На каждый конкурс может быть не больше двух человек

illright / Процесс.md

Last active September 24, 2017 16:36

Процесс посвята

Требуется

illright / Гороскоп.txt

Last active September 1, 2017 10:12

Распределение языков программирования

illright / Слова2.txt

Last active August 30, 2017 19:46

Слова для конкурса Слова (для конкурса)

illright / Конкурсы.md

Last active September 1, 2017 15:18

Конкурсы на посвят

illright / слова.txt

Created August 27, 2017 17:55

Слова для крокодила

illright / MinSpanTree.py

Last active May 6, 2017 08:49

Comparator of Kruskal's and Prim's MST searching algorithms

	# MinSpanTree - Comparator of Kruskal's and Prim's MST searching algorithms
	# Requires `graph.txt` - an adjacency matrix that defines the graph
	# Put dashes (-) where there's no way

	import matplotlib.pyplot as plt
	import matplotlib.patches as mpatches
	import networkx as nx
	from queue import PriorityQueue

	def matrix_to_graph(matrix):

illright / ShortestWay.py

Last active February 18, 2018 10:00

Comparator for Dijkstra's and Ford-Bellman's pathfinding algorithms

	# ShortestWay - comparator for Dijkstra's and Ford-Bellman's pathfinding algorithms
	# Requires `graph.txt` - start and end points and an adjacency matrix that defines the graph
	# Put dashes (-) where there's no way

	import matplotlib.pyplot as plt
	import matplotlib.patches as mpatches
	import networkx as nx
	from queue import PriorityQueue

	inf = float('inf')

illright / alerror.js

Last active June 9, 2017 17:37

JS snippet to redirect errors to an alert (for debugging in Safari)

	window.addEventListener('error', handleError, true);

	function handleError(event) {
	if (event.message) {
	window.alert('error: ' + event.message + ' at linenumber: ' + event.lineno + ' of file: ' + event.filename);
	} else {
	window.alert('error: ' + event.type + ' from element: ' + (event.srcElement \|\| event.target));
	}
	}

illright / LinkComp.py

Last active May 6, 2017 08:48

Script that finds strongly connected components in a directed graph and visualizes them

	# LinkComp - script that finds strongly connected components in a directed graph and visualizes them
	# Requires `graph.txt` - adjacency matrix that defines the graph
	import numpy as np
	import matplotlib.pyplot as plt
	import networkx as nx
	import re

	g = []
	ptn = re.compile('[01]')
	with open('graph.txt') as f: