基于python实现的三次样条插值和均值插值法实现

from openpyxl import load_workbook # 读取excel文件 import logging as log import utils # 日志格式化 from bean.user_info_bean import UserInfoBean log.basicConfig(format='%(asctime)s - [line:%(lineno)d] - %(levelname)s: %(message)s', level=log.info) # 数据起始行 data_row_start = 2 # 数据终止行 data_row_end = 108 def _user_vital_signs(excel_data, days, types, start_col): """ 获取病人生命体征时序数据 :param excel_data: :param days: 数据时序天数 :param types: 数据类型总数 :param start_col: 病人生命体征起始列,包含数据第一列 :return: """ for row_index in range(data_row_start, data_row_end + 1, 1): log.info("============================================================开始第" + str(row_index) + "行数据处理") # 体温 log.info("======================开始处理体温数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 0) # 心率 log.info("======================开始处理心率数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 1) # # 呼吸评率 log.info("======================开始处理呼吸评率数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 2) # 收缩压 log.info("======================开始处理收缩压数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 3) # 舒张压 log.info("======================开始处理舒张压数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 4) # 平均动脉压 log.info("======================开始处理平均动脉压数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 5) # 休克指数 log.info("======================开始处理休克指数数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 6) # 尿量 # log.info("======================开始处理尿量数据==========================") # utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, data_start, 7) # # 摄入量 # log.info("======================开始处理摄入量数据==========================") # utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, data_start, 8) # # 输入量 # log.info("=======================开始处理输入量数据==========================") # utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, data_start, 9) def biochemical_index(excel_data, days, types, start_col): """ 处理病人的生化指标 :param excel_data: excel :param days: 数据时序天数 :param types: 数据类型总数 :param start_col: 起始列,包含数据第一列 :return: """ for row_index in range(data_row_start, data_row_end + 1, 1): log.info("============================================================开始第" + str(row_index) + "行数据处理") # 尿素 log.info("======================开始处理尿素数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 0) # 肌酐 log.info("======================开始处理肌酐数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 1) # 血糖 log.info("======================开始处理血糖数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 2) # 白蛋白 log.info("======================开始处理白蛋白数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 3) # 天门冬氨酸氨基转移酶 log.info("======================开始处理天门冬氨酸氨基转移酶数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 4) # 丙氨酸氨基转移酶 log.info("======================开始处理丙氨酸氨基转移酶数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 5) # 总胆红素 log.info("======================开始处理总胆红素数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 6) # 降钙素原 log.info("======================开始处理降钙素原数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 7) # 白细胞计数 log.info("======================开始处理白细胞计数原数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 8) # 中性粒细胞数 log.info("======================开始处理中性粒细胞数数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 9) # 血小板计数 log.info("======================开始处理血小板计数数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 10) # C反应蛋 log.info("======================开始处理C反应蛋数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 11) # 乳酸 log.info("======================开始处理乳酸数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 12) # 氧饱和度 log.info("======================开始处理氧饱和度数据==========================") utils.get_excel_data_by_sequentially_processed(excel_data, row_index, days, types, start_col, 13) if __name__ == '__main__': # file_url 文件地址 file_url = "/Users/wangweijie/workspace/data/ndz_data_20211211.xlsx" # sheet_name 需要操作的sheet名称 sheet_name = "ndzList" # 获取需要操作的数据 wb = load_workbook(file_url, data_only=True) data = wb[sheet_name] # data 数据不用担心 # days 数据时序天数 # types 数据类型总数 # start_col 信息起始列数 # 病人基础数据 _user_vital_signs(data, 14, 7, 24) # 处理病人生化指标 biochemical_index(data, 14, 14, 122) wb.save('脓毒症_插值.xlsx') # def __get_user_info_list(excel_data): # """ # 获取病人信息集合 # :param excel_data: excel处理对象 # :return: 病人信息集合 # """ # # 病人信息集合 # user_info_list = [] # # 遍历病人信息列 # for row_index in range(data_row_start, data_row_end + 1, 1): # user_info = UserInfoBean() # user_info.rows_index = row_index # # 病人名称 # user_info.name = str(excel_data.cell(column=2, row=row_index).value) # user_info.sex = str(excel_data.cell(column=3, row=row_index).value) # user_info.age = str(excel_data.cell(column=4, row