Having a plausible structure, Python is virtually the most popular programming tool among newbies. Essentially, people who have been trying to carry out computational studies, are enthusiastic to learn develop their own computational analysis in Python. For instance, Rhett Allain, an Associate Professor of Physics at Southeastern Louisiana University, is also a blog writer in WIRED that has issued several topics regarding his perspective. He often uses Python to demonstrate graphic and figure out numerical studies. He even shares videos on his YouTube channel related Python and libraries.
I have every so often encounter several questions regarding computational analysis with Python. Actually, conducting a numerical studies either with Python, Matlab or C++ is alike that you should understand physical incident, find appropriate mathematical model, carry out discretization studies, and apply a matrix solver in case problem is differential equation. Otherwise, it would be an easy easy peasy issue. In case you dare to solve a differential equation with Python, you must have been up and running with programming in Python. Despite, you still need to improve your scientific computational knowledge with Python libraries as to having an efficient process. Without libraries, to solve the most easiest ODE could take several hours. Here libraries that you need to know during computational analysis:
For example, yet you can solve a ODE with Numpy, Scipy can comprise some specific fields that sustain more convenient path through solution. It highly pertains to your effort and creativity. A Python package expressed as PyFoam has been available to carry out computational fluid dynamics analysis. The package uses OpenFOAM as an infrastructure and manipulates codes from C++ to Python. Although a CFD solver is available for Python, I highly advice to you learn OpenFOAM at first to understand phenomenon eminently. An another Python package in accordance with heat transfer has been issued officially. Yet I haven't examined it yet, I would courage you to go over it (Click for Python HT). Having experienced Python for several years, I have even collected some codes that include heat transfer models for 1D and rarely 2D barring PyFoam and HT. All the documents are obtained from the original websites where they have been released. Hope that the examples trigger your curiosity: The Heat Equation - Python implementation (the flow of heat through an ideal rod) Finite difference methods for diffusion processes (1D diffusion - heat transfer equation) Finite Difference Solution (Time Dependent 1D Heat Equation using Implicit Time Stepping) Fluid Dynamics Pressure (Pressure Drop Modelling) Complex functions (flow around a cylinder) Finite Difference Solution (Time Dependent 1D Heat Equation using Explicit Time Stepping) Fluid Dynamics (The Shallow Equations in 1D) Lax-Wendroff Method (1D Advection Equation) Python and Diffusion Equation (Heat Transfer) Python 1D Diffusion (Including Scipy) Finite Difference Heat Equation (Including Numpy) Heat Transfer - Euler (Github) Second-order Linear Diffusion (The Heat Equation) 1D Diffusion (The Heat equation) Solving Heat Equation with Python (YouTube-Video) The examples above comprise numerical solution of some PDEs and ODEs. There is no an example including PyFoam (OpenFOAM) or HT packages. I assure you that as you check examples regarding numerical solution like above, you would properly understand how numerical study works in Pyhton. Don't afraid to keep programming on.
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If you have no any experience related to GUI (graphical user interface), it seems that includes various hurdles barring your ability. In general, people (new starters) don't want to dare GUI because it generates a connotation that hard to carry a script out through programming. Instead, it is indeed simple. The GUI library of python has lots of eases that provides developer to generate a convenient structure in a path between GUI and script. It would be enough to having some examples of codes that you would generate your own GUI. As for other libraries, I have also been picking such codes as to thrive GUI model. Aside from the Python Libraries document, GUI file includes complete examples which are specified between two of "-----". Check the examples incrementally and pursue trial and error.
Having such experienced with Python, my favorite method through learning path is trial and error. I really fond of it that enables you to discover your abilities in terms of creativity whilst you try to integrate library to your script and thrive regarding your perspective. For instance, I try to foresee the sub-functions of library instead directly consume them. In case I couldn't find necessary information and would need a deep dive, I start to search for a comprehensive document related to library and go over whole lessons. Up to now, I have collected several examples of various libraries that you would easily apply trial and error method. Have a look and discover your potential. Here is the list of the libraries that document encompasses: #BOOLEAN #LIST, SORT AND TUBLES #MATH #RANDOM #STATISTICS #ITERTOOLS #DATETIME #TEMPFILE #CALENDER #HTML #HTTP #TURTLE #ITERATIVE #ZIPFILE #TEXTFILE #MATPLOTLIB #NUMPY #SCIPY Please check the purpose of library in advance at which you are willing to conduct some trial and error studies thereby you can negate the ambiguities. The list and document file is kept fresh that I'm to add new ones as to sustain a comprehensive source. Each row starts with # specify a new sub function. Do not forget to import library before up and running.
The document comprises various subtopics related to fluid mechanics which is also detailed with attractive figures from historical sources. You can go over fluid mechanics with this document.
Being curious about programming but never dare to start, I want to encourage you with Python. Yet various programs (C, C++, Fortran) have been available to get a deep dive through programming career, Python has a unique mellow structure. Having experienced with it for 3 years, I would advice you that programming in Python creates a connotation that is talking with computer, indeed.
It is important that you have to ensure about your goal through learning section of Python. When I started to Pyhton, I had no specific goal to accomplish. I only wanted to learn some programming skills that have attacked me. Through this 3 years, I wholeheartedly wanna say that I have spent the at least one year of this time within unnecessary lessons. Even so, I have had lots of documents from various sub-topic related to programming in Python. I am , though, a curious person who want to share what have learnt. Therefore, I decided to share my document that I have collected through 3 years. I share free-lessons (official) from various source. Up to first course, I advice you that it would be nice to download Python from official website: https://www.python.org/ Download Python 3.6 It is fully free open source. Hope to see you programming ! |