## Ask Slashdot: Replacing a TI-84 With Software On a Linux Box? 254

yanom writes

*"I'm currently a high school student using my TI-84 for mathematics courses. It has all the functionality I need (except CAS), but saying that the hardware is dated is putting it nicely. Waiting 4-5 seconds for a simple function to be graphed on its 96x64 screen just makes me want to hurl it at the wall. Recently, I've begun to notice the absurdity of doing my math homework on a 70's era microchip when I have an i7 machine with Linux within arm's reach. I've begun looking for software packages that could potentially replace the graphing calculator's functionality, including Xcas and Maxima, but both lack what I consider basic calculator functionality — xcas can't create a table of values for a function, and maxima can't use degrees, only radians. So, does anyone know of a good software package to replace my graphing calculator (and maybe provide CAS to boot)?"*
## Re:Sage or Python + IPython + SciPy + NumPy (Score:4, Interesting)

I concur: the Python shell is a very very powerful calculator given that you can define functions in the interpreter. There are many graphics packages for Python; Matplotlib is perhaps the most complete albeit not the symplest. As suggested above, installing Python with the IPython shell, NumPy and SciPy, enables the "PyLab" IPython mode, which is similar to what Matlab would offer in terms of graphics and computation integration.

Simpler to install and learn is perhaps Octave (with plots using GnuPlot), which would behave similarly. Although for the long term, I'd say learning the Python shell is more useful than learning Octave.

## Re:Sorry About That (Score:4, Interesting)

## Re:Sage or Python + IPython + SciPy + NumPy (Score:3, Interesting)

## Re:R; apt-get install r-base (Score:4, Interesting)

What advanced stats do you have in mind that can be done easily in Matlab but not in R? And I think your assessment of the relative acceptance of the two is out of date. R awareness is growing fast.

The choice really depends on what you are doing. Matlab is industrial strength engineering software. R is a a powerful statistics oriented programming language. In my experience, R's statistical capabilities are a strength relative to Matlab. Data handling (such as reading a csv file without barfing) is much easier in R than in Matlab. Moreover, Matlab is quite expensive. This is fine in a professional setting, but a showstopper if you're a small operation. The poster can get a student license, but why not use Octave or R? The two languages are actually similar in many respects, see David Heibeler's page [umaine.edu].

I know researchers who have ditched Matlab in favor of R/C++. It really depends on what you're doing.