Python

Python is an open source programming language created by Guido van Rossum in 1991. It is an interpreted high-level language, which enhances the readability of the code. This allows the user to create programs in an easier way and producing shorter codes than other programming languages. Python has a large user’s community whose provides support and creates packages, libraries and modules which extends the capabilities and applications of Python to areas such as scientific and engineering simulations, machine learning, computational chemistry, data visualization or its implementation in embedded systems, among others. It is available for the major operating systems, including Linux based OS, Windows and Mac OS.

There exists two versions of Python, Python 2.x and Python 3.x, which minor differences in their syntaxes. Python 2.x is the classical Python programming language, whereas Python 3.x provides some new features and is the current version of Python.

IDEs

Python can be used through a text editor, such as Notepad++, Atom or Gedit, to create the script and then be executed using a terminal to run the program. However, there exist many Integrated Development Environments (IDEs) which can help in the creation of our projects. Some IDEs used for programming in Python are Spyder, PyDev, PyCharm and Geany.

Packages

The core provides the basic capabilities: data types, data structures, functions definition, control structures as conditionals sentences and loops. However, the specific functions for scientific computing are supplied by packages. The main modules used are the following:

• NumPy: provides support to work with arrays and matrices of numeric data, linear algebra and other number capabilities.

• SciPy: this module complements NumPy and provides algorithms for linear algebra, integration, interpolation, linear algebra and optimization, among others.

• matplotlib: it is a 2D plotting library which, in combination with NumPy, it is capable to produce high quality figures in different formats.

• pandas: it is package focused in data analysis and statistics

• seaborn: it is a data visualization library based on matplotlib oriented to statistical graphics. It has a great integration with pandas.

Nevertheless, there are other packages for other specific tasks, as symbolic mathematics (SymPy), visualization of 3D graphics (MayaVi), etc.

LaTeX is a platform for prepare documents specially oriented for scientific documents, with specific support for mathematical expressions.

To create a document in LaTeX a predefined type of text must be selected to determine the appropriate global format. The default styles are book, report, article and letter. The text in LaTeX is introduced as plain text, and different functions can be used to define the text format, include images, tables, etc. Once the document is written in plain text, it is compiled and the final document is generated with the format defined.

LaTeX can be a little intimidating the first times, but presents many advantages for the preparation of scientific documents. The introduction of mathematical expressions faster than other methods, with support for a large variety of mathematical symbols, the introduction of subscripts and superscripts, Greek letters, and so on. Other great feature is the automatic numeration of sections, figures, tables, equations and bibliographic references, which is automatically updated when new references are added or some of them are removed.

Install LaTeX in Ubuntu: link

Install LaTeX in Windows:

• Install MiKTeX: link

• Once the installation is completed, MiKTeX will update automatically

• Install TeXstudio: link

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