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Globally Coupled Mapの時系列データをCSVファイルに保存する

Last updated at Posted at 2024-04-05

Step0. 使用するパッケージ

import numpy as np
import matplotlib.pyplot as plt
plt.style.use('ggplot') #グラフのスタイル
plt.rcParams['figure.figsize'] = [8, 3] # グラフサイズ設定
plt.rcParams['font.size'] = 10 #フォントサイズ
import random
import pandas as pd
import csv
import warnings
warnings.simplefilter('ignore')

Step1. 写像を定義

写像を定義
def f(x, alpha):
	y = 1 - alpha*x*x
	return y

def coupled_f(x_list, alpha, e):
	total = 0
	y_list = []
	num = len(x_list)

	for n in range(num):
		total += f(x_list[n], alpha)
	for n in range(num):
		y_list.append((1 - e) * f(x_list[n], alpha) + (e / num) * total)
	return y_list

Step2. 時系列を生成

時系列を生成
def series(alpha, e, initial, length, trans_period):
	num_coupled = len(initial)  # 結合数
	x_list = [n + trans_period for n in range(length)]
	y_list = []

	for n in range(num_coupled):
		y_list.append([initial[n]])
	length -= 1
	for n1 in range(length + trans_period):
		pre_y_list = []
		for n2 in range(len(initial)):
			pre_y_list.append(y_list[n2][n1])

		after_y_list = coupled_f(pre_y_list, alpha, e)
		for n2 in range(len(initial)):
			y_list[n2].append(after_y_list[n2])

	for n1 in range(num_coupled):
		y_list[n1] = y_list[n1][trans_period:]
	return x_list, np.transpose(y_list)

Step3. CSVファイルに書き込み

CSVファイルに保存
data = []

for sublist1, sublist2 in zip(x_list, y_list):
  data.append([sublist1] + sublist2.tolist())

header = ["index"]
for n in range(len(y_list[0])):
  header.append("Element_{}".format(n))
# CSVファイルに書き込む
with open('data_set.csv', 'w', newline='') as csvfile:  # 'w'は書き込みモード、newline=''は改行コードを指定
  csv_writer = csv.writer(csvfile)
  csv_writer.writerow(header)  # ヘッダーを書き込む
  csv_writer.writerows(data)  # データを書き込む
読み込んでプロット
dataset = "data_set.csv"
df = pd.read_csv(
  dataset,
  parse_dates=True,
  index_col="index"
)
print(df)
df.plot()
plt.show()
実行結果
       Element_0  Element_1  Element_2
index                                 
1000    0.922458  -0.007941   0.922458
1001   -0.270728   0.818381  -0.270728
1002    0.819108   0.055648   0.819108
1003   -0.002265   0.852572  -0.002265
1004    0.922458  -0.007941   0.922458

...
1026    0.819108   0.055648   0.819108
1027   -0.002265   0.852572  -0.002265
1028    0.922458  -0.007941   0.922458
1029   -0.270728   0.818381  -0.270728

image.png

Appendix. パッケージ化したものをGithubに公開しました.

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