NEWS

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nestedscales 0.2.0 (2026-11-03)

Breaking changes

• from and to are now source and target everywhere: the frame arguments of recast_scale(), recast_crosswalk(), recast_to_atoms(), recast_from_atoms(), reconcile_scale(), recast_product() and the navigation functions, the scale arguments and label columns of scale_map(), scale_map_between() and their registry, and the columns of scale_atom_pairs(). recast() takes the scale as scale and the source frame as source. The crosswalk columns n_from and w_from are unchanged. No deprecation aliases.
• clear_scale_rules(), clear_scale_maps() and clear_scale_distances() take name (and scope where it applies); clear_scale_maps() can now remove named keys.
• The backend helpers .ms_* are now the backend_* functions: backend_of() (errors on an unsupported input), backend_is_lazy(), backend_schema(), backend_lazy(), backend_pull(), backend_restore() and backend_bind_rows(), plus the new backend_scan() and backend_distinct(). They are documented together under ?backend.

New features

• Member attributes and aliases. A scale carries two optional long tables keyed by (frame, unit): attributes (a value with its kind, bounds, unit_of_measure, source and note) and aliases (alternative labels). scale_from_leaftable() takes them as attributes= and aliases=; attach_attributes_scale() and attach_aliases_scale() append rows and never overwrite; scale_attributes() reads them, resolved along the hierarchy when a frame is given; scale_aliases() and scale_match() resolve labels exactly and report ambiguity. convert_scale() converts value columns row by row with a resolved attribute: a property is invertible, a factor is one-way (SCALE_ATTRIBUTE_KINDS). Both tables survive filter_scale(), [, prune_scale() and clustering, which now keep a subclass as well; scale_payload_collapse() is the hook a subclass with a positional payload overrides for prune_scale(). Objects saved by 0.1.x load unchanged.
• Definition files. write_scale() and read_scale() exchange a scale as a language-neutral definition: a JSON header with the tables inline, or a <name>.scale/ bundle with Arrow IPC or CSV tables; YAML is accepted as input and as an output option. scale_write_payload(), scale_read_payload() and register_scale_class() let a dimension package store and restore its subclass.
• Catalogue. register_scale_dir(), list_scale_dirs(), clear_scale_dirs() and scale_catalog() list the definitions shipped by installed packages; read_scale(id) takes a catalogue id.
• Shipped definition carriers: 71 fuels in group > carrier > fuel from the energypal taxonomy, with the IPCC 2006 default net calorific values and CO2 emission factors as attributes and energypal's spellings and model commodity codes as aliases (?shipped_scales). The IPCC tables ship as inst/extdata/ipcc2006_fuel_defaults.csv.
• write_scale_dataset() writes _scales/manifest.json; a legacy manifest.yaml is still read. jsonlite is a new import.

Documentation

• New vignettes: vignette("anatomy") (the object, its tables and what the validator guarantees) and vignette("attributes") (attributes, aliases and conversion on the shipped carriers). The article Fuels, regions and months on the package site joins a fuel scale, a GeoScale and a Calendar on one table.

nestedscales 0.1.1

• write_scale_dataset() now falls back to uncompressed Arrow IPC files, with a warning, when the requested compression codec is unavailable in the installed Arrow build.

nestedscales 0.1.0

• First release. nestedscales is the dimension-agnostic core under timescales and geoscales: their Calendar and Geoscale classes are subclasses of its NestedScale, so every verb below works on calendars and region hierarchies as well as on any other dimension.

Scales

• A NestedScale is a flat table of atoms plus the ordered frames that group them. Build one with scale_from_leaftable(); read it with scale_frames(), scale_units(), scale_key(), scale_leaftable(), scale_weights(), scale_rank() and scale_atom_level().
• Frames may cross-cut, and memberships may be partial (NA). The atoms may be the codes of the finest frame or, as for a calendar, combinations of frames held in the key column.
• scale_family(), scale_ancestry(), scale_nests(), scale_children(), scale_parents(), scale_descendants() and scale_ancestors() navigate the hierarchy; scale_share() and scale_coverage() report weights.
• Frames need not nest. scale_nests(), scale_crosses() and scale_is_uniform() report the structure a pair of frames (or one frame) actually has, computed from the atoms; the order of frames is the convention the direction-dependent rules (share, residuals, reconciliation) follow.
• filter_scale() (or x[frame, unit]) and prune_scale() subset and collapse a scale, recording the result's coverage of the original.
• scale_class(), scale_is() and their product counterparts stand in for the classes, which are not exported; the package's surface is its functions.

Conversion

• recast_scale() converts data between resolutions in either direction with the rules sum, weighted_mean, mean, copy, sd, share and logshare (SCALE_RULES), one per value column if needed. Other columns are kept as identifiers.
• recast_to_atoms() and recast_from_atoms() are the two halves of the route, and recast between two scales that share atom keys.
• recast_crosswalk() runs the same engine over a crosswalk built elsewhere, such as timescales' mapping of one calendar onto another.
• recast() is the S7 generic that timescales and geoscales extend, so one pipeline can recast time and space in turn.
• scale_map(x, from, to) returns the crosswalk between two frames of a scale and scale_map_between(from, to) the one between two scales; register_scale_map() / register_scale_map_between() and register_scale_rule() record exact crosswalks and per-column rules. A value column without a rule is an error, never a guess.
• join_scale() attaches a scale's labels, coarser frames (attach =), shares and weights to a dataset.
• Declared residuals (scale_from_leaftable(residuals = ), scale_residuals()) aggregate upward but never receive a share when a coarse value is split. reconcile_scale() compares aggregated data with an independent total and can balance the gap.

Data backends and large data

• Every verb accepts a data.frame, tibble, data.table, dtplyr table or arrow table/dataset, and returns the same class. Lazy inputs return a query unless collect = TRUE.
• A target whose sources are only partly present comes back NA; missing_sources = "ignore" aggregates whatever is there instead.
• diagnostics = controls the checks that scan the data (off by default for lazy inputs); batch = and batch_by = process a job in chunks of identifier values.

Products of scales

• scale_product() combines several scales (time x space, ...) into one multi-index without building its atoms. product_size(), product_keys(), product_frames(), product_weights(), product_coverage() and scale_axes() describe it; product_atoms() realises the grid on request.
• recast_product() converts any subset of the axes in one call, with rules per value column and axis. join_product() and filter_product() work axis by axis.

Clustering

• cluster_scale() groups units by their data (k-medoids, hierarchical or k-means) and returns the scale with the clusters as a new frame, so the rest of the package applies to them directly.
• cluster_contiguous() keeps clusters contiguous in order or in an adjacency graph; cluster_medoids() returns representative units; cluster_sweep() reports cluster quality across a range of k.
• scale_distance() and its registry (SCALE_DISTANCES, register_scale_distance()) supply level and shape distances.

Arrays and storage

• as_scale_array() and as_scale_table() convert between long data and a dense array over a scale or product.
• write_scale_dataset(), open_scale_dataset() and scale_dataset_info() store data as a partitioned Arrow dataset together with its scales, so it reopens ready to recast.

Building a dimension package

• vignette("nestedscales") introduces the representation and the main functions; the package website includes a roadmap of what the package offers and what is planned.
• A dimension package defines a NestedScale subclass, as timescales and geoscales do. scale_alias_property() gives an inherited property the dimension's own name; scale_vocab() puts the dimension's words in error messages; scale_payload_slice() keeps per-atom data (such as geometry) in step when rows are subset; scale_atom_pairs() lets a dimension generate its atom layer.
• .ms_backend() and the other .ms_* helpers provide the backend handling to packages built on nestedscales.