Dataset

Dataset{K,T,N,L} <: DimensionalData.AbstractDimStack{K,T,N,L}

Container of dimensional arrays sharing some dimensions.

This type is an DimensionalData.AbstractDimStack that implements the same interface as DimensionalData.DimStack and has identical usage.

Constructors

Dataset(data::DimensionalData.AbstractDimArray...)
Dataset(data::Tuple{Vararg{<:DimensionalData.AbstractDimArray}})
Dataset(data::NamedTuple{Keys,Vararg{<:DimensionalData.AbstractDimArray}})
Dataset(
    data::NamedTuple,
    dims::Tuple{Vararg{DimensionalData.Dimension}};
    metadata=DimensionalData.NoMetadata(),
)

In most cases, use convert_to_dataset to create a Dataset instead of directly using a constructor.

convert_to_dataset(obj; group = :posterior, kwargs...) -> Dataset

Convert a supported object to a Dataset.

In most cases, this function calls convert_to_inference_data and returns the corresponding group.

namedtuple_to_dataset(data; kwargs...) -> Dataset

Convert NamedTuple mapping variable names to arrays to a Dataset.

Any non-array values will be converted to a 0-dimensional array.

Keywords

• attrs::AbstractDict{<:AbstractString}: a collection of metadata to attach to the 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:
  • Symbol: dimension name
  • Type{<:DimensionsionalData.Dimension}: dimension type
  • DimensionsionalData.Dimension: dimension, potentially with indices
  • Nothing: no dimension name provided, dimension name is automatically generated
• coords: a collection indexable by dimension name specifying the indices of the given dimension. If indices for a dimension in dims are provided, they are used even if the dimension contains its own indices. If a dimension is missing, its indices are automatically generated.