A 题：震源属性识别模型构建与震级预测的代码分析
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2023-08-24
08:03:34
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代码分析：
问题一：
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
import matplotlib.font_manager as fm
# 读取文件夹中的地震波数据和标签
data = []
labels = []
folder_path = "A/"
# 读取文件夹中的所有数据文件
for i in range(1, 8):
for j in range(1, 21):
file_path = folder_path + f"附件{i}/{j}.txt"
with open(file_path, "r") as file:
lines = file.readlines()
wave_data = []
for line in lines:
line_data = line.strip().split() # 分割成单个浮点数
line_data = np.array([float(num) for num in line_data]) #
转换为浮点数类型
wave_data.extend(line_data)
data.append(wave_data)
labels.append("天然地震")
for i in range(1, 31):
file_path = folder_path + f"附件 8/{i}.txt"
with open(file_path, "r") as file:
lines = file.readlines()
wave_data = []
for line in lines:
line_data = line.strip().split() # 分割成单个浮点数
line_data = np.array([float(num) for num in line_data]) # 转换
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