Compare two double type variables within epsilonWhen naming your double epsilon java for the threshold of difference, should you name it delta or epsilon? Specifically, which of the two is the correct term for the smallest value that a floating-point number can represent? In computer science in particular, the term epsilon also refers to machine espilon which measures the difference double epsilon java 1. That latter number is 1. Note however that before comparing floats for "proximity", you need to have an idea of their scale.
Java: Floating point equality
Join Stack Overflow to learn, share knowledge, and build your career. I wrote a class that tests for equality, less than, and greater than with two doubles in Java.
My general case is comparing price that can have an accuracy of a half cent. Is the epsilon I chose adequate for those cases? You do NOT use double to represent money. Then you can specify how exactly to do rounding which is sometimes dictated by law in financial applications! Any rounding error that occurs due to the storage of floating point values will occur smaller than 0.
I regularly use 1E-6 or 0. Is there a specific reason you're using floating-point for currency, or would things be better off with an arbitrary-precision, fixed-point number format?
I have no idea what the specific problem that you're trying to solve is, but you should think about whether or not half a cent is really something you want to work with, or if it's just an artifact of using an imprecise number format.
If you are dealing with money I suggest checking the Money design pattern originally from Martin Fowler's book on enterprise architectural design. I suggest reading this link for the motivation: While I agree with the idea that double is bad for money, still the idea of comparing doubles has interest.
In particular the suggested use of epsilon is only suited to numbers in a specific range. Here's a more general use of an epsilon, relative to the ratio of the two numbers test for 0 omitted:.
Floating point numbers only have so many significant digits, but they can go much higher. If your app will ever handle large numbers, you will notice the epsilon value should be different. It's not a good representation of money, unless you are damn sure you'll never handle more than a million dollars in this system.
If you're calculationg money values you really shouldn't use float values. Money is actually countable values. The cents or pennys etc. You could store, and calculate money values as integers and divide by e. Using float's can lead to strange rounding errors Anyway, if your epsilon is supposed to define the accuracy, it looks a bit too small too accurate As other commenters correctly noted, you should never use floating-point arithmetic when exact values are required, such as for monetary values.
The main reason is indeed the rounding behaviour inherent in floating-points, but let's not forget that dealing with floating-points means also having to deal with infinite and NaN values. As an illustration that your approach simply doesn't work, here is some simple test code. The errors occurs because of the loss if significant bits on subtraction if two floating-point values have different exponents. If you think of applying a more advanced "relative difference" approach as suggested by other commenters, you should read Bruce Dawson's excellent article Comparing Floating Point Numbers, Edition , which shows that this approach has similar shortcomings and that there is actually no fail-safe approximate floating-point comparison that works for all ranges of floating-point numbers.
Email Sign Up or sign in with Google. Java double comparison epsilon Ask Question. You have awaken the wrath of some people here! See here if you really want to use floating point numbers: For further discussion of Money and the use of BigDecimal check out: I'd never read that and it's great to get a better understanding of this topic. Other issues aside, reduce chances of coding error by removing duplicated code. Seriously, using floating point types to represent money is extremely unprofessional.
Michael Borgwardt k 59 It is something fundamental in scientific computing, not a "stupid hack". Goldberg's paper on the subject agrees on that one.
Seriously, you shouldn't assume that just because that is how you do things that it is the best way in all cases. Having worked at four different banks, I have never seen a trading system which used BigDecimal, nor would a recommend using them. Peter, what would you recommend for money instead? My preference would be a Long. However I'm extremely hesitant to roll my own for the situation. I have done it before RichardGomes suggesting there is one correct answer isn't reflected by reality.
You can get representation error regardless of which you chose. The problem with fixed precision is that I would rather be out by 0. I understand your point and my answer is more or less trivial: In this industry we have to have alarms which tell us when something went very wrong. One example is that Nomura warned Knight Capital when they Nomura detected that a client was making too much losses in a row, for 40 minutes, which later was attributed to a programming error.
The problem of using doubles is that you will have very small programming errors rounding errors very difficult to be detected. Java doubles will hold their precision better than your given epsilon of 0. Josh Lee k 22 Yuval Adam k 74 The moredesignpatterns server appears to have gone away and not been replaced. The article is on archive. If you can use BigDecimal, then use it, else: Shouldn't that be Double.
Here's a more general use of an epsilon, relative to the ratio of the two numbers test for 0 omitted: That's very dangerous due to zero division. Karl 5, 4 24 Floating point does not represent values like 0. Even within reasonable range like 0. Run "print int 1. Strindhaug 4, 1 22 Sign up or log in Sign up using Google. Sign up using Facebook.