ktnyt

class ConvolutionalAutoencoder(FunctionSet):
    def __init__(self, n_in, n_out, ksize, stride=1, pad=0, wscale=1, bias=0, nobias=False):
        super(ConvolutionalAutoencoder, self).__init__(
            encode=F.Convolution2D(n_in, n_out, ksize, stride=stride, pad=pad, wscale=wscale, bias=bias, nobias=nobias),
            decode=F.Convolution2D(n_out, n_in, ksize, stride=stride, pad=pad, wscale=wscale, bias=bias, nobias=nobias)
        )

    def forward(self, x_data, train=True):
        x = Variable(x_data)
        t = Variable(x_data)

ktnyt

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm, datasets

import brica1

# SVM Component Definition

ktnyt

import numpy as np
from chainer import Variable, FunctionSet, optimizers
import chainer.functions  as F
import data

import brica1

class SLP(FunctionSet):
    def __init__(self, n_input, n_output):
        super(SLP, self).__init__(

ktnyt

import argparse
import numpy as np
from sklearn.datasets import fetch_mldata
from chainer import Variable, FunctionSet, optimizers, cuda
import chainer.functions  as F
import brica1

class Perceptron():
    def __init__(self, n_in, n_out, use_cuda=False):
        self.model = FunctionSet(

ktnyt

#!/bin/sh

if [ -d treasure_hunt ]
then
    rm -r treasure_hunt
fi

mkdir treasure_hunt

echo 'Aye aye mate! Welcome to the treasure hunt!' >> treasure_hunt/README

ktnyt

#!/usr/bin/env perl
use strict;
use warnings;

my %rank_hour; # Access per hour
my %rank_file; # Access per file

open LOG, "<", "access_log";     # Open log file
open CSV, ">", "access_log.csv"; # Open CSV output file

ktnyt

require 'formula'

# Contact celery [at] g-language.org for questions

# Or should I call this formula plain ecell...?
class Ecell4 < Formula
  homepage 'http://www.e-cell.org/'
  url 'https://github.com/ecell/ecell4/tarball/master'
  sha1 '2b1bdf70b0bdfd09e091943eb110b1aab03db6c6'
  version '4'

ktnyt

import numpy as np
import matplotlib.pyplot as plt

def Hadamard(n):
    def Hn(H=np.array([[1, 1], [1, -1]], dtype=np.complex64), n=n):
        if n > 1:
            return Hn(H=np.kron(np.array([[1, 1], [1, -1]], dtype=np.complex64), H), n=n-1)
        return H

    return Hn(n=n)

ktnyt

#!/usr/bin/env ruby
require 'net/http'
require 'uri'
require 'json'

url = 'http://hack.sfc.keioac.jp/sfcbusapi/index.php'
uri = URI.parse( url )

res = Net::HTTP.get( uri )
m = /^callback\((.+)\);$/.match( res )

ktnyt

#include <stdio.h>
#include <stdlib.h>

void reverse(char** Pstring);
int match(char a, char b);

int main(int argc, char* argv[]) {
  if(argc < 2) {
    fprintf(stderr, "Usage: needle <sequence 1> <sequence 2>");
  }