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This is related to PEP 3149, tags in shared library extensions. Only applies
to Linux (for now). See also #1749.
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Now the dict repr mode for struct dtypes always includes the itemsize=
parameter, so that it will always produce the exact same memory layout.
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descriptor
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This will require validation that object dtypes don't overlap with
other fields in a follow-on commit.
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In the case referenced in ticket #1790, the itemsize was set before
the padded size was calculated, so the intent was clearly that it
should have been aligned.
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The 'struct'-based repr adds this parameter, as the general way to
be able to reconstruct the dtype.
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This includes preserving the 'align=True' parameter through the
new NPY_ALIGNED_STRUCT dtype flag. The code now detects whether
the list version of structured dtype construction would match
the data layout, to choose between list and struct based construction.
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Since ones_like is a ufunc (unlike zeros_like and empty_like), it by
default checks the casting rule. This disables that check completely.
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This is an experimental change, to see what kind of ripple effects
tightening up the semantics of NumPy just a little bit produce.
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Highlights:
* Tighten up date unit vs time unit casting rules,
and integrate the NPY_CASTING enum deeper into the datetime conversions
* Determine a unit when converting from a string array,
similar to when converting from lists of strings
* Switch local/utc handling to a timezone= parameter,
which also accepts a datetime.tzinfo object. This, for
example, enables the use of the pytz library with numpy.datetime64
* Remove the events metadata, make the old API functions raise
exceptions, and rename the "frequency" metadata name to "timeunit"
* Abstract the flexible dtype mechanism into a function,
so that it can be more easily changed without having to
add code to many places
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Since the datetime adds a new flexible dtype (datetime with generic units),
updating all the places where flexible dtypes are adjusted was error-prone.
Thus, this has been moved to a single place.
At the same time, I've added sizes for the various number types, so
they don't produce size-one strings by default anymore
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The default is 'same_kind', which allows data loss, but prevents
crossing the date unit/time unit boundary. As a special case,
printing dates with a timezone specified requires 'unsafe' casting.
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The events don't fit well within the datetime, causing many special
cases and complicating the datetime code. A better way to proceed,
which received approval from Travis with regard to the reason events
were introduced in the first place, is to do the following:
* Generalize the structured arrays so they work with ufuncs
* Either use NPY_UBYTE, or introduce a new integer modulo N type
* The structured dtype [('date', 'M8[D]'), ('event', 'u8')], then
will operate identically to the design of events in datetime.
These other changes will have much use elsewhere as well.
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Also clean up the tests to work with the stricter date unit vs time unit
boundary that has been added.
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Also add some tests using the pytz library.
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Also move datetime string functions to their own source file.
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--include-paths. Updated docs.
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* sortlib:
STY: Delete commented out lines and add some comments.
ENH: Generate the npysort library for linking during build, but do not install it.
ENH: Make npy_sort.h private until the proper interface gets sorted out.
ENH: Remove the _sort module.
ENH: Directly initialize arraytypes with the sorting functions in the sort library.
STY: Rename sort functions again, omit the npy_ bit from the suffix.
ENH: Rename the sort functions using lower case suffix instead of upper case prefix. The name are now of the form <sortkind>_<npy_type>.
ENH: Make scons build the npysort library.
ENH: Move sorting functions into a library.
STY: Move npy_intp definitions and associated formats into npy_common.h.
STY: Reorganize core/setup.py a bit.
ENH: Break out the sort functions into a separate file.
ENH: Rename the sorting directory to npysort.
ENH: Move comparison functions into an include file. Make include file for the future sorting library. Use prefixed numpy types.
ENH: Rename _sortmodule.c.src and move it into a new sorting directory. Fix the build to deal with the new name and location.
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install it.
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library.
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case prefix. The name are now of the form <sortkind>_<npy_type>.
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