manuel-delverme

import networkx as nx
from collections import defaultdict

def get_percolated_cliques(G, k):
    perc_graph = nx.Graph()
    cliques = [frozenset(c) for c in nx.find_cliques(G) if len(c) >= k]
    perc_graph.add_nodes_from(cliques)

    # First index which nodes are in which cliques
    membership_dict = defaultdict(list)

manuel-delverme

#!/usr/bin/python
import networkx as nx
from datetime import datetime
import sys
import csv
import os
import random
import glob
from itertools import combinations
from collections import defaultdict

manuel-delverme

#!/bin/bash

# play YUV444 FULL HD file 
gst-launch-1.0 -v filesrc location=size_1920x1080.yuv ! \
    videoparse width=1920 height=1080 framerate=25/1 format=GST_VIDEO_FORMAT_Y444 ! \
    videoconvert ! \
    autovideosink

# play YUV422 FULL HD file 
gst-launch-1.0 -v filesrc location=size_1920x1080.yuv ! \

manuel-delverme

#include <stdio.h>
#include <stdlib.h>
#define N_ROWS 5
#define N_COLS 5
void main(){
    char swamp[N_ROWS][N_COLS] = {
        {'*' , '*', '.', '*', '.' }, 
        {'.' , '.', '.', '.', '.' }, 
        {'.' , '.', '*', '.', '*' }, 
        {'.' , '*', '.', '*', '*' }, 

manuel-delverme

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#define N 100

struct Names

{
    char name[20];
    char surname[20];

manuel-delverme

#!/usr/bin/env python
from pick import pick

urls = [ '__'*i for i in range(1000)]
names = [ '-_^'*i for i in range(1000)]

title = 'scroll down to crash'
style, _ = pick(names, title)

print "not happening"

manuel-delverme

import numpy as np
import matplotlib.pyplot as plt
import scipy.cluster.hierarchy as hcluster
from sklearn.manifold import TSNE

import collections
import random

import fireplace.utils
from fireplace import cards

manuel-delverme

import numpy as np
import matplotlib.pyplot as plt
from adjustText import adjust_text
import json

notes = []
together = [(0, 1.0, 0.4), (25, 1.0127692669427917, 0.41), (50, 1.016404709797609, 0.41), (75, 1.1043426359673716, 0.42), (100, 1.1610446924342996, 0.44), (125, 1.1685687930691457, 0.43), (150, 1.3486407784550272, 0.45), (250, 1.4013999168008104, 0.45)]
embed = [(y,y) for (x,y,z) in together]
embed += [(y*1.1,y) for (x,y,z) in together]
embed += [(y,y*1.1) for (x,y,z) in together]

manuel-delverme

from pprint import pprint

import hdbscan as hdbscan
import numpy as np
import matplotlib.pyplot as plt
# import scipy.cluster.hierarchy as hcluster
from sklearn.manifold import TSNE
from sklearn.decomposition import PCA
import sklearn.metrics.pairwise

manuel-delverme

import requests
import json
from fireplace.utils import random_draft
from fireplace import cards
from hearthstone.enums import CardClass
from hearthstone import cardxml

def classify(y, x):
    for klass_name in ["ROGUE", "MAGE", "WARRIOR", "HUNTER", "PRIEST", "PALADIN", "WARLOCK", "SHAMAN", "DRUID"]:
        if klass_name.lower() in y.lower():