# data 0.10.0 data: ^0.10.0 copied to clipboard

A time and space efficient collection of data structures and algorithms to deal with data in Dart.

# Dart Data #

Dart Data is a fast and space efficient library to deal with data in Dart, Flutter and the web. As of today this mostly includes data structures and algorithms for vectors and matrices, but at some point might also include graphs and other mathematical structures.

This library is open source, stable and well tested. Development happens on GitHub. Feel free to report issues or create a pull-request there. General questions are best asked on StackOverflow.

The package is hosted on dart packages. Up-to-date class documentation is created with every release.

## Tutorial #

Below are step-by-step instructions of how to use this library. More elaborate examples are included with the examples.

### Installation #

Follow the installation instructions on dart packages.

Import the core-package into your Dart code using:

```
import 'package:data/data.dart';
```

### How to solve a linear equation? #

Solve 'A * x = b', where 'A' is a matrix and 'b' a vector:

```
final a = Matrix<double>.fromRows(DataType.float64, [
[2, 1, 1],
[1, 3, 2],
[1, 0, 0],
]);
final b = Vector<double>.fromList(DataType.float64, [4, 5, 6]);
final x = a.solve(b.columnMatrix).column(0);
print(x.format(valuePrinter: Printer.fixed()); // prints '6 15 -23'
```

### How to find the eigenvalues of a matrix? #

Find the eigenvalues of a matrix 'A':

```
final a = Matrix<double>.fromRows(DataType.float64, [
[1, 0, 0, -1],
[0, -1, 0, 0],
[0, 0, 1, -1],
[-1, 0, -1, 0],
]);
final decomposition = a.eigenvalue;
final eigenvalues = Vector<double>.fromList(
DataType.float64, decomposition.realEigenvalues);
print(eigenvalues.format(valuePrinter: Printer.fixed(precision: 1))); // prints '-1.0 -1.0 1.0 2.0'
```

### How to find all the roots of a polynomial? #

To find the roots of `x^5 + -8x^4 + -72x^3 + 242x^2 + 1847x + 2310`

:

```
final polynomial = Polynomial.fromCoefficients(DataType.int32, [1, -8, -72, 242, 1847, 2310]);
final roots = polynomial.roots;
print(roots.map((root) => root.real)); // [-5, -3, -2, 7, 11]
print(roots.map((root) => root.imaginary)); // [0, 0, 0, 0, 0]
```

## Misc #

### License #

The MIT License, see LICENSE.

The matrix decomposition algorithms are a direct port of the JAMA: A Java Matrix Package released under public domain.

Some of the distributions and special functions are a port of the JavaScript Statistical Library released under MIT.