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HuangHai
2025-09-12 21:31:45 +08:00
parent 14df704f6c
commit a3813e77d6
13 changed files with 356 additions and 815 deletions
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233
Model/RuYuanZaiYuanCountModel.py
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@@ -1,4 +1,6 @@
import json
import os
from Util.YuCeUtil import YuCeUtil
class RuYuanZaiYuanModel:
@@ -28,46 +30,118 @@ class RuYuanZaiYuanModel:
return [], []
@staticmethod
def generate_preschool_education_config(education_stage='preschool'):
def generate_preschool_education_config(education_stage='preschool', area_name='云南省'):
# 验证教育阶段参数
if education_stage not in RuYuanZaiYuanModel.EDUCATION_STAGES:
education_stage = 'preschool' # 默认使用学前
# 获取学前教育相关数据
enrollment_data, in_school_data = RuYuanZaiYuanModel.load_student_data()
# 提取云南省级数据
yunnan_enroll = next((item for item in enrollment_data if item["area_name"] == "云南省"), None)
# 提取指定区域数据
area_enroll = next((item for item in enrollment_data if item["area_name"] == area_name), None)
if not yunnan_enroll:
if not area_enroll:
return {}
# # 构建学前教育数据
# 构建学前教育数据
urban_data = [] # 城区数据
town_data = [] # 镇区数据
rural_data = [] # 乡村数据
total_enroll = [] # 总人数
# 提取年份数据(2015-2024)
years = [str(year) for year in range(2015, 2025)]
# 提取年份数据(2015-2035)
years = [str(year) for year in range(2015, 2036)]
# 初始化预测工具（只针对学前教育进行预测）
forecast_util = None
forecast_results = {}
forecast_urban_enrollment = {}
if education_stage == 'preschool':
# 获取数据目录
data_directory = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), 'Data')
# 创建预测实例，使用传入的区域名称
forecast_util = YuCeUtil(data_directory, area_name)
# 运行预测
forecast_util.run_forecast()
# 获取预测结果
forecast_results = forecast_util.forecast_results
forecast_urban_enrollment = forecast_util.forecast_urban_enrollment
for year in years:
# 使用传入的教育阶段参数
enroll_data = yunnan_enroll["education_data"].get(education_stage, {}).get(year, {})
# 特殊处理中职数据格式（只有total字段）
if education_stage == 'vocational':
total_value = enroll_data.get("total", 0)
urban_data.append(0) # 中职没有城区数据
town_data.append(0) # 中职没有镇区数据
rural_data.append(0) # 中职没有乡村数据
total_enroll.append(total_value / 10000) # 转换为万人
if int(year) <= 2024:
# 2015-2024年使用实际数据
enroll_data = area_enroll["education_data"].get(education_stage, {}).get(year, {})
# 特殊处理中职数据格式（只有total字段）
if education_stage == 'vocational':
total_value = enroll_data.get("total", 0)
urban_data.append(0) # 中职没有城区数据
town_data.append(0) # 中职没有镇区数据
rural_data.append(0) # 中职没有乡村数据
total_enroll.append(total_value / 10000) # 转换为万人
else:
urban_data.append(enroll_data.get("urban", 0) / 10000) # 转换为万人
town_data.append(enroll_data.get("town", 0) / 10000) # 转换为万人
rural_data.append(enroll_data.get("rural", 0) / 10000) # 转换为万人
# 计算总和作为总人数
calculated_total = enroll_data.get("urban", 0) + enroll_data.get("town", 0) + enroll_data.get("rural", 0)
total_enroll.append(calculated_total / 10000) # 转换为万人
else:
urban_data.append(enroll_data.get("urban", 0) / 10000) # 转换为万人
town_data.append(enroll_data.get("town", 0) / 10000) # 转换为万人
rural_data.append(enroll_data.get("rural", 0) / 10000) # 转换为万人
# 计算总和作为总人数
calculated_total = enroll_data.get("urban", 0) + enroll_data.get("town", 0) + enroll_data.get("rural", 0)
total_enroll.append(calculated_total / 10000) # 转换为万人
# 2025-2035年使用预测数据
if education_stage == 'preschool' and forecast_util:
if year in forecast_results:
total_value = forecast_results[year]
# 获取城区招生数
urban_value = forecast_urban_enrollment.get(int(year), {}).get('urban', 0)
remaining_value = total_value - urban_value
# 假设乡镇和农村按历史比例分配剩余部分
# 查找最近一年的乡镇和农村比例
recent_year = str(int(year) - 1)
if recent_year in area_enroll["education_data"].get(education_stage, {}):
recent_data = area_enroll["education_data"].get(education_stage, {}).get(recent_year, {})
recent_town = recent_data.get("town", 0)
recent_rural = recent_data.get("rural", 0)
recent_remaining = recent_town + recent_rural
if recent_remaining > 0:
town_value = int(remaining_value * (recent_town / recent_remaining))
rural_value = remaining_value - town_value
else:
town_value = int(remaining_value / 2)
rural_value = remaining_value - town_value
else:
town_value = int(remaining_value / 2)
rural_value = remaining_value - town_value
urban_data.append(urban_value / 10000)
town_data.append(town_value / 10000)
rural_data.append(rural_value / 10000)
total_enroll.append(total_value / 10000)
else:
# 没有预测数据，使用前一年数据
if len(total_enroll) > 0:
urban_data.append(urban_data[-1])
town_data.append(town_data[-1])
rural_data.append(rural_data[-1])
total_enroll.append(total_enroll[-1])
else:
urban_data.append(0)
town_data.append(0)
rural_data.append(0)
total_enroll.append(0)
else:
# 非学前教育或没有预测工具，使用前一年数据
if len(total_enroll) > 0:
urban_data.append(urban_data[-1])
town_data.append(town_data[-1])
rural_data.append(rural_data[-1])
total_enroll.append(total_enroll[-1])
else:
urban_data.append(0)
town_data.append(0)
rural_data.append(0)
total_enroll.append(0)
# 添加2022年基数的粉色折线
base_year = "2022"
@@ -75,7 +149,7 @@ class RuYuanZaiYuanModel:
base_index = years.index(base_year) if base_year in years else 0
# 获取2022年的总人数作为基数
base_value = total_enroll[base_index] if base_index < len(total_enroll) else 0
# 创建2022年基数折线数据（2022-2024年）
# 创建2022年基数折线数据（2022-2035年）
base_2022_line = []
for i, year in enumerate(years):
# 只在2022年及之后显示基数线
@@ -95,7 +169,7 @@ class RuYuanZaiYuanModel:
return data
@staticmethod
def generate_in_school_education_config(education_stage='preschool'):
def generate_in_school_education_config(education_stage='preschool', area_name='云南省'):
# 验证教育阶段参数
if education_stage not in RuYuanZaiYuanModel.EDUCATION_STAGES:
education_stage = 'preschool' # 默认使用学前
@@ -103,10 +177,10 @@ class RuYuanZaiYuanModel:
# 获取在校生相关数据
enrollment_data, in_school_data = RuYuanZaiYuanModel.load_student_data()
# 提取云南省级数据
yunnan_in_school = next((item for item in in_school_data if item["area_name"] == "云南省"), None)
# 提取指定区域数据
area_in_school = next((item for item in in_school_data if item["area_name"] == area_name), None)
if not yunnan_in_school:
if not area_in_school:
return {}
# 构建在校生数据
@@ -115,27 +189,96 @@ class RuYuanZaiYuanModel:
rural_data = [] # 乡村数据
total_in_school = [] # 总人数
# 提取年份数据(2015-2024)
years = [str(year) for year in range(2015, 2025)]
# 提取年份数据(2015-2035)
years = [str(year) for year in range(2015, 2036)]
# 初始化预测工具（只针对学前教育进行预测）
forecast_util = None
enrollment_in_school = {}
if education_stage == 'preschool':
# 获取数据目录
data_directory = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), 'Data')
# 创建预测实例，使用传入的区域名称
forecast_util = YuCeUtil(data_directory, area_name)
# 运行预测
forecast_util.run_forecast()
# 获取预测结果
enrollment_in_school = forecast_util.enrollment_in_school
for year in years:
# 使用传入的教育阶段参数
in_school_year_data = yunnan_in_school["student_data"].get(education_stage, {}).get(year, {})
# 特殊处理中职数据格式（只有total字段）
if education_stage == 'vocational':
total_value = in_school_year_data.get("total", 0)
urban_data.append(0) # 中职没有城区数据
town_data.append(0) # 中职没有镇区数据
rural_data.append(0) # 中职没有乡村数据
total_in_school.append(total_value / 10000) # 转换为万人
if int(year) <= 2024:
# 2015-2024年使用实际数据
in_school_year_data = area_in_school["student_data"].get(education_stage, {}).get(year, {})
# 特殊处理中职数据格式（只有total字段）
if education_stage == 'vocational':
total_value = in_school_year_data.get("total", 0)
urban_data.append(0) # 中职没有城区数据
town_data.append(0) # 中职没有镇区数据
rural_data.append(0) # 中职没有乡村数据
total_in_school.append(total_value / 10000) # 转换为万人
else:
urban_data.append(in_school_year_data.get("urban", 0) / 10000) # 转换为万人
town_data.append(in_school_year_data.get("town", 0) / 10000) # 转换为万人
rural_data.append(in_school_year_data.get("rural", 0) / 10000) # 转换为万人
# 计算总和作为总人数
calculated_total = in_school_year_data.get("urban", 0) + in_school_year_data.get("town", 0) + in_school_year_data.get("rural", 0)
total_in_school.append(calculated_total / 10000) # 转换为万人
else:
urban_data.append(in_school_year_data.get("urban", 0) / 10000) # 转换为万人
town_data.append(in_school_year_data.get("town", 0) / 10000) # 转换为万人
rural_data.append(in_school_year_data.get("rural", 0) / 10000) # 转换为万人
# 计算总和作为总人数
calculated_total = in_school_year_data.get("urban", 0) + in_school_year_data.get("town", 0) + in_school_year_data.get("rural", 0)
total_in_school.append(calculated_total / 10000) # 转换为万人
# 2025-2035年使用预测数据
if education_stage == 'preschool' and forecast_util:
if int(year) in enrollment_in_school:
total_value = enrollment_in_school[int(year)]
# 获取城区比例（使用最近一年的城区比例）
recent_year = str(int(year) - 1)
if recent_year in area_in_school["student_data"].get(education_stage, {}):
recent_data = area_in_school["student_data"].get(education_stage, {}).get(recent_year, {})
recent_urban = recent_data.get("urban", 0)
recent_total = recent_data.get("urban", 0) + recent_data.get("town", 0) + recent_data.get("rural", 0)
if recent_total > 0:
urban_ratio = recent_urban / recent_total
else:
urban_ratio = 0.5
else:
urban_ratio = 0.5
# 计算城乡分布
urban_value = int(total_value * urban_ratio)
remaining_value = total_value - urban_value
# 假设乡镇和农村按5:5分配剩余部分
town_value = int(remaining_value * 0.5)
rural_value = remaining_value - town_value
urban_data.append(urban_value / 10000)
town_data.append(town_value / 10000)
rural_data.append(rural_value / 10000)
total_in_school.append(total_value / 10000)
else:
# 没有预测数据，使用前一年数据
if len(total_in_school) > 0:
urban_data.append(urban_data[-1])
town_data.append(town_data[-1])
rural_data.append(rural_data[-1])
total_in_school.append(total_in_school[-1])
else:
urban_data.append(0)
town_data.append(0)
rural_data.append(0)
total_in_school.append(0)
else:
# 非学前教育或没有预测工具，使用前一年数据
if len(total_in_school) > 0:
urban_data.append(urban_data[-1])
town_data.append(town_data[-1])
rural_data.append(rural_data[-1])
total_in_school.append(total_in_school[-1])
else:
urban_data.append(0)
town_data.append(0)
rural_data.append(0)
total_in_school.append(0)
# 添加2022年基数的粉色折线
base_year = "2022"
@@ -143,7 +286,7 @@ class RuYuanZaiYuanModel:
base_index = years.index(base_year) if base_year in years else 0
# 获取2022年的总人数作为基数
base_value = total_in_school[base_index] if base_index < len(total_in_school) else 0
# 创建2022年基数折线数据（2022-2024年）
# 创建2022年基数折线数据（2022-2035年）
base_2022_line = []
for i, year in enumerate(years):
# 只在2022年及之后显示基数线