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package main

import (
	"bytes"
	"encoding/binary"
	"fmt"
	"os"
)

func main() {

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package main

import (
	"fmt"
	"os"
)

func main() {

	if len(os.Args) != 3 {

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import numpy as np
import chainer
import math
import argparse

def ngram_sentences(sentences, n=1):
    parse = lambda words, n : list(zip(*(words[i:] for i in range(n))))
    arr = []
    for sentence in sentences:
        arr.extend(parse(sentence, n))

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import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import gaussian_kde
import matplotlib.animation as animation

def gaussian_kernel(x, sigma):
    return 1 / (np.sqrt(2*np.pi)*sigma) * np.exp(-(x**2)/(2*(sigma**2)))

def x_update(x, xi, sigma):
    return np.sum(gaussian_kernel(xi - x, sigma) * x) / np.sum(gaussian_kernel(xi - x, sigma))