submit calculate_solar_angle.R

Author: Questions1

cal_solar_angle.R

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+
+library(oce)  # 加载这个包用来计算太阳仰角以及离太阳的距离
+library(plyr)
+
+setwd('C:/Users/wn006/Desktop/开放数据-光伏功率-国能日新（新）/data')
+
+train_1 = read.csv("train_1.csv", fileEncoding = 'UTF-8')
+train_2 = read.csv("train_2.csv", fileEncoding = 'UTF-8')
+train_3 = read.csv("train_3.csv", fileEncoding = 'UTF-8')
+train_4 = read.csv("train_4.csv", fileEncoding = 'UTF-8')
+
+test_1 = read.csv("test_1.csv", fileEncoding = 'UTF-8')
+test_2 = read.csv("test_2.csv", fileEncoding = 'UTF-8')
+test_3 = read.csv("test_3.csv", fileEncoding = 'UTF-8')
+test_4 = read.csv("test_4.csv", fileEncoding = 'UTF-8')
+
+train_1$时间 = as.character(train_1$时间)
+train_2$时间 = as.character(train_2$时间)
+train_3$时间 = as.character(train_3$时间)
+train_4$时间 = as.character(train_4$时间)
+
+test_1$时间 = as.character(test_1$时间)
+test_2$时间 = as.character(test_2$时间)
+test_3$时间 = as.character(test_3$时间)
+test_4$时间 = as.character(test_4$时间)
+
+
+add_solar = function(data, longitude, latitude)
+{
+  cal_4_solar = function(time_str)
+  {
+    # 计算出太阳仰角， 离太阳的距离, 并根据大气折射进行校正
+    result = sunAngle(as.POSIXct(time_str, tz="Asia/Taipei"), 
+                      longitude = longitude, latitude = latitude, 
+                      useRefraction = TRUE)
+    
+    # 计算出年份，月份，天数等等，作为特征
+    time_list = as.POSIXlt(time_str, tz="Asia/Taipei")
+    
+    year = time_list$year
+    month = time_list$mon + 1  # 月份居然从0开始
+    yday = time_list$yday
+    mday = time_list$mday
+    hour = time_list$hour
+    minute = time_list$min
+    second = time_list$sec
+    hours_float = hour + minute/60 + second/3600
+    
+    # 把计算出的结果统一存到result这个list里，然后返回
+    result$time = NULL  # 这个浮点日期没啥意义，删掉
+    result$hours_float = hours_float
+    result$mday = mday
+    result$yday = yday
+    result$month = month
+    result$year = year
+    
+    return(result)
+  }
+  
+  # 把计算出的结果存一个dataframe
+  pre_df = t(sapply(data$时间, cal_4_solar))
+  
+  solar_df = data.frame(matrix(unlist(pre_df), nrow=dim(pre_df)[1], ncol=dim(pre_df)[2], byrow=FALSE))
+  colnames(solar_df) = colnames(pre_df)
+  # 把计算出的特征dataframe和原始的dataframe合并起来, 然后返回
+  cbind_df = cbind(data, solar_df)
+  
+  return(cbind_df)
+}
+
+# 下面这个应该是太阳能电池板所在位置的经纬度，但是不知道的话，就先猜一下吧，
+# 只要能提取出时间和太阳仰角、距离等的非线性关系即可，平移一些没关系
+# 下面选了青海西宁市的经纬度作为标准来计算
+longitude = 101.78  # 东经
+latitude = 36.62  # 北纬
+
+train_1_new = add_solar(train_1, longitude, latitude)
+train_2_new = add_solar(train_2, longitude, latitude)
+train_3_new = add_solar(train_3, longitude, latitude)
+train_4_new = add_solar(train_4, longitude, latitude)
+
+test_1_new = add_solar(test_1, longitude, latitude)
+test_2_new = add_solar(test_2, longitude, latitude)
+test_3_new = add_solar(test_3, longitude, latitude)
+test_4_new = add_solar(test_4, longitude, latitude)
+
+setwd('C:/Users/wn006/Desktop/开放数据-光伏功率-国能日新（新）/data_new')
+
+write.csv(train_1_new, "train_1_new.csv", row.names = FALSE, fileEncoding = 'UTF-8')
+write.csv(train_2_new, "train_2_new.csv", row.names = FALSE, fileEncoding = 'UTF-8')
+write.csv(train_3_new, "train_3_new.csv", row.names = FALSE, fileEncoding = 'UTF-8')
+write.csv(train_4_new, "train_4_new.csv", row.names = FALSE, fileEncoding = 'UTF-8')
+
+write.csv(test_1_new, "test_1_new.csv", row.names = FALSE, fileEncoding = 'UTF-8')
+write.csv(test_2_new, "test_2_new.csv", row.names = FALSE, fileEncoding = 'UTF-8')
+write.csv(test_3_new, "test_3_new.csv", row.names = FALSE, fileEncoding = 'UTF-8')
+write.csv(test_4_new, "test_4_new.csv", row.names = FALSE, fileEncoding = 'UTF-8')
+
+