proxyC 0.5.2
Bug fixes
- Update tests to pass CRAN check with Intel MKL.
proxyC 0.5.1
Bug fixes
- Add workaround for a compilation error when clang 20 is used
(#65).
proxyC 0.5.0
New features and
improvements
- Enable
simil() nad dist() to perform
masked similarity/distance computation. If a pattern matrix is given via
the mask argument, it computes scores for selected pairs of
rows or columns. Pattern matrices can be created using newly added
mask() function.
- Calculate “dice” and “edice” using Armadillo’s linear algebra
functions in
simil(). As a result, computation of these
scores became as fast as “cosine”, “correlation” and “euclidean”.
- Add
crossprod() and tcrossprod() using the
same infrastructure as simil() and
dist().
proxyC 0.4.2
New features and
improvements
- Reduce the overhead for dense similarity matrices by improving
rounding numbers and conversion to Rcpp vectors.
- Return a dense matrix if
sparse = FALSE to save space
in RAM.
proxyC 0.4.1
Bug fixes
- Make detection of Intel oneAPI Threads Building Blocks (TBB) library
more reliable.
proxyC 0.4.0
New features and
improvements
- Use more recent Intel oneAPI Threads Building Blocks (TBB) library
to improve the stability in parallel computing.
- Add
options(proxyC.threads) to control the number of
threads in parallel computing (but
RCPP_PARALLEL_NUM_THREADS still has effect).
New system requirements
- The RcppParallel package is no longer required as the TBB library in
the operating system (Linux and MacOS) or Rtools (Windows) is used.
- Linux and MacOS must have the TBB library to enable parallel
computing before installing this package from the source.
proxyC 0.3.4
New features and
improvements
- Add “fjaccard” to
simil() for Fuzzy Jaccard similarity
(#42).
proxyC 0.3.3
New features and
improvements
- Explicitly setting
use_nan = FALSE will suppress
warnings in simil() and dist().
- Add vignettes to explain how the similarity and distance measures
are computed.
proxyC 0.3.2
Bug fixes
- Make further changes for Matrix v1.4-2.
proxyC 0.3.1
New features and
improvements
- Add “jensen” to
dist() for Jensen-Shannon divergence as
a symmetric version of Kullback-Leibler divergence.
- Change how
x and y are coerced to
dgCMatrix for Matrix v1.4-2.
proxyC 0.3.0
New features and
improvements
- Add “jeffreys” to
dist() for Jeffreys divergence. It is
a symmetric version of Kullback-Leibler divergence (#31).
proxyC 0.2.4
New features and
improvements
rowSds(), colSds(),
rowZeros() and colZeros() return row or column
names. They also work with both dense and sparse matrices (#28).
proxyC 0.2.3
Bug fixes
- Change “hamman” to “hamann” in
simil() to correct
misspelling (#26).
proxyC 0.2.2
New features
simil() and dist() work with both dense
and sparse matrices.
use_nan = TRUE can be used not only for correlation but
for all the distance and similarity measures.
proxyC 0.2.1
New features
- Computing the correlation similarity on vectors with a standard
deviation will generate a zero correlation and a warning. The warning
can be turned off by setting
use_nan = TRUE, in which case
the computed correlation similarity will be NaN instead
(#21).
Bug fixes
- Fixed infinite values being returned by the correlation similarity
(#20).
proxyC 0.2.0
New features
- Added a
diag argument to compute similarity/distance
only for corresponding rows or columns (#13).
- Added a
smooth parameter to chisquared and kullback
leibler distances to solve negative values in sparse matrices
(#15).
- Added the hamming distance (#18)
Bug fixes
- Fixed the chi-squared distance to match
stats::chisq.test() (#14).
- Fixed a bug in pairwise similarity/distance computation when
drop0 = TRUE (#17).
proxyC 0.1.5
New features
- Add the
drop0 argument to address the floating point
precision issue (#10).
Bug fixes
- The digit argument is now passed to
dist() (#11).
proxyC 0.1.4
New features
- Add
rowSds(), colSds(),
rowZeros() and colZeros() (#9).
proxyC 0.1.3
Bug fixes
- No longer assumes symmetry of resulting matrix when
x != y (#4).
New features
- Add the
digits argument to correct rounding errors in
C++ (#5).