Question

我在R中有以下netcdf文件：

"file oceandata.nc has 2 dimensions:"
"lon   Size: 2160"
"lat   Size: 900"
"------------------------"
"file oceandata.nc has 14 variables:"
"float bio1[lon,lat]  Longname:bio1: Annual Mean Temp Missval:1e+30"
"float bio4[lon,lat]  Longname:bio4: Temp Seasonality (standard deviation * 100) Missval:1e+30"
"float bio8[lon,lat]  Longname:bio8: Mean Temp of Wettest Quarter Missval:1e+30"
"float bio9[lon,lat]  Longname:bio9: Mean Temp of Driest Quarter Missval:1e+30"
"float bio10[lon,lat]  Longname:bio10: Mean Temp of Warmest Quarter Missval:1e+30"
"float bio11[lon,lat]  Longname:bio11: Mean Temp of Coldest Quarter Missval:1e+30"
"float bio12[lon,lat]  Longname:bio12: Annual Precipitation Missval:1e+30"
"float bio13[lon,lat]  Longname:bio13: Precipitation of Wettest Month Missval:1e+30"
"float bio14[lon,lat]  Longname:bio14: Precipitation of Driest Month Missval:1e+30"
"float bio15[lon,lat]  Longname:bio15: Precipitation Seasonality (coefficient of variation) Missval:1e+30"
"float bio16[lon,lat]  Longname:bio16: Precipitation of Wettest Quarter Missval:1e+30"
"float bio17[lon,lat]  Longname:bio17: Precipitation of Driest Quarter Missval:1e+30"
"float bio18[lon,lat]  Longname:bio18: Precipitation of Warmest Quarter Missval:1e+30"
"float bio19[lon,lat]  Longname:bio19: Precipitation of Coldest Quarter Missval:1e+30"

我想对文件中的14个变量执行PCA，但我不确定如何解决此问题，或者在我能够执行此操作之前是否需要将数据转换为其他格式。

到目前为止，我已经完成了（下面的错误消息）：

ocean <- open.ncdf("oceandata.nc")

bio1 <- get.var.ncdf(nc=ncdf, varid="bio1")

bio4 <- get.var.ncdf(nc=ncdf, varid="bio4")

bio8 <- get.var.ncdf(nc=ncdf, varid="bio8")

bio9 <- get.var.ncdf(nc=ncdf, varid="bio9")

dim(bio1)

[1] 2160 900

class(bio1)

[1]“矩阵”

oceanvars <- cbind(bio1,bio4, bio8, bio9)

colnames(oceanvars) <- c("bio1", "bio4", "bio8", "bio9")

colnames<-中的错误（*tmp*，值= c（“bio1”，“bio4”，“bio8”，“bio9”：'dimnames'的长度[2]不等于数组范围

pairs(oceanvars)

plot.new（）出错：数字边距太大

pca1 <- princomp(oceanvars, scores=TRUE, cor=TRUE)

princomp.default中的错误（oceanvars，scores = TRUE，cor = TRUE）：'princomp'只能用于比变量更多的单位

任何建议都会非常感谢！

Answer 1

为什么你假设cbind 4个矩阵每个900列，导致一个矩阵对象有4列，允许分配c（＆＃34; bio1＆＃34;，＆＃34; bio4＆＃ 34;，＆＃34; bio8＆＃34;，＆＃34; bio9＆＃34;）作为列名。

据我所知，您有四个变量Annual Mean Temp，Temp Seasonality，Mean Temp of Wettest Quarter和Mean Temp of Driest Quarter共有1944000个空间对象，您希望通过PCA。

很遗憾，您不提供可重现的示例，而是通过

创建oceanvars

oceanvars <- cbind( c(bio1), c(bio4), c(bio8), c(bio9) )

应该已经做到了。原因是，c()将矩阵融合为一个简单的向量。

更通用，更简洁的程序会将melt您的矩阵与3列data.frames或更大的data.tables进行比较，然后再merge组合lon和lat，然后将值列作为矩阵提供给princomp。

如何在R中使用netcdf数据进行PCA

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