| Commit message (Collapse) | Author | Age | Files | Lines |
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Fixed a number of references that were malformatted and broken links.
Module still needs work, particularly in standardizing return values.
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Fixed some broken links, references, and missing values. Also reverted
some earlier edits to return value descriptions to make them less
confusing.
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[ci skip]
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BUG: Make RandomState.seed, RandomState.randint and RandomState.shuffle threadsafe
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BUG: Make RandomState.set_state and RandomState.get_state threadsafe
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change '{ndarray, float}' -> 'ndarray or float' as {} are for
when the value is an enumeration
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The change is to make a stronger statement that the covariance matrix must
be positive-semidefinite and that if it is not, then the results are not
guaranteed across NumPy versions.
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BUG: ImportError: No module named thread
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Fixes #5136. Import dummy_threading if importing threading fails.
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This fixes issue #2138 by checking that the range (i.e. high - low) is finite
before invoking `rk_uniform`.
A test case was added to ensure valid ranges do not throw, but invalid ranges
do.
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http://lists.alioth.debian.org/pipermail/glibc-bsd-commits/2014-September/004163.html
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TST: accept small error in threaded random test
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freebsd and windows change x87 precision mode (fctrl bit 8 and 9) from
extended to double in child threads so the random numbers cannot be
exactly the same from master and child threads.
see gh-4909
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Pep8 numpy random
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This is in numpy/random/mtrand/mtrand.pyx where the choice function
was using comparisons of the form `None != p`.
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closes gh-4526
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-- Addresses https://github.com/numpy/numpy/issues/4763
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rho results in 0. for kappa < 1.4e-8 whch leads to nans appearing and an
infinite loop.
the second order taylor expansion is more precise up to at least 1e-5.
Closes gh-4720
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mtrand accepts seeds larger than 32 bit but silently truncates them back
to 32 bit. This can lead to accidentally getting the same random stream
for two different seeds, e.g. 1 and 1 + 2**40.
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The random module currently relies on the GIL for the state
synchronization which hampers threading performance.
Instead add a lock to the RandomState object and take it for all
operations calling into randomkit while releasing the GIL.
This allows parallizing random number generation using multiple states
or asynchronous generation in a worker thread.
Note that with a large number of threads the standard mersenne twister
used may exhibit overlap if the number of parallel streams is large
compared to the size of the state space, though due to the limited
scalability of Python in regards to threads this is likely not a big
issue.
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DOC: standardize "size" arg description in random module docstrings
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random module
there were many different versions for no good reason
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Instead generate at build time. The generated sources are still part of
the sdist.
tools/cythonize.py is copied from SciPy with small changes to the
configuration.
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Adds check with np.isnan(p) and raises ValueError if check is positive.
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Explicitly Test that the default shape does not raise a
DeprecationWarning.
Check that a covariance matrix that is not positive-semidefinite
raises a RuntimeWarning.
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numpy.random.multivariate_normal uses SVD to obtain the covariance
square root, but the result will be incorrect if the covariance is not
positive-semidefinite and no warning will be given. However, a check can
be made even while using the SVD by checking if the rows of u.T and v
have the same sign, where u and v are given by u, d, v = svd(a).
A deprecation warning is also fixed. When the default size was used an
empty list was passed to multiply.reduce, which resulted in a default
float 1. for a shape index. That is no longer legal. The problem is
fixed by using an array reshape, which also avoids potential overflow in
the original computation.
Closes #4489.
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np.random.permutation returns an array, which can be sliced.
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Closes gh-3173
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closes gh-4270 and gh-3263
also regenerate with cython 0.20.1
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improve random.choice performance and regen with cython 0.20
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Fixed warning is "Non-trivial type declarators in shared declaration".
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Use kahan_sum as multinomial does.
Closes gh-4188
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randomkit.c uses fopen which requires LFS mode to support larger than 64
bit files on 32 bit systems.
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This caused slowness and wrong/potentially wrong results
when the binomial result is larger then a native C int.
Closes gh-3352
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In the PDF used for the example plot of the Laplace distribution only the location parameter loc instead of the absolute difference between random variable and loc was divided by the scale parameter. For the example at hand this makes no difference as loc is 0 and lambda is 1. For different values, however, the plot makes no sense.
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Run the 2to3 ws_comma fixer on *.py files. Some lines are now too long
and will need to be broken at some point. OTOH, some lines were already
too long and need to be broken at some point. Now seems as good a time
as any to do this with open PRs at a minimum.
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Now is as good a time as any with open PR's at a low.
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