added base scripts and questions except for matrices and other-type-of-plots. previous commit only removed unwanted files.

10 files changed, 1544 insertions, 0 deletions

diff --git a/dictionaries/script.rst b/dictionaries/script.rst
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+.. 8.4 LO: dictionaries (2)
+.. ------------------------
+.. * empty 
+.. * filled 
+.. * accessing via keys 
+.. * .values(), .keys() 
+.. * in 
+.. * iteration
+
+============
+Dictionaries
+============
+
+{{{ show the welcome slide }}}
+
+Welcome to the spoken tutorial on dictionaries.
+
+{{{ switch to next slide, outline slide }}}
+
+In this tutorial, we will see how to create empty dictionaries, learn
+about keys and values of dictionaries. Checking for elements and
+iterating over elements.
+
+{{{ switch to next slide on overview of dictionaries }}}
+
+A dictionary in general, is designed to look up meanings of
+words. Similarly, Python dictionary is also designed to look up for a
+specific key and retrieve the corresponding value. Dictionaries are
+data structures that provide key-value mappings.  Dictionaries are
+similar to lists except that instead of the values having integer
+indexes, dictionaries have keys or strings as indexes.
+
+Before we can proceed, start your IPython interpreter with the
+``-pylab`` option.
+
+{{{ start ipython interpreter by issuing command ipython -pylab }}}
+
+Let us start by creating an empty dictionary, type the following in
+your IPython interpreter.
+::
+
+    mt_dict = {}    
+
+Notice that unlike lists curly braces are used define ``dictionary``,
+
+{{{ move the mouse over curly braces to grab attention }}}
+
+Now let us see how to create a filled dictionary,
+::
+
+    extensions = {'jpg' : 'JPEG Image', 'py' : 'Python script', 'html' : 'Html document', 'pdf' : 'Portable Document Format'}
+
+Notice that each key-value pair is separated by a comma
+
+{{{ move the mouse over the commas to grab attention }}}
+
+and each key and value are separated using a colon.
+
+{{{ move the mouse over the colon one by one to grab attention }}}
+
+Here, we defined four entries in the dictionary extensions. The keys
+are
+
+{{{ spell the keys letter by letter }}}
+
+jpg, py, html, and pdf.
+
+Simply type,
+::
+
+    extensions
+
+in the interpreter to see the content of the dictionary. Notice that
+in dictionaries the order cannot be predicted and you can see that the
+values are not in the order that we entered in.
+
+Like in lists, the elements in a dictionary can be accessed using the
+index, here the index is the key. Try,
+::
+
+    print extensions['jpg']
+
+It printed JPEG Image. And now try,
+::
+
+    print extensions['zip']
+
+Well it gave us an error, saying that the key 'zip' is not in the
+dictionary.
+
+Pause here for some time and try few more keys. Also try jpg in
+capital letters.
+
+{{{ switch to next slide, adding and deleting keys and values in
+dictionaries }}}
+
+Well that was about creating dictionaries, now how do we add or delete
+items. We can add new items into dictionaries as,
+::
+
+    extensions['cpp'] = 'C++ code'
+
+and delete items using the ``del`` keyword as,
+::
+
+    del extension['pdf']
+
+Let us check the content of the dictionary now,
+::
+
+    extensions
+
+So the changes have been made. Now let us try one more thing,
+::
+
+    extensions['cpp'] = 'C++ source code'
+    extensions
+
+As you can see, it did not add a new thing nor gave an error, but it
+simply replaces the existing value with the new one.
+
+Now let us learn how to check if a particular key is present in the
+dictionary. For that we can use ``in``,
+::
+
+    'py' in extensions
+    'odt' in extensions
+
+So in short it will return ``True`` if the key is found in the
+dictionary, and will return ``False`` if key is not present. Note that
+we can check only for container-ship of keys in dictionaries and not
+values.
+
+{{{ switch to next slide, Retrieve keys and values }}}
+
+Now let us see how to retrieve the keys and values. We can use the
+method ``keys()`` for getting a list of the keys in a particular
+dictionary and the method ``values()`` for getting a list of
+values. Let us try them,
+::
+
+    extensions.keys()
+
+It returned the ``list`` of keys in the dictionary extensions. And now
+the other one,
+::
+
+    extensions.values()
+
+It returned the ``list`` of values in the dictionary.
+
+{{{ switch to next slide, problem statement for the next solved
+exercise }}}
+
+Now let us try to print the data in the dictionary. We can use ``for``
+loop to iterate.
+::
+
+    for each in extensions.keys():
+        print each, "-->", extensions[each]
+
+
+{{{ switch to next slide, recap }}}
+
+This brings us to the end of this tutorial, we learned dictionaries
+and saw how to create an empty dictionary, build a dictionary with
+some data in it, adding data, ``keys()`` and ``values()`` methods, and
+iterating over the dictionaries.
+
+{{{ switch to next slide, thank you slide }}}
+
+Thank you!
+
+..  Author: Anoop Jacob Thomas <anoop@fossee.in>
+    Reviewer 1:
+    Reviewer 2:
+    External reviewer:
diff --git a/getting-started-with-arrays/script.rst b/getting-started-with-arrays/script.rst
new file mode 100644
index 0000000..eb9ba80
--- /dev/null
+++ b/getting-started-with-arrays/script.rst
@@ -0,0 +1,242 @@
+.. 4.1 LO: getting started with arrays (2) [anoop] 
+.. ------------------------------------------------
+.. * why arrays 
+..   + speed - simply say 
+..   + array level operations 
+.. * creating arrays 
+..   + direct data 
+..   + list conversion 
+..   + homogeneous 
+..   + builtins - identitiy, zeros, 
+.. * array operations 
+..   + =+ - * /= 
+
+===========================
+Getting started with Arrays
+===========================
+
+{{{ show the welcome slide }}}
+
+Welcome to the spoken tutorial on getting started with arrays.
+
+{{{ switch to next slide, outline slide }}}
+
+In this tutorial, we will learn about arrays, how to convert a list
+into an array and also why an array is preferred over lists. And array
+operations.
+
+{{{ switch to next slide on overview of array }}}
+
+Arrays are homogeneous data structures, unlike lists, arrays cannot
+have heterogeneous data elements, that is, it can have only one type
+of data type, either all integers, or strings, or float, and not a
+mix.
+
+Arrays are really fast in mathematical operations when compared to
+lists, it is at least 80 to 100 times faster than lists.
+
+{{{ switch to the next slide, creating arrays }}}
+
+Now let us see how to create arrays.
+
+I am assuming that you have your IPython interpreter running with the
+``-pylab`` option, so that you have the required modules loaded.
+
+To create an array we will use the function ``array()`` as,
+::
+
+    a1 = array([1,2,3,4])
+
+Notice that here we created a one dimensional array. Also notice the
+object we passed to create an array. Now let us see how to create a
+two dimensional array. Pause here and try to do it yourself before
+looking at the solution.
+
+This is how we create two dimensional arrays.
+::
+
+    a2 = array([[1,2,3,4],[5,6,7,8]])
+
+Let us see an easy method of creating an array with elements 1 to 8.
+::
+
+    ar = arange(1,9)
+
+And it created a single dimensional array of elements from 1 to 8.
+::
+
+    print ar
+
+And how can we make it a two dimensional array of order 2 by 4. Pause
+here and try to do it yourself, try ``ar.tab`` and find a suitable
+method for that.
+
+We can use the function ``reshape()`` for that purpose and it can be
+done as,
+::
+
+    ar.reshape(2,4)
+    ar.reshape(4,2)
+    ar = ar.reshape(2,4)
+
+Now, let us see how to convert a list object to an array. As you have
+already seen, in both of the previous statements we have passed a
+list, so creating an array can be done so, first let us create a list
+``l1``
+::
+
+    l1 = [1,2,3,4]
+
+Now we can convert the list to an array as,
+::
+
+    a3 = array(l1)
+
+
+{{{ switch to the next slide, problem statement of unsolved exercise 1 }}}
+
+Create a three dimensional array of the order (2,2,4).
+
+{{{ switch to the next slide, shape of an array }}}
+
+To find the shape of an array we can use the object ``.shape``, let us
+check the shape of the arrays we have created so far,
+::
+
+    a1.shape
+
+``a1.shape`` object is a tuple, and since a1 is a single dimensional
+array, it returned a tuple (4,).
+
+{{{ switch to the next slide, unsolved exercise 2 }}}
+
+Find out the shape of the other two arrays that we have created.
+
+{{{ Array can have only a single type of data }}}
+
+Now let us try to create a new array with a mix of elements and see
+what will happen,
+::
+
+    a4 = array([1,2,3,'a string'])
+
+Well, we expected an error as previously I said that an array can have
+only homogeneous elements, but it didn't give an error. Let us check
+the values in the new array created. In your IPython terminal type,
+::
+
+    a4
+
+Did you notice it, 
+
+{{{ highlight all the array elements one by one using mouse 
+movements }}}
+
+all the elements have been implicitly type casted as string, though
+our first three elements were integers.
+
+{{{ switch to the next slide, identity & zeros methods }}}
+
+An identity matrix is a square matrix in which all the diagonal
+elements are one and rest of the elements zero. We can create an
+identity matrix using the method ``identity()``.
+
+The function ``identity()`` takes an integer argument,
+::
+
+    identity(3)
+
+As you can see the identity method returned a three by three square
+array with all the diagonal elements as one and the rest of the
+elements as zero.
+
+``zeros()`` function accepts a tuple, which is the order of the array
+we want to create, and it generates an array with all elements zero.
+
+{{{ switch to the next slide, problem statement of the solved exercise
+1 }}}
+
+Let us creates an array of the order four by five with all the
+elements zero. We can do it using the method zeros,
+::
+
+    zeros((4,5))
+
+Notice that we passed a tuple to the function zeros.
+
+{{{ switch to next slide, learning exercise }}}
+
+We learned two functions ``identity()`` and ``zeros()``, find out more
+about the functions ``zeros_like()``, ``ones()``, ``ones_like()``.
+
+{{{ switch to next slide, array operations }}}
+
+Try the following, first check the value of a1,
+::
+
+    a1
+
+``a1`` is a single dimensional array, and now try,
+::
+
+    a1 * 2
+
+It returned a new array with all the elements multiplied by 2.
+::
+
+    a1
+
+note that the value of a1 still remains the same.
+
+Similarly with addition,
+::
+
+    a1 + 2
+
+it returns a new array, with all the elements summed with two. But
+again notice that the value of a1 has not been changed.
+::
+
+    a1
+
+You may change the value of a1 by simply assigning the newly returned
+array as,
+::
+
+    a1 += 2
+
+Notice the change in elements of a,
+::
+
+    a
+
+We can use all the mathematical operations with arrays, Now let us try
+this
+::
+
+   a1 = array([1,2,3,4])
+   a2 = array([1,2,3,4])
+   a1 + a2
+
+Returns an array with element by element addition,
+::
+
+    a1 * a2
+
+Returns an array with element by element multiplication, notice that
+it does not perform matrix multiplication.
+
+{{{ switch to next slide, recap slide }}}
+
+So this brings us to the end of this tutorial, in this tutorial we
+covered basics of arrays, how to create an array, converting a list to
+an array, basic array operations etc.
+
+{{{ switch to next slide, thank you }}}
+
+Thank you!
+
+..  Author: Anoop Jacob Thomas <anoop@fossee.in>
+    Reviewer 1:
+    Reviewer 2:
+    External reviewer:
diff --git a/getting-started-with-for/script.rst b/getting-started-with-for/script.rst
new file mode 100644
index 0000000..ce6e26c
--- /dev/null
+++ b/getting-started-with-for/script.rst
@@ -0,0 +1,273 @@
+.. 3.2 LO: getting started with =for= (2) [anoop] 
+.. -----------------------------------------------
+.. * blocks in python 
+..   + (indentation) 
+.. * blocks in ipython 
+..   + ... prompt 
+..   + hitting enter 
+.. * =for= with a list 
+.. * =range= function 
+
+=============================
+Getting started with for loop
+=============================
+
+{{{ show welcome slide }}}
+
+Hello and welcome to the tutorial getting started with ``for`` loop. 
+
+{{{ switch to next slide, outline slide }}}
+
+In this tutorial we will learn about ``for`` loops in python, and also
+learn how to write blocks of code in Python.
+
+.. #[Nishanth]: Instead of saying basics of indenting code,
+                say How to define code blocks in Python
+
+{{{ switch to next slide, about whitespaces }}}
+
+In Python whitespace is significant, and the blocks are visually
+separated.
+
+.. #[nishanth]: Simply tell how blocks are defined in python.
+                The details like braces are not used and its
+                advantages like neat code can be told after completely
+                explaining the indentation
+
+.. #[Amit]: Do you want to do that here. May be its better to talk about 
+   this after some initiation into the idea of blocks. 
+
+The best practice is to indent the code using four spaces.
+
+.. #[Nishanth]: Even this detail may be skipped. Simply say use 4 spaces
+                for indentation. Do that while typing so that they can
+                actually see what is being typed.
+
+Now let us move straight into ``for`` loop.
+
+{{{ switch to next slide, problem statement of exercise 1 }}}
+
+
+Write a for loop which iterates through a list of numbers and find the
+square root of each number.
+::
+
+    numbers are 1369, 7225, 3364, 7056, 5625, 729, 7056, 576, 2916
+
+.. #[nishanth]: making new list with square roots induces extra complication
+                like appending which has no use case here
+
+.. #[Nishanth]: The problem focuses more on square root and creation
+                of list. The problem must be simple and focusing on 
+                nothing more but the indentation and for loop.
+                May be change the problem to print squares than to
+                print square roots.
+
+For the problem, first we need to create a ``list`` of numbers and
+then iterate over the list and find the square root of each element in
+it. And let us create a script, rather than typing it out in the
+interpreter itself. Create a script called list_roots.py and type the
+following.
+
+{{{ open the text editor and paste the following code there }}}
+::
+
+    numbers = [1369, 7225, 3364, 7056, 5625, 729, 7056, 576, 2916]
+    for each in numbers:
+        print "Square root of", each, "is", sqrt(each)
+    print "This is not in for loop!"
+
+..  numbers = [1, 12, 3, 4, 21, 17]
+    for each in numbers:
+        print each, each * each
+
+.. #[nishanth]: I don't see a use case to append the sq_root to
+                square_roots. It is only complicating stuff.
+                Simply iterate and print.
+
+{{{ save the script }}}
+
+Now save the script, and run it from your IPython interpreter. I
+assume that you have started your IPython interpreter using ``-pylab``
+option.
+
+Run the script as,
+::
+
+    %run -i list_roots.py
+
+.. #[Nishanth]: you don't have to use the -i option here
+
+{{{ run the script }}}
+
+So that was easy! All what we did was iterate over the list element by
+element and then use the element for calculation. Note that here we
+used two variables. One the variable ``numbers``, which is a list,
+another one ``each``, which is the element of list under consideration
+in each cycle of the ``for`` loop. The variable names can be chosen by
+you.
+
+.. #[Nishanth]: The details like we didn't have to find the length
+                are relevant for people who have programmed in C or
+                other languages earlier. But for a newbie it is more
+                of confusing extra info. That part may be skipped.
+                Simply go ahead and focus on the syntax of for loop.
+                And how the variable name is used inside the for loop.
+                If you modify the question to only print, the extra 
+                variable sq_root can also be avoided. let it be more
+                about "each", "numbers" and "for". no other new names.
+
+{{{ show the script which was created }}}
+
+Note that the lines after ``for`` statement, is indented using four
+spaces.
+
+{{{ highlight the line after for statement }}}
+
+It means that line is part of the for loop. And it is a block of code,
+although it is only a single statement in the block. And the fourth
+line or the immediate line after the ``for`` block is not indented,
+
+{{{ highlight the fourth line - the line just after for loop }}}
+
+it means that it is not part of the ``for`` loop and the lines after
+that doesn't fall in the scope of the ``for`` loop. Thus each block is
+separated by the indentation level. Thus marking the importance of
+white-spaces in Python.
+
+{{{ switch to the slide which shows the problem statement of the first
+problem to be tried out }}}
+
+Now a question for you to try, from the given numbers make a list of
+perfect squares and a list of those which are not. The numbers are,
+::
+    
+    7225, 3268, 3364, 2966, 7056, 5625, 729, 5547, 7056, 576, 2916
+
+{{{ switch to next slide, problem statement of second problem in
+solved exercise}}}
+
+Now let us try a simple one, to print the square root of numbers in
+the list. And this time let us do it right in the IPython
+interpreter. 
+
+{{{ switch focus to the IPython interpreter }}}
+
+So let us start with making a list. Type the following
+::
+
+    numbers = [1369, 7225, 3364, 7056, 5625, 729, 7056, 576, 2916]
+    for each in numbers:
+
+and now you will notice that, as soon as you press the return key
+after for statement, the prompt changes to four dots and the cursor is
+not right after the four dots but there are four spaces from the
+dots. Please note that IPython automatically indents the block. The
+four dots tell you that you are inside a block. Now type the rest of
+the ``for`` loop,
+
+.. #[Nishanth]: Tell that IPython does auto indentation.
+
+::
+
+        print "Square root of", each, "is", sqrt(each)
+
+Now we have finished the statements in the block, and still the
+interpreter is showing four dots, which means you are still inside the
+block. To exit from the block press return key or the enter key twice
+without entering anything else. It printed the square root of each
+number in the list, and that is executed in a ``for`` loop.
+
+Now, let us find the cube of all the numbers from one to ten. But this
+time let us try it in the vanilla version of Python interpreter.
+
+Start the vanilla version of Python interpreter by issuing the command
+``python`` in your terminal.
+
+{{{ open the python interpreter in the terminal using the command
+python to start the vanilla Python interpreter }}}
+
+Start with,
+::
+    
+    for i in range(1,11):
+
+and press enter once, and we will see that this time it shows four
+dots, but the cursor is close to the dots, so we have to indent the
+block. The vanilla version of Python interpreter does not indent the
+code automatically. So enter four spaces there and then type the
+following
+::
+    
+        print i, "cube is", i**3
+
+Now when we hit enter, we still see the four dots, to get out of the
+block, hit enter once again
+
+.. #[Nishanth]: Here also the overhead on print can be reduced.
+                Think of a simple print statement. This statement
+                will be confusing for a newbie.
+                We can focus more on indentation in python.
+
+.. #[nishanth]: Not sure if you must use range here. You can 
+                define a list of numbers and iterate on it.
+                Then say this list can also be generated using
+                the range function and hence introduce range.
+
+Okay! so the main thing here we learned is how to use Python
+interpreter and IPython interpreter to specify blocks. But while we
+were generating the multiplication table we used something new,
+``range()`` function. ``range()`` is an inbuilt function in Python
+which can be used to generate a ``list`` of integers from a starting
+number to an ending number. Note that the ending number that you
+specify will not be included in the ``list``.
+
+.. #[Nishanth]: Show some examples of range without the step argument
+                May be give an exercise with negative numbers as arguments
+
+Now, let us print all the odd numbers from 1 to 50. Let us do it in
+our IPython interpreter for ease of use.
+
+{{{ switch to next slide, problem statement of the next problem in
+solved exercises }}}
+
+{{{ switch focus to ipython interpreter }}}
+
+The problem can be solved by just using the ``range()`` function.
+
+It can be solved as,
+::
+
+    print range(1,51,2)
+
+This time we passed three parameters to ``range()`` function unlike
+the previous case where we passed only two parameters. The first two
+parameters are the same in both the cases. The first parameter is the
+starting number of the sequence and the second parameter is the end of
+the range. Note that the sequence doesn't include the ending
+number. The third parameter is for stepping through the sequence. Here
+we gave two which means we are skipping every alternate element.
+
+{{{ switch to next slide, recap slide }}}
+
+Thus we come to the end of this tutorial. We learned about blocks in
+Python, indentation, blocks in IPython, for loop, iterating over a
+list and then the ``range()`` function.
+
+.. #[Amit]: There does seem to too much overhead of details. Should
+            the first example be done using script is it necessary. 
+	    Do add some things in evolutionary manner. Like introducing 
+	    range as a list and doing a very very simple for loop.Like
+	    iterating over [1,2,3] .Before getting into a problem.
+	    And club details about problem in one paragraph and syntactic details
+	    in other.
+
+{{{ switch to next slide, thank you slide }}}
+
+Thank you!
+
+..  Author: Anoop Jacob Thomas <anoop@fossee.in>
+    Reviewer 1: Nishanth
+    Reviewer 2: Amit Sethi
+    External reviewer:
+
diff --git a/matrices/script.rst b/matrices/script.rst
new file mode 100644
index 0000000..fa30811
--- /dev/null
+++ b/matrices/script.rst
@@ -0,0 +1,265 @@
+.. 4.3 LO: Matrices (3) [anoop] 
+.. -----------------------------
+.. * creating matrices 
+..   + direct data 
+..   + list conversion 
+..   + builtins - identitiy, zeros, 
+.. * matrix operations 
+..   + + - * / 
+..   + dot 
+..   + inv 
+..   + det 
+..   + eig 
+..   + norm 
+..   + svd 
+
+========
+Matrices
+========
+{{{ show the welcome slide }}}
+
+Welcome to the spoken tutorial on Matrices.
+
+{{{ switch to next slide, outline slide }}}
+
+In this tutorial we will learn about matrices, creating matrices and
+matrix operations.
+
+{{{ creating a matrix }}}
+
+All matrix operations are done using arrays. Thus all the operations
+on arrays are valid on matrices also. A matrix may be created as,
+::
+
+    m1 = matrix([1,2,3,4])
+
+Using the tuple ``m1.shape`` we can find out the shape or size of the
+matrix,
+::
+
+    m1.shape
+
+Since it is a one row four column matrix it returned a tuple, one by
+four.
+
+A list can be converted to a matrix as follows,
+::
+
+    l1 = [[1,2,3,4],[5,6,7,8]]
+    m2 = matrix(l1)
+
+Note that all matrix operations are done using arrays, so a matrix may
+also be created as
+::
+
+    m3 = array([[5,6,7,8],[9,10,11,12]])
+
+{{{ switch to next slide, matrix operations }}}
+
+We can do matrix addition and subtraction as,
+::
+
+    m3 + m2
+
+does element by element addition, thus matrix addition.
+
+Similarly,
+::
+
+    m3 - m2
+
+it does matrix subtraction, that is element by element
+subtraction. Now let us try,
+::
+
+    m3 * m2
+
+Note that in arrays ``array(A) star array(B)`` does element wise
+multiplication and not matrix multiplication, but unlike arrays, the
+operation ``matrix(A) star matrix(B)`` does matrix multiplication and
+not element wise multiplication. And in this case since the sizes are
+not compatible for multiplication it returned an error.
+
+And element wise multiplication in matrices are done using the
+function ``multiply()``
+::
+
+    multiply(m3,m2)
+
+Now let us see an example for matrix multiplication. For doing matrix
+multiplication we need to have two matrices of the order n by m and m
+by r and the resulting matrix will be of the order n by r. Thus let us
+first create two matrices which are compatible for multiplication.
+::
+
+    m1.shape
+
+matrix m1 is of the shape one by four, let us create another one of
+the order four by two,
+::
+
+    m4 = matrix([[1,2],[3,4],[5,6],[7,8]])
+    m1 * m4
+
+thus unlike in array object ``star`` can be used for matrix multiplication
+in matrix object.
+
+{{{ switch to next slide, recall from arrays }}}
+
+As we already saw in arrays, the functions ``identity()``,
+``zeros()``, ``zeros_like()``, ``ones()``, ``ones_like()`` may also be
+used with matrices.
+
+{{{ switch to next slide, matrix operations }}}
+
+To find out the transpose of a matrix we can do,
+::
+
+    print m4
+    m4.T
+
+Matrix name dot capital T will give the transpose of a matrix
+
+{{{ switch to next slide, Euclidean norm of inverse of matrix }}}
+
+Now let us try to find out the Euclidean norm of inverse of a 4 by 4
+matrix, the matrix being,
+::
+
+    m5 = matrix(arange(1,17).reshape(4,4))
+    print m5
+
+The inverse of a matrix A, A raise to minus one is also called the
+reciprocal matrix such that A multiplied by A inverse will give 1. The
+Euclidean norm or the Frobenius norm of a matrix is defined as square
+root of sum of squares of elements in the matrix. Pause here and try
+to solve the problem yourself, the inverse of a matrix can be found
+using the function ``inv(A)``.
+
+And here is the solution, first let us find the inverse of matrix m5.
+::
+
+    im5 = inv(m5)
+
+And the euclidean norm of the matrix ``im5`` can be found out as,
+::
+
+    sum = 0
+    for each in array(im5.flatten())[0]:
+        sum += each * each
+    print sqrt(sum)
+
+{{{ switch to next slide, infinity norm }}}
+
+Now try to find out the infinity norm of the matrix im5. The infinity
+norm of a matrix is defined as the maximum value of sum of the
+absolute of elements in each row. Pause here and try to solve the
+problem yourself.
+
+The solution for the problem is,
+::
+
+    sum_rows = []
+    for i in im5:
+        sum_rows.append(abs(i).sum())
+    print max(sum_rows)
+
+{{{ switch to slide the ``norm()`` method }}}
+
+Well! to find the Euclidean norm and Infinity norm we have an even easier
+method, and let us see that now.
+
+The norm of a matrix can be found out using the method
+``norm()``. Inorder to find out the Euclidean norm of the matrix im5,
+we do,
+::
+
+    norm(im5)
+
+And to find out the Infinity norm of the matrix im5, we do,
+::
+
+    norm(im5,ord=inf)
+
+This is easier when compared to the code we wrote. Do ``norm``
+question mark to read up more about ord and the possible type of norms
+the norm function produces.
+
+{{{ switch to next slide, determinant }}}
+
+Now let us find out the determinant of a the matrix m5. 
+
+The determinant of a square matrix can be obtained using the function
+``det()`` and the determinant of m5 can be found out as,
+::
+
+    det(m5)
+
+{{{ switch to next slide, eigen vectors and eigen values }}}
+
+The eigen values and eigen vector of a square matrix can be computed
+using the function ``eig()`` and ``eigvals()``.
+
+Let us find out the eigen values and eigen vectors of the matrix
+m5. We can do it as,
+::
+
+    eig(m5)
+
+Note that it returned a tuple of two matrices. The first element in
+the tuple are the eigen values and the second element in the tuple are
+the eigen vectors. Thus the eigen values are,
+::
+
+    eig(m5)[0]
+
+and the eigen vectors are,
+::
+
+    eig(m5)[1]
+
+The eigen values can also be computed using the function ``eigvals()`` as,
+::
+
+    eigvals(m5)
+
+{{{ switch to next slide, singular value decomposition }}}
+
+Now let us learn how to do the singular value decomposition or S V D
+of a matrix.
+
+Suppose M is an m×n matrix whose entries come from the field K, which
+is either the field of real numbers or the field of complex
+numbers. Then there exists a factorization of the form
+
+    M = U\Sigma V star
+
+where U is an (m by m) unitary matrix over K, the matrix \Sigma is an
+(m by n) diagonal matrix with nonnegative real numbers on the
+diagonal, and V*, an (n by n) unitary matrix over K, denotes the
+conjugate transpose of V. Such a factorization is called the
+singular-value decomposition of M.
+
+The SVD of matrix m5 can be found as
+::
+
+    svd(m5)
+
+Notice that it returned a tuple of 3 elements. The first one U the
+next one Sigma and the third one V star.
+    
+{{{ switch to next slide, recap slide }}}
+
+So this brings us to the end of this tutorial. In this tutorial, we
+learned about matrices, creating matrices, matrix operations, inverse
+of matrices, determinant, norm, eigen values and vectors and singular
+value decomposition of matrices.
+
+{{{ switch to next slide, thank you }}}
+
+Thank you!
+
+..  Author: Anoop Jacob Thomas <anoop@fossee.in>
+    Reviewer 1:
+    Reviewer 2:
+    External reviewer:
diff --git a/other-type-of-plots/script.rst b/other-type-of-plots/script.rst
new file mode 100644
index 0000000..010045b
--- /dev/null
+++ b/other-type-of-plots/script.rst
@@ -0,0 +1,220 @@
+.. 2.4 LO: other types of plots (3) [anoop] 
+.. -----------------------------------------
+.. * scatter 
+.. * pie chart 
+.. * bar chart 
+.. * log 
+.. * illustration of other plots, matplotlib help
+
+===================
+Other type of plots
+===================
+
+{{{ show the first slide }}}
+
+Hello and welcome to the tutorial other type of plots.
+
+{{{ show the outline slide }}}
+
+In this tutorial we will cover scatter plot, pie chart, bar chart and
+log plot. We will also see few other plots and also introduce you to
+the matplotlib help.
+
+
+Let us start with scatter plot. 
+
+{{{ switch to the next slide }}}
+
+In a scatter plot, the data is displayed as a collection of points,
+each having the value of one variable determining the position on the
+horizontal axis and the value of the other variable determining the
+position on the vertical axis. This kind of plot is also called a
+scatter chart, scatter diagram and scatter graph.
+
+Before we proceed further get your IPython interpreter running with
+the ``-pylab`` option. Start your IPython interpreter as
+::
+
+    ipython -pylab
+
+{{{ open the ipython interpreter in the terminal using the command
+ipython -pylab }}}
+
+{{{ switch to the next slide having the problem statement of first
+exercise }}}
+
+Now, let us plot a scatter plot showing the percentage profit of company A
+from the year 2000-2010. The data for the same is available in the
+file ``company-a-data.txt``. 
+
+{{{ open the file company-a-data.txt and show the content }}}
+
+The data file has two lines with a set of values in each line, the
+first line representing years and the second line representing the
+profit percentages.
+
+{{{ close the file and switch to the terminal }}}
+
+To product the scatter plot first we need to load the data from the
+file using ``loadtxt``. We learned in one of the previous sessions,
+and it can be done as ::
+
+    year,profit = loadtxt('/home/fossee/other-plot/company-a-data.txt',dtype=type(int()))
+
+Now in-order to generate the scatter graph we will use the function 
+``scatter()`` 
+::
+
+	scatter(year,profit)
+
+Notice that we passed two arguments to ``scatter()`` function, first
+one the values in x-coordinate, year, and the other the values in
+y-coordinate, the profit percentage.
+
+{{{ switch to the next slide which has the problem statement of
+problem to be tried out }}}
+
+Now here is a question for you to try out, plot the same data with red
+diamonds. 
+
+**Clue** - *try scatter? in your ipython interpreter* 
+
+.. scatter(year,profit,color='r',marker='d')
+
+Now let us move on to pie chart.
+
+{{{ switch to the slide which says about pie chart }}}
+
+A pie chart or a circle graph is a circular chart divided into
+sectors, illustrating proportion.
+
+{{{ switch to the slide showing the problem statement of second
+exercise question }}}
+
+Plot a pie chart representing the profit percentage of company A, with
+the same data from file ``company-a-data.txt``. So let us reuse the
+data we have loaded from the file previously.
+
+We can plot the pie chart using the function ``pie()``.
+::
+
+   pie(profit,labels=year)
+
+Notice that we passed two arguments to the function ``pie()``. The
+first one the values and the next one the set of labels to be used in
+the pie chart.
+
+{{{ switch to the next slide which has the problem statement of
+problem to be tried out }}}
+
+Now here is a question for you to try out, plot a pie chart with the
+same data with colors for each wedges as white, red, black, magenta,
+yellow, blue, green, cyan, yellow, magenta and blue respectively.
+
+**Clue** - *try pie? in your ipython interpreter* 
+
+.. pie(t,labels=s,colors=('w','r','k','m','y','b','g','c','y','m','b'))
+
+{{{ switch to the slide which says about bar chart }}}
+
+Now let us move on to bar chart. A bar chart or bar graph is a chart
+with rectangular bars with lengths proportional to the values that
+they represent.
+
+{{{ switch to the slide showing the problem statement of third
+exercise question }}}
+
+Plot a bar chart representing the profit percentage of company A, with
+the same data from file ``company-a-data.txt``. 
+
+So let us reuse the data we have loaded from the file previously.
+
+We can plot the bar chart using the function ``bar()``.
+::
+
+   bar(year,profit)
+
+Note that the function ``bar()`` needs at least two arguments one the
+values in x-coordinate and the other values in y-coordinate which is
+used to determine the height of the bars.
+
+{{{ switch to the next slide which has the problem statement of
+problem to be tried out }}}
+
+Now here is a question for you to try, plot a bar chart which is not
+filled and which is hatched with 45\ :sup:`o` slanting lines as shown
+in the image in the slide.
+
+**Clue** - *try bar? in your ipython interpreter* 
+
+.. bar(year,profit,fill=False,hatch='/')
+
+{{{ switch to the slide which says about bar chart }}}
+
+Now let us move on to log-log plot. A log-log graph or log-log plot is
+a two-dimensional graph of numerical data that uses logarithmic scales
+on both the horizontal and vertical axes. Because of the nonlinear
+scaling of the axes, a function of the form y = ax\ :sup:`b` will
+appear as a straight line on a log-log graph
+
+{{{ switch to the slide showing the problem statement of fourth
+exercise question }}}
+
+
+Plot a `log-log` chart of y=5*x\ :sup:`3` for x from 1-20.
+
+Before we actually plot let us calculate the points needed for
+that. And it could be done as,
+::
+
+    x = linspace(1,20,100)
+    y = 5*x**3
+
+Now we can plot the log-log chart using ``loglog()`` function,
+::
+
+    loglog(x,y)
+
+To understand the difference between a normal ``plot`` and a ``log-log
+plot`` let us create another plot using the function ``plot``.
+::
+
+    figure(2)
+    plot(x,y)
+
+{{{ show both the plots side by side }}}
+
+So that was ``log-log() plot``.
+
+{{{ switch to the next slide which says: "How to get help on
+matplotlib online"}}}
+
+Now we will see few more plots and also see how to access help of
+matplotlib over the internet.
+
+Help about matplotlib can be obtained from
+matplotlib.sourceforge.net/contents.html
+
+.. #[[Anoop: I am not so sure how to do the rest of it, so I guess we
+   can just browse through the side and tell them few. What is your
+   opinion??]]
+
+Now let us see few plots from
+matplotlib.sourceforge.net/users/screenshots.html
+
+{{{ browse through the site quickly }}}
+
+{{{ switch to recap slide }}}
+
+Now we have come to the end of this tutorial. We have covered scatter
+plot, pie chart, bar chart, log-log plot and also saw few other plots
+and covered how to access the matplotlib online help.
+
+{{{ switch to the thank you slide }}}
+
+Thank you!
+
+..  Author: Anoop Jacob Thomas <anoop@fossee.in>
+    Reviewer 1:
+    Reviewer 2:
+    External reviewer:
diff --git a/savefig/script.rst b/savefig/script.rst
new file mode 100644
index 0000000..506428e
--- /dev/null
+++ b/savefig/script.rst
@@ -0,0 +1,118 @@
+.. 2.5 LO: saving plots (2) 
+.. -------------------------
+.. * Outline 
+..   + basic savefig 
+..   + png, pdf, ps, eps, svg 
+..   + going to OS and looking at the file 
+
+=======
+Savefig
+=======
+
+Hello and welcome to the tutorial. In this tutorial you will learn how
+to save plots using Python.
+
+Start your IPython interpreter with the command ::
+
+  ipython -pylab
+
+It will start your IPython interpreter with the required python
+modules for plotting and saving your plots.
+
+{{{ Open ipython }}}
+
+Now let us plot something, let us plot a sine wave from minus 3 pi to
+3 pi. Let us start by calculating the required points for the plot. It
+can be done using linspace as, ::
+
+  x = linspace(-3*pi,3*pi,100)
+
+We have stored required points in x. Now let us plot the points using
+the statement ::
+
+  plot(x,sin(x))
+
+{{{ Keep the plot open }}}
+
+Done! we have made a very basic sine plot, now let us see how to save
+the plot for future use so that you can embed the plot in your
+reports.
+
+{{{ Switch the focus to IPython interpreter window }}}
+
+For saving the plot, we will use savefig function, and it has to be
+done with the plot window open. The statement is, ::
+
+  savefig('/home/fossee/sine.png')
+
+Notice that ``savefig`` function takes one argument which is a string
+which is the filename. The last 3 characters after the ``.`` in the
+filename is the extension or type of the file which determines the
+format in which you want to save.
+
+{{{ Highlight the /home/fossee part using mouse movements }}}
+
+Also, note that we gave the full path or the absolute path to which we
+want to save the file.
+
+{{{ Highlight the .png part using mouse movements }}}
+
+Here I have used an extension ``.png`` which means i want to save the
+image as a PNG file.
+
+Now let us locate ``sine.png`` file saved. We saved the file to
+``/home/fossee`` so let us navigate to ``/home/fossee`` using the
+file browser.
+
+{{{ Open the browser, navigate to /home/fossee and highlight the file
+sine.png }}}
+
+Yes, the file ``sine.png`` is here and let us check it.
+
+{{{ Open the file sine.png and show it for two-three seconds and then
+close it and return to IPython interpreter, make sure the plot window
+is still open, also don't close the file browser window }}}
+
+So in-order to save a plot, we use ``savefig`` function. ``savefig``
+can save the plot in many formats, such as pdf - portable document
+format, ps - post script, eps - encapsulated post script, svg -
+scalable vector graphics, png - portable network graphics which
+support transparency etc.
+
+.. #[[slide must give the extensions for the files - Anoop]]
+
+Let us now try to save the plot in eps format. ``eps`` stands for
+encapsulated post script, and it can be embedded in your latex
+documents.
+
+{{{ Switch focus to the already open plot window }}}
+
+We still have the sine plot with us, and now let us save the plot as
+``sine.eps``.
+
+{{{ Switch focus to IPython interpreter }}}
+
+Now, We will save the plot using the function ``savefig`` ::
+
+  savefig('/home/fossee/sine.eps')
+
+{{{ Switch focus to file browser window }}}
+
+Now let us go to ``/home/fossee`` and see the new file created.
+
+{{{ Highlight the file sine.eps with a single mouse click for 2
+seconds and then double click and open the file }}}
+
+Yes! the new file ``sine.eps`` is here.
+
+Now you may try saving the same in pdf, ps, svg formats.
+
+Let us review what we have learned in this session! We have learned to
+save plots in different formats using the function ``savefig()``.
+
+Thank you!
+
+..  Author: Anoop Jacob Thomas <anoop@fossee.in>
+    Reviewer 1:
+    Reviewer 2:
+    External reviewer:
diff --git a/using python modules/four_plot.png b/using python modules/four_plot.png
new file mode 100644
index 0000000..00a3a7a
--- /dev/null
+++ b/using python modules/four_plot.png
diff --git a/using python modules/four_plot.py b/using python modules/four_plot.py
new file mode 100644
index 0000000..b158717
--- /dev/null
+++ b/using python modules/four_plot.py
@@ -0,0 +1,11 @@
+x=linspace(-5*pi, 5*pi, 500)
+plot(x, x, 'b')
+plot(x, -x, 'b')
+plot(x, sin(x), 'g', linewidth=2)
+plot(x, x*sin(x), 'r', linewidth=3)
+legend(['x', '-x', 'sin(x)', 'xsin(x)'])
+annotate('origin', xy = (0, 0))
+title('Four Plot')
+xlim(-5*pi, 5*pi)
+ylim(-5*pi, 5*pi)
+#show()
diff --git a/using python modules/script.rst b/using python modules/script.rst
new file mode 100644
index 0000000..aa00863
--- /dev/null
+++ b/using python modules/script.rst
@@ -0,0 +1,227 @@
+.. 9.3 LO: using python modules (3)
+.. ---------------------------------
+.. * executing python scripts from command line
+.. * import
+.. * scipy
+.. * pylab
+.. * sys
+.. * STDLIB modules show off
+
+====================
+Using Python modules
+====================
+{{{ show the welcome slide }}}
+
+Welcome to the spoken tutorial on using python modules.
+
+{{{ switch to next slide, outline slide }}}
+
+In this tutorial, we will see how to run python scripts from command
+line, importing modules, importing scipy and pylab modules.
+
+{{{ switch to next slide on executing python scripts from command line }}}
+
+Let us create a simple python script to print hello world. Open your
+text editor and type the following,
+
+{{{ open the text editor and type the following }}}
+::
+
+    print "Hello world!"
+    print
+
+and save the script as hello.py,
+
+{{{ save the script as hello.py }}}
+
+Till now we saw how to run a script using the IPython interpreter
+using the
+::
+
+    %run -i hello.py
+
+option, but that is not the correct way of running a python
+script. 
+
+The correct method is to run it using the Python interpreter. Open the
+terminal and navigate to the directory where hello.py is,
+
+{{{ open terminal and navigate to directory where hello.py was saved }}}
+
+now run the Python script as,
+::
+
+    python hello.py
+
+It executed the script and we got the output ``Hello World!``.
+
+{{{ highlight ``python filename`` syntax on slide while narrating }}}
+
+The syntax is python space filename.
+
+Now recall the four plot problem where we plotted four plots in a single
+figure. Let us run that script from command line.
+
+If you don't have the script, 
+
+{{{ open the four_plot.py file in text editor }}}
+
+just pause here and create a python script with the following lines
+and save it as four_plot.py.
+
+Now let us run four_plot.py as a python script.
+::
+
+    python four_plot.py
+
+Oops! even though it was supposed to work, it didn't. It gave an error
+``linspace()`` is not defined, which means that the function
+``linspace()`` is not available in the current name-space.
+
+But if you try to run the same script using ``%run -i four_plot.py``
+in your IPython interpreter started with the option ``-pylab`` it will
+work, because the ``-pylab`` option does some work for us by importing
+the required modules to our name-space when ipython interpreter
+starts. And thus we don't have to explicitly import modules.
+
+So now let us try to fix the problem and run the script in command
+line,
+
+add the following line as the first line in the script,
+{{{ add the line as first line in four_plot.py and save }}}
+::
+
+    from scipy import *
+
+Now let us run the script again,
+::
+
+    python four_plot.py
+
+Now it gave another error plot not defined, let us edit the file again
+and add the line below the line we just added,
+{{{ add the line as second line in four_plot.py and save }}}
+::
+
+    from pylab import *
+
+And run the script,
+::
+
+    python four_plot.py
+
+Yes! it worked. So what did we do?
+
+We actually imported the required modules using the keyword ``import``.
+It could have also be done as,
+
+{{{ highlight the following in slide and say it loud }}}
+::
+
+    from scipy import linspace
+
+instead of,
+::
+
+    from scipy import *
+
+So in practice it is always good to use function names instead of
+asterisk or star. As if we use asterisk to import from a particular
+module then it will replace any existing functions with the same name
+in our name-space.
+
+So let us modify four_plot.py as,
+{{{ delete the first two lines and add the following }}}
+::
+
+    from scipy import linspace, pi, sin
+    from pylab import plot, legend, annotate, title, show
+    from pylab import xlim, ylim
+
+{{{ switch to next slide }}}
+it could also be done as,
+
+..     import scipy
+..     import pylab
+..     x = scipy.linspace(-5*scipy.pi, 5*scipy.pi, 500)
+..     pylab.plot(x, x, 'b')
+..     pylab.plot(x, -x, 'b')
+..     pylab.plot(x, scipy.sin(x), 'g', linewidth=2)
+..     pylab.plot(x, x*scipy.sin(x), 'r', linewidth=3)
+..     pylab.legend(['x', '-x', 'sin(x)', 'xsin(x)'])
+..     pylab.annotate('origin', xy = (0, 0))
+..     pylab.xlim(-5*scipy.pi, 5*scipy.pi)
+..     pylab.ylim(-5*scipy.pi, 5*scipy.pi)
+
+
+Notice that we use ``scipy.pi`` instead of just ``pi`` as in the
+previous method, and the functions are called as ``pylab.plot()`` and
+``pylab.annotate()`` and not as ``plot()`` and ``annotate()``.
+
+{{{ switch to next slide, problem statement }}}
+
+Write a script to plot a sine wave from minus two pi to two pi.
+
+Pause here and try to solve the problem yourself before looking at the
+solution.
+
+It can solved as,
+
+{{{ open sine.py and show it }}}
+
+the first line we import the required functions ``linspace()`` and
+``sin()`` and constant ``pi`` from the module scipy. the second and
+third line we import the functions ``plot()``, ``legend()``,
+``show()``, ``title()``, ``xlabel()`` and ``ylabel()``. And the rest
+the code to generate the plot.
+
+We can run it as,
+{{{ now switch focus to terminal and run the script }}}
+::
+
+    python sine.py
+
+{{{ switch to next slide, What is a module? }}}
+
+So till now we have been learning about importing modules, now what is
+a module?
+
+A module is simply a file containing Python definitions and
+statements. Definitions from a module can be imported into other
+modules or into the main module.
+
+{{{ switch to next slide, Python standard library }}}
+
+Python has a very rich standard library of modules
+
+Python's standard library is very extensive, offering a wide range of
+facilities. Some of the standard modules are,
+
+for Math: math, random
+for Internet access: urllib2, smtplib
+for System, Command line arguments: sys
+for Operating system interface: os
+for regular expressions: re
+for compression: gzip, zipfile, tarfile
+And there are lot more.
+
+Find more information at Python Library reference,
+``http://docs.python.org/library/``
+
+The modules pylab, scipy, Mayavi are not part of the standard python
+library.
+
+{{{ switch to next slide, recap }}}
+
+This brings us to the end of this tutorial, in this tutorial we
+learned running scripts from command line, learned about modules, saw
+the python standard library.
+
+{{{ switch to next slide, thank you slide }}}
+
+Thank you!
+
+..  Author: Anoop Jacob Thomas <anoop@fossee.in>
+    Reviewer 1:
+    Reviewer 2:
+    External reviewer:
diff --git a/using python modules/sine.py b/using python modules/sine.py
new file mode 100644
index 0000000..109308e
--- /dev/null
+++ b/using python modules/sine.py
@@ -0,0 +1,11 @@
+from scipy import linspace, pi, sin
+from pylab import plot, legend, show, title
+from pylab import xlabel, ylabel
+
+x = linspace(-2*pi,2*pi,100)
+plot(x,sin(x))
+legend(['sin(x)'])
+title('Sine plot')
+xlabel('x')
+ylabel('sin(x)')
+show()