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‎NEWS.md

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ClimaAnalysis.jl Release Notes
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===============================
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v0.5.9
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------
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## Features
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### Reorder dimensions
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Before, resampling requires that the order of the dimensions is the same between the two
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`OutputVar`s. This feature adds the functionality of reordering the dimensions in a
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`OutputVar` to match the ordering of dimensions in another `OutputVar`. See the example
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below of this functionality.
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```julia
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julia> src_var.dims |> keys |> collect
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2-element Vector{String}:
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"long"
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"lat"
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julia> dest_var.dims |> keys |> collect
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2-element Vector{String}:
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"lat"
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"long"
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julia> reordered_var = ClimaAnalysis.reordered_as(src_var, dest_var);
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julia> reordered_var.dims |> keys |> collect
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2-element Vector{String}:
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"lat"
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"long"
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```
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v0.5.8
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------
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‎docs/Project.toml

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ClimaAnalysis = "29b5916a-a76c-4e73-9657-3c8fd22e65e6"
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Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
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GeoMakie = "db073c08-6b98-4ee5-b6a4-5efafb3259c6"
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OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
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[compat]
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CairoMakie = "0.12.5"
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Documenter = "1"
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GeoMakie = "0.7.3"
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OrderedCollections = "1.3"

‎docs/src/api.md

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@@ -54,6 +54,7 @@ Var.has_altitude
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Var.conventional_dim_name
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Var.dim_units
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Var.range_dim
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Var.reordered_as
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Var.resampled_as
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Var.convert_units
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Var.integrate_lonlat

‎docs/src/howdoi.md

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@@ -67,6 +67,51 @@ The `Atmos` module in `ClimaAnalysis` comes with a function,
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`OutputVar` is returned where the values are linearly interpolated on fixed
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pressure levels.
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## How do I reorder the dimensions in a `OutputVar` to match the dimensions in another `OutputVar`?
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You can use the `reordered_as(src_var, dest_var)` function where `src_var` is a `OutputVar`
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with the dimensions you want to reorder to match the dimensions in the OutputVar `dest_var`.
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```@setup reordered_as
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import ClimaAnalysis
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import OrderedCollections: OrderedDict
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src_long = 0.0:180.0 |> collect
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src_lat = 0.0:90.0 |> collect
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src_data = ones(length(src_long), length(src_lat))
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src_dims = OrderedDict(["long" => src_long, "lat" => src_lat])
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src_attribs = Dict("long_name" => "hi")
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src_dim_attribs = OrderedDict([
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"long" => Dict("units" => "test_units1"),
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"lat" => Dict("units" => "test_units2"),
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])
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src_var =
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ClimaAnalysis.OutputVar(src_attribs, src_dims, src_dim_attribs, src_data)
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dest_long = 20.0:180.0 |> collect
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dest_lat = 30.0:90.0 |> collect
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dest_data = zeros(length(dest_lat), length(dest_long))
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dest_dims = OrderedDict(["lat" => dest_lat, "long" => dest_long])
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dest_attribs = Dict("long_name" => "hi")
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dest_dim_attribs = OrderedDict([
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"lat" => Dict("units" => "test_units4"),
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"long" => Dict("units" => "test_units3"),
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])
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dest_var = ClimaAnalysis.OutputVar(
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dest_attribs,
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dest_dims,
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dest_dim_attribs,
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dest_data,
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)
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```
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```@repl reordered_as
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src_var.dims |> keys |> collect
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dest_var.dims |> keys |> collect
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reordered_var = ClimaAnalysis.reordered_as(src_var, dest_var);
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reordered_var.dims |> keys |> collect
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```
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## How do I resample the data in a `OutputVar` using the dimensions from another `OutputVar`?
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You can use the `resampled_as(src_var, dest_var)` function where `src_var` is a

‎src/Var.jl

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units,
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dim_units,
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range_dim,
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reordered_as,
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resampled_as,
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has_units,
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convert_units,
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return nothing
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end
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"""
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reordered_as(src_var::OutputVar, dest_var::OutputVar)
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Reorder the dimensions in `src_var` to match the ordering of dimensions in `dest_var`.
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"""
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function reordered_as(src_var::OutputVar, dest_var::OutputVar)
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# Get the conventional dim names for both src_var and dest_var
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conventional_dim_name_src = conventional_dim_name.(keys(src_var.dims))
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conventional_dim_name_dest = conventional_dim_name.(keys(dest_var.dims))
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# Check if the dimensions are the same (order does not matter)
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Set(conventional_dim_name_src) == Set(conventional_dim_name_dest) || error(
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"Dimensions are not the same between src ($conventional_dim_name_src) and dest ($conventional_dim_name_dest)",
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)
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# Find permutation indices to reorder dims
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reorder_indices =
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indexin(conventional_dim_name_dest, conventional_dim_name_src)
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# Reorder dims, dim_attribs, and data, but not attribs
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ret_dims = deepcopy(src_var.dims)
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ret_dims = OrderedDict(collect(ret_dims)[reorder_indices])
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ret_attribs = deepcopy(src_var.attributes)
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# Cannot assume that every dimension is present in dim_attribs so we loop to reorder the
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# best we can and merge with src_var.dim_attributes to add any remaining pairs to
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# ret_dim_attribs
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ret_dim_attribs = empty(src_var.dim_attributes)
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src_var_dim_attribs = src_var.dim_attributes |> deepcopy
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src_var_dim_names = collect(keys(src_var.dims))
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for idx in reorder_indices
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dim_name = src_var_dim_names[idx]
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haskey(src_var_dim_attribs, dim_name) &&
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(ret_dim_attribs[dim_name] = src_var_dim_attribs[dim_name])
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end
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merge!(ret_dim_attribs, src_var_dim_attribs)
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ret_data = copy(src_var.data)
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ret_data = permutedims(ret_data, reorder_indices)
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return OutputVar(ret_attribs, ret_dims, ret_dim_attribs, ret_data)
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end
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"""
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resampled_as(src_var::OutputVar, dest_var::OutputVar)
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‎test/test_Var.jl

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end
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@testset "Reordering" begin
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# Reordering the dimensions of a var to match itself
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src_long = 0.0:180.0 |> collect
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src_lat = 0.0:90.0 |> collect
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src_data = ones(length(src_long), length(src_lat))
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src_dims = OrderedDict(["long" => src_long, "lat" => src_lat])
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src_attribs = Dict("long_name" => "hi")
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src_dim_attribs = OrderedDict([
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"long" => Dict("units" => "test_units1"),
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"lat" => Dict("units" => "test_units2"),
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])
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src_var = ClimaAnalysis.OutputVar(
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src_attribs,
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src_dims,
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src_dim_attribs,
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src_data,
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)
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reordered_var = ClimaAnalysis.reordered_as(src_var, src_var)
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@test reordered_var.attributes == src_var.attributes
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@test reordered_var.dims == src_var.dims
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@test reordered_var.dim_attributes == src_var.dim_attributes
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@test reordered_var.data == src_var.data
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# Reordering the dimensions of src_var to match a different order of dimensions in
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# dest_var
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dest_long = 20.0:180.0 |> collect
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dest_lat = 30.0:90.0 |> collect
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dest_data = zeros(length(dest_lat), length(dest_long))
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dest_dims = OrderedDict(["lat" => dest_lat, "long" => dest_long])
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dest_attribs = Dict("long_name" => "hi")
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dest_dim_attribs = OrderedDict([
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"lat" => Dict("units" => "test_units4"),
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"long" => Dict("units" => "test_units3"),
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])
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dest_var = ClimaAnalysis.OutputVar(
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dest_attribs,
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dest_dims,
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dest_dim_attribs,
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dest_data,
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)
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reordered_var = ClimaAnalysis.reordered_as(src_var, dest_var)
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@test reordered_var.attributes == src_var.attributes
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@test reordered_var.dims ==
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OrderedDict(["lat" => src_lat, "long" => src_long])
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@test reordered_var.dim_attributes == OrderedDict([
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"lat" => Dict("units" => "test_units2"),
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"long" => Dict("units" => "test_units1"),
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])
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@test reordered_var.data == ones(length(src_lat), length(src_long))
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# Reordering but dim_attributes is not available for every dimension
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src_dim_attribs_one = OrderedDict(["lat" => Dict("units" => "test_units2")])
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src_dim_attribs_empty = empty(src_dim_attribs_one)
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src_dim_attribs_extra = OrderedDict([
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"extra_info" => "hi",
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"lat" => Dict("units" => "test_units2"),
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])
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src_var_one = ClimaAnalysis.OutputVar(
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src_attribs,
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src_dims,
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src_dim_attribs_one,
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src_data,
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)
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src_var_empty = ClimaAnalysis.OutputVar(
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src_attribs,
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src_dims,
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src_dim_attribs_empty,
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src_data,
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)
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src_var_extra = ClimaAnalysis.OutputVar(
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src_attribs,
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src_dims,
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src_dim_attribs_extra,
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src_data,
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)
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reordered_var = ClimaAnalysis.reordered_as(src_var_one, dest_var)
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@test reordered_var.dim_attributes == src_dim_attribs_one
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reordered_var = ClimaAnalysis.reordered_as(src_var_empty, dest_var)
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@test reordered_var.dim_attributes == src_dim_attribs_empty
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reordered_var = ClimaAnalysis.reordered_as(src_var_extra, dest_var)
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@test reordered_var.dim_attributes == OrderedDict([
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"lat" => Dict("units" => "test_units2"),
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"extra_info" => "hi",
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])
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# Error checking for dimensions not being the same in both
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src_long = 20.0:180.0 |> collect
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src_lat = 30.0:90.0 |> collect
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src_dims = OrderedDict(["long" => src_long, "lat" => src_lat])
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src_data = ones(length(src_long), length(src_lat))
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dest_lat = 30.0:90.0 |> collect
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dest_dims = OrderedDict(["lat" => dest_lat])
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dest_data = ones(length(src_lat))
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src_var = ClimaAnalysis.OutputVar(src_dims, src_data)
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dest_var = ClimaAnalysis.OutputVar(dest_dims, dest_data)
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@test_throws ErrorException ClimaAnalysis.reordered_as(src_var, dest_var)
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end
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@testset "Resampling" begin
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src_long = 0.0:180.0 |> collect
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src_lat = 0.0:90.0 |> collect

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