O( log* N ) is “iterated logarithm”: In computer science, the iterated logarithm of n, written log* n (usually read “log star”), is the number of times the logarithm function must be iteratively applied before the result is less than or equal to 1.
To get the logarithm with a custom base using math.log: import math number = 74088 # = 42^3 base = 42 exponent = math.log(number, base) # = 3 To get the logarithm with a custom base using numpy.log: import numpy as np array = np.array([74088, 3111696]) # = [42^3, 42^4] base = 42 exponent = … Read more
I have to agree that it’s pretty weird the first time you see an O(log n) algorithm… where on earth does that logarithm come from? However, it turns out that there’s several different ways that you can get a log term to show up in big-O notation. Here are a few: Repeatedly dividing by a … Read more
O(log log n) terms can show up in a variety of different places, but there are typically two main routes that will arrive at this runtime. Shrinking by a Square Root As mentioned in the answer to the linked question, a common way for an algorithm to have time complexity O(log n) is for that … Read more
I finally found some time to do some experiments in order to understand the difference between them. Here’s what I discovered: log only allows positive values, and lets you choose how to handle negative ones (mask or clip). symlog means symmetrical log, and allows positive and negative values. symlog allows to set a range around … Read more
Your code is doing a log of a number that is less than or equal to zero. That’s mathematically undefined, so Python’s log function raises an exception. Here’s an example: >>> from math import log >>> log(-1) Traceback (most recent call last): File “<pyshell#59>”, line 1, in <module> log(-1) ValueError: math domain error Without knowing … Read more
You can use the Axes.set_yscale method. That allows you to change the scale after the Axes object is created. That would also allow you to build a control to let the user pick the scale if you needed to. The relevant line to add is: ax.set_yscale(‘log’) You can use ‘linear’ to switch back to a … Read more
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 … Read more
np.log is ln, whereas np.log10 is your standard base 10 log.
This is the function that I use for this calculation: public static int binlog( int bits ) // returns 0 for bits=0 { int log = 0; if( ( bits & 0xffff0000 ) != 0 ) { bits >>>= 16; log = 16; } if( bits >= 256 ) { bits >>>= 8; log += … Read more