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ENH: Add kwarg support for vectorize (tickets #2100, #1156, and #1487) (clean)
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This is a substantial rewrite of vectorize to remove all introspection and
caching behaviour. This greatly simplifies the logic of the code, and allows
for much more generalized behaviour, simultaneously fixing tickets #1156,
#1487, and #2100. There will probably be a performance hit because caching is
no longer used (but should be able to be reinstated if needed).
As vectorize is a convenience function with poor performance in general,
perhaps this is okay. Rather than trying to inspect the function to determine
the number of arguments, defaults, and argument names, we just use the
arguments passed on the call to determine the behaviour on each call.
All tests pass and code is fully covered
Fixes:
Ticket #2100: kwarg support for vectorize
- API: Optional excluded argument to exclude some args from vectorization.
- Added documentation, examples, and coverage tests
- Added additional coverage test and base case for functions with no args
- Factored original behaviour into _vectorize_call
- Some minor documentation and error message corrections
Ticket #1156: Support vectorizing over instance methods
- No longer an issue since everything is determined by the call.
Ticket: #1487: result depends on execution order
- No longer caching, so the behaviour is as was expected.
ENH: Simple cache for vectorize
- Added simple cache to prevent vectorize from calling pyfunc twice on the first
argument when determining the output types and added regression test.
- Added documentation for excluded positional arguments.
- Documentation cleanups.
- Cleaned up variable names.
ENH: Performance improvements for backward compatibility of vectorize.
After some simple profiling, I found that the wrapping used to
support the caching of the previous commit wasted more time than
it saved, so I added a flag to allow the user to toggle. Moral:
caching makes sense only if the function is expensive and is off
by default.
I also compared performance with the original vectorize and opted
for keeping a cache of _ufunc if otypes is specified and there are
no kwargs/excluded vars. This case is easy to implement, and allows
users to reproduce (almost) the old performance characteristics if
needed. (The new version is about 5% slower in this case).
It would be much more complicated to add a similar cache in the case
where kwargs are used, and since a wrapper is used here, the
performance gain would be negligible (profiling showed that wrapping
was a more significant slowdown than the extra call to frompyfunc).
- API: Added cache kwarg which allows the user to toggle caching
of the first result.
- DOC: Added Notes section with a discussion of performance and a
warning that vectorize should not be used for performance.
- Added private _ufunc member to implement old-style of cache for
special case with no kwargs, excluded, and with otypes specified.
- Modified test case.
Partially address ticket #1982
- I tried to use hasattr(outputs, '__len__') rather than
isinstance(outputs, tuple) in order to allow for functions to return
lists. This, however, means that strings will get vectorized over
each character which breaks previous behaviour. Keeping old
behaviour for now.
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behavior.
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The ipmt function was also fixed to handle broadcasting. The tests
were improved and extended to cover the broadcasting capability.
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Fix incorrect python version checks in test_print.py.
Fix missing build_err_msg import and wrong variable in test_io.py.
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ENH: Give digitize left or right open interval option
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The various padding functions are exposed as options to a public 'pad'
function. Example:
pad(a, 5, mode='mean')
Current modes are 'constant', 'edge', 'linear_ramp', 'maximum', 'mean',
'median', 'minimum', 'reflect', 'symmetric', 'wrap', and <function>
This commit includes unit tests and doctests and is based on feature
request ticket #655.
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Make imports from numpy.testing explicit.
Use np namespace.
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The interp function was computing slopes for all intervals, even when there
were only a few points to be interpolated. Now it only does so when the
number of interpolation points exceeds the number of sample points.
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This is caused by the inconsistent floating point handling of Python itself.
On Windows with 2.5:
>>> "%s" % 1e-6
'1e-006'
With 2.6:
>>> "%s" % 1e-6
'1e-06'
Reviewed as PR-225.
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This one wasn't actually converted to a test error, because it's not a
RuntimeWarning. Maybe need to add an option to raise on UserWarning too.
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This should fix the test errors seen on both MinGW and MSVC9 related to this.
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This allows these objects to be freed by refcount, rather than requiring
the gc, which can be useful in some situations.
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payment) functions. Added doctests and unit tests.
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This should fix:
* http://projects.scipy.org/numpy/ticket/1848
* http://projects.scipy.org/scipy/ticket/1449
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This required some extensive changes, like:
* Making logical_or, logical_and, and logical_not on object arrays behave
like their Python equivalents instead of calling methods on the objects
* Changing the units for a fair number of the binary operations to
None, so they don't get initialized to their unit values at the start
A consequence of this is that multi-dimensional reductions like sum, prod,
any, or all no longer need to make copies, so are faster in some cases.
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I suggest using a separate keyword argument for structured arrays. It might
also be nice to be able to add a manual header.
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A warning for empty files is issued, including file name. Closes #1793.
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* pull-105:
STY: Put spaces around the '&' and '|' operators.
STY: Fix 'copy' 'copyto' typo and remove some trailing whitespace.
ENH: Use np.copyto instead of np.fill in some places
ENH: core: Add np.copyto, PyArray_MaskedMoveInto, PyArray_MaskedCopyInto
ENH: core: Add support for masked strided transfer functions
NEP: missingdata: Add a small note about single NA vs multi-NA
NEP: missingdata: Describe a possible way multi-NA could be added in the future
NEP: missingdata: Change the mask definition
STY: Some small stylistic changes
ENH: nditer: Add the basic checking and input of the MASK-related flags
NEP: missingdata: Design the mask binary format so it's extensible with a payload
DEP: core: Move 'fortran' macro into the deprecated header
ENH: nditer: Add the per-operand masked iteration flags
WRN: Get rid of some of the deprecation warnings about 'O4'
DEP: core: Move NPY_AO into the deprecated API header
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The 'den' metadata was always 1, except during construction, so there
is no reason for it to exist. The variable is kept in the struct
for 1.6 ABI compatibility, however.
The datetime_data function used ctypes. Moving the function to C is
no more difficult, and a bit cleaner in my opinion.
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A timing script justifying the switching criterion is attached to ticket 1603.
Thanks to Neil Crighton.
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inputs
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