spin-glass

- 回答が途中で切れる場合は、全体の回答にかかるチャット数と現在のチャットの番号を3/10といった形式で明示してください。

spin-glass

# /bin/bash
echo "Hello, world!"

spin-glass

\documentclass[a4j,12pt,dvipdfmx]{jsarticle}
\usepackage{tikz}
\usepackage[dvipdfmx]{hyperref}
\usetikzlibrary{positioning,fit,arrows.meta}

\begin{document}
  \begin{tikzpicture}
    \node[draw,circle,minimum size=1cm] (alpha) {$\alpha$};
    \node[draw,circle,minimum size=1cm, right=1cm of alpha] (theta) {$\theta_d$};
    \node[draw,circle,minimum size=1cm, right=1cm of theta] (z) {$z_{d,i}$};

spin-glass

<div id='list'>
  <child v-for='item in items' :key='item.id' :child='item'></child>
</div>

<script>
Vue.component('child', {
    props: ['child'],
    template: '<li>{{ child.name }}</li>'
})

spin-glass

from sklearn.preprocessing import LabelBinarizer, OneHotEncoder

label = ['a', 'b', 'a']
binarized_label = LabelBinarizer().fit_transform(label) # [[1], [2], [2]]
# 以下は２クラスの場合のみ必要
one-hot_label = OneHotEncoder().fit_transform(binarized_label).toarray()

spin-glass

from keras.utils import np_utils
from sklearn.preprocessing import LabelEncoder
import numpy as np
 
feature_labels = np.array([1, 1, 2, 3, 4, 3, 4])
encoder = LabelEncoder()
encoder.fit(feature_labels)
feature_labels = encoder.transform(feature_labels)
feature_labels = np_utils.to_categorical(feature_labels)
 

spin-glass

lists = [0, 1, 2, 0, 1, 4, 0, 2, 3, 3]

# periods = [2, 2, 3]
# average = [1.5, 2.5, 2.6]
# が欲しい

periods = []
average = []
amount = 0
k = 0

spin-glass

N = gets.to_i
nums = gets.split.map(&:to_i)
cnt = 0;
nums.each_with_index{|num, i|
    nums_dup = nums.dup #浅いコピー
    nums_dup.delete_at(i)
    cnt += 1 if nums_dup.find{|n| n + num == 256}
}

puts cnt > 0 ? "yes" : "no"

spin-glass

public class Client {
  public static void main (String[] args) {
    System.out.println("start");
    Factory myFactory;
    myFactory = new Factory();
    Component myComponent = myFactory.getComponent();
    myComponent.prtTicket();
    System.out.println("end");
  }
}