Compare ⋅ arviz-devs/ArviZ.jl

        :predictions_constant_data => predictions_constant_data,
    ]
        group_data === nothing && continue
        group_dict = convert(Dict, group_data)
        group_dataset =
            convert_to_constant_dataset(group_dict; library = library, kwargs...)
            convert_to_constant_dataset(group_data; library = library, kwargs...)
        concat!(all_idata, InferenceData(; group => group_dataset))
    end


@@ -28,7 +28,7 @@

Loading

    end
end

Dataset(; kwargs...) = xarray.Dataset(; kwargs...)
Dataset(; kwargs...) = Dataset(xarray.Dataset(; kwargs...))
@inline Dataset(data::Dataset) = data

@inline PyObject(data::Dataset) = getfield(data, :o)

@@ -116,25 +116,27 @@

Loading

    library = nothing,
    attrs = nothing,
)
    obj = convert(Dict, obj)
    base = arviz.data.base
    coords = coords === nothing ? Dict{String,Vector}() : coords
    dims = dims === nothing ? Dict{String,Vector{String}}() : dims

    data = Dict{String,Any}()
    obj = _asstringkeydict(obj)
    coords = _asstringkeydict(coords)
    dims = _asstringkeydict(dims)
    attrs = _asstringkeydict(attrs)

    data = Dict{String,PyObject}()
    for (key, vals) in obj
        vals = _asarray(vals)
        val_dims = get(dims, key, nothing)
        (val_dims, val_coords) =
            base.generate_dims_coords(size(vals), key; dims = val_dims, coords = coords)
        data[string(key)] = xarray.DataArray(vals; dims = val_dims, coords = val_coords)
        data[key] = xarray.DataArray(vals; dims = val_dims, coords = val_coords)
    end

    default_attrs = base.make_attrs()
    if library !== nothing
        default_attrs = merge(default_attrs, Dict("inference_library" => string(library)))
    end
    attrs = attrs === nothing ? default_attrs : merge(default_attrs, attrs)
    attrs = merge(default_attrs, attrs)
    return Dataset(data_vars = data, coords = coords, attrs = attrs)
end


@@ -175,6 +175,10 @@

Loading

@inline _asarray(x) = [x]
@inline _asarray(x::AbstractArray) = x

_asstringkeydict(x) = Dict(String(k) => v for (k, v) in pairs(x))
_asstringkeydict(x::Dict{String}) = x
_asstringkeydict(::Nothing) = Dict{String,Any}()

function enforce_stat_types(dict)
    return Dict(k => get(sample_stats_types, k, eltype(v)).(v) for (k, v) in dict)
end

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88.13% 100.00% +0.07%

Handle mixtures of NamedTuple and Dict for constant datasets better (#97)

sethaxen

9c3a89a

CI Passed

+3

88.06% 25.00% +0.35%

Fixes to auto-installation using pip (#95)

sethaxen

b458349

CI Passed

Files		•	•	•	Coverage
src	+3	+3	ø	ø	^0.07% 88.13%
Project Totals (13 files)	539	475	0	64	88.13%

257	257		:predictions_constant_data => predictions_constant_data,
258	258		]
259	259		group_data === nothing && continue
260		-	group_dict = convert(Dict, group_data)
261	260		group_dataset =
262		-	convert_to_constant_dataset(group_dict; library = library, kwargs...)
	261	+	convert_to_constant_dataset(group_data; library = library, kwargs...)
263	262		concat!(all_idata, InferenceData(; group => group_dataset))
264	263		end
265	264

116	116		library = nothing,
117	117		attrs = nothing,
118	118		)
119		-	obj = convert(Dict, obj)
120	119		base = arviz.data.base
121		-	coords = coords === nothing ? Dict{String,Vector}() : coords
122		-	dims = dims === nothing ? Dict{String,Vector{String}}() : dims
123	120
124		-	data = Dict{String,Any}()
	121	+	obj = _asstringkeydict(obj)
	122	+	coords = _asstringkeydict(coords)
	123	+	dims = _asstringkeydict(dims)
	124	+	attrs = _asstringkeydict(attrs)
	125	+
	126	+	data = Dict{String,PyObject}()
125	127		for (key, vals) in obj
126	128		vals = _asarray(vals)
127	129		val_dims = get(dims, key, nothing)
128	130		(val_dims, val_coords) =
129	131		base.generate_dims_coords(size(vals), key; dims = val_dims, coords = coords)
130		-	data[string(key)] = xarray.DataArray(vals; dims = val_dims, coords = val_coords)
	132	+	data[key] = xarray.DataArray(vals; dims = val_dims, coords = val_coords)
131	133		end
132	134
133	135		default_attrs = base.make_attrs()
134	136		if library !== nothing
135	137		default_attrs = merge(default_attrs, Dict("inference_library" => string(library)))
136	138		end
137		-	attrs = attrs === nothing ? default_attrs : merge(default_attrs, attrs)
	139	+	attrs = merge(default_attrs, attrs)
138	140		return Dataset(data_vars = data, coords = coords, attrs = attrs)
139	141		end
140	142

175	175		@inline _asarray(x) = [x]
176	176		@inline _asarray(x::AbstractArray) = x
177	177
	178	+	_asstringkeydict(x) = Dict(String(k) => v for (k, v) in pairs(x))
	179	+	_asstringkeydict(x::Dict{String}) = x
	180	+	_asstringkeydict(::Nothing) = Dict{String,Any}()
	181	+
178	182		function enforce_stat_types(dict)
179	183		return Dict(k => get(sample_stats_types, k, eltype(v)).(v) for (k, v) in dict)
180	184		end

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28	28		end
29	29		end
30	30
31		-	Dataset(; kwargs...) = xarray.Dataset(; kwargs...)
	31	+	Dataset(; kwargs...) = Dataset(xarray.Dataset(; kwargs...))
32	32		@inline Dataset(data::Dataset) = data
33	33
34	34		@inline PyObject(data::Dataset) = getfield(data, :o)

Compare b458349 ... +0 ... 9c3a89a

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2 Commits

Compare `b458349 ... +0 ... 9c3a89a`