Python/C3/Leastsquarefit/English
Visual Cue  Narration 

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Containing title, name of the production team along with the logo of MHRD 
Hello friends and welcome to the tutorial on 'Least Square Fit'. 
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Learning objectives 
At the end of this tutorial, you will be able to,

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Prerequisite slide 
Before beginning this tutorial,we would suggest you to complete the tutorial on "Using plot interactively", "Loading data from files" and "Getting started with arrays".
Let us start this tutorial with the help of an example. 
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Assignment 1 
Generate a least square fit line for l v/s t^2 using the data in the file 'pendulum.txt'. 
Open the file 'pendulum.txt' and show  We have an input file generated from a simple pendulum experiment.
It contains two columns of data. The first column is the length of the pendulum and the second is the corresponding time period of the pendulum. As we know, the square of time period of a pendulum is directly proportional to its length, we shall plot l vs t^2 and verify this. To read the input file and parse the data, we are going to use the loadtxt function. Switch to the terminal. 
ipython pylab
l, t = loadtxt("/home/fossee/pendulum.txt", unpack=True) l t 
We can see that l and t are two sequences containing length and time values correspondingly.
Let us first plot l vs t^2. 
tsq = t * t
plot(l, tsq, 'bo') Switch to the plot window 
We can see that there is a visible linear trend, but we do not get a straight line connecting them. We shall, therefore, generate a least square fit line.
We will first generate the two matrices tsq and A. Then we will use the lstsq function to find the values of m and c. 
Switch to the terminal
inter_mat = array((l, ones_like(l))) inter_mat 
let us now generate the A matrix with l values. We shall first generate a 2 x 90 matrix with the first row as l values and the second row as ones. Then take the transpose of it. Type 
A = inter_mat.T
A 
We see that we have intermediate matrix. Now we need the transpose. Type 
result = lstsq(A, tsq)  Now we have both the matrices A and tsq. We only need to use the lstsq Type 
m, c = result[0]
m c 
The result is a sequence of values. The first item in this sequence, is the matrix p i.e., the values of m and c. 
tsq_fit = m * l + c
plot(l, tsq, 'bo') plot(l, tsq_fit, 'r') 
Now that we have m and c, we need to generate the fitted values of t^2. Type 
We get the least square fit of l vs t^2.  
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Summary slide 
This brings us to the end of the tutorial. In this tutorial, we have learnt to,

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Self assessment questions slide 
Here are some self assessment questions for you to solve

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Solution of self assessment questions on slide 
And the answers,
Enumerated list ends without a blank line; unexpected unindent. A = array(u, ones_like(u)).T result = lstsq(A, v) m, c = result[0] lst_line = m * u + c 
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Acknowledgment slide 
Hope you have enjoyed this tutorial and found it useful. Thank you! 