[Numpy-discussion] NumPy 1.8.0rc2 release

[David Cournapeau]

It looks better than rc1, thanks for the great work. I have only tested on
rh5 for now, but building the following against numpy 1.7.1 and running
against 1.8.0 rc2 only give a few failures for the full list of packages
supported by Enthought. Bottleneck / larry are caused by numpy, the sklearn
may be a bug in numpy or scikit learn or scipy (eigh issue).

List of packages:

GDAL-1.10.0
MDP-3.3
Pycluster-1.50
ScientificPython-2.9.0
SimPy-2.2
astropy-0.2.4
basemap-1.0.6
biopython-1.59
chaco-4.3.0
enable-4.3.0
fastnumpy-1.0
fwrap-0.1.1
h5py-2.2.0
llvmmath-0.1.1
matplotlib-1.3.0
mayavi-4.3.0
netCDF4-1.0.5
networkx-1.8.1
nltk-2.0.1
numba-0.10.2
opencv-2.4.5
pandas-0.12.0
pyfits-3.0.6
pygarrayimage-0.0.7
pygrib-1.9.2
pyhdf-0.8.3
pysparse-1.2.dev213
pytables-2.4.0
scikits.image-0.8.2
scikits.rsformats-0.1
scikits.timeseries-0.91.3
scimath-4.1.2
scipy-0.12.0
traits-4.3.0

As for the bottleneck/larry failures (for reference):

 ======================================================================
  FAIL: Test nanargmin.
  ----------------------------------------------------------------------
  Traceback (most recent call last):
    File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/nose/case.py",
line 197, in runTest
      self.test(*self.arg)
    File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/bottleneck/tests/func_test.py",
line 78, in unit_maker
      assert_array_equal(actual, desired, err_msg)
    File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/numpy/testing/utils.py",
line 718, in assert_array_equal
      verbose=verbose, header='Arrays are not equal')
    File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/numpy/testing/utils.py",
line 644, in assert_array_compare
      raise AssertionError(msg)
  AssertionError:
  Arrays are not equal

  func nanargmin | input a44 (float32) | shape (4,) | axis -1

  Input array:
  [ nan  nan  nan  nan]

  (mismatch 100.0%)
   x: array(nan)
   y: array('Crashed',
        dtype='|S7')

  ======================================================================
  FAIL: Test nanargmax.
  ----------------------------------------------------------------------
  Traceback (most recent call last):
    File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/nose/case.py",
line 197, in runTest
      self.test(*self.arg)
    File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/bottleneck/tests/func_test.py",
line 78, in unit_maker
      assert_array_equal(actual, desired, err_msg)
    File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/numpy/testing/utils.py",
line 718, in assert_array_equal
      verbose=verbose, header='Arrays are not equal')
    File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/numpy/testing/utils.py",
line 644, in assert_array_compare
      raise AssertionError(msg)
  AssertionError:
  Arrays are not equal

  func nanargmax | input a44 (float32) | shape (4,) | axis -1

  Input array:
  [ nan  nan  nan  nan]

  (mismatch 100.0%)
   x: array(nan)
   y: array('Crashed',
        dtype='|S7')

  ----------------------------------------------------------------------
  Ran 124 tests in 85.714s

  FAILED (failures=2)
FAIL

and larry:

======================================================================
ERROR: Failure: IndexError (too many indices)
----------------------------------------------------------------------
Traceback (most recent call last):
  File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/nose/loader.py",
line 253, in generate
    for test in g():
  File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/la/tests/all_nan_test.py",
line 31, in test_all_nan
    actual = getattr(lar(), method)(*parameters)
  File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/la/deflarry.py",
line 3066, in quantile
    x = quantile(self.x, q, axis=axis)
  File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/la/farray/normalize.py",
line 289, in quantile
    y = np.apply_along_axis(_quantileraw1d, axis, x, q)
  File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/numpy/lib/shape_base.py",
line 79, in apply_along_axis
    res = func1d(arr[tuple(i.tolist())],*args)
  File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/la/farray/normalize.py",
line 228, in _quantileraw1d
    xi = xi[idx,:]
IndexError: too many indices

======================================================================
ERROR: larry.quantile_1
----------------------------------------------------------------------
Traceback (most recent call last):
  File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/la/tests/deflarry_test.py",
line 3401, in test_quantile_1
    actual = self.l1.quantile(2)
  File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/la/deflarry.py",
line 3066, in quantile
    x = quantile(self.x, q, axis=axis)
  File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/la/farray/normalize.py",
line 289, in quantile
    y = np.apply_along_axis(_quantileraw1d, axis, x, q)
  File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/numpy/lib/shape_base.py",
line 79, in apply_along_axis
    res = func1d(arr[tuple(i.tolist())],*args)
  File
"/home/vagrant/src/master-env/lib/python2.7/site-packages/la/farray/normalize.py",
line 228, in _quantileraw1d
    xi = xi[idx,:]
IndexError: too many indices

(more similar)


On Mon, Oct 14, 2013 at 10:37 PM, Charles R Harris <
charlesr.harris at gmail.com> wrote:

> Hi All,
>
> NumPy 1.8.0rc2 is up now on sourceforge<http://sourceforge.net/projects/numpy/files/NumPy/1.8.0rc2/>.
> Binary builds are included, except for Python 3.3 on windows. Many thanks
> to Ralf for the binaries and to those who found and fixed the bugs in rc1.
> Please test this thoroughly, especially if you have access to one of the
> less common platforms. Testing of rc1 turned up several bugs that would
> have been a embarrassment if they had made their way into the release and
> we are very happy that they were discovered.
>
> Chuck
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>
>
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