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Python - abs vs fabs

2016-01-14 14:09 507 查看

abs(-5)

Second

import math
math.fabs(-5)

How do these methods differ?

python

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edited Feb
22 '14 at 16:46

Paul Draper
22.6k1156111

asked May 27 '12 at 7:16

Mateusz Jagiełło
89521426

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3 Answers

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math.fabs()

converts
its argument to float if it can (if it can't, it throws an exception). It then takes the absolute value, and returns the result as a float.

In addition to floats,

abs()

also
works with integers and complex numbers. Its return type depends on the type of its argument.

In [7]: type(abs(-2))
Out[7]: int

In [8]: type(abs(-2.0))
Out[8]: float

In [9]: type(abs(3+4j))
Out[9]: float

In [10]: type(math.fabs(-2))
Out[10]: float

In [11]: type(math.fabs(-2.0))
Out[11]: float

In [12]: type(math.fabs(3+4j))
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
/home/alexei/<ipython-input-12-8368761369da> in <module>()
----> 1 type(math.fabs(3+4j))

TypeError: can't convert complex to float

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edited Sep
19 '15 at 17:47

jesterjunk
1,059811

answered May 27 '12 at 7:21

NPE
225k29470666

abs

works
with far more than just integers and floats, and the result type is not always the same as the argument, e.g.

abs(3+4j)

. – agf May
27 '12 at 7:24

add in a comment about

fabs

taking
longer due to its always-float nature and you've got the right answer! – Patrick
Perini May
27 '12 at 7:25

@agf: Thanks for reminding me about complex numbers. Out of interest, what other classes of things can

__builtin__.abs()

be
successfully applied to? – NPE May
27 '12 at 7:31

@aix Any user defined class that defines the

__abs__

magic
method – agf May
27 '12 at 17:59

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Edit: as @aix suggested, a better (more fair) way to compare the speed difference:

In [1]: %timeit abs(5)
10000000 loops, best of 3: 86.5 ns per loop

In [2]: from math import fabs

In [3]: %timeit fabs(5)
10000000 loops, best of 3: 115 ns per loop

In [4]: %timeit abs(-5)10000000 loops, best of 3: 88.3 ns per loop

In [5]: %timeit fabs(-5)10000000 loops, best of 3: 114 ns per loop

In [6]: %timeit abs(5.0)
10000000 loops, best of 3: 92.5 ns per loop

In [7]: %timeit fabs(5.0)
10000000 loops, best of 3: 93.2 ns per loop

In [8]: %timeit abs(-5.0)
10000000 loops, best of 3: 91.8 ns per loop

In [9]: %timeit fabs(-5.0)
10000000 loops, best of 3: 91 ns per loop

So it seems

abs()

only
has slight speed advantage over

fabs()

for
integers. For floats,

abs()

and

fabs()

demonstrate
similar speed.

In addition to what @aix has said, one more thing to consider is the speed difference:

In [1]: %timeit abs(-5)10000000 loops, best of 3: 102 ns per loop

In [2]: import math

In [3]: %timeit math.fabs(-5)10000000 loops, best of 3: 194 ns per loop

abs()

is
faster than

math.fabs()

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edited Nov
12 '13 at 0:33

answered May 27 '12 at 7:22

Kay Zhu
12.8k34162

You're not comparing apples to apples there. Use

from
math import fabs

for sure, and try

-5.0

for
both. – agf May
27 '12 at 7:25

@agf Thanks for pointing it out! That was dumb of me. – Kay
Zhu May
27 '12 at 7:31

Also unreliable timing results? You first had abs(-5) at 102ns, then later show it as 88.3ns. Never draw conclusions
from a single run of any benchmark, even if it internally tries to avoid the issues as timeit does. – Peter
Hansen Jan
3 '13 at 2:11

Two more points: this still compares apples and oranges, since abs is looked up in the builtins, while fabs is at module
namespace. Do "xabs = abs" then xabs(num) to remove that effect. Also, with Python 3.2 things change quite a bit and apparently abs() is quite a bit faster (>2x), at least on floats. – Peter
Hansen Jan
3 '13 at 2:14

@PeterHansen You are right, those are from two runs under different system loads. Though when compared within the same
set of tests, the relative difference is still valid. Also, thanks for pointing out the namespace difference -- I didn't consider that. I haven't tried it on 3.2, but that's good to know! I will update my answer with your suggestions a bit later :) Thanks
again! – Kay Zhu Jan
3 '13 at 2:20

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