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  • Book Overview & Buying Scientific Computing with Python 3
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Scientific Computing with Python 3

Scientific Computing with Python 3

By : Claus Führer, Claus Fuhrer, Olivier Verdier, Jan Erik Solem
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Scientific Computing with Python 3

Scientific Computing with Python 3

4 (2)
By: Claus Führer, Claus Fuhrer, Olivier Verdier, Jan Erik Solem

Overview of this book

Python can be used for more than just general-purpose programming. It is a free, open source language and environment that has tremendous potential for use within the domain of scientific computing. This book presents Python in tight connection with mathematical applications and demonstrates how to use various concepts in Python for computing purposes, including examples with the latest version of Python 3. Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more.
Table of Contents (17 chapters)
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References

Basic types

Let's go over the basic data types that you will encounter in Python.

Numbers

A number may be an integer, a real number, or a complex number. The usual operations are:

  • addition and subtraction, + and -
  • multiplication and division, * and /
  • power, **

Here is an example:

2 ** (2 + 2) # 16
1j ** 2 # -1
1. + 3.0j

Note

The symbol for complex numbers

j  is a symbol to denote the imaginary part of a complex number. It is a syntactic element and should not be confused with multiplication by a variable. More on complex numbers can be found in section Numeric Types of Chapter 2, Variables and Basic Types.

Strings

Strings are sequences of characters, enclosed by simple or double quotes:

'valid string'
"string with double quotes"
"you shouldn't forget comments"
'these are double quotes: ".." '

You can also use triple quotes for strings that have multiple lines:

"""This is
 a long,
 long string"""

Variables

A variable is a reference to an object. An object may have several references. One uses the assignment operator = to assign a value to a variable:

x = [3, 4] # a list object is created
y = x # this object now has two labels: x and y
del x # we delete one of the labels
del y # both labels are removed: the object is deleted

The value of a variable can be displayed by the print function:

x = [3, 4] # a list object is created
print(x)

Lists

Lists are a very useful construction and one of the basic types in Python. A Python list is an ordered list of objects enclosed by square brackets. One can access the elements of a list using zero-based indexes inside square brackets:

L1 = [5, 6]
L1[0] # 5
L1[1] # 6
L1[2] # raises IndexError
L2 = ['a', 1, [3, 4]]
L2[0] # 'a'
L2[2][0] # 3
L2[-1] # last element: [3,4]
L2[-2] # second to last: 1

Indexing of the elements starts at zero. One can put objects of any type inside a list, even other lists. Some basic list functions are as follows:

  • list(range(n))} creates a list with n elements, starting with zero:
      print(list(range(5))) # returns [0, 1, 2, 3, 4]
  • len gives the length of a list:
      len(['a', 1, 2, 34]) # returns 4
  • append is used to append an element to a list:
      L = ['a', 'b', 'c']
      L[-1] # 'c'
      L.append('d')
      L # L is now ['a', 'b', 'c', 'd']
      L[-1] # 'd'

Operations on lists

  • The operator + concatenates two lists:
          L1 = [1, 2]
          L2 = [3, 4]
          L = L1 + L2 # [1, 2, 3, 4]
  • As one might expect, multiplying a list with an integer concatenates the list with itself several times:

    n*L is equivalent to making n additions.

          L = [1, 2]
          3 * L # [1, 2, 1, 2, 1, 2]

Boolean expressions

A Boolean expression is an expression that may have the value True or False. Some common operators that yield conditional expressions are as follow:

  •  Equal, ==
  •  Not equal, !=
  •  Less than, Less than or equal to, < , <=
  •  Greater than, Greater than or equal to, > , >=

One combines different Boolean values with or and and. The keyword not , gives the logical negation of the expression that follows. Comparisons can be chained so that, for example, x < y < z is equivalent to x < y and y < z. The difference is that y is only evaluated once in the first example. In both cases, z is not evaluated at all when the first condition, x < y, evaluates to False:

2 >= 4  # False
2 < 3 < 4 # True
2 < 3 and 3 < 2 # False
2 != 3 < 4 or False # True
2 <= 2 and 2 >= 2 # True
not 2 == 3 # True
not False or True and False # True!

Note

Precedence rules

The <, >, <=, >=, !=, and == operators have higher precedence than not.  The operators and, or have the lowest precedence. Operators with higher precedence rules are evaluated before those with lower.

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