FAQ: Difference between revisions
→How do I make Octave use more precision?
Carandraug (talk | contribs) (→How can I get involved in Octave development?: add a section telling to not just send email with a list of skills (adapted from the book Open Advice) Also remove advice about using debugger -- it is too advanced to recommend for starters) |
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Alternatively, one may use arbitrary precision arithmetic, which has as much precision as is practical to hold in your computer's memory. The ''symbolic'' package, when it works, has a vpa() function for arbitrary precision arithmetic. Note that arbitrary precision arithmetic must be implemented '''in software''' which makes it much slower than hardware floats. | Alternatively, one may use arbitrary precision arithmetic, which has as much precision as is practical to hold in your computer's memory. The ''symbolic'' package, when it works, has a vpa() function for arbitrary precision arithmetic. Note that arbitrary precision arithmetic must be implemented '''in software''' which makes it much slower than hardware floats. | ||
At present, however, the symbolic package is almost useless, since even when you get it to compile and not crash, it cannot handle any array type, which hardly helps for an array-oriented language like Octave. If this limitation is not important to you, attempt to use the symbolic package | At present, however, the symbolic package is almost useless, since even when you get it to compile and not crash, it cannot handle any array type, which hardly helps for an array-oriented language like Octave. If this limitation is not important to you, attempt to use the symbolic package. | ||
Consider carefully if your problem really needs more precision. Often if you're running out of precision the problem lies fundamentally in your methods being [http://en.wikipedia.org/wiki/Numerical_stability numerically unstable], so more precision will not help you here. If you absolutely must use arbitrary-precision arithmetic, you're at present better off using a CAS instead of Octave. An example of such a CAS is [http://sagemath.org Sage]. | Consider carefully if your problem really needs more precision. Often if you're running out of precision the problem lies fundamentally in your methods being [http://en.wikipedia.org/wiki/Numerical_stability numerically unstable], so more precision will not help you here. If you absolutely must use arbitrary-precision arithmetic, you're at present better off using a CAS instead of Octave. An example of such a CAS is [http://sagemath.org Sage]. | ||