What is the Best Object-Oriented Language for Scientific Computing?

In summary, the individual is a first year theoretical physics master considering focusing on scientific simulations. They currently use C for simulations but are interested in learning an object oriented language for easier implementation of parallel programming and visualization of results. They mention having taken a Java course in the past and are considering learning C++ as it is widely used. They are also interested in having flexibility in other areas. A suggestion is made to focus on C++ first and then branch out to other languages, specifically Python. The individual expresses concerns about Python potentially being too slow for their needs, but it is noted that there is a large engineering/scientific community and tools for scientific computing and visualization. It is also suggested that if Python is not fast enough, they can
  • #1
Grieverheart
31
0
I'm in my first year of theoretical physics master and I'm considering of following the path of scientific simulations. At the moment I use C for my simulations. I would additionally like to learn an object oriented language. I followed a course in Java about 2 years ago, so that would be easier to learn again. What I generally need is an object oriented language with high performance, easy implementation of parallel programming and visualisation of results. Also I think I'm going to learn C++ since it's used everywhere, so I don't know if it's worth learning any additional object oriented language. I want to focus on the things I said above but I would like to have some flexibility in other areas too.
So, any suggestions?
 
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  • #2
Why don't you focus on C++ first and then see if OOP comes easily to you. After that you can start branching out even more.
 
  • #3
I wouldn't waste my time on C++ or that other language that tried to overcome C++ shortcomings (Java).

You should look into Python!

Python is very easy to use. You can start programming in a non-OOP manner and start including objects as you see fit.

Also, there is a huge engineering/scientific community behind Python. There are many tools for scientific computing and for visualization.

Should Python not be fast enough for intensive number crunching operations, you can write that particular part in either C or Fortran and easily call it from Python.
 
  • #4
If you already know C, switching to C++ will be relatively easy. At the same time it will mean your OOP will inherit bad habits from your C programming, that's typical.
 
  • #5
I have done OOP in Java although that was quite some time ago. I was going to learn python at first, it seems to fit for most of my needs but it seems really slow. I read it can get close to C, C++ speeds with NumPy/SciPy (which are actually using C). That doesn't feel quite right :S . I guess in the long run it's best to learn several and use every language at where it's best.
 

Related to What is the Best Object-Oriented Language for Scientific Computing?

1. What is Scientific Computing Language?

Scientific Computing Language is a programming language specifically designed for scientific and numerical computation. It allows scientists and researchers to write code that can perform complex calculations and simulations, making it an essential tool in various scientific fields such as physics, chemistry, and biology.

2. What are the benefits of using Scientific Computing Language?

There are several benefits of using Scientific Computing Language, including its ability to handle large datasets and perform complex calculations efficiently. It also has a wide range of libraries and packages that make it easier to perform specific scientific tasks. Additionally, it has a simple syntax that is easy to learn for those with a background in mathematics or science.

3. Which programming languages fall under Scientific Computing Language?

Some of the most commonly used programming languages in scientific computing include Python, MATLAB, R, and Fortran. These languages are specifically designed for scientific and numerical computation and have a wide range of libraries and packages that make them suitable for various scientific applications.

4. What are some real-world applications of Scientific Computing Language?

Scientific Computing Language is used in various real-world applications, such as weather forecasting, financial modeling, drug discovery, and image processing. It is also used in research and development in fields such as physics, chemistry, biology, and engineering. Additionally, it is used in data analysis and visualization in various industries.

5. Is Scientific Computing Language difficult to learn?

While learning any new programming language requires time and effort, Scientific Computing Language is generally considered to have a relatively gentle learning curve. Its syntax is straightforward, and there are plenty of online resources and communities available for support and guidance. Additionally, many universities and online platforms offer courses and tutorials on how to use Scientific Computing Language for scientific applications.

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