cooccure 0.1.1
- First CRAN release. Package renamed from
cooccur
(GitHub-only development name) to cooccure to avoid
collision with an unrelated archived CRAN package of the same name.
- Internal engine rewritten on top of
Matrix::sparseMatrix / Matrix::crossprod. The
previous implementation allocated dense n x k and
k x k matrices, which hit R’s vector memory limit on
corpora with many documents and items (e.g. citation networks > ~100k
unique references). The sparse rewrite stays in triplet form end-to-end
and scales linearly with the number of non-zero co-occurrences.
attr(x, "matrix") and
attr(x, "raw_matrix") are now sparse Matrix objects.
as_matrix() densifies them on demand so existing downstream
code keeps working.- Added
Matrix to Imports.
- Delimited parsers (
.co_parse_delimited,
.co_parse_multi_delimited) vectorised:
trimws(), NA/empty filtering, and per-row deduplication now
run as single C-level calls over the flattened token vector rather than
as per-row R calls. Cuts overall runtime on a 166k-row x
20-items-per-row citation corpus from ~6.2 s to ~3.4 s (~1.8x
faster).
cooccure 0.1.0
- Initial development release (distributed as
cooccur on
GitHub).
cooccurrence() (alias co()) builds
co-occurrence networks from six input formats: delimited fields,
multi-column delimited, long/bipartite, binary matrices, wide sequences
(field = "all"), and lists of character vectors.- Eight similarity measures:
none, jaccard,
cosine, inclusion, association,
dice, equivalence, relative.
- Eight scaling methods:
minmax, log,
log10, binary, zscore,
sqrt, proportion, none.
counting = "fractional" implements the
Perianes-Rodriguez et al.
- weighted pair count.
weight_by parameter supports weighted long-format input
(e.g. LDA topic-document probabilities).split_by computes a separate network per group and
returns a combined edge data frame.output argument returns edges in default, Gephi,
igraph, cograph, or matrix form.- S3 converters:
as_matrix(), as_igraph(),
as_tidygraph(), as_cograph(),
as_netobject().
- Shiny app accessible via
launch_app().