metaweave 0.4.1

Prepare the first CRAN submission with updated maintainer metadata.
Replace publication vignettes with one self-contained spatial tutorial.
Exclude repository website files from the source archive.
Document returned objects for public workflow functions.
Summaries exclude forbidden self-links when self_links = FALSE, using species identity. Unrestricted networks and plain matrices are unchanged.

metaweave 0.4.0

Adds maxent_model() for directed maximum-entropy ensembles constrained by connectance, link count, or degree sequences.
Supports directed unipartite food webs, optional self-links, locally isolated random streams, and optional retention of ensemble members.
Extends ecological_network objects with explicit directed and self_links fields.
Adds validation, unit tests, and a reproducible maximum-entropy vignette.

Renames the package and framework from rangerast to MetaWeave.
Positions the package around weaving regional ecological information into local spatial networks.
Adds probability_matrix_model() for direct use of named species-pair probability matrices, including ensemble predictions from external models.
Adds a self-contained methods and simulation vignette covering inference, spatial reconstruction, sampling error, and standardized metrics.

Generalizes bipartite inference from hard-coded palm and mammal groups to arbitrary named ecological groups.
Adds block_model() and local_block_network() as the generic block-model API.
Adds reconstruct_networks() and run_spatial_inference() as generic end-to-end workflows.
Ecological networks now record their row and column group identities.
Network summaries now expose generic row_richness and column_richness metrics.
Keeps sbm_model(), local_probability_network(), and the original downscaling wrappers for backward compatibility.
Fixes network-index construction when coordinate values carry names.

Introduces model-agnostic objects for distributions, assemblages, inference models, ecological networks, network collections, and spatial results.
Adds spatial assembly and range-rasterization utilities.
Adds the stochastic block model inference backend.
Adds simulation, network summaries, spatial mapping, and compatibility wrappers for the original downscaling workflow.