landgraph 0.0.4
- Documentation now matches terradish.
nu is an
effective-information value that the user supplies, not a SNP, locus, or
feature count. The help for cov_from_biallelic() explains
the count-standardized scale and why terradish divides by
N[1] only with equal sample sizes. The help and the
vignette describe the "gower" default for
diagonal and how missing data and NA coding
are handled.
dist_from_cov() keeps the dimnames of its input and
drops every attribute except diagonal and
centered, so terradish can still flag a
"within" diagonal.
fst_from_biallelic() names its result by
rownames(Y) and accepts N in any form accepted
by cov_from_biallelic(). A locus-length N
vector was previously recycled down the columns and misaligned; that
case now gives different (correct) values. No other results change.
dist_from_biallelic() gains N = NULL and
passes ... to cov_from_biallelic().
deme_graph() requires k to be a single
positive whole number for neighbours = "knn", and documents
its coords element.
deme_graph() objects are no longer described as
interchangeable with terradish fitting graphs, and
edge_gradient() no longer cites a terradish directed model
that does not exist.
- DESCRIPTION cites the implemented methods, and
citation("landgraph") reports the installed version.
landgraph 0.0.3
- Default to the Gower diagonal for grouped genetic covariance. This
preserves site centering and avoids mixing covariance and
within-population variance scales. Explicit within and legacy auto
choices remain available.
landgraph 0.0.2
- Record covariance diagonal construction and centering metadata
without changing numerical values. Distinguish pooled allele-frequency
centering with unequal sample sizes and centering before diagonal
replacement.
- Clarify rare-variant weighting, unequal sampling variance, and the
use of Gower covariances for Wishart models. FST ratio estimates are not
Wishart responses.
landgraph 0.0.1
- Initial release. Shared landscape-genetic primitives extracted from
terradish so that landscape-genetic network methods stand on a common,
dependency-light base.
- Graph:
deme_graph() builds a lightweight deme/landscape
graph (vertex coordinates + undirected edge list) from coordinates, with
Delaunay, k-nearest- neighbor, or lattice (rook/queen) adjacency. The
result is class c("landgraph", "terradish_graph").
- Genetic covariance / distance:
cov_from_biallelic(),
cov_from_genetic_data(), fst_from_biallelic(),
dist_from_cov(), dist_from_biallelic().
- Directional edge covariates:
edge_gradient() (gradient
of a scalar potential) and edge_flow() (projection of a
vector flow field, carrying a curl component).
cov_from_biallelic() applies the per-locus pooled
frequency correctly per column (fixes a column-major recycling error
that affected multi-deme covariances).