iterated-function | 易学教程

What is O(log* N)?

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问题 What is O(log* N) ? I know big-Oh, the log* is unknown. 回答1: 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. 回答2: The log* N bit is an iterated algorithm which grows very slowly, much slower than just log N . You basically just keep iteratively 'logging' the answer until it gets below one (E.g:

Extract number of raster cells included in a SpatialPolygons

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问题 I would like to create a function to count the number of raster cells within the polygons of a SpatialPolygonsDataframe object and adding the value as a new column without using a loop. I cannot find how to do it... Here is my code: library(sp) library(raster) # Create a SpatialPolygonsDataframe and a raster objets to overlay # Polygons p1 <- rbind(c(-180,-20), c(-140,55), c(-50, 0), c(-140,-60), c(-180,-20)) p2 <- rbind(c(-10,0), c(140,60), c(160,0), c(140,-55), c(-10,0)) p3 <- rbind(c(-125

What is O(log* N)?

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What is O(log* N) ? I know big-Oh, the log* is unknown. 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. The log* N bit is an iterated algorithm which grows very slowly, much slower than just log N . You basically just keep iteratively 'logging' the answer until it gets below one (E.g: log(log(log(...log(N))) ), and the number of times you had to log() is the answer. Anyway, this is a five-year