fix bugs

src/Interpolation/bilinear_helper.jl

@@ -38,8 +38,8 @@ function approx(x, y, xout)
   return yout
 end
 
-array(val; dims) = reshape(val, dims...)
-array(val, dims) = array(val; dims)
+# array(val; dims) = reshape(val, dims...)
+# array(val, dims) = array(val; dims)
 
 function meshgrid(x, y)
   X = repeat(x', length(y), 1)

src/Interpolation/utilize.jl

@@ -1,19 +1,5 @@
 export rm_empty, weighted_nanmean!, weighted_nanmean, earth_dist
-
-function weighted_nanmean(x::AbstractVector{T1}, w::AbstractVector{T2}) where {T1,T2}
-  T = promote_type(T1, T2)
-  ∑ = ∅ = T(0)
-  ∑w = ∅w = T2(0)
-
-  @inbounds for i = eachindex(x)
-    # if !isnan(x[i]); end
-    xᵢ = x[i]
-    notnan = xᵢ == xᵢ
-    ∑ += ifelse(notnan, x[i] * w[i], ∅)
-    ∑w += ifelse(notnan, w[i], ∅w)
-  end
-  return ∑ / ∑w
-end
+import Ipaper: weighted_nanmean
 
 # byrow
 function weighted_nanmean(mat::AbstractMatrix{T1}, w::AbstractVector{T2}) where {T1,T2}

src/NetCDFTools.jl

@@ -21,6 +21,11 @@ import DataFrames: AbstractDataFrame, GroupedDataFrame
 using Ipaper
 @reexport using Ipaper.sf
 
+export exact_extract, coverage_fraction
+
+function exact_extract end
+function coverage_fraction end
+
 include("NCDataset.jl")
 
 include("tools.jl")

src/precompile.jl

@@ -13,17 +13,16 @@ precompile(nc_calendar, (String,))
     "http://esgf-data04.diasjp.net/thredds/dodsC/esg_dataroot/CMIP6/ScenarioMIP/CSIRO-ARCCSS/ACCESS-CM2/ssp126/r1i1p1f1/day/huss/gn/v20210317/huss_day_ACCESS-CM2_ssp126_r1i1p1f1_gn_20150101-20641231.nc",
     "http://esgf-data04.diasjp.net/thredds/dodsC/esg_dataroot/CMIP6/ScenarioMIP/CSIRO-ARCCSS/ACCESS-CM2/ssp126/r1i1p1f1/day/huss/gn/v20210317/huss_day_ACCESS-CM2_ssp126_r1i1p1f1_gn_20650101-21001231.nc"
   ]
-
-
-  @compile_workload begin 
+
+  @compile_workload begin
     info = CMIP.CMIPFiles_info(fs; detailed=false)
     info_s = CMIP.CMIPFiles_summary(info)
 
     # compile bilinear
     for T in (Float64, Float32)
       lon = 70:5:140
       lat = 15:5:55
-      
+
       Lon = 70:2.5:140
       Lat = 15:2.5:55
       Z = rand(T, length(lon), length(lat), 2)

src/tools.jl

@@ -29,7 +29,7 @@ function split_chunk(n::Int, nchunk=4; chunk=nothing, ratio_small::Real=0.0)
     lst[end-1] = i_beg:i_end
     deleteat!(lst, nchunk)
   end
-  lst
+  return lst
 end
 
 function split_chunk(x::Union{UnitRange,AbstractVector}, nchunk=4; kw...)
@@ -47,7 +47,35 @@ function split_date(dates; ny_win=10, kw...)
   lst_index = map(grp -> begin
       findall(indexin(years, grp) .!== nothing)
     end, lst)
-  lst_index
+  return lst_index
 end
 
-export split_chunk, split_date
+
+function updateMask!(A::AbstractArray{T,2}, mask::BitMatrix) where {T<:Real}
+  missval = T(NaN)
+  A[.!mask] .= missval
+  return A
+end
+
+function updateMask!(A::AbstractArray{T,3}, mask::BitMatrix) where {T<:Real}
+  missval = T(NaN)
+  nlon, nlat, ntime = size(A)
+  # lgl = .!mask
+  @inbounds @par for k in 1:ntime
+    for j = 1:nlat, i = 1:nlon
+      !mask[i, j] && (A[i, j, k] = missval)
+    end
+  end
+  return A
+end
+
+function updateMask!(A::AbstractArray{T,N}, mask::BitMatrix) where {T<:Real,N}
+  @inbounds for t in axes(A, N)
+    ind = (repeat([:], N - 1)..., t)
+    x = @view A[ind...]
+    updateMask!(x, mask)
+  end
+  A
+end
+
+export split_chunk, split_date, updateMask!

test/interp/test-weighted_nanmean.jl

@@ -1,4 +1,4 @@
-using Test
+using Test, Ipaper, NetCDFTools
 
 @testset "weighted_nanmean" begin
   x = [1, 2, 3, NaN]

test/runtests.jl

@@ -1,7 +1,6 @@
 using Test
 using NetCDFTools
 using Ipaper, Dates
-import NetCDFTools: weighted_nanmean
 
 dir_root = dirname(dirname(@__FILE__))
 proj_path(f) = dirname(dirname(@__FILE__)) * "/" *  f

test/test-Ipaper.jl

@@ -1,15 +1,16 @@
 using Test, NetCDFTools, Ipaper
 
+
 @testset "updateMask" begin
   A = array(1.0:16, (4, 4)) |> collect
   mask = A .> 10
   updateMask!(A, mask)
-  length(findall(A .> 10)) == 6
+  @test length(findall(A .> 10)) == 6
 
-  A = rand(4, 4, 2)
-  mask = A[:, :, 1] .> 0.5
+  A = rand(4, 4, 2, 2)
+  mask = A[:, :, 1, 1] .> 0.5
   updateMask!(A, mask)
-  @test isempty(findall(A[:, :, 1] .<= 0.5))
+  @test isempty(findall(A[:, :, 1, 1] .<= 0.5))
 end