Added xlim and ylim.
* Solving Equations
*** Outline
***** Introduction
******* What are we going to do?
******* How are we going to do?
******* Arsenal Required
********* working knowledge of arrays
*** Script
Welcome.
In this tutorial we shall look at solving linear equations, roots
of polynomials and other non-linear equations. In the process, we
shall look at defining functions.
Let's begin with solving linear equations.
{show a slide of the equations}
We shall use the solve function, to solve this system of linear
equations. Solve requires the coefficients and the constants to
be in the form of matrices to solve the system of linear equations.
We begin by entering the coefficients and the constants as
matrices.
In []: A = array([[3,2,-1],
[2,-2,4],
[-1, 0.5, -1]])
In []: b = array([1, -2, 0])
Now, we can use the solve function to solve the given system.
In []: x = solve(A, b)
Type x, to look at the solution obtained.
Next, we verify the solution by obtaining a product of A and x,
and comparing it with b. Note that we should use the dot function
here, and not the * operator.
In []: Ax = dot(A, x)
In []: Ax
The result Ax, doesn't look exactly like b, but if you carefully
observe, you will see that it is the same as b. To save yourself
this trouble, you can use the allclose function.
allclose checks if two matrices are close enough to each other
(with-in the specified tolerance level). Here we shall use the
default tolerance level of the function.
In []: allclose(Ax, b)
The function returns True, which implies that the product of A &
x, and b are close enough. This validates our solution x.
Let's move to finding the roots of polynomials. We shall use the
roots function to calculate the roots of the polynomial x^2-5x+6.
The function requires an array of the coefficients of the
polynomial in the descending order of powers.
In []: coeffs = [1, -5, 6]
In []: roots(coeffs)
As you can see, roots returns the coefficients in an array.
To find the roots of any arbitrary function, we use the fsolve
function. We shall use the function sin(x)+cos^2(x) as our
function, in this tutorial. First, of all we import fsolve, since it
is not already available to us.
In []: from scipy.optimize import fsolve
Now, let's look at the arguments of fsolve using fsolve?
In []: fsolve?
The first argument, func, is a python function that takes atleast
one argument. So, we should now define a python function for the
given mathematical expression sin(x)+cos^2(x).
The second argument, x0, is the initial estimate of the roots of
the function. Based on this initial guess, fsolve returns a root.
Before, going ahead to get a root of the given expression, we
shall first learn how to define a function in python.
Let's define a function called f, which returns values of the
given mathematical expression (sin(x)+cos^2(x)) for a each input.
In []: def f(x):
return sin(x)+cos(x)*cos(x)
def, is a key word in python that tells the interpreter that a
function definition is beginning. f, here, is the name of the
function and x is the lone argument of the function. The whole
definition of the function is done with in an indented block. Our
function f has just one line in it's definition.
You can test your function, by calling it with an argument for
which the output value is know, say x = 0. We can see that
sin(x) + cos^2(x) has a value of 1, when x = 0.
Let's check our function definition, by calling it with 0 as an
argument.
In []: f(0)
We can see that the output is as expected.
Now, that we have our function, we can use fsolve to obtain a root
of the expression sin(x)+cos^2(x). Recall that fsolve takes
another argument, the initial guess. Let's use 0 as our initial
guess.
In []: fsolve(f, 0)
fsolve has returned a root of sin(x)+cos^2(x) that is close to 0.
That brings us to the end of this tutorial on solving linear
equations, finding roots of polynomials and other non-linear
equations. We have also learnt how to define functions and call
them.
Thank you!
*** Notes