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diff --git a/plotting-data/script.rst b/plotting-data/script.rst index 166256c..f2a0a29 100644 --- a/plotting-data/script.rst +++ b/plotting-data/script.rst @@ -16,38 +16,51 @@ .. Author : Amit - Internal Reviewer : + 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 -============================= -Hello and welcome , this tutorial on Plotting Experimental data is -presented by the fossee team. +=============================== {{{ Show the slide containing title }}} +Hello and welcome , this tutorial on Plotting Experimental data is +presented by the fossee team. {{{ Show the Outline Slide }}} +.. #[[Anoop: outline slide is missing]] + Here we will discuss plotting Experimental data. 1. We will see how we can represent a sequence of numbers in Python. -2. We will also become fimiliar with elementwise squaring of such a +2. We will also become familiar with elementwise squaring of such a sequence. -3. We will also see how we can use our graph to indicate Error. +3. How to plot data points using python. -One needs to be fimiliar with the concepts of plotting +4. We will also see how we can use our graph to indicate Error. + +One needs to be familiar with the concepts of plotting mathematical functions in Python. -We will use data from a Simple Pendulum Experiment to illustrate our -points. +We will use data from a Simple Pendulum Experiment to illustrate. + +.. #[[Anoop: what do you mean by points here? if you mean the + points/numbered list in outline slide, then remove the usage point + from here.]] {{{ Simple Pendulum data Slide }}} - +.. #[[Anoop: slides are incomplete, work on slides and context + switches]] As we know for a simple pendulum length,L is directly proportional to @@ -55,104 +68,151 @@ 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. To tell ipython a sequence of values we write the sequence in -comma seperated values inside two square brackets. This is also called List -so to create two sequences +of values. We define a sequence by comma seperated values inside two square brackets. +This is also called List.Lets create two sequences L and t. -L,t type in ipython shell. :: +.. #[[Anoop: instead of saying "to tell ipython a sequence of values" + and make it complicated, we can tell, we define a sequence as]] - In []: L = [0.1, 0.2, 0.3, 0.4, 0.5,0.6, 0.7, 0.8, 0.9] - - In []: t= [0.69, 0.90, 1.19,1.30, 1.47, 1.58, 1.77, 1.83, 1.94] +.. #[[Anoop: sentence is incomplete, can be removed]] +{{{ Show the initializing L&T slide }}} - -To obtain the square of sequence t we will use the function square +Type in ipython shell :: + + 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] + + +To obtain the square of sequence t we will use the function square with argument t.This is saved into the variable tsquare.:: - In []: tsquare=square(t) - + tsquare=square(t) + tsqaure array([ 0.4761, 0.81 , 1.4161, 1.69 , 2.1609, 2.4964, 3.1329, 3.3489, 3.7636]) +.. #[[Anoop: how do you get the array([ 0.4761 ....]) output?]] + Now to plot L vs T^2 we will simply type :: - In []: plot(L,t,.) + plot(L,tsquare,'.') + +.. #[[Anoop: be consistent with the spacing and all.]] '.' here represents to plot use small dots for the point. :: - In []: clf() + clf() You can also specify 'o' for big dots.:: - In []: plot(L,t,o) + plot(L,tsquare,'o') - In []: clf() + clf() -{{{ Slide with Error data included }}} +Following are exercises that you must do. + +%% %% Plot the given experimental data with large dots.The data is +on your screen. + +%% %% Plot the given experimental data with small dots. +The data is on your screen + + +Please, pause the video here. Do the exercises and then continue. -Now we shall try and take into account error into our plots . The -Error values for L and T are on your screen.We shall again intialize -the sequence values in the same manner as we did for L and t :: - In []: delta_L= [0.08,0.09,0.07,0.05,0.06,0.00,0.06,0.06,0.01] - - In []: delta_T= [0.04,0.08,0.11,0.05,0.03,0.03,0.01,0.07,0.01] +.. #[[Anoop: Make sure code is correct, corrected plot(L,t,o) to + plot(L,t,'o')]] + + + +.. #[[Anoop: again slides are incomplete.]] + +For any experimental there is always an error in measurements due to +instrumental and human constaraints.Now we shall try and take into +account error into our plots . The Error values for L and T are on +your screen.We shall again intialize the sequence values in the same +manner as we did for L and t + +The error data we will use is on your screen. + +{{{ Show the Adding Error Slide }}} +.. #[[Anoop: give introduction to error and say what we are going to + do]] + +:: + + 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] Now to plot L vs T^2 with an error bar we use the function errorbar() The syntax of the command is as given on the screen. :: - In []: errorbar(L,tsquare,xerr=delta_L, yerr=delta_T, fmt='b.') + errorbar(L,tsquare,xerr=delta_L, yerr=delta_T, fmt='b.') -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. +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 big red dots just change +similarly we can draw the same error bar with big red dots just change the parameters to fmt to 'ro'. :: - In []: clf() - In []: errorbar(L,tsquare,xerr=delta_L, yerr=delta_T, fmt='ro') + clf() + errorbar(L,tsquare,xerr=delta_L, yerr=delta_T, fmt='ro') thats it. you can explore other options to errorbar using the documentation of errorbar.:: - In []: errorbar? + errorbar? +Following is an exercise that you must do. -{{{ Summary Slides }}} +%% %% Plot the given experimental data with large green dots.Also include +the error in your plot. -In this tutorial we have learnt : +Please, pause the video here. Do the exercise and then continue. -1. How to declare a sequence of number , specifically the kind of sequence we learned was a list. -2. Plotting experimental data extending our knowledge from mathematical functions. -3. The various options available for plotting dots instead of lines. -4. Plotting experimental data such that we can also represent error. We did this using the errorbar() function. - {{{ Show the "sponsored by FOSSEE" slide }}} + +{{{ Show Summary Slide }}} + +In this tutorial we have learnt : +1. How to declare a sequence of numbers. + +2. Plotting experimental data. + +#. The various options available for plotting dots instead of lines. + +#. Plotting experimental data such that we can also represent error. + + + + {{{ Show the "sponsored by FOSSEE" slide }}} + +.. #[[Anoop: again slides are incomplete]] + This tutorial was created as a part of FOSSEE project. Hope you have enjoyed and found it useful. - Thankyou - - +Thank You! -Author : Amit Sethi -Internal Reviewer : -Internal Reviewer 2 : |