With <iomanip>, you can use std::fixed and std::setprecision Here is an example #include <iostream> #include <iomanip> int main() { double d = 122.345; std::cout << std::fixed; std::cout << std::setprecision(2); std::cout << d; } And you will get output 122.34
From the Floating-Point Guide: What can I do to avoid this problem? That depends on what kind of calculations you’re doing. If you really need your results to add up exactly, especially when you work with money: use a special decimal datatype. If you just don’t want to see all those extra decimal places: simply … Read more
I think what you’re looking for is not directly possible. One important property of equality is that it is transitive. (ie. If a == b and b == c, then a == c). With a distance measure, though, you really don’t want this property. Example: Take a single float (for simplicity). Suppose we want to … Read more
The float function can do this: >>> float(‘1.31E+01’) 13.1 or for a list: >>> map(float, [‘3.76E+00’, ‘1.31E+01’, ‘1.14E+01’]) [3.76, 13.1, 11.4]
You have to convert the operands to floats first and then divide, otherwise you’ll perform an integer division (no decimal places). Laconic solution (requires Data.Function) foo = (/) `on` fromIntegral which is short for foo a b = (fromIntegral a) / (fromIntegral b) with foo :: Int -> Int -> Float
From Wikipedia : In computing, NaN (Not a Number) is a value of the numeric data type representing an undefined or unrepresentable value, especially in floating-point calculations. Systematic use of NaNs was introduced by the IEEE 754 floating-point standard in 1985, along with the representation of other non-finite quantities like infinities. And from MSDN : … Read more
The reason they are not stored this way by default is that the range of valid values that can fit in a fixed set of bits is smaller. Your float class can store numbers between 1/MAXINT and MAXINT (plus or minus). A C/C++ float can represent numbers between 1E+37 and 1E-37 (plus or minus). In … Read more
It also depends on instruction mix. Your processor will have several computation units standing by at any time, and you’ll get maximum throughput if all of them are filled all the time. So, executing a loop of mul’s is just as fast as executing a loop or adds – but the same doesn’t hold if … Read more
From what I understand you’re only guaranteed identical results provided that you’re dealing with the same instruction set and compiler, and that any processors you run on adhere strictly to the relevant standards (ie IEEE754). That said, unless you’re dealing with a particularly chaotic system any drift in calculation between runs isn’t likely to result … Read more