[SwitchBot] 03 温湿度データ取得&グラフ化 浴室乾燥テスト

import os
import time
import json
import hashlib
import hmac
import base64
import uuid
import requests
import datetime
import pandas as pd
import matplotlib.pyplot as plt
from os.path import exists
import subprocess
import numpy as np

dir_name = "/SwitchBot/data"

device_id = "XXX"
token = 'XXX'
secret = 'XXX'

nonce = str(uuid.uuid4())
t = int(round(time.time() * 1000))
string_to_sign = "{}{}{}".format(token, t, nonce)
string_to_sign = bytes(string_to_sign, "utf-8")
secret = bytes(secret, "utf-8")
sign = base64.b64encode(
    hmac.new(secret, msg=string_to_sign, digestmod=hashlib.sha256).digest()
)

apiHeader = {}
apiHeader["Authorization"] = token
apiHeader["Content-Type"] = "application/json"
apiHeader["charset"] = "utf8"
apiHeader["t"] = str(t)
apiHeader["sign"] = str(sign, "utf-8")
apiHeader["nonce"] = nonce

response = requests.get(
    f"https://api.switch-bot.com/v1.1/devices/{device_id}/status",
    headers=apiHeader,
)
devices = response.json()

timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
response_file = f"{dir_name}/json/status_{device_id}_{timestamp}.json"
with open(response_file, "w") as f:
    json.dump(devices, f, ensure_ascii=False, indent=4)

print("Success get device status.")

# CSVファイルを作成(データ行を追加する)
timestamp_date = datetime.datetime.now().strftime("%Y%m%d")
csv_file = f"{dir_name}/{timestamp_date}_{device_id}_data.csv"

# デバイスのステータスから必要なデータを抽出
temperature = devices['body']['temperature']
humidity = devices['body']['humidity']
battery = devices['body']['battery']

# 湿度が60%以下の場合に通知を送る(動作不可)
if humidity <= 60:
    subprocess.run(['osascript', '-e', f'display notification "Humidity is {humidity}%" with title "Humidity Alert"'])

# 絶対湿度を計算
absolute_humidity = (6.112 * np.exp((17.67 * temperature) / (temperature + 243.5)) * humidity * 2.1674) / (273.15 + temperature)

# CSVファイルにデータを追加
data = {
    'timestamp': [timestamp],
    'temperature': [temperature],
    'relative_humidity': [humidity],
    'absolute_humidity': [absolute_humidity],
    'battery': [battery]
}

df = pd.DataFrame(data)

if exists(csv_file):
    df.to_csv(csv_file, mode='a', header=False, index=False)
else:
    df.to_csv(csv_file, mode='w', header=True, index=False)

print("Success append data to CSV.")

# CSVファイルからグラフを作成する(上書き更新)
plot_file = f"{dir_name}/{timestamp_date}_{device_id}_data_plot.png"

# CSVファイルを読み込む
df = pd.read_csv(csv_file)

# タイムスタンプをdatetime型に変換
df['timestamp'] = pd.to_datetime(df['timestamp'], format='%Y%m%d%H%M%S')

# 絶対湿度の移動平均を計算（5分間の移動平均）
df.set_index('timestamp', inplace=True)
df['absolute_humidity_ma'] = df['absolute_humidity'].rolling('5T').mean()

# グラフを作成
fig, ax1 = plt.subplots(figsize=(10, 5))

ax1.set_xlabel('Timestamp')
ax1.set_ylabel('Temperature (°C)', color='tab:red')
ax1.plot(df.index, df['temperature'], label='Temperature', color='tab:red')
ax1.tick_params(axis='y', labelcolor='tab:red')
ax1.set_ylim(20, 50)

ax2 = ax1.twinx()
ax2.set_ylabel('Absolute Humidity (g/m³)', color='tab:blue')
ax2.plot(df.index, df['absolute_humidity_ma'], label='Absolute Humidity (5-min MA)', color='tab:blue')
ax2.tick_params(axis='y', labelcolor='tab:blue')
ax2.set_ylim(20, 60)

fig.tight_layout(rect=[0, 0, 1, 0.95])  # タイトルが切れないように調整
plt.title('Temperature and Absolute Humidity (5-min MA) over Time', pad=20)
plt.xticks(rotation=45)
ax1.xaxis.set_major_formatter(plt.matplotlib.dates.DateFormatter('%H:%M:%S'))

# グラフを保存
plt.savefig(plot_file)
plt.close()

print("Success create plot.")