E.g. For floats:

// create a vector counting from 0 to 99
std::vector<float> x = VTf::range(100);

// calculate the mean
double mean = VTf::mean(x);

// calculate the standard deviation
double std = VTf::standardDeviation(x);

// calculate the maximum index
int maxIndex = VTf::maxIndex(x);

// multiply every element by 4
std::vector<float> y = VTf::multiply(x,4.0);

// calcualte the Euclidean distance between the two vectors
double distance = VTf::euclideanDistance(x,y);

E.g. For doubles:

// create a vector counting from 0 to 99
std::vector<double> x = VTd::range(100);

// calculate the mean
double mean = VTd::mean(x);

// calculate the standard deviation
double std = VTd::standardDeviation(x);

// calculate the maximum index
int maxIndex = VTd::maxIndex(x);

// multiply every element by 4
std::vector<double> y = VTd::multiply(x,4.0);

// calcualte the Euclidean distance between the two vectors
double distance = VTd::euclideanDistance(x,y);

E.g. For long:

// create a vector counting from 0 to 99
std::vector<long> x = VTl::range(100);

// calculate the mean
double mean = VTl::mean(x);

// calculate the standard deviation
double std = VTl::standardDeviation(x);

// calculate the maximum index
int maxIndex = VTl::maxIndex(x);

// multiply every element by 4
std::vector<long> y = VTl::multiply(x,4.0);

// calcualte the Euclidean distance between the two vectors
double distance = VTl::euclideanDistance(x,y);

Example Functions

The following are some example functions that the toolkit includes:

Simple info about a vector:

• sum()
• max()
• min()
• maxIndex()
• minIndex()

Simple statistics:

• mean()
• median()
• standardDeviation()
• variance()

Working with scalars or other vectors:

• multiply()
• divide()
• add()
• subtract()

Distance and Similarity:

• euclideanDistance()
• cosineSimilarity()
• cosineDistance()

Other Handy Things:

• getEvenElements()
• getOddElements()
• printVector()
• isAllPositiveOrZero()
• contains()
• reverse()

and lots of other functions of these types.

Version History

v1.0.4 - 25/10/2014

• Updated documentation

v1.0.3 - 25/10/2014

• Added unit tests
• Added vector scaling
• Added functions for quickly creating vectors

v1.0.2 - 22/10/2014

• Updated documentation

v1.0.1 - 22/10/2014

• First full version

License

Copyright (c) 2014 Adam Stark

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.