Adding plotting data

3 files changed, 255 insertions, 0 deletions

diff --git a/getting-started-with-lists/slides.org b/getting-started-with-lists/slides.org
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+#+LaTeX_CLASS: beamer
+#+LaTeX_CLASS_OPTIONS: [presentation]
+#+BEAMER_FRAME_LEVEL: 1
+
+#+BEAMER_HEADER_EXTRA: \usetheme{Warsaw}\useoutertheme{infolines}\usecolortheme{default}\setbeamercovered{transparent}
+#+COLUMNS: %45ITEM %10BEAMER_env(Env) %10BEAMER_envargs(Env Args) %4BEAMER_col(Col) %8BEAMER_extra(Extra)
+#+PROPERTY: BEAMER_col_ALL 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 :ETC
+#+OPTIONS:   H:5 num:t toc:nil \n:nil @:t ::t |:t ^:t -:t f:t *:t <:t
+
+#+TITLE: Plotting Data 
+#+AUTHOR: FOSSEE
+#+DATE: 2010-09-14 Tue
+#+EMAIL:     info@fossee.in
+
+# \author[FOSSEE] {FOSSEE}
+
+# \institute[IIT Bombay] {Department of Aerospace Engineering\\IIT Bombay}
+# \date{}
+
+* Tutorial Plan 
+** How to create lists
+** Structure of lists  
+** Access list elements
+** Append elements to lists
+** Deleting elements from lists
+
+
+* Summary
+
+  l=[1,2,3,4]
+  l[-1]
+  l.append(5)
+  del(l[2])
+  len(l)
+
diff --git a/plotting-data/plotting-data.rst b/plotting-data/plotting-data.rst
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+Plotting   Experimental  Data  
+=============================   
+Hello  and welcome , this tutorial on  Plotting Experimental data is 
+presented by the fossee  team.  
+
+{{{ Show the slide containing title }}}
+
+
+{{{ Show the Outline Slide }}}
+
+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
+sequence. 
+
+3. We will also see how we can use our graph to indicate Error.
+
+One needs   to  be  fimiliar  with  the   concepts  of  plotting
+mathematical functions in Python.
+
+We will use  data from a Simple Pendulum  Experiment to illustrate our
+points. 
+
+{{{ Simple Pendulum data Slide }}} 
+
+  
+  
+  
+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 
+comma  seperated values inside two square brackets.  This is also  called List 
+so to create two sequences
+
+L,t type in ipython shell. ::
+
+    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]
+
+
+  
+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)
+  
+   array([  0.4761, 0.81 , 1.4161,  1.69 , 2.1609,  2.4964, 3.1329, 
+   3.3489, 3.7636])
+
+  
+Now to plot L vs T^2 we will simply type ::
+
+  In []: plot(L,t,.)
+
+'.' here represents to plot use small dots for the point. ::
+
+  In []: clf()
+
+You can also specify 'o' for big dots.::
+ 
+  In []: plot(L,t,o)
+
+  In []: clf()
+
+
+{{{ Slide with Error data included }}}
+
+
+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]
+
+
+  
+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.')
+
+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 
+the parameters to fmt to 'ro'. ::
+
+    In []: clf()
+    In []: 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?
+
+
+{{{ Summary Slides }}}
+
+In this tutorial we have learnt : 
+
+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 }}}
+
+
+
+This tutorial was created as a part of FOSSEE project.
+
+Hope you have enjoyed and found it useful.
+
+ Thankyou
+
+ 
+
+Author              : Amit Sethi
+Internal Reviewer   :
+Internal Reviewer 2 : 
diff --git a/plotting-data/slides.org b/plotting-data/slides.org
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+#+LaTeX_CLASS: beamer
+#+LaTeX_CLASS_OPTIONS: [presentation]
+#+BEAMER_FRAME_LEVEL: 1
+
+#+BEAMER_HEADER_EXTRA: \usetheme{Warsaw}\useoutertheme{infolines}\usecolortheme{default}\setbeamercovered{transparent}
+#+COLUMNS: %45ITEM %10BEAMER_env(Env) %10BEAMER_envargs(Env Args) %4BEAMER_col(Col) %8BEAMER_extra(Extra)
+#+PROPERTY: BEAMER_col_ALL 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 :ETC
+#+OPTIONS:   H:5 num:t toc:nil \n:nil @:t ::t |:t ^:t -:t f:t *:t <:t
+
+#+TITLE: Plotting Experimental Data
+#+AUTHOR: FOSSEE
+#+DATE: 2010-09-14 Tue
+#+EMAIL:     info@fossee.in
+
+# \author[FOSSEE] {FOSSEE}
+
+# \institute[IIT Bombay] {Department of Aerospace Engineering\\IIT Bombay}
+# \date{}
+
+* Tutorial Plan 
+** Plotting Experiment Data and Error Bars 
+* Pre-requisites 
+** Plotting simple analytical Functions 
+* plot L vs. T^2 
+
+#+ORGTBL: L vs T^2 orgtbl-to-latex
+
+  | L   | T    |
+  | 0.1 | 0.69 |
+  | 0.2 | 0.90 |
+  | 0.3 | 1.19 |
+  | 0.4 | 1.30 |
+  | 0.5 | 1.47 |
+  | 0.6 | 1.58 |
+  | 0.7 | 1.77 |
+  | 0.8 | 1.83 |
+  | 0.9 | 1.94 |
+  
+  
+
+
+* Initializing L & T
+  : 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]
+* square()
+  : In []: tsquare=square(t)
+  
+  : array([ 0.4761,  0.81  ,  1.4161,  1.69  ,  2.1609,  2.4964,  3.1329,
+  :       3.3489,  3.7636])
+
+  
+* Plotting   
+  : In[]: plot(L,t,.)
+  
+
+  : In[]: plot(L,t,o)
+
+* Adding an Error Column 
+
+
+  |   L |    T | /Delta L | /Delta T |
+  | 0.1 | 0.69 |     0.08 |     0.04 |
+  | 0.2 | 0.90 |     0.09 |     0.08 |
+  | 0.3 | 1.19 |     0.07 |     0.11 |
+  | 0.4 | 1.30 |     0.05 |     0.05 |
+  | 0.5 | 1.47 |     0.06 |     0.03 |
+  | 0.6 | 1.58 |     0.00 |     0.03 |
+  | 0.7 | 1.77 |     0.06 |     0.01 |
+  | 0.8 | 1.83 |     0.06 |     0.07 |
+  | 0.9 | 1.94 |     0.01 |     0.01 |
+ 
+ 
+* Plotting Error bar 
+  
+  : In[]: delta_L= [0.08,0.09,0.07,0.05,0.16,
+  :                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]
+
+  
+