jassler

import time
import json

### SETTINGS ###
# number of elements
N = 4

# save cache dictionary?
# if True, file 'N=3.txt' is created ('3' is replaced by whatever N is)
SAVE_CACHE_TO_FILE = False

jassler

import readline

def max_heapify(A, s, recCall = 1) -> int:
    left = 2*(s+1)-1
    right = 2*(s+1)
    
    if left < len(A) and A[left] > A[s]:
        largest = left
    else:
        largest = s

jassler

# A small application to demonstrate the calculation steps for the Banzhaf Score and Shapley-Shubik Index
# using the methods proposed by Kirsch, Werner, and Jessica Langner. "Power indices and minimal winning coalitions." Social Choice and Welfare 34.1 (2010): 33-46.

library(shiny)
library(sets)
library(partitions)
library(socialranking)
library(MASS)

jassler

######################################
# List of minimal winning coalitions #
######################################
mwcs <- list(c(1,2), c(1,3,4), c(1,3,5), c(1,4,5))
quota <- 6
onlyIntegerSolutions <- TRUE

######################################
#        All the other stuff         #
######################################

jassler

const { Telegraf } = require('telegraf')
var https = require('https');

https.get('https://lichess.org/api/puzzle/daily', res => {
    var body = ''
    res.on('data', chunk => body += chunk)
    res.on('end', () => sendPuzzle(JSON.parse(body)))
})

function sendPuzzle(game) {

jassler

from collections import defaultdict
import random

actions = ['N', 'E', 'S', 'W']
transition = {
  'N': lambda s: (s[0] - 1, s[1]),
  'S': lambda s: (s[0] + 1, s[1]),
  'E': lambda s: (s[0], s[1] + 1),
  'W': lambda s: (s[0], s[1] - 1)
}

jassler

using System;
using System.Diagnostics;
using System.IO;
using System.IO.Compression;
using System.Windows;

namespace Unzippidy
{
    class Program
    {