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This is the case for x in {int, bool, str, float, complex, object}.
Using the np.{x} version is deceptive as it suggests that there is a
difference. This change doesn't affect any external behaviour. The
`long` type is missing in python 3, so np.long is still useful
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Bare except is very rarely the right thing
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Fixes #8815
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Also adds a test for the disabled-by-design behaviour - this would return
raw matrices, not masked arrays
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I mostly use that object to bind 1D arrays as columns, so I added an example for that use case.
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DOC: Mention boolean arrays in the ix_ documentation.
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This code was only here for Python 2.5 compatibility, but numpy requires 2.7
at minimum
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Closes gh-6863.
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closes gh-6062
done with help of Sebastian Berg! =)
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ENH: add np.stack
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The motivation here is to present a uniform and N-dimensional interface for
joining arrays along a new axis, similarly to how `concatenate` provides a
uniform and N-dimensional interface for joining arrays along an existing axis.
Background
~~~~~~~~~~
Currently, users can choose between `hstack`, `vstack`, `column_stack` and
`dstack`, but none of these functions handle N-dimensional input. In my
opinion, it's also difficult to keep track of the differences between these
methods and to predict how they will handle input with different
dimensions.
In the past, my preferred approach has been to either construct the result
array explicitly and use indexing for assignment, to or use `np.array` to
stack along the first dimension and then use `transpose` (or a similar method)
to reorder dimensions if necessary. This is pretty awkward.
I brought this proposal up a few weeks on the numpy-discussion list:
http://mail.scipy.org/pipermail/numpy-discussion/2015-February/072199.html
I also received positive feedback on Twitter:
https://twitter.com/shoyer/status/565937244599377920
Implementation notes
~~~~~~~~~~~~~~~~~~~~
The one line summaries for `concatenate` and `stack` have been (re)written to
mirror each other, and to make clear that the distinction between these functions
is whether they join over an existing or new axis.
In general, I've tweaked the documentation and docstrings with an eye toward
pointing users to `concatenate`/`stack`/`split` as a fundamental set of basic
array manipulation routines, and away from
`array_split`/`{h,v,d}split`/`{h,v,d,column_}stack`
I put this implementation in `numpy.core.shape_base` alongside `hstack`/`vstack`,
but it appears that there is also a `numpy.lib.shape_base` module that contains
another larger set of functions, including `dstack`. I'm not really sure where
this belongs (or if it even matters).
Finally, it might be a good idea to write a masked array version of `stack`.
But I don't use masked arrays, so I'm not well motivated to do that.
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Fixes #5804
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Fixed typos in docstrings were updated for functions where the parameter
names in the docstring didn't match the function signature.
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Allows access to internal functions for the file.
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The rules enforced are the same as those used for scipy.
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The zerosize_ok flag to nditer was missing, so that it did not
allow for 0-sized iteration.
Closes gh-3714
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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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Following deprecations would cause problems otherwise.
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The idioms fixer makes the following replacements.
1) int <- bool
2) comparison or identity of types <- isinstance
3) a.sort() <- sorted(a)
There were two problems that needed to be dealt with after the
application of the fixer. First, the replacement of comparison or
identity of types by isinstance was not always correct. The isinstance
function returns true for subtypes whereas many of the places where the
fixer made a substitution needed to check for exact type equality.
Second, the sorted function was applied to arrays, but because it treats
them as iterators and constructs a sorted list from the result, that is
the wrong thing to do.
Closes #3062.
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The next builtin has been available since Python 2.6 and allows
`it.next()` to be replaced by `next(it)`. In Python 3 the `next` method
is gone entirely, replaced entirely by the `__next__` method. The next
fixer changes all the `it.next()` calls to the new form and renames the
`next` methods to `__next__`. In order to keep Numpy code backwards
compatible with Python 2, a `next` method was readded to all the Numpy
iterators after the fixer was run so they all contain both methods. The
presence of the appropriate method could have been made version
dependent, but that looked unduly complicated.
Closes #3072.
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In Python 3 `map` is an iterator while in Python 2 it returns a list.
The simple fix applied by the fixer is to inclose all instances of map
with `list(...)`. This is not needed in all cases, and even where
appropriate list comprehensions may be preferred for their clarity.
Consequently, this patch attempts to use list comprehensions where it
makes sense.
When the mapped function has two arguments there is another problem that
can arise. In Python 3 map stops execution when the shortest argument
list is exhausted, while in Python 2 it stops when the longest argument
list is exhausted. Consequently the two argument case might need special
care. However, we have been running Python3 converted versions of numpy
since 1.5 without problems, so it is probably not something that affects
us.
Closes #3068
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Add `print_function` to all `from __future__ import ...` statements
and use the python3 print function syntax everywhere.
Closes #3078.
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DOC: Formatting fixes using regex
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also other spacing or formatting mistakes
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2to3 apply import fixer
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The new import `absolute_import` is added the `from __future__ import`
statement and The 2to3 `import` fixer is run to make the imports
compatible. There are several things that need to be dealt with to make
this work.
1) Files meant to be run as scripts run in a different environment than
files imported as part of a package, and so changes to those files need
to be skipped. The affected script files are:
* all setup.py files
* numpy/core/code_generators/generate_umath.py
* numpy/core/code_generators/generate_numpy_api.py
* numpy/core/code_generators/generate_ufunc_api.py
2) Some imported modules are not available as they are created during
the build process and consequently 2to3 is unable to handle them
correctly. Files that import those modules need a bit of extra work.
The affected files are:
* core/__init__.py,
* core/numeric.py,
* core/_internal.py,
* core/arrayprint.py,
* core/fromnumeric.py,
* numpy/__init__.py,
* lib/npyio.py,
* lib/function_base.py,
* fft/fftpack.py,
* random/__init__.py
Closes #3172
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Make AdvancedNew iter more 0-d aware
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In python3 range is an iterator and `xrange` has been removed. This has
two consequence for code:
1) Where a list is needed `list(range(...))` must be used.
2) `xrange` must be replaced by `range`
Both of these changes also work in python2 and this patch makes both.
There are three places fixed that do not need it, but I left them in
so that the result would be `xrange` clean.
Closes #3092
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This should be harmless, as we already are division clean. However,
placement of this import takes some care. In the future a script
can be used to append new features without worry, at least until
such time as it exceeds a single line. Having that ability will
make it easier to deal with absolute imports and printing updates.
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Fix ndindex for 0-d arrays.
Add tests for tuple arguments to ndindex
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