lan496

(define (square x) (* x x))

(define (cube x) (* x x x))

(define (abs x)
	(if (< x 0)
		(- x)
		x
	)
)

lan496

#include <iostream>
#include <cstdio>
#include <map>

int collatz(std::map<int,int> &count,long long n){
    int res=0;
    while(!(n&1)){
        res++;
        n=(n>>1);
    }

lan496

set nocompatible

set number
set ruler
set cursorline
set nocursorcolumn
set laststatus=2
set cmdheight=2
set showmatch
set helpheight=999

lan496

# -*- coding: utf-8 -*-
import sys
import urllib2
from bs4 import BeautifulSoup

def sample_getter(path, problemId):
    directory = path + "/" + str(problemId)
    url = "http://judge.u-aizu.ac.jp/onlinejudge/description.jsp?id=" + str(problemId)
    html = urllib2.urlopen(url)
    soup = BeautifulSoup(html)

lan496

import numpy as np
import requests
import matplotlib.pyplot as plt


def get_material_id(name):
    material_dict = {
        '1,1,1,2,3,3,3-Heptafluoropropane (R227ea)': 'C431890',
        '1,1,1,2,3,3-Hexafluoropropane (R236ea)': 'C431630',
        '1,1,1,3,3,3-Hexafluoropropane (R236fa)': 'C690391',

lan496

import numpy as np
import matplotlib.pyplot as plt

#################################################
F = 8.0
J = 40  # site
dt = 0.05  # 6 hours
dt_forcast = 0.05
delta_TLM = 1e-9
alpha = 3.0 ** 2  # P^a_0 = alpha * I

lan496

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from scipy import sparse
from PIL import Image


class Wave:

    def __init__(self, N, a):

lan496

import numpy as np
from scipy.special import iv
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.utils.validation import check_is_fitted


class ExpSineSquaredSampler(BaseEstimator, TransformerMixin):
    """
    Approximates feature map of an Exp-Sine-Squared kernel by its Fourier series expansion.
    Exp-Sine-Squared kernel is given by:

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lan496