path: root/plotting_data/script.rst

.. Objectives
.. ----------

.. By the end of this tutorial, you will be able to

.. 1. Defining a list of numbers
.. 2. Squaring a list of numbers
.. 3. Plotting data points.
.. 4. Plotting errorbars.


.. Prerequisites
.. -------------

..   1. getting started with plotting

     
.. Author              : Amit 
   Internal Reviewer   : Anoop Jacob Thomas<anoop@fossee.in> 
   External Reviewer   :
   Checklist OK?       : <put date stamp here, if OK> [2010-10-05]

.. #[[Anoop: Add quickref]]
.. #[[Anoop: Slides are incomplete, add summary slide, thank you slide
   etc.]]

===============================
Plotting   Experimental  Data  
===============================   

.. L1

<<<<<<< HEAD
{{{ Show the  first slide containing title, name of the production
team along with the logo of MHRD }}}
=======
Hello and welcome to this tutorial on  Plotting Experimental data, 
presented by the fossee team.  
>>>>>>> 1020097fa446ad8c6bdff784d5d0da9e98a55892

.. R1 

Hello Friens.Welcome to this tutorial on  "Plotting Experimental data"

<<<<<<< HEAD
.. L2
 
{{{ Show the Objectives Slide }}}

.. R2

At the end of this tutorial, you will be able to,

 1. Define a list of numbers.
 #. perform elementwise squaring of the list. 
 #. Plot data points.
 #. plot errorbars.

.. R3
=======
One needs   to  be  familiar  with  the   concepts  of  plotting
mathematical functions in Python.
>>>>>>> 1020097fa446ad8c6bdff784d5d0da9e98a55892

We will use data from a Simple Pendulum Experiment to illustrate. 

.. L3

{{{ Simple Pendulum data Slide }}} 

.. R4

As we know for a simple pendulum, length L is directly  proportional to 
the square of time T. We shall be plotting L and T^2 values.

First  we will have  to initiate L and  T values. We initiate them as sequence 
of values.  We define a sequence by comma seperated values inside two square brackets.  
This is also called a List.Let's create two sequences L and t.

.. L4
 
::

    L = [0.1, 0.2, 0.3, 0.4, 0.5,0.6, 0.7, 0.8, 0.9]
    
    T= [0.69, 0.90, 1.19,1.30, 1.47, 1.58, 1.77, 1.83, 1.94]

.. R5

To obtain the square of sequence T we will use the function square
with argument T.This is saved into the variable tsquare.

.. L5

::

    Tsquare=square(T)
    Tsqaure
    array([  0.4761, 0.81 , 1.4161,  1.69 , 2.1609,  2.4964, 3.1329, 
    3.3489, 3.7636])

.. R6  

Now to plot L vs T^2, we will simply type 

.. L6

<<<<<<< HEAD
::
=======
This clears the plot.

You can also specify 'o' for big dots.::
 
  plot(L,tsquare,'o')
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    plot(L,Tsquare,'.')

.. R7

<<<<<<< HEAD
here '.' represents to plot use small dots for the point.
You can also specify 'o' for big dots.
=======
Pause video here and solve this exercise. Resume the video once done.
>>>>>>> 1020097fa446ad8c6bdff784d5d0da9e98a55892

.. L7
::
    
    clf()
    plot(L,Tsquare,'o')
    clf()

.. L8

<<<<<<< HEAD
.. R8

For any experimental there is always an error in measurements due to
instrumental and human constraints.Now we shall try and take these errors into
account in our plots . 

.. L9

{{{ Show the slide 'Question 1' }}}

.. R9

Pause the video here, try out the following exercise and resume the video.
=======
.. #[[Anoop: Make sure code is correct, corrected plot(L,t,o) to
   plot(L,t,'o')]]
>>>>>>> 1020097fa446ad8c6bdff784d5d0da9e98a55892

Plot the given experimental data with large dots.The data is
on your screen. 

.. L10

{{{ Show slide "Question 1 data' }}}

.. R10

The error data we will use is on your screen.

.. R11

We shall again intialize the sequence values in the same manner as we did for L and T.

.. L11

::

    delta_L= [0.08,0.09,0.07,0.05,0.06,0.00,0.06,0.06,0.01]
    delta_T= [0.04,0.08,0.03,0.05,0.03,0.03,0.04,0.07,0.08]

.. R12
  
Now to plot L vs T^2 with an error bar we use the function ``errorbar()``.

.. L12 
::

    errorbar(L,tsquare,xerr=delta_L, yerr=delta_T, fmt='bo')

.. R13

This gives a plot with error bar for x and y axis. The dots are of
blue color. The parameters xerr and yerr are error on x and y axis and
fmt is the format of the plot.

similarly we can draw the same error bar with small red dots just change
the parameters of fmt to 'r.'. 

.. L13
::

    clf()
    errorbar(L,tsquare,xerr=delta_L, yerr=delta_T, fmt='r.')

.. R14

you can explore other options to errorbar using the documentation 
of errorbar.

.. L14

::

<<<<<<< HEAD
    errorbar?
=======
Please, pause the video here. Do the exercises and then continue.
>>>>>>> 1020097fa446ad8c6bdff784d5d0da9e98a55892

.. L15

{{{ Show slide with 'Question 2' }}}

.. R15

Pause the video here, try out the following exercise and resume the video.

Plot the given experimental data with small dots.Also include
the error in your plot. 

.. L16

{{{ Show slide 'Question 2 data' }}}

.. R16

The data is on your screen

.. L17

{{{ Show Summary Slide }}}

.. R17

let's revise quickly what we have learnt today.In this tutorial we learnt 

1. to declare a sequence of numbers using the function ``array``.
#. to perform elemtwise squaring using the ``square`` function.
#. to use the various options available for plotting like dots,lines.
#. to Plot experimental data such that we can also represent error by using the
   ``errorbar()`` function. 

.. R18

Here are some self assessment questions for you to solve

1. Square the following sequence. 
   
   distance_values=[2.1,4.6,8.72,9.03]

2. Plot L v/s T in red plusses.

.. L18
    
{{Show self assessment questions slide}}

.. L19

(solution of self assessment questions on slide)

.. R19

And the answers,

1.  To square a sequence of values, we use the function ``square``
::
 
    square(distance_values)

2. We pass an additional argument stating the desired parameter
::

    plot(L,T,'r+')

.. L20

{{{ Show the Thankyou slide }}}

.. R20

Hope you have enjoyed and found it useful.
Thank You!