ybenjo

from scipy.sparse import lil_matrix, csr_matrix
from scipy.sparse.csgraph import maximum_bipartite_matching
import random

N = 10
M = 10
random.seed(0)
for x in range(5):
    mat = lil_matrix((N, M))

ybenjo

# coding: utf-8
require 'json'
require 'time'
require 'digest/md5'

srand(0)

data = JSON.load(open("#{__dir__}/checkins.json").read)
output_file = "#{__dir__}/checkins.ics"

ybenjo

import numpy as np
import chainer
from chainer import functions as F
from chainer import links as L


class NFMClassifier(chainer.Chain):
    def __init__(self, n_feature, n_dim_emb, n_dim_1, n_dim_2):
        np.random.seed(6162)
        self.n_feature = n_feature

ybenjo

from xgboost import XGBClassifier

model = XGBClassifier(seed = 1)

# XOR Pattern
train_data = [
    [1, 0],
    [0, 1],
    [1, 1],
    [0, 0],

ybenjo

# Version: 0.6a2
from xgboost import XGBRegressor

model = XGBRegressor(seed = 1)

# XOR pattern + [0, 0, 0]
train_data = [
    [1, 0] + [0] * 3,
    [0, 1] + [0] * 3,
    [1, 1] + [0] * 3,

ybenjo

#!/usr/bin/env ruby
# cat data.tsv | ccut -d delim -c name,name,name...

require 'trollop'
opts = Trollop::options do
  opt :delim, 'delimitor', default: "\t"
  opt :column, 'column name(s)', type: String
end

delim = opts[:delim]

ybenjo

import numpy as np
import sys
from collections import defaultdict
from lmfit import minimize, Parameters
from sklearn.decomposition import FastICA
import math

# This script is (incomplete and buggy) implementation of 
# The Web as a Jungle: Non-Linear Dynamical Systems for Co-evolving Online Activities, (WWW 2015).
# http://www.cs.kumamoto-u.ac.jp/~yasuko/PUBLICATIONS/www15-ecoweb.pdf

ybenjo

require 'json'

class Hoge
  def initialize
    @a=1
    @b='hoge'
    @c={:a => 1}
  end

  def to_json

ybenjo

// Generated by CoffeeScript 1.9.2
(function() {
  module.exports = function(robot) {
    return robot.hear(/mecab (.*)/i, function(msg) {
      var MeCab, mecab, ret, text;
      text = msg.match[1];
      MeCab = new require('mecab-async');
      mecab = new MeCab();
      ret = mecab.parseSync(text);
      return msg.send(text);

ybenjo

module.exports = (robot) ->

  robot.hear /mecab (.*)/i, (msg) ->
    text = msg.match[1]

    MeCab = new require 'mecab-async'
    mecab = new MeCab()
    ret = mecab.parseSync(text)
    msg.send text