Merge f4bab84 into cd0f907

JuliaClimate · Apr 30, 2020 · ba038e9 · ba038e9
2 parents cd0f907 + f4bab84
commit ba038e9
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Showing 11 changed files with 212 additions and 137 deletions.
diff --git a/Project.toml b/Project.toml
@@ -19,8 +19,10 @@ IterTools = "c8e1da08-722c-5040-9ed9-7db0dc04731e"
 NCDatasets = "85f8d34a-cbdd-5861-8df4-14fed0d494ab"
 NaNMath = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
 NetCDF = "30363a11-5582-574a-97bb-aa9a979735b9"
+Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Polynomials = "f27b6e38-b328-58d1-80ce-0feddd5e7a45"
 ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
+PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 Shapefile = "8e980c4a-a4fe-5da2-b3a7-4b4b0353a2f4"
@@ -33,16 +35,15 @@ AxisArrays = "0.3, 0.4"
 ClimateBase = "0.6"
 DataFrames = "0.19, 0.20"
 Distances = "0.7, 0.8"
-Extremes = "0.1.1"
+Extremes = "0.1"
 GeoStats = "0.11"
 Interpolations = "0.12"
-InverseDistanceWeighting = "0.2, 0.3"
 IterTools = "1.1, 1.2, 1.3"
 NCDatasets = "0.9, 0.10"
 NaNMath = "0.3"
-NetCDF = "0.7, 0.8, 0.9"
-Polynomials = "0.5, 0.6, 0.7"
+NetCDF = "0.7, 0.8, 0.9, 0.10"
+Polynomials = "0.5, 0.6, 0.7, 0.8"
 ProgressMeter = "1"
 Reexport = "0.2"
 Shapefile = "0.4, 0.5, 0.6"
-julia = "1.2, 1.3"
+julia = "1.2, 1.3, 1.4"
diff --git a/deps/build.jl b/deps/build.jl
@@ -1,65 +1,9 @@
-# using Pkg
+using Pkg
+using PyCall
 
-# using BinDeps
-# import CondaBinDeps
+if lowercase(get(ENV, "CI", "false")) == "true"
 
-# if lowercase(get(ENV, "CI", "false")) == "true"
+        ENV["PYTHON"] = ""
+        Pkg.build("PyCall")
 
-#     let basepython = get(ENV, "PYTHON", "python2")
-#         envpath = joinpath(@__DIR__, "env")
-#         run(`pip install --user virtualenv`)
-#         run(`virtualenv --python=$basepython $envpath`)
-
-#         if Sys.iswindows()
-#             python = joinpath(envpath, "Scripts", "python.exe")
-#         else
-#             python = joinpath(envpath, "bin", "python2")
-#         end
-#         run(`$python -m pip install numpy`)
-#         run(`$python -m pip install scipy`)
-#         run(`$python -m pip install matplotlib`)
-#         run(`$python -m pip install https://github.com/matplotlib/basemap/archive/v1.0.7rel.tar.gz`)
-#         run(`$python -m pip install git+https://github.com/matplotlib/cmocean`)
-
-#         ENV["PYTHON"] = python
-#         Pkg.build("PyCall")
-
-#         if VERSION >= v"0.7.0"
-#             using Libdl
-#         end
-
-#         function validate_netcdf_version(name,handle)
-#             f = Libdl.dlsym_e(handle, "nc_inq_libvers")
-#             #
-#             # Example
-#             # banner = "4.5.6.7 of Apr 1 2000 00:00:00"
-#             banner = unsafe_string(ccall(f,Ptr{UInt8},()))
-
-#             # remove the date
-#             # verstr = "4.5.6.7"
-#             verstr = split(banner)[1]
-
-#             # vernumbers = ["4","5","6","7"]
-#             vernumbers = split(verstr,r"[.-]")
-
-#             # major_minor_patch = ["4","5","6"]
-#             major_minor_patch = vernumbers[1:min(3,length(vernumbers))]
-
-#             # ver = v"4.5.6"
-#             ver = VersionNumber([parse(Int,s) for s in major_minor_patch]...)
-
-#             return ver > v"4.2"
-#         end
-
-#         @BinDeps.setup
-#         libnetcdf = library_dependency("libnetcdf", aliases = ["libnetcdf4","libnetcdf-7","netcdf"], validate = validate_netcdf_version)
-
-#         CondaBinDeps.Conda.add_channel("anaconda")
-#         provides(CondaBinDeps.Manager, "libnetcdf", libnetcdf)
-#         provides(AptGet, "libnetcdf-dev", libnetcdf, os = :Linux)
-#         # provides(Yum, "netcdf-devel", libnetcdf, os = :Linux)
-
-#         @BinDeps.install Dict(:libnetcdf => :libnetcdf)
-
-#     end
-# end
+end
diff --git a/docs/Project.toml b/docs/Project.toml
@@ -1,5 +1,8 @@
 [deps]
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
+Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 
 [compat]
 Documenter = "0.20, 0.21, 0.22, 0.23, 0.24"
+PyCall = "1.91"
diff --git a/docs/make.jl b/docs/make.jl
@@ -1,6 +1,7 @@
 using Pkg
 Pkg.activate(@__DIR__)
-CI = get(ENV, "CI", nothing) == "true"
+ENV["PYTHON"] = ""
+Pkg.build("PyCall")
 using Documenter, ClimateTools
 
 makedocs(sitename = "ClimateTools.jl",

diff --git a/docs/src/interpolation.md b/docs/src/interpolation.md
@@ -2,16 +2,31 @@
 
 A typical step in climate analysis is to interpolate a given grid onto another grid. `ClimateTools` provides such a tool by wrapping Scipy griddata function. It is intended for visualization or as a 1st step before bias-correcting the `ClimGrid` dataset.
 
-[`regrid`](@ref) function will interpolate the data contained in `ClimGrid A` into the coordinates of `ClimGrid B` and returns a new `ClimGrid C` which contains the interpolated data of `A` into the grid of `B`.
+[`griddata`](@ref) function will interpolate the data contained in `ClimGrid A` into the coordinates of `ClimGrid B` and returns a new `ClimGrid C` which contains the interpolated data of `A` into the grid of `B`.
 
 ```julia
-C = regrid(A::ClimGrid, B::ClimGrid)
+C = griddata(A::ClimGrid, B::ClimGrid)
 ```
 
 It is also possible to interpolate a `ClimGrid` onto specified longitude and latitude vectors and arrays.
 
 ```julia
-C = regrid(A::ClimGrid, lon::AbstractArray{N, T} where N where T, lat::AbstractArray{N, T} where N where T; dimx=[], dimy=[], method::String="linear", min=[], max=[])
+C = griddata(A::ClimGrid, lon::AbstractArray{N, T} where N where T, lat::AbstractArray{N, T} where N where T; dimx=[], dimy=[], method::String="linear", min=[], max=[])
 ```
 
 In the case a longitude and latitude 2D array is provided, the user needs to provide the dimension vectors for `x` and `y`.
+
+## Experimental
+
+ClimateTools also provide a way to uses `GeoStats` geostatistics methods. See function `geostats` for some details.
+
+```julia
+using GeoStats
+using ClimateTools
+
+target = :pr # e.g. precipitation
+n = 30 # max number of neighboring points
+solver = Kriging(target => (maxneighbors=n,))
+
+C = geostats(A::ClimGrid, B::ClimGrid, solver=solver)
+```
diff --git a/src/ClimateTools.jl b/src/ClimateTools.jl
@@ -19,9 +19,10 @@ using Statistics
 using Random
 using Dates
 using GeoStats
-using InverseDistanceWeighting
+# using InverseDistanceWeighting
 using Extremes
 using Distances
+using PyCall
 import Base.vcat
 import Base.getindex
 import Base.show
@@ -40,6 +41,12 @@ import Base: *
 import Base: /
 import Base.findmax
 
+const scipy = PyNULL()
+
+function __init__()
+    copy!(scipy, pyimport_conda("scipy.interpolate", "scipy"))
+end
+
 # Included files
 include("functions.jl")
 include("indices.jl")
@@ -63,8 +70,9 @@ export drought_dc
 export ensemble_mean, ensemble_std, ensemble_max, ensemble_min
 export load, load2D
 export regrid, applymask
+export griddata
 export shapefile_coords, shapefile_coords_poly
-export resample, spatialsubset
+export resample, spatialsubset, timestep
 export qqmap, qqmaptf
 export biascorrect_extremes
 export permute_west_east

diff --git a/src/cf_conventions.jl b/src/cf_conventions.jl
@@ -10,9 +10,8 @@ function get_dimname(ds::NCDatasets.Dataset, dim::String)
     found_dim = "NA"
 
     # try finding with the "axis" attribute
-
     for idim in dimensions
-        if idim != "bnds" && idim != "vertices"
+        if idim != "bnds" && idim != "vertices" && idim != "ts" && idim != "string1"
             if haskey(ds[idim].attrib, "axis")
                 if ds[idim].attrib["axis"] == dim
                     found_dim = idim
@@ -22,7 +21,6 @@ function get_dimname(ds::NCDatasets.Dataset, dim::String)
     end
 
     # if found_dim is still not found, try to find it with the standard_name
-
     if found_dim == "NA"
 
         dim_dict = Dict(["T" => ["time"],
@@ -31,15 +29,14 @@ function get_dimname(ds::NCDatasets.Dataset, dim::String)
                          "Y" => ["latitude"]])
 
         for idim in dimensions
-            if idim != "bnds" && idim != "vertices"
+            if idim != "bnds" && idim != "vertices" && idim != "ts" && idim != "string1"
                 attribs = ds[idim].attrib
                 if haskey(attribs, "standard_name")
                     name = "standard_name"
                 elseif haskey(attribs, "long_name")
                     name = "long_name"
                 end
                 if in(ds[idim].attrib[name], dim_dict[dim])
-                    # ds[idim].attrib[name] == dim_dict[dim]
                     found_dim = idim
                 end
             end