st-scripts: comparison plotting-data/script.rst

equal deleted inserted replaced

-:be96dc6c9743
+:68813d8d80fb
 ..   1. getting started with plotting
 .. 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
-=============================
+===============================
+{{{ Show the slide containing title }}}
 Hello  and welcome , this tutorial on  Plotting Experimental data is
 presented by the fossee  team.
-{{{ Show the slide containing title }}}
 {{{ 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
+We will use  data from a Simple Pendulum Experiment to illustrate.
-points.
+.. #[[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
 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
+of values.  We define a sequence by comma seperated values inside two square brackets.
-comma  seperated values inside two square brackets.  This is also  called List
+This is also  called List.Lets create two sequences L and t.
-so to create two sequences
+.. #[[Anoop: instead of saying "to tell ipython a sequence of values"
-L,t type in ipython shell. ::
+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]
+.. #[[Anoop: sentence is incomplete, can be removed]]
+{{{ Show the initializing L&T slide }}}
+Type in ipython shell ::
+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]
+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
-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
-Now we  shall try  and take into  account error  into our plots . The
+on your screen.
-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 ::
+%% %% Plot the given experimental data with small dots.
+The data is on your screen
-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]
+Please, pause the video here. Do the exercises and then continue.
+.. #[[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()
+clf()
-In []: errorbar(L,tsquare,xerr=delta_L, yerr=delta_T, fmt='ro')
+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
-In this tutorial we have learnt :
+the error in your plot.
-1. How to declare a sequence of number , specifically the kind of sequence we learned was a list.
+Please, pause the video here. Do the exercise and then continue.
-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 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 :

changeset 457	68813d8d80fb
parent 434	c8ffd52305ff