diff -r 8afa31ae6129 -r 06ac45f4de88 plotting-data/script.rst
--- a/plotting-data/script.rst	Tue Nov 09 12:42:40 2010 +0530
+++ b/plotting-data/script.rst	Tue Nov 09 15:10:13 2010 +0530
@@ -44,13 +44,14 @@
 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.
+
+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
@@ -67,29 +68,28 @@
 
 
 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.
 
 .. #[[Anoop: instead of saying "to tell ipython a sequence of values"
    and make it complicated, we can tell, we define a sequence as]]
 
-L,t type in ipython shell.
-
 .. #[[Anoop: sentence is incomplete, can be removed]]
 
-::
+{{{ Show the initializing L&T slide }}}
+
+Type in ipython shell ::
 
-    In []: L = [0.1, 0.2, 0.3, 0.4, 0.5,0.6, 0.7, 0.8, 0.9]
+    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])
 
@@ -98,49 +98,51 @@
   
 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()
 
 
 .. #[[Anoop: Make sure code is correct, corrected plot(L,t,o) to
    plot(L,t,'o')]]
 
-{{{ Slide with Error data included }}}
+
 
 .. #[[Anoop: again slides are incomplete.]]
 
-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
+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]]
 
 ::
 
-  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]
-
-
+    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
@@ -150,18 +152,18 @@
 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?
 
 
-{{{ Summary Slides }}}
+{{{ Show Summary Slide }}}
 
 In this tutorial we have learnt : 
 
@@ -182,5 +184,5 @@
 
 Hope you have enjoyed and found it useful.
 
- Thankyou
+Thank You!