The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
First release of the R package. The repository now holds three
packages that follow one specification (docs/algorithm.md)
and pass one conformance suite (conformance/): the R
package cldreducer at the repository root, the Python
package cld-reducer in python/, and the
JavaScript package cld-reducer in js/. All
three solve the problem with HiGHS and return the same display for the
same input.
reduce_letters() reduces a compact letter display from
pairwise comparisons, and reduce_from_adjacency() does the
same from a matrix of non-significant pairs. Both return a
cld_reduction object with print() and
as.data.frame() methods.piepho2004_wheat,
simple_abc_pairs, and simple_abc_means.cld-reducer in js/, built
on HiGHS compiled to WebAssembly: reduceLetters(),
reduceFromAdjacency(), loadSolver(), and the
error classes CldReducerError,
InvalidInputError, and SolverError. Group
means must be a Map or an array of
{ group, mean }; a plain object is rejected.Preserve exact CSV labels, including leading zeros, NA-like text, and empty strings.
Preserve mixed numeric labels in lists of pair rows and means mappings.
Use one means-column rule for group order and values.
Report uneven adjacency rows as InvalidInputError
with the square-matrix message.
The package moved to python/. The import name
cld_reducer, the public names, the exceptions, and the
cld-reduce command with its flags are unchanged. Installing
from a git URL now needs #subdirectory=python:
pip install "git+https://github.com/aigorahub/cld-reducer.git#subdirectory=python".
The solver is HiGHS through highspy. The
dependencies are highspy, numpy, and
pandas; scipy and networkx are
gone.
Canonical tie-break. Many inputs have several displays with the same, smallest number of assignments (the Piepho 2004 wheat example has 64). The package now returns one fixed display: among all minimal displays, the one whose membership vector is lexicographically greatest in the order of the specification. The result no longer depends on which optimum the solver finds first, so R, Python, and JavaScript agree. For inputs with several minimal displays this can differ from version 0.1.0.
Canonical clique order. Maximal cliques are now
ordered by their sorted group indices, where 0.1.0 used the order of
NetworkX. This order breaks ties between letters, so the letters can be
renamed even for inputs that have only one minimal display. Example:
five groups numbered 0 to 4, no means, and non-significant pairs 01, 02,
03, 04, 14, 24 have one minimal display; group 3 had A in
0.1.0 and has C now.
stats["reduction_pct"] is not rounded any more;
print it with the format you need. The example scripts print one
decimal.
stats["solver_status"] is the text
Optimal, and stats["objective"] is a whole
number.
time_limit is one time budget for all solves of a
call. Each solve gets the time that is left.
Group means must be finite numbers; a missing, infinite, or
non-numeric mean is an InvalidInputError.
A missing group label (None, NaN,
pd.NA, or pd.NaT) is an
InvalidInputError, in the comparisons, the groups, and the
means.
Means with a repeated group label are an
InvalidInputError for reduce_from_adjacency()
too.
Significance text is trimmed of spaces, tabs, carriage returns, and line feeds only. Other white space, such as a no-break space, makes the value invalid.
An empty list of comparisons is a table with zero rows, so the groups come from the means.
A solver value that is not within 1e-6 of 0 or 1 is a
SolverError, also when the value is a whole
number.
These 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.