more
```cpp
include
include
using namespace std;
void hartal(vector & days, int h) {
int n = days.size();
int t = h - 1;
while (t < n) {
int r = t % 7;
if (r != 5 && r != 6)
days[t] = true;
t += h;
}
}继续阅读 »
Twelve days after the initial commit, pipeR tutorial is released!
If you want to write R code fluently and process data elegantly, I strongly recommend that you read this tutorial which is designed to serve as a complete guide to pipeR package, including how it works with dplyr, rlist, and rvest with vivid examples.继续阅读 »
(This post is rewritten to adapt to the latest release of pipeR)
Pipeline is receiving increasing attention in R community these days. It is hard to tell when it begins but more people start to use it since the easy-and-fast dplyr package imports the magic operator %>% from magrittr, the pioneer package of pipeline op继续阅读 »
Problem Description:
Given a sequence of integers a1, …, an and q queries x1, …, xq on it. For each query xi you have to count the number of pairs (l, r) such that 1 ≤ l ≤ r ≤ n and gcd(al, al + 1, …, ar) = xi. is a greatest common divisor of v1, v2, …, vn, that is equal to a largest positive integer that divides all 继续阅读 »
As we know, a Brownian motion is usually formulated as $$dx_t = \mu\,dt+\sigma\,dW_t$$ which is the continuous case of a random walk. In some cases, it is quite convenient to use this formulation to describe the characteristic of asset prices due to its highly unpredictable behavior.继续阅读 »
The motivation of pipeline operator is to make code more readable. In many cases, it indeed better organizes code so that the logic is presented in human-readable fluent style. In other cases, however, such operators can make things worse.继续阅读 »