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Euler Method for solving differential equation
  • Difficulty Level : Easy
  • Last Updated : 13 Apr, 2021

Given a differential equation dy/dx = f(x, y) with initial condition y(x0) = y0. Find its approximate solution using Euler method.
Euler Method : 
In mathematics and computational science, the Euler method (also called forward 
Euler method) is a first-order numerical procedurefor solving ordinary differential 
equations (ODEs) with a given initial value. 
Consider a differential equation dy/dx = f(x, y) with initialcondition y(x0)=y0 
then succesive approximation of this equation can be given by: 
 

y(n+1) = y(n) + h * f(x(n), y(n)) 
where h = (x(n) – x(0)) / n 
h indicates step size. Choosing smaller 
values of h leads to more accurate results 
and more computation time. 
 

Example : 
 

    Consider below differential equation
            dy/dx = (x + y + xy)
    with initial condition y(0) = 1 
    and step size h = 0.025.
    Find y(0.1).
   
    Solution:
    f(x, y) = (x + y + xy)
    x0 = 0, y0 = 1, h = 0.025
    Now we can calculate y1 using Euler formula
    y1 = y0 + h * f(x0, y0)
    y1 = 1 + 0.025 *(0 + 1 + 0 * 1)
    y1 = 1.025
    y(0.025) = 1.025.
    Similarly we can calculate y(0.050), y(0.075), ....y(0.1).
    y(0.1) = 1.11167

 

 



C++




/* CPP  Program to find approximation
   of a ordinary differential equation
   using euler method.*/
#include <iostream>
using namespace std;
 
// Consider a differential equation
// dy/dx=(x + y + xy)
float func(float x, float y)
{
    return (x + y + x * y);
}
 
// Function for Euler formula
void euler(float x0, float y, float h, float x)
{
    float temp = -0;
 
    // Iterating till the point at which we
    // need approximation
    while (x0 < x) {
        temp = y;
        y = y + h * func(x0, y);
        x0 = x0 + h;
    }
 
    // Printing approximation
    cout << "Approximate solution at x = "
         << x << "  is  " << y << endl;
}
 
// Driver program
int main()
{
    // Initial Values
    float x0 = 0;
    float y0 = 1;
    float h = 0.025;
 
    // Value of x at which we need approximation
    float x = 0.1;
 
    euler(x0, y0, h, x);
    return 0;
}

Java




// Java program to find approximation of an ordinary
// differential equation using euler method
import java.io.*;
 
class Euler {
    // Consider a differential equation
    // dy/dx=(x + y + xy)
    float func(float x, float y)
    {
        return (x + y + x * y);
    }
 
    // Function for Euler formula
    void euler(float x0, float y, float h, float x)
    {
        float temp = -0;
 
        // Iterating till the point at which we
        // need approximation
        while (x0 < x) {
            temp = y;
            y = y + h * func(x0, y);
            x0 = x0 + h;
        }
 
        // Printing approximation
        System.out.println("Approximate solution at x = "
                           + x + " is " + y);
    }
 
    // Driver program
    public static void main(String args[]) throws IOException
    {
        Euler obj = new Euler();
        // Initial Values
        float x0 = 0;
        float y0 = 1;
        float h = 0.025f;
 
        // Value of x at which we need approximation
        float x = 0.1f;
 
        obj.euler(x0, y0, h, x);
    }
}
 
// This code is contributed by Anshika Goyal.

Python3




# Python Code to find approximation
# of a ordinary differential equation
# using euler method.
 
# Consider a differential equation
# dy / dx =(x + y + xy)
def func( x, y ):
    return (x + y + x * y)
     
# Function for euler formula
def euler( x0, y, h, x ):
    temp = -0
 
    # Iterating till the point at which we
    # need approximation
    while x0 < x:
        temp = y
        y = y + h * func(x0, y)
        x0 = x0 + h
 
    # Printing approximation
    print("Approximate solution at x = ", x, " is ", "%.6f"% y)
     
# Driver Code
# Initial Values
x0 = 0
y0 = 1
h = 0.025
 
# Value of x at which we need approximation
x = 0.1
 
euler(x0, y0, h, x)

C#




// C# program to find approximation of an ordinary
// differential equation using euler method
using System;
 
class GFG {
 
    // Consider a differential equation
    // dy/dx=(x + y + xy)
    static float func(float x, float y)
    {
        return (x + y + x * y);
    }
 
    // Function for Euler formula
    static void euler(float x0, float y, float h, float x)
    {
 
        // Iterating till the point at which we
        // need approximation
        while (x0 < x) {
            y = y + h * func(x0, y);
            x0 = x0 + h;
        }
 
        // Printing approximation
        Console.WriteLine("Approximate solution at x = "
                          + x + " is " + y);
    }
 
    // Driver program
    public static void Main()
    {
 
        // Initial Values
        float x0 = 0;
        float y0 = 1;
        float h = 0.025f;
 
        // Value of x at which we need
        // approximation
        float x = 0.1f;
 
        euler(x0, y0, h, x);
    }
}
 
// This code is contributed by Vt_m.

PHP




<?php
// PHP Program to find approximation
// of a ordinary differential equation
// using euler method
 
// Consider a differential equation
// dy/dx=(x + y + xy)
 
function func($x, $y)
{
    return ($x + $y + $x * $y);
}
 
// Function for Euler formula
function euler( $x0, $y, $h, $x)
{
    $temp = -0;
 
    // Iterating till the point
    // at which we need approximation
    while($x0 < $x)
    {
        $temp = $y;
        $y = $y + $h * func($x0, $y);
        $x0 = $x0 + $h;
    }
 
    // Printing approximation
    echo "Approximate solution at x = ",
        $x, " is ", $y, "\n";
}
 
// Driver Code
 
// Initial Values
$x0 = 0;
$y0 = 1;
$h = 0.025;
 
// Value of x at which
// we need approximation
$x = 0.1;
 
euler($x0, $y0, $h, $x);
 
 
// This code contributed by aj_36
?>

Javascript




<script>
 
// JavaScript program to find approximation of an ordinary
// differential equation using euler method
 
   // Consider a differential equation
    // dy/dx=(x + y + xy)
    function func(x, y)
    {
        return (x + y + x * y);
    }
   
    // Function for Euler formula
    function euler(x0, y, h, x)
    {
        let temp = -0;
   
        // Iterating till the point at which we
        // need approximation
        while (x0 < x) {
            temp = y;
            y = y + h * func(x0, y);
            x0 = x0 + h;
        }
   
        // Printing approximation
        document.write("Approximate solution at x = "
                           + x + " is " + y);
    }
 
// Driver Code
 
    // Initial Values
    let x0 = 0;
    let y0 = 1;
    let h = 0.025;
   
    // Value of x at which we need approximation
    let x = 0.1;
   
    euler(x0, y0, h, x);
 
// This code is contributed by chinmoy1997pal.
</script>

Output : 
 

Approximate solution at x = 0.1  is  1.11167

 

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