Upgrade to v1.0.2

Author: lindonroberts

docs/history.rst

@@ -10,3 +10,8 @@ Version 1.0.1 (20 Feb 2018)
 ---------------------------
 * Minor bug fix to trust region subproblem solver (the output :code:`crvmin` is calculated correctly) - this has minimal impact on the performance of Py-BOBYQA.
 
+Version 1.0.2 (20 Jun 2018)
+---------------------------
+* Extra optional input :code:`args` which passes through arguments for :code:`objfun` (pull request from `logangrado <https://github.com/logangrado>`_).
+* Bug fixes: default parameters for reduced initialization cost regime, returning correct value from safety steps, retrieving dependencies during installation.
+

docs/userguide.rst

@@ -72,7 +72,7 @@ The :code:`solve` function has several optional arguments which the user may pro
 
 These arguments are:
 
-* :code:`args` - a tuple of extra arguments passed to the objective function. This feature is new, and not yet avaiable in the PyPI version of Py-BOBYQA; instead, use Python's built-in function :code:`lambda`.
+* :code:`args` - a tuple of extra arguments passed to the objective function.
 * :code:`bounds` - a tuple :code:`(lower, upper)` with the vectors :math:`a` and :math:`b` of lower and upper bounds on :math:`x` (default is :math:`a_i=-10^{20}` and :math:`b_i=10^{20}`). To set bounds for either :code:`lower` or :code:`upper`, but not both, pass a tuple :code:`(lower, None)` or :code:`(None, upper)`.
 * :code:`npt` - the number of interpolation points to use (default is :code:`2*len(x0)+1`). Py-BOBYQA requires :code:`n+1 <= npt <= (n+1)*(n+2)/2` for a problem with :code:`len(x0)=n`. Larger values are particularly useful for noisy problems.
 * :code:`rhobeg` - the initial value of the trust region radius (default is :math:`0.1\max(\|x_0\|_{\infty}, 1)`).

manual.pdf

@@ -22,4 +22,4 @@
 
 """
 
-__version__ = '1.0.1'
+__version__ = '1.0.2'

pybobyqa/version.py

@@ -39,7 +39,7 @@
     author='Lindon Roberts',
     author_email='[email protected]',
     url="https://github.com/numericalalgorithmsgroup/pybobyqa/",
-    download_url="https://github.com/numericalalgorithmsgroup/pybobyqa/archive/v1.0.1.tar.gz",
+    download_url="https://github.com/numericalalgorithmsgroup/pybobyqa/archive/v1.0.2.tar.gz",
     packages=['pybobyqa'],
     license='GNU GPL',
     keywords = "mathematics derivative free optimization",