Are there data types with better precision than float?
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6This is actually two questions with different answers. 1: double precision values in python are floats, and 2: a better precision data type than float would be decimal. Can questions like this be split somehow? The accepted answer addresses #2, but most upvoted answer addresses #1.bsplosion– bsplosion2019-03-15 14:30:14 +00:00Commented Mar 15, 2019 at 14:30
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5 Answers
Python's built-in float type has double precision (it's a C double in CPython, a Java double in Jython). If you need more precision, get NumPy and use its numpy.float128.
7 Comments
Jeff
Apparently,
numpy.float128 often has 64 bit precision on a 64 bit system. numpy.float128(1) + numpy.float128(2**-64) - numpy.float128(1) returns 0.0. See stackoverflow.com/a/29821557/420755
Fusca Software
0.1 + 0.2 is not exact 0.3 in python, in every other language this is a float problem but never a double problem. Why it is not exact 0.3 in python?
Hans Musgrave
@FuscaSoftware It's a problem in other languages too. IEEE doubles can't represent 0.3 exactly. That sounds like a formatting artifact.
alexpanter
Funnily enough this was not mentioned in their documentation page, or any other page that speaks about "float precision" in Python.
sol
@FuscaSoftware ... i dont understand ... "%.21f" % (0.2 + 0.3) '0.500000000000000000000' ... seems ok
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- Unlike hardware based binary floating point, the decimal module has a user alterable precision (defaulting to 28 places) which can be as large as needed for a given problem.
If you are pressed by performance issuses, have a look at GMPY
3 Comments
Piotr Findeisen
If I were asking the original question, then @larsmans's would be the answer (even though formally it's off-topic).
PleaseHelp
@PiotrFindeisen where is that answer?
Piotr Findeisen
No idea, but now I'd refer to @FredFoo. Generally "Double precision floating values in Python?" → "
float-s are double precision"For some applications you can use Fraction instead of floating-point numbers.
>>> from fractions import Fraction
>>> Fraction(1, 3**54)
Fraction(1, 58149737003040059690390169)
(For other applications, there's decimal, as suggested out by the other responses.)
3 Comments
Janus Troelsen
how do I choose between Decimal and Fraction? Fraction seems better since it can represent continuing fractions which I guess Decimal can't?
Gareth Rees
@Janus: consider your requirements, and pick the one that fits them better. Use
Decimal when you want to work with approximate numbers that have fixed (but configurable) precision. Use Fraction when you want to work with exact ratios, and are prepared to put up with their unbounded storage requirements.
danijar
Does Fraction support all the operations you can do with float?
May be you need Decimal
>>> from decimal import Decimal
>>> Decimal(2.675)
Decimal('2.67499999999999982236431605997495353221893310546875')
Comments
Here is my solution. I first create random numbers with random.uniform, format them in to string with double precision and then convert them back to float. You can adjust the precision by changing '.2f' to '.3f' etc..
import random
from decimal import Decimal
GndSpeedHigh = float(format(Decimal(random.uniform(5, 25)), '.2f'))
GndSpeedLow = float(format(Decimal(random.uniform(2, GndSpeedHigh)), '.2f'))
GndSpeedMean = float(Decimal(format(GndSpeedHigh + GndSpeedLow) / 2, '.2f')))
print(GndSpeedMean)
3 Comments
kravemir
Well. Double precision means double length binary representation of variable compared to binary representation of float. Not two decimal places.
Bittikettu
You are right. I might have used bad search criteria when I had this problem myself and this is the outcome. Some others might search this same issue like I did and end up here. Hopefully they find some relief. :)
Wauzl
This is the worst way I can think of to round a float to two decimal places. You should at least use
numpy.floor(100*a)/100 to truncate a number a to two decimal places.