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This release fixes a number of bugs, rewrites the blockmodeling
algorithms and speeds up several functions considerably. Results of
signed_blockmodel() and
signed_blockmodel_general() differ from earlier versions
(see below).
as_adj_complex() now respects the attr
argument and works with named vertices. This also fixes
laplacian_matrix_complex(),
as_incidence_complex() and complex_walks() for
attributes other than "type".laplacian_matrix_signed(sparse = TRUE) no longer
errors. Normalized Laplacians (signed and complex) no longer return
NaN for isolated vertices.sample_islands_signed() always returns
islands.n * islands.size vertices (previously failed when
the highest-numbered vertices had no edges).balance_score(method = "walk") no longer overflows to
NaN on dense networks.
balance_score(method = "triangles") returns NA
for networks without triangles.triad_census_signed() returns the census in canonical
order.eigen_centrality_signed() returns a real vector for
directed networks (or errors if the dominant eigenvalue is
complex).ggblock() colors ties correctly if only one sign is
present. ggsigned(type = "complex") now uses
attr for edge colors and no longer overwrites the
type attribute.as_signed_proj() handles vertex names containing
"-", "pos" or "neg".complex_walks() validates k.signed_blockmodel_general() returned a membership that
did not match the reported criterion, and a wrong (even negative)
criterion for alpha != 0.5. The meaning of
alpha now matches signed_blockmodel().signed_blockmodel(annealing = FALSE) no longer returns
the random initial partition for networks with large blocks, and it
always takes the best improving move.signed_blockmodel() and
signed_blockmodel_general() validate k,
alpha and blockmat (square, symmetric for
undirected networks).attr argument of igraph. Values of
multiple edges are still summed.data-raw/triad_tables.R).src/Makevars.sample_gnp_signed() and
sample_bipartite_signed() validate p_neg.ggblock(), ggsigned()
and frustration_exact().count_signed_triangles(),
signed_triangles() and
count_complex_triangles() are vectorized (several hundred
times faster on networks with many triangles).as_incidence_complex() and degree_signed()
are vectorized and use sparse matrices. complex_walks() is
about twice as fast.graph_circular_signed() computes arc lengths directly
from the sampled angles, which also avoids NaNs from
rounding errors.signed_blockmodel(annealing = TRUE) no longer uses
stats::optim() and is about 25x faster.signed_triangles() that resulted in
wrong vertex ids (#20)frustration_exact() to vignetteis_signed,graph_from_adjacency_matrix_signed,
and graph_from_edgelist_signed()sample_gnp_signed(),
sample_bipartite_signed()frustration_exact() to compute the exact number
of frustrated edgesas_unsigned_2mode()as_signed_proj()triad_census_signed()avatar datasetcomplex_walks()pn_index()stringsAsFactors issue in
complex_matrices.RThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.