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BUG: np.ma.compress treated inputs in wrong order; closes #2495
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The previous behavior when setting a field after indexing to
select an element was suitable for the hard mask case, but
not for the default soft mask. In addition, the _hardmask
value was not being set at all in the mvoid instance. With
this changeset, the _hardmask is passed in and __setitem__
takes it into account.
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enables a few extra tests
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While ddof has basically no effect on corrcoef, it exists,
but it was not passed on correctly (instead only bias would
be passed on). Fixes gh-3336
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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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Update masked array copy to preserve array order
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Test to ensure that MaskedArray.filled() doesn't change the order of the array.
This test is a little messy because there are problems constructing an F-contiguous masked array in the first place. I had to explicitly pass in F-contiguous arrays for data and mask.
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Using 'K' to try to match array order, fixes https://github.com/numpy/numpy/issues/3156
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The unicode fixer strips the u from u'hi' and converts the unicode type
to str. The first won't work for Python 2 and instead we replace the u
prefix with the sixu function borrowed from the six compatibility
package. That function calls the unicode constructor with the
'unicode_escape' encoder so that the many tests using escaped unicode
characters like u'\u0900' will be handled correctly. That makes the
sixu function a bit different from the asunicode function currently in
numpy.compat and also provides a target that can be converted back to
the u prefix when support for Python 3.2 is dropped. Python 3.3
reintroduced the u prefix for compatibility.
The unicode fixer also replaces 'unicode' with 'str' as 'unicode' is no
longer a builtin in Python 3. For code compatibility, 'unicode' is
defined either as 'str' or 'unicode' in numpy.compat so that checks like
if isinstance(x, unicode):
...
will work properly for all python versions.
Closes #3089.
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2to3: Apply types fixer.
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Python 3 removes the builtin types from the types module. The types
fixer replaces such references with the builtin types where possible
and also takes care of some special cases:
types.TypeNone <- type(None)
types.NotImplementedType <- type(NotImplemented)
types.EllipsisType <- type(Ellipsis)
The only two tricky substitutions are
types.StringType <- bytes
types.LongType <- int
These are fixed up to support both Python 3 and Python 2 code by
importing the long and bytes types from numpy.compat.
Closes #3240.
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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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2to3: Apply zip fixer.
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In Python 3 zip returns an iterator instead of a list. Consequently, in
places where an iterator won't do it must be enclosed in list(...).
Lists instead of iterators are also used in array constructors as using
iterators there usually results in an object array containing an
iterator object.
Closes #3094
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The basestring class is not defined in Python 3 and the fixer replaces
it with str. In order to have a common code base we define basestring in
numpy/compat/py3k.py to be str when the Python version is >= 3,
otherwise basestring and import it where needed. That works for most
cases, but there are a few files where the version dependent define
needs to be in the file.
Closes #3042.
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The numliterals fixer replaces the old style octal number like '01' by
'0o1' removes the 'L' suffix.
Octal values were previously mistakenly specified in some dates, those
uses have been corrected by removing the leading zeros.
Simply Removing the 'L' suffix should not be a problem, but in some
testing code it looks neccesary, so in those places the Python long
constructor is used instead.
The 'long' type is no longer defined in Python 3. Because we need to
have it defined for Python 2 it is added to numpy/compat/np3k.py where
it is defined as 'int' for Python 3 and 'long' for Python 2. The `long`
fixer then needs to be skipped so that it doesn't undo the good work.
Closes #3074, #3067.
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This replaces python backtics with repr(...). The backtics were mostly
used to generate strings for printing with a string format and it is
tempting to replace `'%s' % repr(x)` with `'%r' % x`. That would work
except where `x` happened to be a tuple or a dictionary but, because it
would be significant work to guarantee that and because there are not
many places where backtics are used, the safe path is to let the repr
replacements stand.
Closes #3083.
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2to3: apply `dict` fixer.
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In Python3 `dict.items()`, `dict.keys()`, and `dict.values()` are
iterators. This causes problems when a list is needed so the 2to3 fixer
explicitly constructs a list when is finds on of those functions.
However, that is usually not necessary, so a lot of the work here has
been cleaning up those places where the fix is not needed. The big
exception to that is the `numpy/f2py/crackfortran.py` file. The code
there makes extensive use of loops that modify the contents of the
dictionary being looped through, which raises an error. That together
with the obscurity of the code in that file made it safest to let the
`dict` fixer do its worst.
Closes #3050.
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MAINT: Cleanup some imports involving reduce.
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Because reduce has been available in functools since Python 2.6 we
can get rid of the version checks we currently have before we import
it.
Also removes some reduce related skips in tools/py3tool.py. We were
already skipping the reduce fixer so this has no effect other than
cleaning up the code.
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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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2to3: Apply `imports` fixer.
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The `imports` fixer deals with the standard packages that have been
renamed, removed, or methods that have moved.
cPickle -- removed, use pickle
commands -- removed, getoutput, getstatusoutput moved to subprocess
urlparse -- removed, urlparse moved to urllib.parse
cStringIO -- removed, use StringIO or io.StringIO
copy_reg -- renamed copyreg
_winreg -- renamed winreg
ConfigParser -- renamed configparser
__builtin__ -- renamed builtins
In the case of `cPickle`, it is imported as `pickle` when python < 3 and
performance may be a consideration, but otherwise plain old `pickle` is
used.
Dealing with `StringIO` is a bit tricky. There is an `io.StringIO`
function in the `io` module, available since Python 2.6, but it expects
unicode whereas `StringIO.StringIO` expects ascii. The Python 3
equivalent is then `io.BytesIO`. What I have done here is used BytesIO
for anything that is emulating a file for testing purposes. That is more
explicit than using a redefined StringIO as was done before we dropped
support for Python 2.4 and 2.5.
Closes #3180.
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DOC: Formatting fixes using regex
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also other spacing or formatting mistakes
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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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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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Replaces the
raise Exception, msg:
form with
raise Exception(msg):
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DOC -- add another paragraph note to ndarray.view docs
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More detail: Views are only sensitive to under-the-hood storage when
the dtype storage size has changed.
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Since most numpy operations are not sensitive to underlying data
structure (C-ordered arrays vs fortran-ordered arrays, versus slices or
transposes of arrays, etc.), but structured-array views ARE sensitive to
that, it is worth saying it explicitly in the documentation.
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Example: except ValueError,msg: -> except ValueError as msg:
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This removes files and code supporting scons builds. After this change
numpy will only support builds using distutils or bento. The removal of
scons has been discussed on the list several times and a decision has been
made that scons support is no longer needed. This was originally discussed
for numpy 1.7 and because the distutils and bento methods are still
available we are skipping the usual deprecation period.
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cannot access masked array rows with np.object dtype (Fixes #2432)
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(which doesn't work when it is a recarray containing object fields), just create a copy with the np.array constructor.
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TST: Catch possible warnings
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Previously the test sometimes fails with the following error:
======================================================================
ERROR: Test a special case for var
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/travis/virtualenv/python3.2/lib/python3.2/site-packages/numpy/ma/tests/test_core.py", line 2731, in test_varstd_specialcases
_ = method(out=mout)
File "/home/travis/virtualenv/python3.2/lib/python3.2/site-packages/numpy/ma/core.py", line 4778, in std
np.power(out, 0.5, out=out, casting='unsafe')
RuntimeWarning: invalid value encountered in power
----------------------------------------------------------------------
Now we catch it, as recommended by the thread:
http://old.nabble.com/Should-abs(-nan-)-be-supported--td34389839.html
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Don't reset the fill_value of a MaskedArray when calling view() with no dtype
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