请写出预测某地温度的python代码,需要满足的功能如下:第一,该代码是基于lstm模型的预测,第二,需要结合粒子群算法优化lstm模型的参数,第三,请告诉我你所写出的代码的数据集的具体格式,最后,请确保该代码能够完美运行

以下是基于LSTM模型预测某地温度的Python代码，同时结合粒子群算法优化LSTM模型的参数：

import numpy as np
import pandas as pd
from keras.models import Sequential
from keras.layers import LSTM, Dense
from keras.optimizers import Adam
from pyswarm import pso

# 读取数据集
data = pd.read_csv('temperature_data.csv')

# 数据预处理
data['date'] = pd.to_datetime(data['date'])
data.set_index('date', inplace=True)
data = data.resample('D').mean().interpolate()

# 定义训练集和测试集
train_size = int(len(data) * 0.8)
train_data = data[:train_size]
test_data = data[train_size:]

# 定义函数，用于创建LSTM模型
def create_lstm_model(params):
    model = Sequential()
    model.add(LSTM(units=int(params[0]), input_shape=(1, 1)))
    model.add(Dense(units=1))
    optimizer = Adam(lr=params[1])
    model.compile(loss='mean_squared_error', optimizer=optimizer)
    return model

# 定义函数，用于训练LSTM模型
def train_lstm_model(params):
    model = create_lstm_model(params)
    X_train = np.reshape(train_data.values, (train_data.shape[0], 1, 1))
    y_train = train_data.values
    model.fit(X_train, y_train, epochs=100, batch_size=1, verbose=0)
    return model