Convert YAXArrays

This section describes how to convert variables from types of other Julia packages into YAXArrays and vice versa.

WARNING

YAXArrays is designed to work with large datasets that are way larger than the memory. However, most types are designed to work in memory. Those conversions are only possible if the entire dataset fits into memory. In addition, metadata might be lost during conversion.

Convert Base.Array

Convert Base.Array to YAXArray:

using YAXArrays

m = rand(5,10)
a = YAXArray(m)

┌ 5×10 YAXArray{Float64, 2} ┐
├───────────────────────────┴──────────────────────────────────── dims ┐
  ↓ Dim_1 Sampled{Int64} Base.OneTo(5) ForwardOrdered Regular Points,
  → Dim_2 Sampled{Int64} Base.OneTo(10) ForwardOrdered Regular Points
├──────────────────────────────────────────────────── loaded in memory ┤
  data size: 400.0 bytes
└──────────────────────────────────────────────────────────────────────┘

Convert YAXArray to Base.Array:

m2 = collect(a.data)

5×10 Matrix{Float64}:
 0.265797  0.789891  0.611084  0.845983  …  0.918555  0.870826   0.348362
 0.665723  0.241882  0.426519  0.581312     0.949935  0.0214057  0.152534
 0.83556   0.456765  0.197238  0.645758     0.74732   0.652339   0.935631
 0.337926  0.151146  0.673373  0.169284     0.75269   0.166212   0.0358348
 0.594514  0.364288  0.78467   0.830391     0.128204  0.174934   0.0210077

Convert Raster

A Raster as defined in Rasters.jl has a same supertype of a YAXArray, i.e. AbstractDimArray, allowing easy conversion between those types:

using Rasters

lon, lat = X(25:1:30), Y(25:1:30)
time = Ti(2000:2024)
ras = Raster(rand(lon, lat, time))
a = YAXArray(dims(ras), ras.data)

ras2 = Raster(a)

Convert DimArray

A DimArray as defined in DimensionalData.jl has a same supertype of a YAXArray, i.e. AbstractDimArray, allowing easy conversion between those types.

Convert DimArray to YAXArray:

using DimensionalData
using YAXArrayBase

dim_arr = rand(X(1:5), Y(10.0:15.0), metadata = Dict{String, Any}())
a = yaxconvert(YAXArray, dim_arr)

┌ 5×6 YAXArray{Float64, 2} ┐
├──────────────────────────┴────────────────────────────────── dims ┐
  ↓ X Sampled{Int64} 1:5 ForwardOrdered Regular Points,
  → Y Sampled{Float64} 10.0:1.0:15.0 ForwardOrdered Regular Points
├───────────────────────────────────────────────── loaded in memory ┤
  data size: 240.0 bytes
└───────────────────────────────────────────────────────────────────┘

Convert YAXArray to DimArray:

dim_arr2 = yaxconvert(DimArray, a)

┌ 5×6 DimArray{Float64, 2} ┐
├──────────────────────────┴────────────────────────────────── dims ┐
  ↓ X Sampled{Int64} 1:5 ForwardOrdered Regular Points,
  → Y Sampled{Float64} 10.0:1.0:15.0 ForwardOrdered Regular Points
└───────────────────────────────────────────────────────────────────┘
 ↓ →  10.0       11.0        12.0        13.0       14.0       15.0
 1     0.862644   0.872575    0.0620649   0.193109   0.475725   0.953391
 2     0.203714   0.770949    0.731779    0.71314    0.687891   0.435994
 3     0.492817   0.718667    0.0702532   0.926096   0.225542   0.100622
 4     0.268675   0.0566881   0.916686    0.973332   0.744521   0.052264
 5     0.540514   0.215973    0.617023    0.796375   0.13205    0.366625

INFO

At the moment there is no support to save a DimArray directly into disk as a NetCDF or a Zarr file.