What is the recommended data type for scientific calculation in .Net?

Question

What is the most recommended data type to use in scientific calculation in .Net? Is it float, double or something else?

Answer 1

Scientific values tend to be "natural" values (length, mass, time etc) where there's a natural degree of imprecision to start with - but where you may well want very, very large or very, very small numbers. For these values, double is generally a good idea. It's fast (with hardware support almost everywhere), scales up and down to huge/tiny values, and generally works fine if you're not concerned with exact decimal values.

decimal is a good type for "artificial" numbers where there's an exact value, almost always represented naturally as a decimal - the canonical example for this is currency. However, it's twice as expensive as double in terms of storage (8 bytes per value instead of 4), has a smaller range (due to a more limited exponent range) and is significantly slower due to a lack of hardware support.

I'd personally only use float if storage was an issue - it's amazing how quickly the inaccuracies can build up when you only have around 7 significant decimal places.

Ultimately, as the comment from "bears will eat you" suggests, it depends on what values you're talking about - and of course what you plan to do with them. Without any further information I suspect that double is a good starting point - but you should really make the decision based on the individual situation.

Answer 2

Well, of course the term “scientific calculation” is a bit vague, but in general, it’s double.

float is largely for compatibility with libraries that expect 32-bit floating-point numbers. The performance of float and double operations (like addition) is exactly the same, so new code should always use double because it has greater precision.

However, the x86 JITter will never inline functions that take or return a float, so using float in methods could actually be slower. Once again, this is for compatibility: if it were inlined, the execution engine would skip a conversion step that reduces its precision, and thus the JITter could inadvertantly change the result of some calculations if it were to inline such functions.

Finally, there’s also decimal. Use this whenever it is important to have a certain number of decimal places. The stereotypical use-case is currency operations, but of course it supports more than 2 decimal places — it’s actually an 80-bit piece of data.

If even the accuracy of 64-bit double is not enough, consider using an external library for arbitrary-precision numbers, but of course you will only need that if your specific scientific use-case specifically calls for it.