Two of the files now use autoconf to insert the correct Perl interpreter.
The dependency "pre-install: replace-interpreter" was useless since then
replace-interpreter would be run once in a direct "bmake update" or
"bmake install", and twice in bulk builds since they first run "bmake
build" and then "bmake install". And even in the latter case, replacing
the interpreter twice had no effect since it was already replaced in the
configure phase.
The package provides basic arithmetic operations to 8 decimal
places for plain TeX or LaTeX. Results are exact when they fit
within the digit limits. Along with the basic package is an
optional extension that adds computation of sin, cos, log,
sqrt, exp, powers and angles. These are also exact when
theoretically possible and are otherwise accurate to at least 7
decimal places. In addition, the package provides a stack-based
programing environment.
It uses python 2.x and gnumeric upstream has turned off the plugin by
default as well.
Add a "python" option for those who really need it.
Update some outdated comments.
Bump PKGREVISION.
Gappa is a tool intended to help verifying and formally proving
properties on numerical programs dealing with floating-point or
fixed-point arithmetic.
Sollya is a tool environment and a library for safe floating-point
code development, particularly targeted at automated implementation
of math libraries like libm.
Derived from wip/sollya.
Upstream NEWS highlights:
(translations and bugfixes omitted)
## 2.7.2
This is a production release with one major bug fix.
The `length()` built-in function can take either a number or an array. If it
takes an array, it returns the length of the array. Arrays can be passed by
reference. The bug is that the `length()` function would not properly
dereference arrays that were references. This is a bug that affects all users.
**ALL USERS SHOULD UPDATE `bc`**.
## 2.7.0
There is only one new feature: **`bc` now has a built-in pseudo-random number
generator** (PRNG).
The PRNG is seeded, making it useful for applications where
`/dev/urandom` does not work because output needs to be reproducible. However,
it also uses `/dev/urandom` to seed itself by default, so it will start with a
good seed by default.
On top of that, four functions were added to `bc`'s [extended math library][16]
to make using the PRNG easier:
* `frand(p)`: Generates a number between `[0,1)` to `p` decimal places.
* `ifrand(i, p)`: Generates an integer with bound `i` and adds it to `frand(p)`.
* `srand(x)`: Randomizes the sign of `x`. In other words, it flips the sign of
`x` with probability `0.5`.
* `brand()`: Returns a random boolean value (either `0` or `1`).
## 2.4.0
* The `bc` `&&` and `||` operators were made available to `dc` through the `M`
and `m` commands, respectively.
* `dc` macros were changed to be tail call-optimized.
The last item, tail call optimization, means that if the last thing in a macro
is a call to another macro, then the old macro is popped before executing the
new macro. This change was made to stop `dc` from consuming more and more memory
as macros are executed in a loop.
The `q` and `Q` commands still respect the "hidden" macros by way of recording
how many macros were removed by tail call optimization.
2018-10-09: 1.0.5 release:
* et.sor: new Estonian module
* Java: fix path separator for Windows by Rens Toonen
* spellout: fix DEFPATH in spellout by Rene Engelhard
* README: conversion to MarkDown by Miklós Vajna
* da.sor: fix "en million", bug report by Hsonesson1
* de.sor: add function year by c-kuehl
* eo.sor: fix ordinal-number, ie. "1-a" by Adolfo Jayme Barrientos
* fi.sor: fixed and more currencies by Tuomas Hietala
* lt.sor: fix ordinal numbers and currencies by Aurimas Fišeras
* pl.sor: fix ordinal numbers 4x, 7x, bug report by tengwar
* sq.sor: add missing 1000-9999
Version 1.0.1 Release Notes
============================
**Version 1.0.1 is the last release that supports Python 3.5**. All newer version will
require 3.6+ so that we can use formatting-strings and rely on dictionaries being ordered.
New features:
- added thermal distribution model and lineshape
- introduced a new argument ``max_nfev`` to uniformly specify the maximum number of function evalutions
**Please note: all other arguments (e.g., ``maxfev``, ``maxiter``, ...) will no longer be passed to the underlying
solver. A warning will be emitted stating that one should use ``max_nfev``.**
- the attribute ``call_kws`` was added to the ``MinimizerResult`` class and contains the keyword arguments that are
supplied to the solver in SciPy.
Bug fixes:
- fixes to the ``load`` and ``__setstate__`` methods of the Parameter class
- fixed failure of ModelResult.dump() due to missing attributes
- ``guess_from_peak`` function now also works correctly with decreasing x-values or when using
pandas
- the ``Parameter.set()`` method now correctly first updates the boundaries and then the value
Various:
- fixed typo for the use of expressions in the documentation
- removal of PY2-compatibility and unused code and improved test coverage
- removed deprecated ``isParameter`` function and automatic conversion of an ``uncertainties`` object
- inaccurate FWHM calculations were removed from built-in models, others labeled as estimates
- corrected spelling mistake for the Doniach lineshape and model
- removed unsupported/untested code for IPython notebooks in lmfit/ui/*
Version 0.49.1:
This is a bugfix release for 0.49.0, it fixes some residual issues with SSA form, a critical bug in the branch pruning logic and a number of other smaller issues:
* Fixed Threading Implementation Typos
* Fixes Remove references to cffi_support from docs and examples
* Fix invalid type in resolve for comparison expr in parfors.
* Fix erroneous rewrite of predicate to bit const on prune.
* Fixes SSA local def scan based on invalid equality assumption.
* Fixes naming error in array_exprs
* Fix. Incorrect race variable detection due to SSA naming.
* Make literal_unroll function work as a freevar.
* Unset the memory manager after EMM Plugin tests
* Fix some SSA issues
* Pin to sphinx=2.4.4 to avoid problem with C declaration
* Fix unifying undefined first class function types issue
* Update example in 5m guide WRT SSA type stability.
* Restore numba.types as public API
These PLIST files have been autogenerated by mk/haskell.mk using
HS_UPDATE_PLIST=yes during a bulk build. They will help to track changes
to the packages. The Haskell packages didn't have PLIST files because
their paths contained package hashes. These hashes are now determined by
mk/haskell.mk, which makes it easy to generate easy to read PLIST files.
1.18.4:
BLD: add i686 for 1.18 builds
BUG: random: ``Generator.integers(2**32)`` always returned 0.
BLD: fix path to libgfortran on macOS
REV: Reverts side-effect changes to casting
BLD: put openblas library in local directory on windows
DOC: Change import error "howto" to link to new troubleshooting...
Major Features:
- Allow fixing parameters in state space models
- Add new version of ARIMA-type estimators (AR, ARIMA, SARIMAX)
- Add STL decomposition for time series
- Functional SIR
- Zivot Andrews test
- Added Oaxaca-Blinder Decomposition
- Add rolling WLS and OLS
- Replacement for AR
Performance Improvements:
- Cythonize innovations algo and filter
- Only perform required predict iterations in state space models
- State space: Improve low memory usability; allow in fit, loglike
Version 1.0.0 Release Notes
New features:
- no new features are introduced in 1.0.0.
Improvements:
- support for Python 2 and use of the ``six`` package are removed.
Various:
- documentation updates to clarify the use of ``emcee``.
Changes from 2.7.0 to 2.7.1
- Python 3.8 support has been added.
- Python 3.4 support is discontinued.
- The tests are now compatible with NumPy 1.18.
- `site.cfg.example` was updated to use the `libraries` tag instead of `mkl_libs`,
which is recommended for newer version of NumPy.
SciPy 1.4.1 is a bug-fix release with no new features
compared to 1.4.0. Importantly, it aims to fix a problem
where an older version of pybind11 may cause a segmentation
fault when imported alongside incompatible libraries.
SciPy 1.4.0 is the culmination of 6 months of hard work. It contains
many new features, numerous bug-fixes, improved test coverage and better
documentation. There have been a number of deprecations and API changes
in this release, which are documented below. All users are encouraged to
upgrade to this release, as there are a large number of bug-fixes and
optimizations. Before upgrading, we recommend that users check that
their own code does not use deprecated SciPy functionality (to do so,
run your code with ``python -Wd`` and check for ``DeprecationWarning`` s).
Our development attention will now shift to bug-fix releases on the
1.4.x branch, and on adding new features on the master branch.
