add YAX

README.md

@@ -107,9 +107,11 @@ using YAXArrays
 Let's assemble a `YAXArray` with 4 dimensions i.e. time, x,y and a variable dimension with two variables.
 
 ```julia
-using YAXArrays, DimensionalData
+using YAXArrays: YAXArrays as YAX, YAXArrays
+using DimensionalData
+
 axlist = (
-    Dim{:time}(range(1, 20, length=20)),
+    YAX.time(range(1, 20, length=20)),
     X(range(1, 10, length=10)),
     Y(range(1, 5, length=15)),
     Dim{:Variable}(["var1", "var2"]))

docs/src/UserGuide/combine.md

@@ -10,10 +10,10 @@ We glue the arrays along the first dimension using `dims = 1`:
 The resulting array `whole_year` still has one dimension, i.e. time, but with 12 instead of 6 elements.
 
 ````@example cat
-using YAXArrays
+using YAXArrays: YAXArrays as YAX, YAXArrays
 
-first_half = YAXArray((Dim{:time}(1:6),), rand(6))
-second_half = YAXArray((Dim{:time}(7:12),), rand(6))
+first_half = YAXArray((YAX.time(1:6),), rand(6))
+second_half = YAXArray((YAX.time(7:12),), rand(6))
 whole_year = cat(first_half, second_half, dims = 1)
 ````
 
@@ -24,10 +24,10 @@ The resulting array `combined` has an additional dimension `variable` indicating
 Note that using a `Dataset` instead is a more flexible approach in handling different variables.
 
 ````@example concatenatecubes
-using YAXArrays
+using YAXArrays: YAXArrays as YAX, YAXArrays
 
-temperature = YAXArray((Dim{:time}(1:6),), rand(6))
-precipitation = YAXArray((Dim{:time}(1:6),), rand(6))
+temperature = YAXArray((YAX.time(1:6),), rand(6))
+precipitation = YAXArray((YAX.time(1:6),), rand(6))
 cubes = [temperature,precipitation]
 var_axis = Dim{:variable}(["temp", "prep"])
 combined = concatenatecubes(cubes, var_axis)

docs/src/UserGuide/compute.md

@@ -11,13 +11,13 @@ This section describes how to create new YAXArrays by performing operations on t
 Let's start by creating an example dataset:
 
 ````@example compute
-using YAXArrays
+using YAXArrays: YAXArrays as YAX, YAXArrays
 using Dates
 
 axlist = (
-    Dim{:time}(Date("2022-01-01"):Day(1):Date("2022-01-30")),
-    Dim{:lon}(range(1, 10, length=10)),
-    Dim{:lat}(range(1, 5, length=15)),
+    YAX.time(Date("2022-01-01"):Day(1):Date("2022-01-30")),
+    lon(range(1, 10, length=10)),
+    lat(range(1, 5, length=15)),
 )
 data = rand(30, 10, 15)
 properties = Dict(:origin => "user guide")
@@ -102,7 +102,7 @@ Dimensions may be added or removed.
 Here, we will define a simple function, that will take as input several `YAXArrays`. But first, let's load the necessary packages.
 
 ````@example mapCube
-using YAXArrays, Zarr
+using YAXArrays: YAXArrays as YAX, YAXArrays, Zarr
 using Dates
 ````
 
@@ -130,15 +130,15 @@ Note the `.` after `f`, this is because we will slice across time, namely, the f
 Here, we do create `YAXArrays` only with the desired dimensions as
 
 ````@ansi mapCube
-lon = YAXArray(Dim{:lon}(range(1, 15)))
-lat = YAXArray(Dim{:lat}(range(1, 10)))
+lon = YAXArray(lon(range(1, 15)))
+lat = YAXArray(lat(range(1, 10)))
 ````
 
 And a time Cube's Axis
 
 ````@example mapCube
 tspan = Date("2022-01-01"):Day(1):Date("2022-01-30")
-time = YAXArray(Dim{:time}(tspan))
+time = YAXArray(YAX.time(tspan))
 ````
 
 note that the following can be extended to arbitrary `YAXArrays` with additional data and dimensions.
@@ -197,14 +197,14 @@ which outputs the same as the `gen_cube.data[1, :, :]` called above.
 Here, we will consider different scenarios, namely how we deal with different input cubes and how to specify the output ones. We will illustrate this with the following test example and the subsequent function definitions. 
 
 ````@example outdims
-using YAXArrays, Dates
+using YAXArrays: YAXArrays as YAX, YAXArrays, Dates
 using Zarr
 using Random
 
 axlist = (
-    Dim{:time}(Date("2022-01-01"):Day(1):Date("2022-01-05")),
-    Dim{:lon}(range(1, 4, length=4)),
-    Dim{:lat}(range(1, 3, length=3)),
+    YAX.time(Date("2022-01-01"):Day(1):Date("2022-01-05")),
+    lon(range(1, 4, length=4)),
+    lat(range(1, 3, length=3)),
     Dim{:variables}(["a", "b"])
 )
 
@@ -308,7 +308,7 @@ Here, the goal is to operate at the pixel level (longitude, latitude), and then
 Random.seed!(123)
 data = rand(3.0:5.0, 5, 4, 3)
 
-axlist = (Dim{:lon}(1:4), Dim{:lat}(1:3), Dim{:depth}(1:7),)
+axlist = (lon(1:4), lat(1:3), Dim{:depth}(1:7),)
 yax_2d = YAXArray(axlist, rand(-3.0:0.0, 4, 3, 7))
 ````
 
@@ -318,8 +318,8 @@ and
 Random.seed!(123)
 data = rand(3.0:5.0, 5, 4, 3)
 
-axlist = (Dim{:time}(Date("2022-01-01"):Day(1):Date("2022-01-05")),
-    Dim{:lon}(1:4), Dim{:lat}(1:3),)
+axlist = (YAX.time(Date("2022-01-01"):Day(1):Date("2022-01-05")),
+    lon(1:4), lat(1:3),)
 
 properties = Dict("description" => "multi dimensional test cube")
 yax_test = YAXArray(axlist, data, properties)
@@ -358,14 +358,14 @@ Here we transform a raster array with spatial dimension lat and lon into a vecto
 First, create the raster array:
 
 ````@example compute_mapcube
-using YAXArrays
+using YAXArrays: YAXArrays as YAX, YAXArrays
 using DimensionalData
 using Dates
 
 axlist = (
-    Dim{:time}(Date("2022-01-01"):Day(1):Date("2022-01-30")),
-    Dim{:lon}(range(1, 10, length=10)),
-    Dim{:lat}(range(1, 5, length=15)),
+    YAX.time(Date("2022-01-01"):Day(1):Date("2022-01-30")),
+    lon(range(1, 10, length=10)),
+    lat(range(1, 5, length=15)),
 )
 data = rand(30, 10, 15)
 raster_arr = YAXArray(axlist, data)
@@ -431,14 +431,14 @@ For example, we can execute each date of a time series in a different CPU thread
 The following code does a time mean over all grid points using multiple CPUs of a local machine:
 
 ````julia
-using YAXArrays
+using YAXArrays: YAXArrays as YAX, YAXArrays
 using Dates
 using Distributed
 
 axlist = (
-    Dim{:time}(Date("2022-01-01"):Day(1):Date("2022-01-30")),
-    Dim{:lon}(range(1, 10, length=10)),
-    Dim{:lat}(range(1, 5, length=15)),
+    YAX.time(Date("2022-01-01"):Day(1):Date("2022-01-30")),
+    lon(range(1, 10, length=10)),
+    lat(range(1, 5, length=15)),
 )
 data = rand(30, 10, 15)
 properties = Dict(:origin => "user guide")

docs/src/UserGuide/create.md

@@ -7,7 +7,7 @@ This section describes how to create arrays and datasets by filling values direc
 We can create a new YAXArray by filling the values directly:
 
 ````@example create
-using YAXArrays
+using YAXArrays: YAXArrays as YAX, YAXArrays
 a1 = YAXArray(rand(10, 20, 5))
 ````
 
@@ -18,9 +18,9 @@ We can also specify the dimensions with custom names enabling easier access:
 using Dates
 
 axlist = (
-    Dim{:time}(Date("2022-01-01"):Day(1):Date("2022-01-30")),
-    Dim{:lon}(range(1, 10, length=10)),
-    Dim{:lat}(range(1, 5, length=15)),
+    YAX.time(Date("2022-01-01"):Day(1):Date("2022-01-30")),
+    lon(range(1, 10, length=10)),
+    lat(range(1, 5, length=15)),
 )
 data2 = rand(30, 10, 15)
 properties = Dict(:origin => "user guide")

docs/src/UserGuide/faq.md

@@ -80,11 +80,11 @@ It is possible to concatenate several cubes that shared the same dimensions usin
 
 Let's create two dummy cubes
 ````@example howdoi
-using YAXArrays
+using YAXArrays: YAXArrays as YAX, YAXArrays
 axlist = (
-    Dim{:time}(range(1, 20, length=20)),
-    Dim{:lon}(range(1, 10, length=10)),
-    Dim{:lat}(range(1, 5, length=15))
+    YAX.time(range(1, 20, length=20)),
+    lon(range(1, 10, length=10)),
+    lat(range(1, 5, length=15))
     )
 
 data1 = rand(20, 10, 15)
@@ -324,7 +324,7 @@ You will not be able to save this dataset, first you will need to rename those `
 In this section we will use `MarketData.jl` and `TimeSeries.jl` to simulate some stocks.
 
 ````@example howdoi
-using YAXArrays, DimensionalData
+using YAXArrays: YAXArrays as YAX, YAXArrays, DimensionalData
 using MarketData, TimeSeries
 
 stocks = Dict(:Stock1 => random_ohlcv(), :Stock2 => random_ohlcv(), :Stock3 => random_ohlcv())
@@ -334,7 +334,7 @@ d_keys = keys(stocks)
 currently there is not direct support to obtain `dims` from a `TimeArray`, but we can code a function for it
 
 ````@example howdoi
-getTArrayAxes(ta::TimeArray) = (Dim{:time}(timestamp(ta)), Dim{:variable}(colnames(ta)), );
+getTArrayAxes(ta::TimeArray) = (YAX.time(timestamp(ta)), Dim{:variable}(colnames(ta)), );
 nothing # hide
 ````
 then, we create the `YAXArrays` as

docs/src/get_started.md

@@ -19,7 +19,7 @@ import Pkg; Pkg.add("YAXArrays")
 Create a simple array from random numbers given the size of each dimension or axis:
 
 ```@example quickstart
-using YAXArrays
+using YAXArrays: YAXArrays as YAX, YAXArrays
 
 a = YAXArray(rand(2,3))
 ```
@@ -31,7 +31,7 @@ using DimensionalData
 
 # axes or dimensions with name and tick values
 axlist = (
-    Dim{:time}(range(1, 20, length=20)),
+    YAX.time(range(1, 20, length=20)),
     X(range(1, 10, length=10)),
     Y(range(1, 5, length=15)),
     Dim{:variable}(["temperature", "precipitation"])

src/dims.jl

@@ -24,5 +24,4 @@ export height, depth
 @dim depth ZDim
 
 @dim time TimeDim "time"
-@dim Time TimeDim "time"
-
+@dim Time TimeDim "time"

test/Datasets/datasets.jl

@@ -416,7 +416,8 @@ end
 end
 
 @testset "Saving, OutDims" begin
-    using YAXArrays, Zarr, NetCDF, ArchGDAL
+    using YAXArrays: YAXArrays as YAX, YAXArrays
+    using Zarr, NetCDF, ArchGDAL
     using Dates
 
     flolat(lo, la, t) = (lo + la + Dates.dayofyear(t))
@@ -430,10 +431,10 @@ end
         xout .= flola.(lo, la)
     end
 
-    lon = YAXArray(Dim{:lon}(range(1, 15)))
-    lat = YAXArray(Dim{:lat}(range(1, 10)))
+    lon = YAXArray(lon(range(1, 15)))
+    lat = YAXArray(lat(range(1, 10)))
     tspan = Date("2022-01-01"):Day(1):Date("2022-01-30")
-    time = YAXArray(Dim{:time}(tspan))
+    time = YAXArray(YAX.time(tspan))
 
     properties = Dict{String, Any}("name" => "out_array")