Use DiskArrays.view_disk to create views of AbstractVariable

Project.toml

@@ -4,7 +4,7 @@ keywords = ["netcdf", "GRIB", "climate and forecast conventions", "oceanography"
 license = "MIT"
 desc = "CommonDataModel is a module that defines types common to NetCDF and GRIB data"
 authors = ["Alexander Barth <barth.alexander@gmail.com>"]
-version = "0.4.0"
+version = "0.4.1"
 
 [deps]
 CFTime = "179af706-886a-5703-950a-314cd64e0468"

src/CommonDataModel.jl

@@ -11,6 +11,7 @@ import DiskArrays:
     AbstractDiskArray, 
     AbstractSubDiskArray, 
     subarray,
+    view_disk,
     writeblock!,
     readblock!,
     ChunkStyle,
@@ -36,6 +37,8 @@ import Base:
     reduce,
     show,
     size,
+    vec,
+    view,
     write
 
 import Statistics

src/subvariable.jl

@@ -92,16 +92,11 @@ close(ds)
 
 """
 function Base.view(a::AbstractVariable,i...) 
-    i2 = DiskArrays._replace_colon.(size(a), i) # TODO improve
-    return SubVariable(SubArray(a, i2))
+    disk_sub_array = DiskArrays.view_disk(a, i...)
+    return SubVariable(DiskArrays.subarray(disk_sub_array))
 end
 
-# copied from https://github.com/JuliaIO/DiskArrays.jl/blob/6522ba32759f81945396890ebba5525d33342244/src/subarray.jl#L28
-# this is done to not depend on DiskArray Internals.
-_replace_colon(s, ::Colon) = Base.OneTo(s)
-_replace_colon(s, r) = r
-
-Base.view(a::AbstractVariable, i::CartesianIndices) = view(a, i.indices...)
+Base.vec(a::AbstractVariable) = view(a, :)
 
 dimnames(ds::SubDataset) = dimnames(ds.ds)
 defDim(ds::SubDataset,name::SymbolOrString,len) = defDim(ds.ds,name,len)

test/test_subvariable.jl

@@ -252,3 +252,14 @@ v = select(sst_view,
 @test size(v) == (4,3,8)
 @test all(v[:,1,1] .≈ 2:5)
 @test all(v[1,:,2] .≈ [3,5,7])
+
+
+## regression test for https://github.com/JuliaGeo/NCDatasets.jl/issues/287
+fname = tempname()
+ds = TDS(fname, "c")
+v = defVar(ds, "temperature", zeros(10,11), ("lon", "lat"))
+m = iseven.(reshape(1:(10*11),(10,11)))
+
+@test size(view(v,m)) == (count(m),)
+v[m] .= 1
+@test Array(v) == m