PHP Class MathPHP\NumericalAnalysis\NumericalIntegration\RectangleMethod

In numerical analysis, the rectangle method is a technique for approximating the definite integral of a function. The rectangle method belongs to the closed Newton-Cotes formulas, a group of methods for numerical integration which approximate the integral of a function. We can either directly supply a set of inputs and their corresponding outputs for said function, or if we explicitly know the function, we can define it as a callback function and then generate a set of points by evaluating that function at n points between a start and end point. We then use these values to interpolate a Lagrange polynomial. Finally, we integrate the Lagrange polynomial to approximate the integral of our original function. The rectangle method is produced by integrating the zero-th degree Lagrange Polynomial https://en.wikipedia.org/wiki/Rectangle_method http://www.efunda.com/math/num_integration/num_int_newton.cfm
Inheritance: extends NumericalIntegration
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Public Methods

Method Description
approximate ( $source, $args ) : number Use the Rectangle Method to aproximate the definite integral of a function f(x). Our input can support either a set of arrays, or a callback function with arguments (to produce a set of arrays). Each array in our input contains two numbers which correspond to coordinates (x, y) or equivalently, (x, f(x)), of the function f(x) whose definite integral we are approximating.

Method Details

approximate() public static method

The bounds of the definite integral to which we are approximating is determined by the our inputs. Example: approximate([0, 10], [3, 5], [10, 7]) will approximate the definite integral of the function that produces these coordinates with a lower bound of 0, and an upper bound of 10. Example: approximate(function($x) {return $x**2;}, 0, 4 ,5) will produce a set of arrays by evaluating the callback at 5 evenly spaced points between 0 and 4. Then, this array will be used in our approximation. Rectangle Rule: xn ⁿ⁻¹ xᵢ₊₁ ∫ f(x)dx = ∑ ∫ f(x)dx x₁ ⁱ⁼¹ xᵢ ⁿ = ∑ h [f(xᵢ)] + O(h³f″(x)) ⁱ⁼¹ where h = xᵢ₊₁ - xᵢ note: this implementation does not compute the error term.
public static approximate ( $source, $args ) : number
$source The source of our approximation. Should be either a callback function or a set of arrays. Each array (point) contains precisely two numbers, an x and y. Example array: [[1,2], [2,3], [3,4]]. Example callback: function($x) {return $x**2;}
return number The approximation to the integral of f(x)