I was always curios about how to convert a floating point number into a decimal ASCII string. The equation is trivial after you get to implement it. But the idea behind took me a long while to come up with. For the sake of example I will deal with a single precision floating point of IEEE 754. However, it doesn’t really matter to me how many bits I have to convert into a string, the algorithm stays the same. Floating Point numbers have all this crap about NaNs and QaNs and other weird stuff that I didn’t care about. They are just technical stuff that you have to implement, nothing really hard about it. I am just gonna focus on the way to convert the mantissa (that’s the part of the fraction of the real number) into decimal. I think it’s rather easy to take a look at the implementation of printf in libc of Linux. That way you don’t have a challenge with coming with this, eventually, simple algo on your own.

To simplify matters, I don’t handle big exponents, again it was not my focus. If you wish to change this code to something really usable, it’s possible with some work. Here I am not going to cover the format of the IEEE 754 floating point. I presume you know it, and if not, give it a look here.

void pf(unsigned long x) { unsigned int sign = x >> 31; unsigned int exp = ((x >> 23) & 0xff) - 127; unsigned int man = x & ((1 << 23) - 1); man |= 1 << 23; if (sign) printf("-"); printf("%d", man >> (23 - exp)); printf("."); unsigned int frac = man & ((1 << (23-exp)) - 1); unsigned int base = 1 << (23 - exp); int c = 0; while (frac != 0 && c++ < 6) { frac *= 10; printf("%d", (frac / base)); frac %= base; } printf("\n");} }

You can see in the beginning that we extract the sign bit, exponent and mantissa from the *raw* number we got as a parameter. Then we fix the exponent since it is biased, though it’s a really nice trick, I won’t cover it today. And we set bit 24 in the mantissa, because we assume we got a *normalized* floating point number where bit 24th in the data is implied and not saved to spare this extra bit… Printing the sign is self explantory. And then we print the integer part of the mantissa, while taking care of the exponent. This is where a too big or too small exponent will screw up things. But for small integers everything is fine just yet.

Now the fun begins, converting the mantissa from base 2 to base 10. Yipi kay hey. Let’s see. We store the fraction part of the floating point number and the base. For now let’s ignore this base variable and we will get back to it later. We limit the loop to print 6 digits or less when there is no more what to print. The algorithm here is to ‘pull’ the digits over to be in the integer part of the number and print that part which is straight forward (though it’s only a digit and not a whole integer). Then we see how much more digits we have left to print and repeat the body of the loop until we’re done or printed enough digits.

I will try to explain this loop again this way: Let’s say you want to print the number 5/6 in decimal. How will you do that? That’s the key algorithm for converting the number to decimal as well in our case. I was told by a friend that children are taught this method in elemtary school, maybe I lacked of that class or we didn’t have it. :) Then what we are doing is: multiplying the 5 by 10 then see how many times it gets in the result: 50/6 = 8, then we do a modulu with 6, getting 50%6=2. And starting again, 2*10=20; 20 / 6 = 3; 20%6=2; 2*10=20; 20/6=3 and over and over again, the final result is 0.8333… This is similar to 1/3, try this algo on 1/4 and you will see that you get 2 and then 5 and then you reach 0 and stop, resulting in 0.25.

Back to the code above, we take the fraction part and we have a base, take a long breath – of 2 powered by the number of bits the fraction use to be stored. Why is that the base?

Like when you convert an integer to decimal, you have to multiply every set bit by 2**index, where the index is the index of the set bit in the integer stream. For example: 111b is 1*2**0 + 1*2**1 + 1*2**2 = 1 + 2 + 4 = 7. The same goes for bits that are on the right side of the point (thus fractions): .11b is 1*2**(-1) + 1*2**(-2) = 1/2 + 1/4 = 0.75. Notice that the indices this time are negative, and power of negative number is division, therefore: 1/base**(-index). Now *instead of doing this conversion per bit*, we can do it simply by dividing the fraction *once*, in our example: 11b by 4. (base powered by number of bits, 2**2=4). Now we *treat the fraction as an integer and divide it by the new calculated base*; we get 3/4 = 0.75. We saw how the conversion can be done easily and we need a way to print the result of such division… And now we’re back to the description above of how to print a simple fraction. This time we know the reasons behind the fraction and the base. Note that the base is bigger than the fraction by nature, otherwise we won’t have a correct input for the algo and then it won’t work well.

How to use the above code:

float x = 1337.99;

pf(*(unsigned long*)&x);

printf(“%f”, x);

Running the code using a different number every time, you will see that printf %f actually rounds the number where we print it as a raw floating number, without touching it. Therefore, next time I will talk about rounding the number.

It’s not worked for big or small x. Example: pf(0x1000000)

sorry,

float x = 0×1000000;

unsigned int &y = &x;

pf(y);

I just wanted people to know how to basic algorithm works. I didn’t write a complete implementation that’s why it doesn’t work in all cases where you have to shift the virtual point itself.

Anyways you had a bug, try this code:

float x = 0×1000000;

unsigned int y = *(unsigned int*)&x;

pf(y);

> Anyways you had a bug, try this code

c++ like :)

but can mistaken – wrote on memories, long ago do not write c/c++ code – simply search for algorithm, allowing remove number with limited an amount symbol

sorry my translated english

If anyone is interested in the other way conversion (string -> float), I’ve written an extensive article: http://krashan.ppa.pl/articles/stringtofloat. I’ve put some work into the code, so it can be used for the whole range covered by double precision floats. I’ve tried to make the parser working reliably even with extreme cases (like, for example, a million of leading zeros ;-) ). I’ve also taken care about generating proper infinities and zeros for out of range numbers.