154 lines
6.4 KiB
Python
154 lines
6.4 KiB
Python
import os
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from datetime import datetime
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# 设置中文字体支持（如果需要可视化）
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# import matplotlib.pyplot as plt
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# plt.rcParams["font.family"] = ["SimHei", "WenQuanYi Micro Hei", "Heiti TC"]
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class EducationResourceForecast:
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def __init__(self):
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# 数据文件路径
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self.data_dir = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), 'Data')
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# 教育阶段映射
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self.education_stages = {
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'preschool': '学前',
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'primary': '小学',
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'junior': '初中',
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'senior': '高中',
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'vocational': '中职'
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}
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# 预测年份范围
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self.forecast_years = list(range(2023, 2030)) # 2023-2029年
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# 加载数据
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self.teacher_data = self._load_data('TeacherCount.json')
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self.school_area_data = self._load_data('SchoolArea.json')
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# 存储预测结果
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self.forecast_results = {stage: [] for stage in self.education_stages.keys()}
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def _load_data(self, filename):
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"""加载JSON数据文件"""
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import json
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file_path = os.path.join(self.data_dir, filename)
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try:
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with open(file_path, 'r', encoding='utf-8') as f:
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data = json.load(f)
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# 数据文件是数组格式，我们只需要云南省的数据
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for item in data:
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if item.get('area_name') == '云南省':
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return item
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return {}
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except Exception as e:
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print(f"加载文件 {filename} 失败: {e}")
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return {}
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def _get_teacher_data_by_stage(self, stage):
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"""获取特定教育阶段的教师数据"""
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# 教师数据字段映射
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teacher_field_map = {
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'preschool': 'preschool_teachers',
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'primary': 'primary_teachers',
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'junior': 'junior_teachers',
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'senior': 'senior_teachers',
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'vocational': 'vocational_teachers'
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}
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field = teacher_field_map.get(stage)
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if not field or field not in self.teacher_data:
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return []
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teacher_data = []
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# 提取2015-2024年的专任教师数据
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for year in range(2015, 2025):
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year_data = self.teacher_data[field].get(str(year), {})
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# 优先使用专任教师数量
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teacher_count = year_data.get('total_teacher', 0)
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teacher_data.append({
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'year': year,
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'teacher_count': teacher_count
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})
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return teacher_data
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def _get_school_area_data_by_stage(self, stage):
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"""获取特定教育阶段的学校面积数据"""
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# 学校面积字段映射
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area_field_map = {
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'preschool': 'preschool_area',
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'primary': 'primary_area',
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'junior': 'junior_high_area', # 修正字段名
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'senior': 'senior_high_area', # 修正字段名
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'vocational': 'vocational_area'
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}
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field = area_field_map.get(stage)
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if not field or field not in self.school_area_data:
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return []
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area_data = []
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# 提取2015-2024年的学校面积数据
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for year in range(2015, 2025):
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year_data = self.school_area_data[field].get(str(year), {})
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# 优先使用教学面积，如果为0则使用学校总面积
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teaching_area = year_data.get('teaching_total', 0)
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if teaching_area == 0:
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teaching_area = year_data.get('school_total', 0)
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area_data.append({
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'year': year,
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'teaching_area': teaching_area
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})
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return area_data
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def forecast(self):
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"""执行预测"""
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for stage in self.education_stages.keys():
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# 获取历史数据
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teacher_history = self._get_teacher_data_by_stage(stage)
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area_history = self._get_school_area_data_by_stage(stage)
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# 生成最终结果
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for year in self.forecast_years:
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if year <= 2024:
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# 2023-2024年使用实际数据
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# 查找实际教师数据
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teacher_item = next((item for item in teacher_history if item['year'] == year), None)
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teacher_count = teacher_item['teacher_count'] if teacher_item else 0
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# 查找实际面积数据
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area_item = next((item for item in area_history if item['year'] == year), None)
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teaching_area = area_item['teaching_area'] if area_item else 0
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else:
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# 2025-2029年预测数据设为0
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teacher_count = 0
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teaching_area = 0
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# 添加结果，师资缺口/富余字段暂时设为0
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self.forecast_results[stage].append({
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'year': year,
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'teacher_count': round(teacher_count / 10000, 2), # 转换为万人
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'teacher_gap': 0, # 师资缺口/富余暂时设为0
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'teaching_area': round(teaching_area / 10000, 2), # 转换为万平方米
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'is_forecast': year >= 2025 # 标记是否为预测数据
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})
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def print_results(self):
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"""打印预测结果"""
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for stage, chinese_name in self.education_stages.items():
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print(f"\n{chinese_name}教育阶段资源配置预测（2023-2029年）:")
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print("{:<8} {:<12} {:<16} {:<20} {:<10}".format("年份", "专任教师(万人)", "师资缺口/富余", "教学及辅助用房面积(万㎡)", "数据类型"))
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for item in self.forecast_results[stage]:
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data_type = "预测" if item['is_forecast'] else "实际"
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print("{:<8} {:<12.2f} {:<16.2f} {:<20.2f} {:<10}".format(
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item['year'],
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item['teacher_count'],
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item['teacher_gap'],
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item['teaching_area'],
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data_type
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))
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if __name__ == "__main__":
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print("开始执行教育资源配置发展预测...")
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forecast = EducationResourceForecast()
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forecast.forecast()
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forecast.print_results()
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print("\n预测完成！") |