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→How do I make Octave use more precision?
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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. If you would like to get this fixed, [http://octave.1599824.n4.nabble.com/Internal-Precision-Symbolic-tp4645257p4645594.html Jordi Gutiérrez Hermoso has volunteered] to fix the package for 5000 USD, which can be obtained from a kickstarter | 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. If you would like to get this fixed, [http://octave.1599824.n4.nabble.com/Internal-Precision-Symbolic-tp4645257p4645594.html Jordi Gutiérrez Hermoso has volunteered] to fix the package for 5000 USD, which can be obtained from a kickstarter campaign. | ||
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]. | ||