为什么gdal给了我不同于R的变量的最大值和最小值?
这三行将打开并从netcdf文件中读取一个变量:为什么gdal给了我不同于R的变量的最大值和最小值?,r,gdal,netcdf,rgdal,R,Gdal,Netcdf,Rgdal,这三行将打开并从netcdf文件中读取一个变量: f=open.ncdf("C:\\BR_Ji1.nc") A = get.var.ncdf(nc=f,varid="date",verbose=TRUE) B = get.var.ncdf(nc=f,varid="GPP",verbose=TRUE) [1] "get.var.ncdf: entering. Here is varid:" [1] "GPP" [1] "checking to see if pas
f=open.ncdf("C:\\BR_Ji1.nc")
A = get.var.ncdf(nc=f,varid="date",verbose=TRUE)
B = get.var.ncdf(nc=f,varid="GPP",verbose=TRUE)
[1] "get.var.ncdf: entering. Here is varid:"
[1] "GPP"
[1] "checking to see if passed varid is actually a dimvar"
[1] "entering vobjtodimname with varid= GPP"
[1] "vobjtodimname: is a character type varid. This file has 6 dims"
[1] "vobjtodimname: no cases found, returning FALSE"
[1] "get.var.ncdf: isdimvar: FALSE"
[1] "vobjtovarid: entering with varid=GPP"
[1] "Variable named GPP found in file with varid= 17"
[1] "vobjtovarid: returning with varid deduced from name; varid= 17"
[1] "get.var.ncdf: ending up using varid= 17"
[1] "ndims: 2"
[1] "get.var.ncdf: varsize:"
[1] 1 17520
[1] "get.var.ncdf: start:"
[1] 1 1
[1] "get.var.ncdf: count:"
[1] 1 17520
[1] "get.var.ncdf: totvarsize: 17520"
[1] "Getting var of type 3 (1=short, 2=int, 3=float, 4=double, 5=char, 6=byte)"
[1] "get.var.ncdf: C call returned 0"
[1] "count.nodegen: 17520 Length of data: 17520"
[1] "get.var.ncdf: final dims of returned array:"
[1] 17520
[1] "varid: 17"
[1] "nc$varid2Rindex: 1" "nc$varid2Rindex: 2" "nc$varid2Rindex: 0" "nc$varid2Rindex: 0" "nc$varid2Rindex: 3"
[6] "nc$varid2Rindex: 0" "nc$varid2Rindex: 4" "nc$varid2Rindex: 5" "nc$varid2Rindex: 6" "nc$varid2Rindex: 7"
[11] "nc$varid2Rindex: 8" "nc$varid2Rindex: 9" "nc$varid2Rindex: 10" "nc$varid2Rindex: 11" "nc$varid2Rindex: 12"
[16] "nc$varid2Rindex: 13" "nc$varid2Rindex: 14" "nc$varid2Rindex: 15" "nc$varid2Rindex: 16" "nc$varid2Rindex: 17"
[21] "nc$varid2Rindex: 18" "nc$varid2Rindex: 19" "nc$varid2Rindex: 20"
[1] "nc$varid2Rindex[varid]: 14"
[1] "get.var.ncdf: setting missing values to NA"
[1] "missval: -9999 tol: 0.09999"
[1] "get.var.ncdf: implementing add_offset ( FALSE ) and scale_factor ( FALSE )"
[1] "var has NEITHER add_offset nor scale_factor"
**K = get.var.ncdf(nc=f,varid="Qle",verbose=TRUE)
write.table(t(rbind(A,B,K)),"C:\\Ji1-gpp-lat.txt")**
当我查看提取的数据时,我发现我有非常小的负值。
然后我使用gdalinfo,发现最大值是400,最小值是0(这是正常的,值应该是这样的)。你知道我打错号码的原因吗?请看这个问题:。文件元数据中包含的统计信息可能不新鲜,也可能无法精确计算。如果需要精确的统计数据,您应该自己计算,或者确保使用近似值计算这些数据的标志设置为False。您确定这不是显示问题吗?例如,如果
gdalinfo
将数字格式化为整数,则大小很小的负数将显示为0
Re dogdalinfo
,并使用-stats
强制重新生成统计信息。R
报告了什么?如果您了解Python/NumPy,那么您可以使用的另一个好工具是。