General purpose numerical Open Source sofware sought

[ManDay]

Hello, after having used Scilab for the longer part of a while by now, I'm looking to change over to a functionally more enhanced software but am not yet sure which to choose. I've more or less come down to a choice of four programs, of which I would like you to pick the one which you think is the currently most advanced. If however, you happen to have any other suggestion of an open source or free numerical or numerical and CAS software, go ahead with it.

• CERN's ROOT [Wiki]
• SciPy Python-based package [Wiki]
• GNU Octave [Wiki]
• Sage CAS (utilizing others such as SciPy) [Wiki]

I hope a few can contribute to this topic although proprietary is more of a standard in the industry.

 

[ManDay]

I think I've made my choice: ROOT.

After trying it for less than an hour (trouble free installation from the ubuntu repositories) I've to say that I'm already more than impressed. It's at the same time very very powerful, flexible and on the other hand easy to pick up and well documented.

 

[oswaler]

I understand the importance of choosing the right software for your research needs. In terms of open source numerical software, each of the options you have listed has its own strengths and limitations. Here are some factors to consider when making your decision:

1. Functionality: Each of the software programs you have listed has its own set of features and capabilities. It is important to determine which features are essential for your research and which software offers them.

2. User-friendliness: It is important to choose a software that is easy to use and has a user-friendly interface, especially if you are new to numerical software. Consider trying out demos or tutorials of each software to see which one you are most comfortable with.

3. Community support: Open source software often has a strong community of users who can provide support and assistance with any issues you may encounter. It is important to choose a software with an active and helpful community.

4. Compatibility: Make sure the software you choose is compatible with your operating system and any other software you may be using for your research.

Based on these factors, I would recommend considering GNU Octave or SciPy. Both have a wide range of features and a large community of users, making them reliable options for your research needs. However, it is ultimately important to choose the software that best meets your specific research requirements. I also suggest exploring other open source options, such as R, Maxima, or Julia, to see if they offer any unique features that may be beneficial for your work.