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r - r ncdf4 "我找不到请求的变量！"

问题描述

我收到“找不到请求的 var”错误，即使变量名是有效的 - 它适用于其他 netcdf 库 - 包括 NCO、R netcdf4 库和 Panoply：

此示例使用名为test2.nc的文件：

这按预期工作：

library(ncdf4)
nc <- nc_open('test2.nc')
v <- ncvar_get(nc, 'biomass')
image(v)
nc_close(nc)

这不起作用：

library(raster)
r <- raster('test2.nc', 'biomass')
#> Loading required namespace: ncdf4
#> [1] "vobjtovarid4: error #F: I could not find the requsted var (or dimvar) in the file!"
#> [1] "var (or dimvar) name: crs"
#> [1] "file name: test2.nc"
#> Warning in .rasterObjectFromCDF(x, type = objecttype, band = band, ...): NAs
#> introduced by coercion
#> Error in if (band > nbands(r)) {: missing value where TRUE/FALSE needed

由reprex 包于 2021-06-11 创建 (v2.0.0 )

会话信息 
sessioninfo::session_info()
#> - Session info ---------------------------------------------------------------
#>  setting  value                       
#>  version  R version 4.0.2 (2020-06-22)
#>  os       Windows 10 x64              
#>  system   x86_64, mingw32             
#>  ui       RTerm                       
#>  language (EN)                        
#>  collate  English_United States.1252  
#>  ctype    English_United States.1252  
#>  tz       America/Phoenix             
#>  date     2021-06-11                  
#> 
#> - Packages -------------------------------------------------------------------
#>  package     * version date       lib source        
#>  assertthat    0.2.1   2019-03-21 [1] CRAN (R 4.0.2)
#>  backports     1.2.1   2020-12-09 [1] CRAN (R 4.0.3)
#>  cli           2.3.1   2021-02-23 [1] CRAN (R 4.0.4)
#>  codetools     0.2-16  2018-12-24 [2] CRAN (R 4.0.2)
#>  crayon        1.4.1   2021-02-08 [1] CRAN (R 4.0.2)
#>  digest        0.6.27  2020-10-24 [1] CRAN (R 4.0.3)
#>  ellipsis      0.3.1   2020-05-15 [1] CRAN (R 4.0.2)
#>  evaluate      0.14    2019-05-28 [1] CRAN (R 4.0.2)
#>  fansi         0.4.2   2021-01-15 [1] CRAN (R 4.0.3)
#>  fs            1.5.0   2020-07-31 [1] CRAN (R 4.0.3)
#>  glue          1.4.2   2020-08-27 [1] CRAN (R 4.0.2)
#>  highr         0.8     2019-03-20 [1] CRAN (R 4.0.2)
#>  htmltools     0.5.1.1 2021-01-22 [1] CRAN (R 4.0.3)
#>  knitr         1.31    2021-01-27 [1] CRAN (R 4.0.3)
#>  lattice       0.20-41 2020-04-02 [2] CRAN (R 4.0.2)
#>  lifecycle     1.0.0   2021-02-15 [1] CRAN (R 4.0.4)
#>  magrittr      2.0.1   2020-11-17 [1] CRAN (R 4.0.3)
#>  ncdf4         1.17    2019-10-23 [1] CRAN (R 4.0.0)
#>  pillar        1.5.1   2021-03-05 [1] CRAN (R 4.0.4)
#>  pkgconfig     2.0.3   2019-09-22 [1] CRAN (R 4.0.2)
#>  purrr         0.3.4   2020-04-17 [1] CRAN (R 4.0.2)
#>  raster      * 3.4-5   2020-11-14 [1] CRAN (R 4.0.3)
#>  Rcpp          1.0.6   2021-01-15 [1] CRAN (R 4.0.3)
#>  reprex        2.0.0   2021-04-02 [1] CRAN (R 4.0.5)
#>  rgdal         1.5-23  2021-02-03 [1] CRAN (R 4.0.3)
#>  rlang         0.4.10  2020-12-30 [1] CRAN (R 4.0.3)
#>  rmarkdown     2.7     2021-02-19 [1] CRAN (R 4.0.4)
#>  sessioninfo   1.1.1   2018-11-05 [1] CRAN (R 4.0.2)
#>  sp          * 1.4-5   2021-01-10 [1] CRAN (R 4.0.3)
#>  stringi       1.5.3   2020-09-09 [1] CRAN (R 4.0.3)
#>  stringr       1.4.0   2019-02-10 [1] CRAN (R 4.0.2)
#>  styler        1.3.2   2020-02-23 [1] CRAN (R 4.0.2)
#>  tibble        3.1.0   2021-02-25 [1] CRAN (R 4.0.4)
#>  utf8          1.2.1   2021-03-12 [1] CRAN (R 4.0.5)
#>  vctrs         0.3.6   2020-12-17 [1] CRAN (R 4.0.3)
#>  withr         2.4.1   2021-01-26 [1] CRAN (R 4.0.3)
#>  xfun          0.20    2021-01-06 [1] CRAN (R 4.0.3)
#>  yaml          2.2.1   2020-02-01 [1] CRAN (R 4.0.2)
#> 
#> [1] C:/Users/David/Documents/lib/R
#> [2] C:/Program Files/R/R-4.0.2/library

标签： rnetcdfr-rasterncdf4

解决方案

您可以从包中尝试该rast功能。terra它创建一个SpatRaster对象。您可以raster使用该raster函数将对象转换为更高版本。但是，您想在raster包中使用的大多数功能可能都可以通过使用terra包来实现。所以留在SpatRaster课堂上可能没问题。

library(terra)
library(ncdf4)
library(raster)

r <- rast("test2.nc")
r
# class       : SpatRaster 
# dimensions  : 72, 120, 1  (nrow, ncol, nlyr)
# resolution  : 0.04166667, 0.04166667  (x, y)
# extent      : -115, -110, 30, 33  (xmin, xmax, ymin, ymax)
# coord. ref. : +proj=longlat +datum=WGS84 +no_defs 
# source      : test2.nc 
# varname     : biomass (biomass) 
# name        :     biomass 
# unit        : Mg ha-1 y-1 
r2 <- raster(r)
r2
# class      : RasterLayer 
# dimensions : 72, 120, 8640  (nrow, ncol, ncell)
# resolution : 0.04166667, 0.04166667  (x, y)
# extent     : -115, -110, 30, 33  (xmin, xmax, ymin, ymax)
# crs        : +proj=longlat +datum=WGS84 +no_defs 
# source     : test2.nc 
# names      : biomass 
# zvar       : biomass

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