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Author: sethaxen

src/convert_dataset.jl

@@ -4,7 +4,7 @@ Base.convert(::Type{Dataset}, obj::Dataset) = obj
 """
     convert_to_dataset(obj; group = :posterior, kwargs...) -> Dataset
 
-Convert a supported object to a `Dataset`.
+Convert a supported object to a [`Dataset`](@ref).
 
 In most cases, this function calls [`convert_to_inference_data`](@ref) and returns the
 corresponding `group`.

src/convert_inference_data.jl

@@ -1,7 +1,7 @@
 """
     convert(::Type{InferenceData}, obj)
 
-Convert `obj` to an `InferenceData`.
+Convert `obj` to an [`InferenceData`](@ref).
 
 `obj` can be any type for which [`convert_to_inference_data`](@ref) is defined.
 """
@@ -23,7 +23,7 @@ See [`convert_to_dataset`](@ref)
 # Arguments
 
   - `obj` can be many objects. Basic supported types are:
-    
+
       + [`InferenceData`](@ref): return unchanged
       + [`Dataset`](@ref)/`DimensionalData.AbstractDimStack`: add to `InferenceData` as the only
         group
@@ -40,7 +40,7 @@ More specific types may be documented separately.
 
   - `dims`: a collection mapping variable names to collections of objects containing
     dimension names. Acceptable such objects are:
-    
+
       + `Symbol`: dimension name
       + `Type{<:DimensionsionalData.Dimension}`: dimension type
       + `DimensionsionalData.Dimension`: dimension, potentially with indices

src/dataset.jl

@@ -4,7 +4,7 @@
 Container of dimensional arrays sharing some dimensions.
 
 This type is an
-[`DimensionalData.AbstractDimStack`](https://rafaqz.github.io/DimensionalData.jl/stable/reference/#DimensionalData.AbstractDimStack)
+[`DimensionalData.AbstractDimStack`](https://rafaqz.github.io/DimensionalData.jl/stable/stacks)
 that implements the same interface as `DimensionalData.DimStack` and has identical usage.
 
 When a `Dataset` is passed to Python, it is converted to an `xarray.Dataset` without copying
@@ -64,8 +64,8 @@ Any non-array values will be converted to a 0-dimensional array.
     dataset, in addition to defaults. Values should be JSON serializable.
   - `library::Union{String,Module}`: library used for performing inference. Will be attached
     to the `attrs` metadata.
-  - `dims`: a collection mapping variable names to collections of objects containing dimension
-    names. Acceptable such objects are:
+  - `dims`: a collection mapping variable names to collections of objects containing
+    dimension names. Acceptable such objects are:
       + `Symbol`: dimension name
       + `Type{<:DimensionsionalData.Dimension}`: dimension type
       + `DimensionsionalData.Dimension`: dimension, potentially with indices

src/from_dict.jl

@@ -1,7 +1,7 @@
 """
     from_dict(posterior::AbstractDict; kwargs...) -> InferenceData
 
-Convert a `Dict` to an `InferenceData`.
+Convert a dictionary to an [`InferenceData`](@ref).
 
 # Arguments
 
@@ -62,8 +62,9 @@ end
 """
     convert_to_inference_data(obj::AbstractDict; kwargs...) -> InferenceData
 
-Convert `obj` to an [`InferenceData`](@ref). See [`from_namedtuple`](@ref) for a description
-of `obj` possibilities and `kwargs`.
+Convert a dictionary to an [`InferenceData`](@ref).
+
+See [`from_dict`](@ref) for a description of `obj` possibilities and `kwargs`.
 """
 function convert_to_inference_data(data::AbstractDict; group=:posterior, kwargs...)
     group = Symbol(group)

src/from_namedtuple.jl

@@ -10,7 +10,7 @@
         kwargs...
     ) -> InferenceData
 
-Convert a `NamedTuple` or container of `NamedTuple`s to an `InferenceData`.
+Convert a `NamedTuple` or container of `NamedTuple`s to an [`InferenceData`](@ref).
 
 If containers are passed, they are flattened into a single `NamedTuple` with array elements
 whose first dimensions correspond to the dimensions of the containers.

src/inference_data.jl

@@ -17,8 +17,8 @@ Construct an inference data from either a `NamedTuple` or keyword arguments of g
 
 Groups must be [`Dataset`](@ref) objects.
 
-Instead of directly creating an `InferenceData`, use the exported `from_xyz` functions or
-[`convert_to_inference_data`](@ref).
+Instead of directly creating an [`InferenceData`](@ref), use the exported `from_xyz`
+functions or [`convert_to_inference_data`](@ref).
 """
 struct InferenceData{group_names,group_types<:Tuple{Vararg{Dataset}}}
     groups::NamedTuple{group_names,group_types}
@@ -57,10 +57,13 @@ Base.getproperty(data::InferenceData, k::Symbol) = getproperty(parent(data), k)
     Base.getindex(data::InferenceData, groups::Symbol; coords...) -> Dataset
     Base.getindex(data::InferenceData, groups; coords...) -> InferenceData
 
-Return a new `InferenceData` containing the specified groups sliced to the specified coords.
+Return a new [`InferenceData`](@ref) containing the specified groups sliced to the
+specified `coords`.
 
-`coords` specifies a dimension name mapping to an index, a `DimensionalData.Selector`, or
-an `IntervalSets.AbstractInterval`.
+`coords` specifies a dimension name mapping to an index, a
+[`DimensionalData.Selector`](https://rafaqz.github.io/DimensionalData.jl/stable/selectors),
+or an
+[`IntervalSets.AbstractInterval`](https://juliamath.github.io/IntervalSets.jl/stable/api/#IntervalSets.AbstractInterval).
 
 If one or more groups lack the specified dimension, a warning is raised but can be ignored.
 All groups that contain the dimension must also contain the specified indices, or an
@@ -116,8 +119,8 @@ with metadata Dict{String, Any} with 1 entry:
   "created_at" => "2022-08-11T11:15:21.4"
 ```
 
-Select data from just the posterior, returning a `Dataset` if the indices index more than
-one element from any of the variables:
+Select data from just the posterior, returning a [`Dataset`](@ref) if the indices index more
+than one element from any of the variables:
 
 ```@repl getindex
 julia> idata[:observed_data, id=At(["a"])]
@@ -164,7 +167,7 @@ end
 """
     Base.setindex(data::InferenceData, group::Dataset, name::Symbol) -> InferenceData
 
-Create a new `InferenceData` containing the `group` with the specified `name`.
+Create a new [`InferenceData`](@ref) containing the `group` with the specified `name`.
 
 If a group with `name` is already in `data`, it is replaced.
 """

src/io.jl

@@ -3,7 +3,7 @@
 
 Load an [`InferenceData`](@ref) from an unopened NetCDF file.
 
-Remaining `kwargs` are passed to [`NCDatasets.NCDataset`](https://alexander-barth.github.io/NCDatasets.jl/stable/dataset/#NCDatasets.NCDataset).
+Remaining `kwargs` are passed to [`NCDatasets.NCDataset`](@extref).
 This method loads data eagerly. To instead load data lazily, pass an opened `NCDataset` to
 `from_netcdf`.
 
@@ -71,8 +71,7 @@ Write `data` to a NetCDF file.
 group the data represents.
 
 `dest` specifies either the path to the NetCDF file or an opened NetCDF file.
-If `dest` is a path, remaining `kwargs` are passed to
-[`NCDatasets.NCDataset`](https://alexander-barth.github.io/NCDatasets.jl/stable/dataset/#NCDatasets.NCDataset).
+If `dest` is a path, remaining `kwargs` are passed to [`NCDatasets.NCDataset`](@extref).
 
 !!! note
     This method requires that NCDatasets is loaded before it can be used.