feat: subtype TplotVariable from AbstractDataVariable

Author: Beforerr

Project.toml

@@ -7,6 +7,7 @@ version = "1.0.0-DEV"
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 DimensionalData = "0703355e-b756-11e9-17c0-8b28908087d0"
 PythonCall = "6099a3de-0909-46bc-b1f4-468b9a2dfc0d"
+SpaceDataModel = "0b37b92c-f0c5-4a52-bd5c-390dec20857c"
 
 [compat]
 DimensionalData = "0.29"

src/DimensionalData.jl

@@ -1,7 +1,26 @@
 using DimensionalData
-import DimensionalData: DimArray
+import DimensionalData: DimArray, dims
 import DimensionalData.Lookups: NoLookup
 
+function get_xarray_dims(x; transpose=false)
+    dim_names = tuple(Symbol.(collect(x.dims))...)
+    dim_names = transpose ? reverse(dim_names) : dim_names
+    coord_names = Symbol.(collect(x.coords.keys()))
+    lookups_values = map(dim_names) do dim
+        if dim in coord_names
+            coord_py = getproperty(x, dim).data
+            coord_type = string(coord_py.dtype.name)
+            coord = coord_type == "datetime64[ns]" ? pyconvert_time(coord_py) : PyArray(coord_py; copy=false)
+            Dim{dim}(coord)
+        else
+            Dim{dim}(NoLookup())
+        end
+    end
+    return lookups_values
+end
+
+DimensionalData.dims(v::TplotVariable) = Tuple(get_xarray_dims(v.py))
+
 function DimensionalData.DimArray(var::TplotVariable; kwargs...)
     pyconvert_dataarray(var.py; kwargs...)
 end
@@ -18,22 +37,9 @@ function pyconvert_dataarray(x; transpose=false)
     data_npy = transpose ? x.data.T : x.data
     data = PyArray(data_npy; copy=false)
 
-    dim_names = tuple(Symbol.(collect(x.dims))...)
-    dim_names = transpose ? reverse(dim_names) : dim_names
-    coord_names = Symbol.(collect(x.coords.keys()))
-    lookups_values = map(dim_names) do dim
-        if dim in coord_names
-            coord_py = getproperty(x, dim).data
-            coord_type = string(coord_py.dtype.name)
-            coord_type == "datetime64[ns]" ? pyconvert_time(coord_py) : PyArray(coord_py; copy=false)
-        else
-            NoLookup()
-        end
-    end
-
-    lookups = NamedTuple{dim_names}(lookups_values)
+    dims = get_xarray_dims(x; transpose)
     metadata = pyconvert(Dict{Any,Any}, x.attrs)
     array_name = pyis(x.name, pybuiltins.None) ? nothing : string(x.name)
 
-    return DimArray(data, lookups; name=array_name, metadata)
+    return DimArray(data, dims; name=array_name, metadata)
 end

src/PySPEDAS.jl

@@ -3,6 +3,9 @@ module PySPEDAS
 using PythonCall
 using PythonCall: pynew
 using Dates
+using SpaceDataModel
+using SpaceDataModel: AbstractDataVariable
+import SpaceDataModel: times
 
 export pyspedas, pytplot
 export tplot, get_data

src/types.jl

@@ -15,12 +15,19 @@ Project(name) = Project(name, pynew(), Ref{Vector{Symbol}}())
 # This somehow could prevent the Segmentation fault, see also https://github.com/JuliaPy/PythonCall.jl/issues/586
 attributes(p::Project) = p.attributes[]
 
-struct TplotVariable
+struct TplotVariable{T,N} <: AbstractDataVariable{T,N}
     name::Symbol
+    data::PyArray{T,N}
     py::Py
 end
 
-TplotVariable(name) = TplotVariable(Symbol(name), pytplot.data_quants[String(name)])
+function TplotVariable(name)
+    py = pytplot.data_quants[String(name)]
+    data = PyArray(py.data; copy=false)
+    TplotVariable(Symbol(name), data, py)
+end
+
+SpaceDataModel.times(var::TplotVariable) = pyconvert_time(var.py.time.data)
 
 struct LoadFunction
     py::Py