--- a/lstsq/script.rst Wed Nov 17 23:24:57 2010 +0530
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,148 +0,0 @@
-.. Objectives
-.. ----------
-
-.. Plotting a least square fit line
-
-.. Prerequisites
-.. -------------
-
-.. 1. Basic Plotting
-.. 2. Arrays
-.. 3. Loading data from files
-
-.. Author : Nishanth Amuluru
- Internal Reviewer : Punch
- External Reviewer :
- Language Reviewer : Bhanukiran
- Checklist OK? : <put date stamp here, not OK> [2010-10-05]
-
-
-.. #[Puneeth: Add pre-requisites.]
-
-Script
-------
-
-Hello friends and welcome to the tutorial on Least Square Fit
-
-{{{ Show the slide containing title }}}
-
-{{{ Show the slide containing the outline slide }}}
-
-In this tutorial, we shall look at generating the least square fit line for a
-given set of points.
-
-First let us have a look at the problem.
-
-{{{ Show the slide containing problem statement. }}}
-
-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.
-
-.. #[Puneeth:] removed the explanation about loadtxt and unpack
-.. option. It's been done in another LO already. simple dependency
-.. should work?
-
-To read the input file and parse the data, we are going to use the
-loadtxt function. Type
-::
-
- 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. Type
-::
-
- tsq = t * t
- plot(l, tsq, 'bo')
-
-{{{ switch to the plot window }}}
-
-.. #[Puneeth:] Moved explanation of least square fit here. seems more
-.. apt.
-
-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.
-
-{{{ show the slide containing explanation on least square fit }}}
-
-As shown in the slide, we are first going to generate the two matrices
-tsq and A. Then we are going to use the ``lstsq`` function to find the
-values of m and c.
-
-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
-::
-
- inter_mat = array((l, ones_like(l)))
- inter_mat
-
-We see that we have intermediate matrix. Now we need the transpose. Type
-::
-
- A = inter_mat.T
- A
-
-Now we have both the matrices A and tsq. We only need to use the ``lstsq``
-Type
-::
-
- result = lstsq(A, tsq)
-
-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. Hence,
-::
-
- m, c = result[0]
- m
- c
-
-Now that we have m and c, we need to generate the fitted values of t^2. Type
-::
-
- tsq_fit = m * l + c
- plot(l, tsq, 'bo')
- plot(l, tsq_fit, 'r')
-
-We get the least square fit of l vs t^2
-
-{{{ Pause here and try out the following exercises }}}
-
-%% 2 %% change the label on y-axis to "y" and save the lines of code
- accordingly
-
-{{{ continue from paused state }}}
-
-{{{ Show summary slide }}}
-
-This brings us to the end of the tutorial.
-we have learnt
-
- * how to generate a least square fit
-
-{{{ Show the "sponsored by FOSSEE" slide }}}
-
-.. #[Nishanth]: Will add this line after all of us fix on one.
-.. This tutorial was created as a part of FOSSEE project, NME ICT, MHRD India
-
-Hope you have enjoyed and found it useful.
-Thank you
-
-
-..
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