fix docs

README.md

@@ -112,15 +112,15 @@ using YAXArrays: YAXArrays as YAX
 
 axlist = (
     YAX.time(range(1, 20, length=20)),
-    X(range(1, 10, length=10)),
-    Y(range(1, 5, length=15)),
+    lon(range(1, 10, length=10)),
+    lat(range(1, 5, length=15)),
     Variables(["var1", "var2"]))
 ```
 ```
 ↓ time     1.0:1.0:20.0,
-→ X        1.0:1.0:10.0,
-↗ Y        1.0:0.2857142857142857:5.0,
-⬔ Variable ["var1", "var2"]
+→ lon      1.0:1.0:10.0,
+↗ lat      1.0:0.2857142857142857:5.0,
+⬔ Variables ["var1", "var2"]
 ```
 
 and the corresponding data.
@@ -150,8 +150,8 @@ ds = YAXArray(axlist, data, props)
 │ 20×10×15×2 YAXArray{Float64,4} │
 ├────────────────────────────────┴─────────────────────────────────────────────── dims ┐
   ↓ time     Sampled{Float64} 1.0:1.0:20.0 ForwardOrdered Regular Points,
-  → X        Sampled{Float64} 1.0:1.0:10.0 ForwardOrdered Regular Points,
-  ↗ Y        Sampled{Float64} 1.0:0.2857142857142857:5.0 ForwardOrdered Regular Points,
+  → lon      Sampled{Float64} 1.0:1.0:10.0 ForwardOrdered Regular Points,
+  ↗ lat      Sampled{Float64} 1.0:0.2857142857142857:5.0 ForwardOrdered Regular Points,
   ⬔ Variable Categorical{String} ["var1", "var2"] ForwardOrdered
 ├──────────────────────────────────────────────────────────────────────────── metadata ┤
   Dict{String, String} with 5 entries:
@@ -170,17 +170,17 @@ ds = YAXArray(axlist, data, props)
 For axis can be via `.` 
 
 ```julia
-ds.X
+ds.lon
 ```
 ```
-X Sampled{Float64} ForwardOrdered Regular Points
+lon Sampled{Float64} ForwardOrdered Regular Points
 wrapping: 1.0:1.0:10.0
 ```
 
 or better yet via `lookup`
 
 ```julia
-lookup(ds, :X)
+lookup(ds, :lon)
 ```
 ```
 Sampled{Float64} ForwardOrdered Regular Points
@@ -189,7 +189,7 @@ wrapping: 1.0:1.0:10.0
 
 note that also the `.data` field can be use
 ```julia
-lookup(ds, :X).data
+lookup(ds, :lon).data
 ```
 ```
 1.0:1.0:10.0
@@ -198,15 +198,15 @@ lookup(ds, :X).data
 The data for one variables, i.e. `var1` can be accessed via:
 
 ```julia
-ds[Variable=At("var1")]
+ds[Variables=At("var1")]
 ```
 ```
 ╭──────────────────────────────╮
 │ 20×10×15 YAXArray{Float64,3} │
 ├──────────────────────────────┴────────────────────────────────────────────── dims ┐
   ↓ time Sampled{Float64} 1.0:1.0:20.0 ForwardOrdered Regular Points,
-  → X    Sampled{Float64} 1.0:1.0:10.0 ForwardOrdered Regular Points,
-  ↗ Y    Sampled{Float64} 1.0:0.2857142857142857:5.0 ForwardOrdered Regular Points
+  → lon  Sampled{Float64} 1.0:1.0:10.0 ForwardOrdered Regular Points,
+  ↗ lat  Sampled{Float64} 1.0:0.2857142857142857:5.0 ForwardOrdered Regular Points
 ├───────────────────────────────────────────────────────────────────────── metadata ┤
   Dict{String, String} with 5 entries:
   "var1" => "one of your variables"

docs/src/UserGuide/combine.md

@@ -31,6 +31,6 @@ using YAXArrays: YAXArrays as YAX
 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"])
+var_axis = Variables(["temp", "prep"])
 combined = concatenatecubes(cubes, var_axis)
 ````

docs/src/UserGuide/compute.md

@@ -132,23 +132,23 @@ 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(lon(range(1, 15)))
-lat = YAXArray(lat(range(1, 10)))
+lon_yax = YAXArray(lon(range(1, 15)))
+lat_yax = 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(YAX.time(tspan))
+time_yax = YAXArray(YAX.time(tspan))
 ````
 
 note that the following can be extended to arbitrary `YAXArrays` with additional data and dimensions.
 
 Let's generate a new `cube` using `mapCube` and saving the output directly into disk.
 
 ````@ansi mapCube
-gen_cube = mapCube(g, (lon, lat, time);
+gen_cube = mapCube(g, (lon_yax, lat_yax, time_yax);
     indims = (InDims(), InDims(), InDims("time")),
     outdims = OutDims("time", overwrite=true, path="my_gen_cube.zarr", backend=:zarr,
     outtype = Float32)
@@ -172,7 +172,7 @@ gen_cube.data[1, :, :]
 but, we can generate a another cube with a different `output order` as follows
 
 ````@ansi mapCube
-gen_cube = mapCube(g, (lon, lat, time);
+gen_cube = mapCube(g, (lon_yax, lat_yax, time_yax);
     indims = (InDims("lon"), InDims(), InDims()),
     outdims = OutDims("lon", overwrite=true, path="my_gen_cube.zarr", backend=:zarr,
     outtype = Float32)
@@ -209,7 +209,7 @@ axlist = (
     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"])
+    Variables(["a", "b"])
 )
 
 Random.seed!(123)

docs/src/UserGuide/faq.md

@@ -338,7 +338,7 @@ 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) = (YAX.time(timestamp(ta)), Dim{:variable}(colnames(ta)), );
+getTArrayAxes(ta::TimeArray) = (YAX.time(timestamp(ta)), Variables(colnames(ta)), );
 nothing # hide
 ````
 then, we create the `YAXArrays` as

docs/src/get_started.md

@@ -28,14 +28,12 @@ a = YAXArray(rand(2,3))
 Assemble a more complex `YAXArray` with 4 dimensions, i.e. time, x, y and a variable type:
 
 ```@example quickstart
-using DimensionalData
-
 # axes or dimensions with name and tick values
 axlist = (
     YAX.time(range(1, 20, length=20)),
-    X(range(1, 10, length=10)),
-    Y(range(1, 5, length=15)),
-    Dim{:variable}(["temperature", "precipitation"])
+    lon(range(1, 10, length=10)),
+    lat(range(1, 5, length=15)),
+    Variables(["temperature", "precipitation"])
 )
 
 # the actual data matching the dimensions defined in axlist
@@ -54,7 +52,7 @@ a2 = YAXArray(axlist, data, props)
 Get the temperature map at the first point in time:
 
 ```@example quickstart
-a2[variable=At("temperature"), time=1].data
+a2[Variables=At("temperature"), time=1].data
 ```
 
 ## Updates