The math. log2() method returns the base-2 logarithm of a number.
Logarithm base 2 of 2 is 1 .
It's good to know that
but also know that
math.log
takes an optional second argument which allows you to specify the base:
In [22]: import math
In [23]: math.log?
Type: builtin_function_or_method
Base Class: <type 'builtin_function_or_method'>
String Form: <built-in function log>
Namespace: Interactive
Docstring:
log(x[, base]) -> the logarithm of x to the given base.
If the base not specified, returns the natural logarithm (base e) of x.
In [25]: math.log(8,2)
Out[25]: 3.0
Depends on whether the input or output is int
or float
.
assert 5.392317422778761 == math.log2(42.0)
assert 5.392317422778761 == math.log(42.0, 2.0)
assert 5 == math.frexp(42.0)[1] - 1
assert 5 == (42).bit_length() - 1
math.log2(x)
import math
log2 = math.log(x, 2.0)
log2 = math.log2(x) # python 3.3 or later
math.frexp(x)
If all you need is the integer part of log base 2 of a floating point number, extracting the exponent is pretty efficient:
log2int_slow = int(math.floor(math.log(x, 2.0))) # these give the
log2int_fast = math.frexp(x)[1] - 1 # same result
Python frexp() calls the C function frexp() which just grabs and tweaks the exponent.
Python frexp() returns a tuple (mantissa, exponent). So [1]
gets the exponent part.
For integral powers of 2 the exponent is one more than you might expect. For example 32 is stored as 0.5x2⁶. This explains the - 1
above. Also works for 1/32 which is stored as 0.5x2⁻⁴.
Floors toward negative infinity, so log₂31 computed this way is 4 not 5. log₂(1/17) is -5 not -4.
x.bit_length()
If both input and output are integers, this native integer method could be very efficient:
log2int_faster = x.bit_length() - 1
- 1
because 2ⁿ requires n+1 bits. Works for very large integers, e.g. 2**10000
.
Floors toward negative infinity, so log₂31 computed this way is 4 not 5.
If you are on python 3.3 or above then it already has a built-in function for computing log2(x)
import math
'finds log base2 of x'
answer = math.log2(x)
If you are on older version of python then you can do like this
import math
'finds log base2 of x'
answer = math.log(x)/math.log(2)
Using numpy:
In [1]: import numpy as np
In [2]: np.log2?
Type: function
Base Class: <type 'function'>
String Form: <function log2 at 0x03049030>
Namespace: Interactive
File: c:\python26\lib\site-packages\numpy\lib\ufunclike.py
Definition: np.log2(x, y=None)
Docstring:
Return the base 2 logarithm of the input array, element-wise.
Parameters
----------
x : array_like
Input array.
y : array_like
Optional output array with the same shape as `x`.
Returns
-------
y : ndarray
The logarithm to the base 2 of `x` element-wise.
NaNs are returned where `x` is negative.
See Also
--------
log, log1p, log10
Examples
--------
>>> np.log2([-1, 2, 4])
array([ NaN, 1., 2.])
In [3]: np.log2(8)
Out[3]: 3.0
http://en.wikipedia.org/wiki/Binary_logarithm
def lg(x, tol=1e-13):
res = 0.0
# Integer part
while x<1:
res -= 1
x *= 2
while x>=2:
res += 1
x /= 2
# Fractional part
fp = 1.0
while fp>=tol:
fp /= 2
x *= x
if x >= 2:
x /= 2
res += fp
return res
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