R - 将相同的脚本应用于多个数据帧

Question

我有一个脚本可以读取包含坐标、降雨量和作物面积数据的 .dat 文件，如下所示。

  East  North    rain  Wheat Sbarley Potato OSR fMaize Total  LCA
10000 510000 1498.73 0.0021     0.5 0.0022   0 0.0056  0.01 0.01
10000 510000 1498.73 0.0021   0.034 0.0022   0 0.0056  0.01 0.01
10000 510000 1498.73 0.0021   0.001 0.0022   0 0.0056  0.01 0.01
10000 515000 1518.51 0.0000    0.12 0.0000   0 0.0000  0.00 0.00
10000 515000 1518.51 0.0000  0.0078 0.0125   0 0.0000  0.00 0.00
10000 515000 1518.51 0.0000       0 0.0000   0   0.03  0.00 0.00

下面的代码通过一系列模型计算小麦的排放量，然后提取数据并生成光栅文件并在 ggplot 中绘制。 read these queries 我很困惑我是否需要制作一个包，或者缺少一些关于如何通过每种作物类型重复代码的非常基本的东西。

library(doBy)
library(ggplot2)
library(plyr)
library(raster)
library(RColorBrewer)
library(rgdal)
library(scales)
library(sp)

### Read in the data
crmet <- read.csv("data.dat")
# Remove NA values
crm <- crmet[ ! crmet$rain %in% -119988, ]
crm <- crm[ ! crm$Wheat %in% -9999, ]

### Set model parameters
a <- 0.1474
b <- 0.0005232
g <- -0.00001518
d <- 0.000003662
N <- 182

### Models
crm$logN2O <- a+(b*crm$rain)+(g*N)+(d*crm$rain*N)
crm$eN2O <- exp(crm$logN2O)
crm$whN2O <- crm$eN2O*crm$Wheat

### Prepare data for conversion to raster
crmet.ras <- crm
crmet.ras <- rename(crmet.ras, c("East"="x","North"="y"))

#### Make wheat emissions raster
wn <- crmet.ras[,c(1,2,13)]
spg <- wn

# Set the Eastings and Northings to coordinates
coordinates(spg) <- ~ x + y
# coerce to SpatialPixelsDataFrame
gridded(spg) <- TRUE
# coerce to raster
rasterDF <- raster(spg)
# Add projection to it - in this case OSBG36
proj4string(rasterDF) <- CRS("+proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +ellps=airy +datum=OSGB36 +units=m +no_defs")
rasterDF

writeRaster(rasterDF, 'wn.tif', overwrite=T)

### Plotting the raster:
whplot <-ggplot(wn, aes(x = x, y = y))+
  geom_tile(aes(fill = whN2O))+
  theme_minimal()+
  theme(plot.title = element_text(size=20, face="bold"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.ticks = element_blank(),
        axis.text.x = element_blank(),
        axis.text.y = element_blank(),
        legend.title = element_text(size=16, face="bold"))+
  scale_fill_gradient(name=expression(paste("", N[2], "O ", Ha^-1, sep="")))+
  xlab ("")+
  ylab ("")+
  labs (title="Nitrous oxide emissions\nfrom Wheat")

whplot

我正在尝试尽可能多地将上述内容转化为函数，但它们都比我在此处和 ?help 文件中找到的示例要复杂得多。非常感谢任何 help/suggestions.

Answer 1

您需要将代码放在一个以数据文件名作为参数的函数中。然后你可以用相关的数据文件名调用你的函数。类似于：

library(doBy)
library(ggplot2)
library(plyr)
library(raster)
library(RColorBrewer)
library(rgdal)
library(scales)
library(sp)

#defining the function
my.neat.function <- function(datafname){
### Read in the data
crmet <- read.csv(datafname)
# Remove NA values
crm <- crmet[ ! crmet$rain %in% -119988, ]
crm <- crm[ ! crm$Wheat %in% -9999, ]

### Set model parameters
a <- 0.1474
b <- 0.0005232
g <- -0.00001518
d <- 0.000003662
N <- 182
### Models
crm$logN2O <- a+(b*crm$rain)+(g*N)+(d*crm$rain*N)
crm$eN2O <- exp(crm$logN2O)
crm$whN2O <- crm$eN2O*crm$Wheat

### Prepare data for conversion to raster
crmet.ras <- crm
crmet.ras <- rename(crmet.ras, c("East"="x","North"="y"))

#### Make wheat emissions raster
wn <- crmet.ras[,c(1,2,13)]
spg <- wn

# Set the Eastings and Northings to coordinates
coordinates(spg) <- ~ x + y
# coerce to SpatialPixelsDataFrame
gridded(spg) <- TRUE
# coerce to raster
rasterDF <- raster(spg)
# Add projection to it - in this case OSBG36
proj4string(rasterDF) <- CRS("+proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +ellps=airy +datum=OSGB36 +units=m +no_defs")
rasterDF

writeRaster(rasterDF, 'wn.tif', overwrite=T)

### Plotting the raster:
whplot <-ggplot(wn, aes(x = x, y = y))+
  geom_tile(aes(fill = whN2O))+
  theme_minimal()+
  theme(plot.title = element_text(size=20, face="bold"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.ticks = element_blank(),
        axis.text.x = element_blank(),
        axis.text.y = element_blank(),
        legend.title = element_text(size=16, face="bold"))+
  scale_fill_gradient(name=expression(paste("", N[2], "O ", Ha^-1, sep="")))+
  xlab ("")+
  ylab ("")+
  labs (title="Nitrous oxide emissions\nfrom Wheat")

whplot
} #end of function definition
my.neat.function("data.dat") #first call to function
my.neat.function("otherdata.dat")#same thing with another dataset

如果模型参数为不同的数据，则需要将参数值的向量作为参数添加到函数中。

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