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Changes are mostly minor, see the Changes file inside the distribution
for more details.
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py-numpy-1.22.4's symbol check mechanism does not work for NetBSD
and the other platforms, because gcc and clang calculate trivial math
functions, for example, log1pl() and expm1l(), with immediate arguments,
for example 0. So compiling 'log1pl(0)' is always successful
even if -lm is not added to the compiler's commandline arguments.
Use GNU autotools style check with ugly workaround.
I have no idea about WASM case. However current mechanism will
not work as expected.
Bump PKGREVISION.
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Changes in Version 1.8-10
o The transform() method now internally uses a list of zoo series (as opposed
to a data.frame of numeric variables, as used in previous versions). This
means that the transformations can really operate on full zoo series.
o Added MATCH() methods for classes "Date", "POSIXct", and "POSIXlt", all
of which essentially match the underlying numeric vector (suggested by
Kurt Hornik).
o In zooreg() the "ts.eps" argument is now also used (in squares) as the
tolerance in the all.equal() comparisons used to determine the underlying
regular time grid.
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1.22.4:
TYP, BUG: Fix ``np.lib.stride_tricks`` re-exported under the...
TST: Bump mypy from 0.931 to 0.940
MAINT: Explicitly re-export the types in ``numpy._typing``
MAINT: Specify sphinx, numpydoc versions for CI doc builds
BUG: Fix typos
ENH, BLD: Fix math feature detection for wasm
MAINT: Fix failing simd and cygwin tests.
MAINT: Fix failing Python 3.8 32-bit Windows test.
BUG: add linux guard
BUG: Allow legacy dtypes to cast to datetime again
BUG: Make mmap handling safer in frombuffer
BUG: Stop using PyBytesObject.ob_shash deprecated in Python 3.11.
ENH: Introduce numpy.core.setup_common.NPY_CXX_FLAGS
BUG: Ensure compile errors are raised correclty
BUG: Fix segmentation fault
MAINT: Update doc requirements
MAINT: Mark ``npy_memchr`` with ``no_sanitize("alignment")`` on clang
DOC: Proposal - make the doc landing page cards more similar...
MAINT: Update Cython version to 0.29.30.
BUG: Fix GCC error during build configuration
REL: Prepare for the NumPy 1.22.4 release.
MAINT: Skip tests that fail on PyPy.
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This package dose not support php80 and php81.
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(from: inst/NEWS)
Changes in version 1.1-3 (2021-10-05)
o fix diffs reported on M1mac
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# dplyr 1.0.9
* New `rows_append()` which works like `rows_insert()` but ignores keys and
allows you to insert arbitrary rows with a guarantee that the type of `x`
won't change (#6249, thanks to @krlmlr for the implementation and @mgirlich
for the idea).
* The `rows_*()` functions no longer require that the key values in `x` uniquely
identify each row. Additionally, `rows_insert()` and `rows_delete()` no
longer require that the key values in `y` uniquely identify each row. Relaxing
this restriction should make these functions more practically useful for
data frames, and alternative backends can enforce this in other ways as needed
(i.e. through primary keys) (#5553).
* `rows_insert()` gained a new `conflict` argument allowing you greater control
over rows in `y` with keys that conflict with keys in `x`. A conflict arises
if a key in `y` already exists in `x`. By default, a conflict results in an
error, but you can now also `"ignore"` these `y` rows. This is very similar to
the `ON CONFLICT DO NOTHING` command from SQL (#5588, with helpful additions
from @mgirlich and @krlmlr).
* `rows_update()`, `rows_patch()`, and `rows_delete()` gained a new `unmatched`
argument allowing you greater control over rows in `y` with keys that are
unmatched by the keys in `x`. By default, an unmatched key results in an
error, but you can now also `"ignore"` these `y` rows (#5984, #5699).
* `rows_delete()` no longer requires that the columns of `y` be a strict subset
of `x`. Only the columns specified through `by` will be utilized from `y`,
all others will be dropped with a message.
* The `rows_*()` functions now always retain the column types of `x`. This
behavior was documented, but previously wasn't being applied correctly
(#6240).
* The `rows_*()` functions now fail elegantly if `y` is a zero column data frame
and `by` isn't specified (#6179).
# dplyr 1.0.8
* Better display of error messages thanks to rlang 1.0.0.
* `mutate(.keep = "none")` is no longer identical to `transmute()`.
`transmute()` has not been changed, and completely ignores the column ordering
of the existing data, instead relying on the ordering of expressions
supplied through `...`. `mutate(.keep = "none")` has been changed to ensure
that pre-existing columns are never moved, which aligns more closely with the
other `.keep` options (#6086).
* `filter()` forbids matrix results (#5973) and warns about data frame
results, especially data frames created from `across()` with a hint
to use `if_any()` or `if_all()`.
* `slice()` helpers (`slice_head()`, `slice_tail()`, `slice_min()`, `slice_max()`)
now accept negative values for `n` and `prop` (#5961).
* `slice()` now indicates which group produces an error (#5931).
* `cur_data()` and `cur_data_all()` don't simplify list columns in rowwise data frames (#5901).
* dplyr now uses `rlang::check_installed()` to prompt you whether to install
required packages that are missing.
* `storms` data updated to 2020 (@steveharoz, #5899).
* `coalesce()` accepts 1-D arrays (#5557).
* The deprecated `trunc_mat()` is no longer reexported from dplyr (#6141).
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Changes to Version 3.0-13
o Handle singularities better in Anova.mlm() (suggestion of Marius Barth).
o Fixed error reporting in logit() (bug reported by Collin Erickson).
o Added pt.cex and cex sub-arguments to legend argument of
scatterplotMatrix() (implicit suggestion of Duncan Mackay).
o New vif.lm() method with options for handling linear models with interactions.
o Fixed bug in cooks.distance.influence.lme() (in effect, incorrect
division by the error variance twice rather than once), and a sign
error in dfbeta.influence.lme() and dfbetas.influence.lme()
(following report by Ben Bolker).
o Added an error.df argument to the default methods of
linearHypothesis() and Anova() for computing F-tests; if the
argument is unspecified, then df.residual() is applied to the model,
and if df.residual() returns NULL or NA, then an asymptotic
chi-square test is substituted for the F-test (in response to a
report by Adrian Olszewski that Anova() fails for gls models when an
F-test is requested).
Changes to Version 3.0-12
o The 'rio` package is now suggested, not required. To use the
Import() and Export() functions users may need to install rio using
install.packages("rio")
o hccm() now reports an interpretable error, except for type = "hc0"
or "hc1", when there are cases with hatvalues = 1 (following problem
reported by Peng Ding).
o Fix bug in rownames in dfbetasPlots.lm() (reported by Shu Fai
Cheun).
o Package 'rio' was moved from Imports to Suggests. Both Import()
and Export() now check for the availability of 'rio' first and
report an error otherwise.
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# Insight 0.17.1
## New supported model classes
* `deltaMethod` (*car*), `marginaleffects`, `marginaleffects.summary`
(*marginaleffects*)
## General
* `get_predicted()` now supports models of class `iv_robust` and `ivreg`.
* For `get_predicted()`, when both `type` and `predict` are given, `type`
will overwrite `predict`. Note that this will print a message, because
`predict` is the preferred argument.
* `get_varcov()` gains `vcov` and `vcov_args` arguments, to specify the
variance-covariance matrix used to compute uncertainty estimates (e.g., for
robust standard errors).
* `get_loglikehood()` improved handling of models from package *estimator*.
## Bug fixes
* Fixed bug in `get_data()` for model objects whose data needs to be recovered
from the environment, and where the data name was a reserved word (e.g., named
like an R function).
* The matrix returned by `get_varcov()` for models of class *bife* now returns
row and column names.
* `find_offset()` did not find offset-terms for `merMod` objects when the
offset was specified as `offset` argument in the function call.
# insight 0.17.0
## Breaking changes
* Arguments `vcov_estimation` and `vcov_type` in `get_predicted()`,
`get_predicted_se()` and `get_predicted_ci()` are replaced by `vcov` and
`vcov_args`, to have a more simplified and common interface to control
robust covariance matrix estimation.
## General
* Improved performance for various functions, in particular `get_data()` and
`model_info()`.
## New functions
* To check for names: `object_has_names()` and `object_has_rownames()`
* To work with lists: `is_empty_object()` and `compact_list()`
* To work with strings: `compact_character()`
* Further utility functions are `safe_deparse()`, `trim_ws()` and `n_unique()`.
## Changes to functions
* `export_table()` now better checks for invalid values of caption and footer
for tables in HTML format, and silently removes, e.g., ansi-colour codes that
only work for text-format.
* `get_data.coxph()` returns the original data frame instead of data with type
coercion.
* `get_loglikelihood()` gets a `check_response` argument, to check if a model
has a transformed response variable (like `log()` or `sqrt()` transformation),
and if so, returns a corrected log-likelihood.
* `get_modelmatrix()` now supports *BayesFactor* models.
* `get_loglikelihood()` and `get_df()` now support more model classes.
* `get_predicted()` was improved for multinomial models from *brms*.
* `get_variance()` was improved to cover more edge cases of (more complex)
random effect structures.
* `get_data()` now includes variables in the returned data frame that were
used in the `subset` argument of regression functions (like `lm()`).
* In some edge cases, where `get_data()` is unable to retrieve the data that
was used to fit the model, now a more informative error is printed.
* `ellipses_info()` now also accepts a list of model objects, is more stable
and returns more information about the provided models (like if all fixed
or random effects are the same across models, if all models are mixed models
or null-models, etc.)
* `check_if_installed()` now works interactively and lets the user prompt
whether to automatically update or install packages.
## Bug fixes
* Fixed incorrect column name conversion in `standardize_names()` for certain
columns returned by `broom::glance()`.
* Fixed issue with correctly detecting Tweedie-models in `model_info()`.
* Fixed issue with `get_datagrid()` for *brms* models with monotonic factors.
* Fixed issue in `find_formula()` when argument `correlation` was defined
outside of `lme()` and `gls()` (@etiennebacher, #525).
* Fixed issue with `get_data()` when back-transforming data from predictors
that used `cos()`, `sin()` or `tan()` transformations.
# insight 0.16.0
## New functions
* `get_datagrid()`, to generate a reference grid, usually used when computing
adjusted predictions or marginal means from regression models.
## Changes to functions
### `get_predicted()`
* `get_predicted()` was revised. Beside the four core options for the `predict`
argument, it is now also possible to use any value that is valid for the
model's `predict()` method's `type` argument.
* `get_predicted()` now supports more models (e.g., from packages like
_GLMMadaptive_ or _survival_).
* `get_predicted()` is now more robust when calculating standard errors of
predictions.
### Other functions
* `get_statistic()` and `find_statistic()` now support *htest* objects.
## General
* Various minor improvements.
# insight 0.15.1
## General
* Improved speed performance, especially for `get_data()`.
## Changes to functions
* `get_data()` for `coxph` models now returns the original factor levels for
variables transformed with `strata()` inside formulas.
# insight 0.15.0
## Breaking changes
* Data management functions (like `reshape_longer()`, or `data_match()`) have
been moved to the *datawizard* package.
* `get_data()` no longer returns factor types for numeric variables that have
been converted to factors on-the-fly within formulas (like `y ~ as.factor(x)`).
Instead, for each numeric variable that was coerced to factor within a formula
gets a `factor` attribute (set to `TRUE`), and the returned data frame gets
a `factors` attribute including all names of affected variables.
## New supported model classes
* Support for `bfsl` (*bfsl*)
## New functions
* New `standardize_column_order()` function can be used to standardize the
column order in output dataframes.
## General
* Improved speed performance for some functions.
* Improved handling of table captions and footers in `export_table()`. See also
the new vignette on exporting data frames into human readable tables here:
https://easystats.github.io/insight/articles/export.html
* Revised `width` argument in `export_table()`, which now allows to set
different column widths across table columns. See examples in
`?export_table`.
* `export_table()` gets a `table_width` argument to split wide tables into
two parts.
* `get_varcov()` for `MixMod` (package *GLMMadaptive*) was revised, and now
allows to return a robust variance-covariance matrix.
* Added more `get_df()` methods.
## Bug fixes
* Fixed issues with manual sigma computation to handle dispersion models in
`get_sigma()`.
* Fixed issue in `find_formula()` for `BayesFactor::lmBF()` with multiple random
effects.
* Fixed issue in `get_parameters.BFBayesFactor()` with wrong sign of difference
estimate for t-tests.
* Argument `width` in `format_value()` was ignored when formatting integer
values and `protect_integers` was set to `TRUE`.
# insight 0.14.5
## New functions
* `find_transformation()` and `get_transformation()` to find or get any function
that was used to transform the response variable in a regression model.
## General
* Improved support for models of class `sampleSelection`.
* Improved documentation.
* `get_modelmatrix()` now supports: `rms::lrm`
* `get_predicted()` supports: `MASS::polr`, `MASS::rlm`, `rms::lrm`, `fixest`,
`bife::bife`, `ordinal::clm`.
* `get_predicted()` standard errors are often much faster to compute.
* `get_predicted()` supports models with "grouped" or "level" outcomes (e.g.,
multinomial logit).
* `get_predicted()` handles factors better.
* Improved documentation
## Changes to functions
* `check_if_installed()` gains a `quietly` argument, if neither stopping nor a
warning message for non-installed packages is requested.
* `get_predicted()`'s `predict` argument now accepts these values: "link",
"expectation", "prediction", "classification", or NULL.
* `get_predicted()` accepts `predict=NULL`, which allows users to push a `type`
argument through the `...` ellipsis, forward to the `predict()` method of the
modelling package.
## Bug fixes
* Fixed issue with parameter names from *emmeans* objects in
`get_parameters()`.
* Fixed issues with unknown arguments in `get_predicted()`.
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(inst/NEWS.Rd or https://cran.r-project.org/web/packages/robustbase/news.html)
NEWS R Documentation
News for R Package robustbase
CHANGES in robustbase VERSION 0.95-0 (2022-04-02, svn r894)
BUG FIXES
* huberM(x, k) now also works in small sample cases with +/-Inf, e.g. for x =
c(-Inf, 1).
NEW FEATURES
* New huberize() utility, notably by default used in mc().
* mc() now by default uses doScale=FALSE in order to guarantee convergence
also in extreme cases when used together with new c.huberize = 1e11. Both
are not back compatible but clearly better in extreme cases, as assessed by
Lukas Graz' BSc thesis. Note that the behavior of the new default doScale=
FALSE has been amended in the C code to be more compatible in its eps
checks with (the previous default) doScale=TRUE.
Lastly, a message() is printed currently, at most once per R session,
whenever mc() is called without an explicit specification of doScale=*,
alerting users to the changed default. This message can be turned off by
setting options(mc_doScale_quiet = TRUE).
* New dataset data(x30o50) as an example of potentially problematic data, not
just for mc().
Misc
* rather "truncating" +/-Inf to <large>, use NA.OK = TRUE in Qn() and Sn()'s
.C() call.
* Our C code no longer uses the DOUBLE_* constants from S, but rather
standard <float.h>.
CHANGES in robustbase VERSION 0.93-9 (2021-09-27, svn r888)
BUG FIXES
* Qn(x) and Sn(x) gain an na.rm = FALSE option and now work when x has NAs
and contains +/- Inf.
Misc
* No longer include 'Rdefines.h' as it is somewhat deprecated.
* In 'src/lmrob.c' add USE_FC_LEN_T and use FCONE rather than the older FCLEN
approach.
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This is a special case of sparse matrices, used by coxme.
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CHANGES IN VGAM VERSION 1.1-6
NEW FEATURES
o Most of the GAIT regression code have new arguments 'd.mlm'
and 'd.mix' but mainly only the dpqr-type functions work!
Some other functions should work such as gaitdpoisson() and
dgaitplot(). Also, is.deflated() and goffset() are new.
o New family function: gaitdnbinomial().
o Upgraded family functions: gaitpoisson() becomes gaitdpoisson(),
gaitlog() becomes gaitdlog(), gaitzeta() becomes gaitdzeta().
o New generic and/or methods functions: KLD(), Pheapseep().
o Some colours are pre-defined for GAITD regression, and the default
colour scheme has changed.
o trim.constraints() has a new 'intercepts = TRUE' argument.
o Many family functions have a 'dpqrfun' component in the @infos slot.
Useful to tie in the modelling function with its density, etc.
o binormal() has a new 'rho.arg' argument.
o Some link functions handle deriv = 4: e.g., loglink(), logitlink().
o vglmfit@misc$history gives the convergence history.
o Improvements to clogloglink() at the boundary 1.
o hdeff.vglm() has a new argument 'theta0'.
o wald.stat() cleaned up internally.
o Tested okay on R 4.1.2.
BUG FIXES and CHANGES
o All GAIT regression code has arguments 'alt.mlm' changed to
'a.mlm', 'inf.mix' changed to 'i.mix', etc. Colours have changed.
[dpqr]gaitpois() have been renamed to [dpqr]gaitdpois(),
and gaitpoisson() to gaitdpoisson().
o [dpqr]zanegbin() no longer supports argument 'prob'.
o hdeff() makes a recursive call if any NAs are in the answer and
fd.only == FALSE. So the answer should then be a 'proper' one.
o Code involving anova() for VGLMs/VGAMs changed to avoid an
error when loading in \pkg{semTools}.
o spikeplot(..., use.table = TRUE) failed wrt x.use and y.use.
o vcov() slightly faster for "vglm" objects. Thanks to Frank Harrell
for comments that led to this.
o linkfun.vglm() changed to linkfunvglm().
CHANGES IN VGAM VERSION 1.1-5
NEW FEATURES
o New functions: meangait(), spikeplot(), trim.constraints().
o iam(i, 1:M, M = M) now works, for selecting a whole row,
and similarly for a column.
o Tested okay on R 4.0.3.
BUG FIXES and CHANGES
o gait[log,poisson,zeta](): arguments llambda.[ai] and lshape.[ai]
equal llambda.p and lshape.p by default. This means only one
argument needs be assigned in order to change them all.
o [dpqr]genpois[12]() has argument 'mean' changed to 'meanpar'.
o gait[log,zeta]() bug fixed wrt missing 'allprobs'.
o qfoldnorm() now uses the bisection method. Thanks to
Mauricio Romero for a suggestion that led to this.
o gait[log,poisson,zeta]() compute the sandwich formula
explicitly for the working weights; this has speed gains.
Their @deriv avoids nested for() loops too.
Their initial value grids have become coarser.
o Functions moved to VGAMdata 1.1-5: yip88, bellff(dr), tikuv(dpqr).
CHANGES IN VGAM VERSION 1.1-4
NEW FEATURES
o Functions score.stat() and wald.stat() offer greater flexibility
by some new arguments, and 'as.summary' changed to 'orig.SE'.
o Influence() computes the influence functions of a "vglm" object.
o Methods functions hdeff.matrix() and hdeff.numeric() are new.
o Family function slot genpoisson()@ weight was updated with
the EIM derived by Easton Huch, and after major changes,
genpoisson() was renamed to genpoisson0().
o New functions: [dpqr]gaitnbinom(), [dpqr]gaitgenpois[012](),
[dpqr]gaitbinom(), dgaitplot(), plotdgait.vglm(), Trunc().
o New family functions: genpoisson[12](dpqr), gaitpoisson()
so that gaitpoisson.mix() and gaitpoisson.mlm() were removed,
gaitlog() so that gaitlog.mix() was removed,
gaitzeta() so that gaitzeta.mix() was removed.
o Tested okay on R 4.0.3.
BUG FIXES and CHANGES
o Deprecated: dgenpois(), genpoisson(), [dpqr]gaitnbinom.m[ix,lm]().
gatnbinomial.m[ix,lm](dpqr), [dpqr]gaitbinom.mlm(),
gaitpoisson.mix(), gaitpoisson.mlm(), gabinomial.mlm(),
gtbinomial().
o 'lhs.prob' changed to 'cdf.max.s'.
o Argument changes for all GAIT code, e.g., 'alter' changed to
'alt.mix' or 'alt.mlm', 'byrow.arg' to 'byrow.ai', etc.
o Functions moved to VGAMdata 1.1-4: oalog, oilog, otlog,
oapospois, oipospois, otpospois, oazeta, oizeta, otzeta, oizipf,
oiposbinomial(dpqr), [dpqr]posbinom, [dpqr]pospois, [dpqr]posnegbin.
o Pearson residuals no longer printed by default in a summary
of a "vglm" object: presid = FALSE.
o Some changes made to plot(vgam()) code for changes in R 4.0.0,
especially if the covariate is a character/factor.
Now avoids "coercing argument of type 'double' to logical" warning.
o negbinomial(lmu = "nbcanlink") had an error relating to "newemu".
CHANGES IN VGAM VERSION 1.1-3
NEW FEATURES
o New functions: [dpqr]gaitpois(), [dpqr]gaitlog(), [dpqr]gaitzeta(),
dextlogF().
o New family functions: gatnbinomial.mix(dpqr),
gaitlog.mix(dpqr), gaitpoisson.mix(dpqr), gaitpoisson.mlm(dpqr),
extlogF1(d).
o New generic and/or methods functions: altered(),
inflated(), truncated(), specialsvglm(),
fix.crossing(), is.crossing().
o Coef.vlm() handles models with contiguous "multilogitlink"s,
e.g., gaitpoisson.mlm().
o get.offset() is now defined as a generic function (returns the
n x M matrix of offsets by default).
o Some .f files have been pruned of unnecessary code.
o New data set: V2.
o Tested okay on R 4.0.0.
BUG FIXES and CHANGES
o Another attempt to .Deprecated() all link function names
which do not end in "link", e.g., loglink() replaces loge(),
logitlink() replaces logit().
o gatpoisson.mix() (now merged into gaitpoisson.mix())
reorders its linear/additive predictors and now handles
length(alter) == 0 (default, so equivalent to poissonff())
and length(alter) == 1.
Ditto for gatnbinomial.mlm(), etc.
o Three argument mismatches found in .f and .c code.
o qlog() and qyules() buggy wrt interval selection prior to
applying bisection.
o 'Rank mismatches' flagged by gfortran10 fixed, by not
calling two subroutines.
o [dpqr]gaitpois.mlm() and [dpqr]gaitpois.mix() have been combined into
[dpqr]gaitpois().
CHANGES IN VGAM VERSION 1.1-2
NEW FEATURES
o New generic and/or methods functions: add1.vglm(),
dfterms(), drop1.vglm(), extractAIC.vglm(),
rootogram4vglm() [based on \pkg{countreg}],
step4vglm().
o New family functions: gabinomial.mlm(), gatnbinomial.mlm(dpqr),
gatpoisson.mix(dpqr), gatpoisson.mlm(dpqr).
o New functions: [dpqr]zipfmb(),
[dpqr]gaitbinom.mlm(), [dpqr]gaitnbinom.mlm(),
[dpqr]gaitpois.mlm(), [dpqr]gaitnbinom.mix(),
[dpqr]gaitpois.mix().
Note that the naming conventions have changed somewhat, especially
regarding the negative binomial distribution.
o Decommissioned functions:
gapoisson(), gtpoisson(),
[dpqr]gabinom(), [dpqr]gapois(),
[dpqr]gibinom(), [dpqr]gipois(),
[dpqr]gtbinom(), [dpqr]gtpois().
o eta2theta() should be able to handle links for, e.g.,
gatpoisson.mlm(), gibinomial().
o posbernoulli.t() has a 'type.fitted' argument.
o gtpoisson.mlm() supports type.fitted = "Pobs.a",
gipoisson.mlm() supports type.fitted = "Pstr.i".
o New data set: backPain2.
o Cleve Moler added to DESCRIPTION as a contributor, to reflect
the use of LINPACK.
o Tested okay on R 3.6.1.
BUG FIXES and CHANGES
o Use of old link function names now result in a call to
.Deprecated(), except for a selected few such as logit() and
probitlink()---this will only be allowed for a limited time.
o negbinomial()@initialize bug fixed for "nbcanlink()" and
multiple responses; thanks to Victor Miranda.
o cens.poisson() gave a warning upon a summary().
Thanks to Jens Heumann for picking this up.
o bisection.basic() returns a warning, not an error, if
it cannot find an interval which covers the root.
o Rank() has an improved implementation and documentation.
o anova.vglm() had some bugs---thanks to Thamron Keowmani for
finding them.
o posnormal() failed when 'constraints' was inputted---thanks
to Michael Zamo for picking this up.
o Improvements to yules(dq).
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SciPy 1.8.1 is a bug-fix release with no new features
compared to 1.8.0. Notably, usage of Pythran has been
restored for Windows builds/binaries.
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It needs a patched version with mkd_latextext which our pkgsrc version does
not provide, but comes with a bundled copy that does.
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Previous workaround could fail to compile when double and long double are
effectively the same type.
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# vctrs 0.4.1
* OOB errors with `character()` indexes use "that don't exist" instead
of "past the end" (#1543).
* Fixed memory protection issues related to common type
determination (#1551, tidyverse/tidyr#1348).
# vctrs 0.4.0
* New experimental `vec_locate_sorted_groups()` for returning the locations of
groups in sorted order. This is equivalent to, but faster than, calling
`vec_group_loc()` and then sorting by the `key` column of the result.
* New experimental `vec_locate_matches()` for locating where each observation
in one vector matches one or more observations in another vector. It is
similar to `vec_match()`, but returns all matches by default (rather than just
the first), and can match on binary conditions other than equality. The
algorithm is inspired by data.table's very fast binary merge procedure.
* The `vec_proxy_equal()`, `vec_proxy_compare()`, and `vec_proxy_order()`
methods for `vctrs_rcrd` are now applied recursively over the fields (#1503).
* Lossy cast errors now inherit from incompatible type errors.
* `vec_is_list()` now returns `TRUE` for `AsIs` lists (#1463).
* `vec_assert()`, `vec_ptype2()`, `vec_cast()`, and `vec_as_location()`
now use `caller_arg()` to infer a default `arg` value from the
caller.
This may result in unhelpful arguments being mentioned in error
messages. In general, you should consider snapshotting vctrs error
messages thrown in your package and supply `arg` and `call`
arguments if the error context is not adequately reported to your
users.
* `vec_ptype_common()`, `vec_cast_common()`, `vec_size_common()`, and
`vec_recycle_common()` gain `call` and `arg` arguments for
specifying an error context.
* `vec_compare()` can now compare zero column data frames (#1500).
* `new_data_frame()` now errors on negative and missing `n` values (#1477).
* `vec_order()` now correctly orders zero column data frames (#1499).
* vctrs now depends on cli to help with error message generation.
* New `vec_check_list()` and `list_check_all_vectors()` input
checkers, and an accompanying `list_all_vectors()` predicate.
* New `vec_interleave()` for combining multiple vectors together, interleaving
their elements in the process (#1396).
* `vec_equal_na(NULL)` now returns `logical(0)` rather than erroring (#1494).
* `vec_as_location(missing = "error")` now fails with `NA` and `NA_character_`
in addition to `NA_integer_` (#1420, @krlmlr).
* Starting with rlang 1.0.0, errors are displayed with the contextual
function call. Several vctrs operations gain a `call` argument that
makes it possible to report the correct context in error messages.
This concerns:
- `vec_cast()` and `vec_ptype2()`
- `vec_default_cast()` and `vec_default_ptype2()`
- `vec_assert()`
- `vec_as_names()`
- `stop_` constructors like `stop_incompatible_type()`
Note that default `vec_cast()` and `vec_ptype2()` methods
automatically support this if they pass `...` to the corresponding
`vec_default_` functions. If you throw a non-internal error from a
non-default method, add a `call = caller_env()` argument in the
method and pass it to `rlang::abort()`.
* If `NA_character_` is specified as a name for `vctrs_vctr` objects, it is
now automatically repaired to `""` (#780).
* `""` is now an allowed name for `vctrs_vctr` objects and all its
subclasses (`vctrs_list_of` in particular) (#780).
* `list_of()` is now much faster when many values are provided.
* `vec_as_location()` evaluates `arg` only in case of error, for performance
(#1150, @krlmlr).
* `levels.vctrs_vctr()` now returns `NULL` instead of failing (#1186, @krlmlr).
* `vec_assert()` produces a more informative error when `size` is invalid
(#1470).
* `vec_duplicate_detect()` is a bit faster when there are many unique values.
* `vec_proxy_order()` is described in `vignette("s3-vectors")` (#1373, @krlmlr).
* `vec_chop()` now materializes ALTREP vectors before chopping, which is more
efficient than creating many small ALTREP pieces (#1450).
* New `list_drop_empty()` for removing empty elements from a list (#1395).
* `list_sizes()` now propagates the names of the list onto the result.
* Name repair messages are now signaled by `rlang::names_inform_repair()`. This
means that the messages are now sent to stdout by default rather than to
stderr, resulting in prettier messages. Additionally, name repair messages can
now be silenced through the global option `rlib_name_repair_verbosity`, which
is useful for testing purposes. See `?names_inform_repair` for more
information (#1429).
* `vctrs_vctr` methods for `na.omit()`, `na.exclude()`, and `na.fail()` have
been added (#1413).
* `vec_init()` is now slightly faster (#1423).
* `vec_set_names()` no longer corrupts `vctrs_rcrd` types (#1419).
* `vec_detect_complete()` now computes completeness for `vctrs_rcrd` types in
the same way as data frames, which means that if any field is missing, the
entire record is considered incomplete (#1386).
* The `na_value` argument of `vec_order()` and `vec_sort()` now correctly
respect missing values in lists (#1401).
* `vec_rep()` and `vec_rep_each()` are much faster for `times = 0` and
`times = 1` (@mgirlich, #1392).
* `vec_equal_na()` and `vec_fill_missing()` now work with integer64 vectors
(#1304).
* The `xtfrm()` method for vctrs_vctr objects no longer accidentally breaks
ties (#1354).
* `min()`, `max()` and `range()` no longer throw an error if `na.rm = TRUE` is
set and all values are `NA` (@gorcha, #1357). In this case, and where an empty
input is given, it will return `Inf`/`-Inf`, or `NA` if `Inf` can't be cast
to the input type.
* `vec_group_loc()`, used for grouping in dplyr, now correctly handles
vectors with billions of elements (up to `.Machine$integer.max`) (#1133).
|
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# broom 0.8.0
-------------------------------------------
This update makes significant improvements to documentation, fixes a
number of bugs, and brings the development flow of the package up to
date with other packages in the tidymodels.
In the big picture, this release:
* Makes many improvements to documentation:
- All tidiers now have example code demonstrating usage in their
documentation. Tidiers for base packages as well as selected
others also include sample code for visualization of results
with ggplot2.
- Code examples in the documentation largely now follow
consistent style---these changes were made largely to reflect
the tidyverse style guide, addressing spacing, object naming,
and commenting, among other things.
- Examples previously marked with `\dontrun` or `\donttest` have
been workshopped to run reliably. * Clarifies errors and
warnings for deprecated and un-maintained tidiers. * Ensures
that tidiers are placed in files named according to the
model-supplying package rather than the model object class for
easier navigability of the source code.
### Bug fixes and other improvements
* Fix `glance.fixest` error when model includes only fixed effects and
no regressors (`#1018` by `@arcruz0`, `#1088` by
`@vincentarelbundock`).
* Address excessive messaging from `tidy.speedlm` (`#1084` by
`@cgoo4`, `#1087` by `@vincentarelbundock`).
* Add `nobs` column to the output of `glance.svyglm` (`#1085` by
`@fschaffner`, `#1086` by `@vincentarelbundock`).
* Ensure `tidy.prcomp` description entries use consistent punctuation
(`#1072` by `@PursuitOfDataScience`).
* Address breaking changes in `glance.fixest` and `tidy.btergm`.
* Simplify handling of `MASS::polr` output in the corresponding `tidy`
and `augment` methods.
* Align continuous integration with current standards in tidymodels
packages.
# broom 0.7.12
-------------------------------------------
Nearly identical source to broom 0.7.11—updates the maintainer email
address to an address listed in other CRAN packages maintained by the
same person.
# broom 0.7.11
-------------------------------------------
* Addressed issue with the ordering of original observations in
`augment.rqs`. Now function preserves the original `data.frame`
names also when the input `data.frame` only has one column (`#1052`
by `@ilapros`).
* Addressed warning from `tidy.rma` when `x$ddf` has length greater
than 1 (`#1064` by `@wviechtb`).
* Fix errors in `glance.lavaan` in anticipation of upcoming `tidyr`
release (`#1067` by `@DavisVaughan`).
* Corrected the confidence interval in `tidy.crr()`. The
`tidy.crr(conf.level=)` argument was previously ignored (`#1068` by
`@ddsjoberg`).
# broom 0.7.10
-------------------------------------------
* Clarifies error when `pysch::mediate` output is dispatched to
`tidy.mediate` (`#1037` by `@LukasWallrich`).
* Allows user to specify confidence level for `tidy.rma` (`#1041` by
`@TarenSanders`)
* Clarifies documentation related to usage of `augment_columns()`;
most package users should use `augment()` in favor of
`augment_columns()`. See `?augment_columns` for more details.
* Extends support for `emmeans` by fixing non-standard column names in
case of asymptotically derived inferential statistics. (`#1046` by
`@crsh`)
* Fixes use of index columns in `augment.mlogit` and adds `.resid`
column to output. (`#1045`, `#1053`, `#1055`, and `#1056` by
`@jamesrrae` and `@gregmacfarlane`)
* Correct column naming of standard error measures in
`glance.survfit()`.
* Various bug fixes and improvements to documentation.
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Recursive lists in the form of R objects, 'JSON', and 'XML', for use
in teaching and examples. Examples include color palettes, Game of
Thrones characters, 'GitHub' users and repositories, music
collections, and entities from the Star Wars universe. Data from the
'gapminder' package is also included, as a simple data frame and in
nested and split forms.
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Ref:
http://mail-index.netbsd.org/pkgsrc-users/2022/05/02/msg035568.html
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# tidyr 1.2.0
## Pivoting
* `pivot_wider()` gains new `names_expand` and `id_expand` arguments for turning
implicit missing factor levels and variable combinations into explicit ones.
This is similar to the `drop` argument from `spread()` (#770).
* `pivot_wider()` gains a new `names_vary` argument for controlling the
ordering when combining `names_from` values with `values_from` column names
(#839).
* `pivot_wider()` gains a new `unused_fn` argument for controlling how to
summarize unused columns that aren't involved in the pivoting process (#990,
thanks to @mgirlich for an initial implementation).
* `pivot_longer()`'s `names_transform` and `values_transform` arguments now
accept a single function which will be applied to all of the columns
(#1284, thanks to @smingerson for an initial implementation).
* `pivot_longer()`'s `names_ptypes` and `values_ptypes` arguments now
accept a single empty ptype which will be applied to all of the columns
(#1284).
## Nesting
* `unnest()` and `unchop()`'s `ptype` argument now accepts a single empty
ptype which will be applied to all `cols` (#1284).
* `unpack()` now silently skips over any non-data frame columns specified by
`cols`. This matches the existing behavior of `unchop()` and `unnest()`
(#1153).
## Rectangling
* `unnest_wider()` and `unnest_longer()` can now unnest multiple columns at
once (#740).
* `unnest_longer()`'s `indices_to` and `values_to` arguments now accept
a glue specification, which is useful when unnesting multiple columns.
* For `hoist()`, `unnest_longer()`, and `unnest_wider()`, if a `ptype` is
supplied, but that column can't be simplified, the result will be a list-of
column where each element has type `ptype` (#998).
* `unnest_wider()` gains a new `strict` argument which controls whether or not
strict vctrs typing rules should be applied. It defaults to `FALSE` for
backwards compatibility, and because it is often more useful to be lax
when unnesting JSON, which doesn't always map one-to-one with R's types
(#1125).
* `hoist()`, `unnest_longer()`, and `unnest_wider()`'s `simplify` argument now
accepts a named list of `TRUE` or `FALSE` to control simplification on a per
column basis (#995).
* `hoist()`, `unnest_longer()`, and `unnest_wider()`'s `transform` argument now
accepts a single function which will be applied to all components (#1284).
* `hoist()`, `unnest_longer()`, and `unnest_wider()`'s `ptype` argument now
accepts a single empty ptype which will be applied to all components (#1284).
## Grids
* `complete()` gains a new `explicit` argument for limiting `fill` to only
implicit missing values. This is useful if you don't want to fill in
pre-existing missing values (#1270).
* `complete()` gains a grouped data frame method. This generates a more correct
completed data frame when groups are involved (#396, #966).
* `complete()` and `expand()` no longer allow you to complete or expand on a
grouping column. This was never well-defined since completion/expansion on a
grouped data frame happens "within" each group and otherwise has the
potential to produce erroneous results (#1299).
## Missing values
* `drop_na()`, `replace_na()`, and `fill()` have been updated to utilize vctrs.
This means that you can use these functions on a wider variety of column
types, including lubridate's Period types (#1094), data frame columns, and
the [rcrd](https://vctrs.r-lib.org/reference/new_rcrd.html) type from vctrs.
* `replace_na()` no longer allows the type of `data` to change when the
replacement is applied. `replace` will now always be cast to the type of
`data` before the replacement is made. For example, this means that using a
replacement value of `1.5` on an integer column is no longer allowed.
Similarly, replacing missing values in a list-column must now be done with
`list("foo")` rather than just `"foo"`.
* `replace_na()` no longer replaces empty atomic elements in list-columns
(like `integer(0)`). The only value that is replaced in a list-column is
`NULL` (#1168).
* `drop_na()` no longer drops empty atomic elements from list-columns
(like `integer(0)`). The only value that is dropped in a list-column is
`NULL` (#1228).
## Bug fixes and minor improvements
### General
* @mgirlich is now a tidyr author in recognition of his significant and
sustained contributions.
* All lazyeval variants of tidyr verbs have been soft-deprecated. Expect them
to move to the defunct stage in the next minor release of tidyr (#1294).
* `any_of()` and `all_of()` from tidyselect are now re-exported (#1217).
* dplyr >= 1.0.0 is now required.
### Pivoting
* `pivot_wider()` now gives better advice about how to identify duplicates when
values are not uniquely identified (#1113).
* `pivot_wider()` now throws a more informative error when `values_fn` doesn't
result in a single summary value (#1238).
* `pivot_wider()` and `pivot_longer()` now generate more informative
errors related to name repair (#987).
* `pivot_wider()` now works correctly when `values_fill` is a data frame.
* `pivot_wider()` no longer accidentally retains `values_from` when pivoting
a zero row data frame (#1249).
* `pivot_wider()` now correctly handles the case where an id column name
collides with a value from `names_from` (#1107).
* `pivot_wider()` and `pivot_longer()` now both check that the spec columns
`.name` and `.value` are character vectors. Additionally, the `.name`
column must be unique (#1107).
* `pivot_wider()`'s `names_from` and `values_from` arguments are now
required if their default values of `name` and `value` don't correspond to
columns in `data`. Additionally, they must identify at least 1 column
in `data` (#1240).
* `pivot_wider()`'s `values_fn` argument now correctly allows anonymous
functions (#1114).
* `pivot_wider_spec()` now works correctly with a 0-row data frame and a `spec`
that doesn't identify any rows (#1250, #1252).
* `pivot_longer()`'s `names_ptypes` argument is now applied after
`names_transform` for consistency with the rectangling functions
(i.e. `hoist()`) (#1233).
* `check_pivot_spec()` is a new developer facing function for validating a pivot
`spec` argument. This is only useful if you are extending `pivot_longer()` or
`pivot_wider()` with new S3 methods (#1087).
### Nesting
* The `nest()` generic now avoids computing on `.data`, making it more
compatible with lazy tibbles (#1134).
* The `.names_sep` argument of the data.frame method for `nest()` is now
actually used (#1174).
* `unnest()`'s `ptype` argument now works as expected (#1158).
* `unpack()` no longer drops empty columns specified through `cols` (#1191).
* `unpack()` now works correctly with data frame columns containing 1 row but
0 columns (#1189).
* `chop()` now works correctly with data frames with 0 rows (#1206).
* `chop()`'s `cols` argument is no longer optional. This matches the
behavior of `cols` seen elsewhere in tidyr (#1205).
* `unchop()` now respects `ptype` when unnesting a non-list column (#1211).
### Rectangling
* `hoist()` no longer accidentally removes elements that have duplicated names
(#1259).
### Grids
* The grouped data frame methods for `complete()` and `expand()` now move the
group columns to the front of the result (in addition to the columns you
completed on or expanded, which were already moved to the front). This should
make more intuitive sense, as you are completing or expanding "within" each
group, so the group columns should be the first thing you see (#1289).
* `complete()` now applies `fill` even when no columns to complete are
specified (#1272).
* `expand()`, `crossing()`, and `nesting()` now correctly retain `NA` values of
factors (#1275).
* `expand_grid()`, `expand()`, `nesting()`, and `crossing()` now silently
apply name repair to automatically named inputs. This avoids a number of
issues resulting from duplicate truncated names
(#1116, #1221, #1092, #1037, #992).
* `expand_grid()`, `expand()`, `nesting()`, and `crossing()` now allow
columns from unnamed data frames to be used in expressions after that
data frame was specified, like `expand_grid(tibble(x = 1), y = x)`. This
is more consistent with how `tibble()` behaves.
* `expand_grid()`, `expand()`, `nesting()`, and `crossing()` now work
correctly with data frames containing 0 columns but >0 rows (#1189).
* `expand_grid()`, `expand()`, `nesting()`, and `crossing()` now return a 1
row data frame when no inputs are supplied, which is more consistent with
`prod() == 1L` and the idea that computations involving the number of
combinations computed from an empty set should return 1 (#1258).
### Missing values
* `drop_na()` no longer drops missing values from all columns when a tidyselect
expression that results in 0 columns being selected is used (#1227).
* `fill()` now treats `NaN` like any other missing value (#982).
# tidyr 1.1.4
* `expand_grid()` is now about twice as fast and `pivot_wider()` is a bit faster
(@mgirlich, #1130).
* `unchop()` is now much faster, which propagates through to various functions,
such as `unnest()`, `unnest_longer()`, `unnest_wider()`, and
`separate_rows()` (@mgirlich, @DavisVaughan, #1127).
* `unnest()` is now much faster (@mgirlich, @DavisVaughan, #1127).
* `unnest()` no longer allows unnesting a list-col containing a mix of vector
and data frame elements. Previously, this only worked by accident, and is
considered an off-label usage of `unnest()` that has now become an error.
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Remove unused includes, fix dependencies where it's not included.
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Upstream changes:
Tue Aug 3 20:32:06 EDT 2021, Chong Gu <chong@purdue.edu>
* DESCRIPTION: Version 2.2-3.
* R: Edited sscomp.
* src: Edits in smolyak.c to comment out unused calccoeff2.
Tue May 26 00:21:21 EDT 2020, Chong Gu <chong@purdue.edu>
* DESCRIPTION: Version 2.2-2.
* R: Added sscomp and sscomp2.
* man: Added documentation for sscomp and sscomp2.
Sat May 16 15:49:33 EDT 2020, Chong Gu <chong@purdue.edu>
* DESCRIPTION: Version 2.2-1.
* R: Bug fixes, code cleanings in numerous places.
Sun May 3 14:34:28 EDT 2020, Chong Gu <chong@purdue.edu>
* DESCRIPTION: Version 2.2-0.
* R: i) Reworked the gssanova, gssanova1, and gssanova0 suites, to
add support for the "polr" family. ii) Added predict9.gssanova
for response scale prediction.
* data: Added wesdr1.
* man: Updated to reflect changes in R and data.
Sat Feb 29 10:50:40 EST 2020, Chong Gu <chong@stat.purdue.edu>
* DESCRIPTION: Version 2.1-12
* src: Bug fix in copu2newton, thanks to Elliott Sales de Andrade.
Fri Feb 28 19:40:49 EST 2020, Chong Gu <chong@stat.purdue.edu>
* DESCRIPTION: Version 2.1-11.
Edits in R/ and man/ to prepare for the coming default
data.frame(...,stringsAsFactors=FALSE).
Merged gsscopu package into this one, adding sscopu/sscopu2 suites
for copula density estimation, and sshzd2d/sshzd2d1 suites for 2-D
hazard estimation.
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(pkgsrc)
- Add two tentative macro, in patch, log1pl, expm1l. Tks tnn@ for hint
(and correct me if misleading)
(upstream)
# igraph 1.3.1
Fixed:
- `graph_from_adjacency_matrix()` now works with sparse matrices even if the
cell values in the sparse matrix are unspecified.
- Fixed crash in `cluster_walktrap()` when `modularity=FALSE` and `membership=FALSE`
- `edge_attr()` does not ignore its `index=...` argument any more.
- `automorphisms()`, `automorphism_group()` and `canonical_permutation()` now
allow all possible values supported by the C core in the `sh` argument.
Earlier versions supported only `"fm"`.
- The `vertex.frame.width` plotting parameter now allows zero and negative
values; these will simply remove the outline of the corresponding vertex.
- The documentation of the `sh` argument of the BLISS isomorphism algorithm in
`isomorphic()` was fixed; earlier versions incorrectly referred to `sh1` and
`sh2`.
- `dominator_tree()` now conforms to its documentation with respect to the
`dom` component of the result: it contains the indices of the dominator
vertices for each vertex and -1 for the root of the dominator tree.
- Mentions of the `"power"` algorithm of `page_rank()` have been removed from
the documentation, as this method is no longer available.
- Several other documentation fixes to bring the docs up to date with new behaviours
in igraph 1.3.
# igraph 1.3.0
The C core is updated to 0.9.7, fixing a range of bugs and introducing a number
of new functions.
Added:
- `has_eulerian_path()` and `has_eulerian_cycle()` decides whether there is an
Eulerian path or cycle in the graph.
- `eulerian_path()` and `eulerian_cycle()` returns the edges and vertices in an
Eulerian path or cycle in the graph.
- `any_loop()` checks whether a graph contains at least one loop edge.
- `is_tree()` checks whether a graph is a tree and also finds a possible root
- `to_prufer()` converts a tree graph into its Prufer sequence
- `make_from_prufer()` creates a tree graph from its Prufer sequence
- `sample_tree()` to sample labelled trees uniformly at random
- `sample_spanning_tree()` to sample spanning trees of an undirected graph
uniformly at random
- `automorphisms()` and `canonical_permutation()` now supports vertex colors
- `random_edge_walk()` to record the edges traversed during a random walk
- `harmonic_centrality()` calculates the harmonic centrality of vertices,
optionally with a cutoff on path lengths
- `mean_distance()` now supports edge weights and it can also return the number
of unconnected vertex pairs when `details=TRUE` is passed as an argument
- `greedy_vertex_coloring()` finds vertex colorings based on a simple greedy
algorithm.
- `bridges()` finds the bridges (cut-edges) of a graph
- The frame width of circle, rectangle and square vertex shapes can now be
adjusted on plots with the `frame.width` vertex attribute or the
`vertex.frame.width` keyword argument, thanks to @simoncarrignon .
See PR #500 for more details.
- `automorphism_group()` returns a possible (not necessarily minimal)
generating set of the automorphism group of a graph.
- `global_efficiency()` calculates the global efficiency of the graph.
- `local_efficiency()` calculates the local efficiency of each vertex in a graph.
- `average_local_efficiency()` calculates the average local efficiency across
the set of vertices in a graph.
- `rewire(each_edge(...))` now supports rewiring only one endpoint of each edge.
- `realize_degseq()` generates graphs from degree sequences in a deterministic
manner. It is also available as `make_(degseq(..., deterministic=TRUE))`.
- `clique_size_counts()` counts cliques of different sizes without storing them all.
- `feedback_arc_set()` finds a minimum-weight feedback arc set in a graph, either
with an exact integer programming algorithm or with a linear-time approximation.
- `make_bipartite_graph()` now handles vertices with names.
- `shortest_paths()` now supports graphs with negative edge weights.
- `min_cut()` now supports s-t mincuts even if `value.only=FALSE`.
- `as.matrix()` now supports converting an igraph graph to an adjacency or edge
list matrix representation. See `as.matrix.igraph()` for more details. This
function was migrated from `intergraph`; thanks to Michal Bojanowski.
Fixed:
- `is_connected()` now returns FALSE for the null graph
- Calling `length()` on a graph now returns the number of vertices to make it
consistent with indexing the graph with `[[`.
- `diameter()` now corrently returns infinity for disconnected graphs when
`unconnected=FALSE`. Previous versions returned the number of vertices plus
one, which was clearly invalid for weighted graphs.
- `mean_distance()` now correctly treats the path length between disconnected
vertices as infinite when `unconnected=FALSE`. Previous versions used the
number of vertices plus one, adding a bias towards this number, even if the
graph was weighted and the number of vertices plus one was not a path length
that could safely have been considered as being longer than any "valid" path.
- `layout_with_sugiyama()` now handles the case of exactly one extra virtual
node correctly; fixes #85
- `bfs()` and `dfs()` callback functions now correctly receive 1-based vertex
indices and ranks; it used to be zero-based in earlier versions
- Accidentally returning a non-logical value from a `bfs()` or `dfs()` callback
does not crash R any more
- Calling `print()` on a graph with a small `max.lines` value (smaller than the
number of lines needed to print the attribute list and the header) does not
raise an error any more; fixes #179
- `as_adjacency_matrix(edges=TRUE, sparse=TRUE)` now consistently returns the
last edge ID for each cell in the matrix instead of summing them.
- Using the `+` and `-` operators with a `path()` object consisting of two
vertices is now handled correctly; fixes #355
- `topo_sort()` now throws an error if the input graph is not acyclic instead
of returning an incorrect partial ordering.
- Weighted transitivity calculations (i.e. `transitivity(mode="barrat")` now
throw an error for multigraphs; the implementation does not work correctly
for multigraphs and earlier versions did not warn about this.
Changed:
- The `neimode` argument of `bfs()` and `dfs()` was renamed to `mode` for sake
of consistency with other functions. The old argument name is deprecated and
will be removed in 1.4.0.
- `bfs()` and `dfs()` callback functions now correctly receive 1-based vertex
indices and ranks; it used to be zero-based in earlier versions. (This is
actually a bugfix so it's also mentioned in the "Fixed" section).
- `closeness()`, `betweenness()` and `edge_betweenness()` now all take a
`cutoff` argument on their own. `estimate_closeness()`, `estimate_betweenness()`
and `estimate_edge_betweenness()` became aliases, with identical signature.
They are _not_ deprecated but their implementation might change in future
versions to provide proper estimation schemes instead of a simple cutoff-based
approximation. If you explicitly need cutoffs and you want your results to be
reproducible with future versions, use `closeness()`, `betweenness()` and
`edge_betweenness()` in your code with a `cutoff` argument.
- `closeness()` now only considers _reachable_ vertices during the calculation;
in other words, closeness centrality is now calculated on a per-component
basis for disconnected graphs. Earlier versions considered _all_ vertices.
Deprecated:
- Using `cutoff=0` for `closeness()`, `betweenness()` and `edge_betweenness()`
is deprecated; if you want exact scores, use a negative cutoff. `cutoff=0`
will be interpreted literally from igraph 1.4.0.
- `centr_degree_tmax()` now prints a warning when it is invoked without an
explicit `loops` argument. `loops` will be mandatory from igraph 1.4.0.
- The `nexus_list()`, `nexus_info()`, `nexus_get()` and `nexus_search()`
functions now return an error informing the user that the Nexus graph
repository has been taken offline (actually, several years ago). These
functions will be removed in 1.4.0.
- The `edges` argument of `as_adjacency_matrix()` is deprecated; it will be
removed in igraph 1.4.0.
Removed:
- The deprecated `page_rank_old()` function and the deprecated `power` method of
`page_rank()` were removed.
# igraph 1.2.11
Dec 27, 2021
No user visible changes.
# igraph 1.2.10
Dec 14, 2021
Fixed:
- The macOS versions of `igraph` were accidentally built without GraphML
support on CRAN; this should now be fixed.
# igraph 1.2.9
Nov 22, 2021
No user visible changes.
# igraph 1.2.8
Oct 26, 2021
No user visible changes.
# igraph 1.2.7
Oct 15, 2021
The C core is updated to 0.8.5, fixing a range of bugs and introducing a number of new functions.
Added:
- cluster_leiden added (#399).
- cluster_fluid_communities added (#454)
Fixed:
- `make_lattice()` correctly rounds `length` to the nearest integer while
printing a warning (#115).
- `make_empty_graph(NULL)` now prints an error instead of producing an
invalid graph (#404).
- `make_graph(c())` now produces an empty graph instead of printing a
misleading error message (#431).
- Printing a graph where some edges have NA as the names of both endpoints
does not produce a misleading error message any more (#410).
- The `types` argument of functions related to bipartite graphs now prints
a warning when the types are coerced to booleans (#476).
- Betweenness normalisation no longer overflows (#442).
- `layout_with_sugiyama()` returns a layout of type matrix even if there is
only one vertex in the graph (#408).
- Plotting a null graph (i.e. a graph with no vertices) does not throw an error
any more (#387).
Deprecated:
- The `membership` argument of `modularity.matrix()` is now deprecated as the
function never needed it anyway.
- `modularity()` now prints a warning when it is applied on a directed graph
because the implementation in igraph's C core does not support directed
graphs as of version 0.8.5. The warning will be turned into an error in
the next minor (1.3.0) version of the R interface; the error will be removed
later when the C core is updated to a version that supports modularity for
directed networks.
- `transitivity()` now prints a warning when its local variant (`type="local"`)
is called on a directed graph or a graph with multiple edges beecause the
implementation in the C core of igraph does not work reliably in these cases
as of version 0.8.5. The warning will be turned into an error in the next
minor (1.3.0) version of the R interface; the error will be removed later
when the C core is updated to a version that supports transitivity for
networks with multiple edges.
Misc:
- Documentation improvements.
# igraph 1.2.6
Oct 5, 2020
No user visible changes.
# igraph 1.2.5
Mar 27, 2020
No user visible changes.
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Bottleneck 1.3.4
================
Bug Fixes
~~~~~~~~~
- Fix Memory leak with big-endian data
Bottleneck 1.3.3
================
Bug Fixes
~~~~~~~~~
- Fix Python 3.10 build
Enhancements
~~~~~~~~~~~~
- Provide pre-compiled wheels for most x86_64 architectures
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2.17:
Unknown changes
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(math/R-RPostgreSQL) Upated 0.7.0 to 0.7.3, explicit ChangeLog/NEWS not updated
but compliant to R-4.2.0, (fix build)
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Interact with Google Sheets through the Sheets API v4
<https://developers.google.com/sheets/api>. "API" is an acronym for
"application programming interface"; the Sheets API allows users to
interact with Google Sheets programmatically, instead of via a web
browser. The "v4" refers to the fact that the Sheets API is currently
at version 4. This package can read and write both the metadata and
the cell data in a Sheet.
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