On 6/8/2014 1:34 PM, Julian Taylor wrote:
Hello,
I'm happy to announce the fist beta release of Numpy 1.9.0.
1.9.0 will be a new feature release supporting Python 2.6 - 2.7 and 3.2
- 3.4.
Due to low demand windows binaries for the beta are only available for
Python 2.7, 3.3 and 3.4.
Please try it and report any issues to the numpy-discussion mailing list
or on github.
The 1.9 release will consists of mainly of many small improvements and
bugfixes. The highlights are:
* Addition of __numpy_ufunc__ to allow overriding ufuncs in ndarray
subclasses. Please note that there are still some known issues with this
mechanism which we hope to resolve before the final release (e.g. #4753)
* Numerous performance improvements in various areas, most notably
indexing and operations on small arrays are significantly faster.
Indexing operations now also release the GIL.
* Addition of nanmedian and nanpercentile rounds out the nanfunction set.
The changes involve a lot of small changes that might affect some
applications, please read the release notes for the full details on all
changes:
https://github.com/numpy/numpy/blob/maintenance/1.9.x/doc/release/1.9.0-notes.rst
Please also take special note of the future changes section which will
apply to the following release 1.10.0 and make sure to check if your
applications would be affected by them.
Source tarballs, windows installers and release notes can be found at
https://sourceforge.net/projects/numpy/files/NumPy/1.9.0b1
Cheers,
Julian Taylor
Hello,
I tested numpy-MKL-1.9.0b1 (msvc9, Intel MKL build) on win-amd64-py2.7
against a few other packages that were built against numpy-MKL-1.8.x.
While numpy and scipy pass all tests, some other packages (matplotlib,
statsmodels, skimage, pandas, pytables, sklearn...) show a few new test
failures (compared to testing with numpy-MKL-1.8.1). Many test errors
are of kind:
ValueError: shape mismatch: value array of shape (24,) could not be
broadcast to indexing result of shape (8,3)
I have attached a list of failing tests. The full test results are at
<http://www.lfd.uci.edu/~gohlke/pythonlibs/tests/20140609-win-amd64-py2.7-numpy-1.9.0b1/>
(compare to
<http://www.lfd.uci.edu/~gohlke/pythonlibs/tests/20140609-win-amd64-py2.7/>)
I have not investigated any further...
Christoph
matplotlib 1.3.1
================
======================================================================
ERROR: test suite for <class
'matplotlib.tests.test_triangulation.test_tri_smooth_contouring'>
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\suite.py", line 208, in run
self.setUp()
File "X:\Python27-x64\lib\site-packages\nose\suite.py", line 291, in setUp
self.setupContext(ancestor)
File "X:\Python27-x64\lib\site-packages\nose\suite.py", line 314, in
setupContext
try_run(context, names)
File "X:\Python27-x64\lib\site-packages\nose\util.py", line 470, in try_run
return func()
File "X:\Python27-x64\lib\site-packages\matplotlib\testing\decorators.py",
line 102, in setup_class
cls._func()
File
"X:\Python27-x64\lib\site-packages\matplotlib\tests\test_triangulation.py",
line 715, in test_tri_smooth_contouring
tri_refi, z_test_refi = refiner.refine_field(z0, subdiv=4)
File "X:\Python27-x64\lib\site-packages\matplotlib\tri\trirefine.py", line
179, in refine_field
subdiv=subdiv, return_tri_index=True)
File "X:\Python27-x64\lib\site-packages\matplotlib\tri\trirefine.py", line
125, in refine_triangulation
] = np.repeat(ancestors[ancestor_mask], 3)
ValueError: shape mismatch: value array of shape (13824,) could not be
broadcast to indexing result of shape (4608,3)
======================================================================
ERROR: test suite for <class
'matplotlib.tests.test_triangulation.test_tri_smooth_gradient'>
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\suite.py", line 208, in run
self.setUp()
File "X:\Python27-x64\lib\site-packages\nose\suite.py", line 291, in setUp
self.setupContext(ancestor)
File "X:\Python27-x64\lib\site-packages\nose\suite.py", line 314, in
setupContext
try_run(context, names)
File "X:\Python27-x64\lib\site-packages\nose\util.py", line 470, in try_run
return func()
File "X:\Python27-x64\lib\site-packages\matplotlib\testing\decorators.py",
line 102, in setup_class
cls._func()
File
"X:\Python27-x64\lib\site-packages\matplotlib\tests\test_triangulation.py",
line 752, in test_tri_smooth_gradient
tri_refi, z_test_refi = refiner.refine_field(V, subdiv=3)
File "X:\Python27-x64\lib\site-packages\matplotlib\tri\trirefine.py", line
179, in refine_field
subdiv=subdiv, return_tri_index=True)
File "X:\Python27-x64\lib\site-packages\matplotlib\tri\trirefine.py", line
125, in refine_triangulation
] = np.repeat(ancestors[ancestor_mask], 3)
ValueError: shape mismatch: value array of shape (5376,) could not be broadcast
to indexing result of shape (1792,3)
======================================================================
ERROR: matplotlib.tests.test_triangulation.test_triinterp
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File
"X:\Python27-x64\lib\site-packages\matplotlib\tests\test_triangulation.py",
line 306, in test_triinterp
(interp_dzsdx, interp_dzsdy) = cubic_user.gradient(x, y)
File "X:\Python27-x64\lib\site-packages\matplotlib\tri\triinterpolate.py",
line 435, in gradient
return_keys=('dzdx', 'dzdy'))
File "X:\Python27-x64\lib\site-packages\matplotlib\tri\triinterpolate.py",
line 208, in _interpolate_multikeys
return_key, valid_tri_index, valid_x, valid_y) * scale
TypeError: NumPy boolean array indexing assignment requires a 0 or
1-dimensional input, input has 2 dimensions
======================================================================
ERROR: matplotlib.tests.test_triangulation.test_triinterpcubic_C1_continuity
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File
"X:\Python27-x64\lib\site-packages\matplotlib\tests\test_triangulation.py",
line 405, in test_triinterpcubic_C1_continuity
check_continuity(interp, (ax, ay), values[:, 0])
File
"X:\Python27-x64\lib\site-packages\matplotlib\tests\test_triangulation.py",
line 366, in check_continuity
(dzx, dzy) = interpolator.gradient([loc_x], [loc_y])
File "X:\Python27-x64\lib\site-packages\matplotlib\tri\triinterpolate.py",
line 435, in gradient
return_keys=('dzdx', 'dzdy'))
File "X:\Python27-x64\lib\site-packages\matplotlib\tri\triinterpolate.py",
line 208, in _interpolate_multikeys
return_key, valid_tri_index, valid_x, valid_y) * scale
TypeError: NumPy boolean array indexing assignment requires a 0 or
1-dimensional input, input has 2 dimensions
======================================================================
ERROR: matplotlib.tests.test_triangulation.test_trirefine
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File
"X:\Python27-x64\lib\site-packages\matplotlib\tests\test_triangulation.py",
line 880, in test_trirefine
refined_triang, refined_z = refiner.refine_field(z, subdiv=1)
File "X:\Python27-x64\lib\site-packages\matplotlib\tri\trirefine.py", line
179, in refine_field
subdiv=subdiv, return_tri_index=True)
File "X:\Python27-x64\lib\site-packages\matplotlib\tri\trirefine.py", line
116, in refine_triangulation
found_index[refi_triangles] = np.repeat(ancestors, 3)
ValueError: shape mismatch: value array of shape (24,) could not be broadcast
to indexing result of shape (8,3)
pandas 0.14.0
=============
======================================================================
ERROR: test_interp_regression (pandas.tests.test_generic.TestSeries)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\pandas\tests\test_generic.py", line
501, in test_interp_regression
interp_s = ser.reindex(new_index).interpolate(method='pchip')
File "X:\Python27-x64\lib\site-packages\pandas\core\generic.py", line 2582,
in interpolate
**kwargs)
File "X:\Python27-x64\lib\site-packages\pandas\core\internals.py", line 2197,
in interpolate
return self.apply('interpolate', **kwargs)
File "X:\Python27-x64\lib\site-packages\pandas\core\internals.py", line 2164,
in apply
applied = getattr(b, f)(**kwargs)
File "X:\Python27-x64\lib\site-packages\pandas\core\internals.py", line 667,
in interpolate
**kwargs)
File "X:\Python27-x64\lib\site-packages\pandas\core\internals.py", line 733,
in _interpolate
interp_values = np.apply_along_axis(func, axis, data)
File "D:\Build\Test\numpy-build\numpy\lib\shape_base.py", line 86, in
apply_along_axis
res = func1d(arr[tuple(i.tolist())], *args, **kwargs)
File "X:\Python27-x64\lib\site-packages\pandas\core\internals.py", line 730,
in func
bounds_error=False, **kwargs)
File "X:\Python27-x64\lib\site-packages\pandas\core\common.py", line 1489, in
interpolate_1d
bounds_error=bounds_error, **kwargs)
File "X:\Python27-x64\lib\site-packages\pandas\core\common.py", line 1541, in
_interpolate_scipy_wrapper
new_y = method(x, y, new_x)
File "X:\Python27-x64\lib\site-packages\scipy\interpolate\_monotone.py", line
221, in pchip_interpolate
return P(x)
File "X:\Python27-x64\lib\site-packages\scipy\interpolate\_monotone.py", line
98, in __call__
out = self._bpoly(x, der, extrapolate)
File "X:\Python27-x64\lib\site-packages\scipy\interpolate\interpolate.py",
line 673, in __call__
self._evaluate(x, nu, extrapolate, out)
File "X:\Python27-x64\lib\site-packages\scipy\interpolate\interpolate.py",
line 1071, in _evaluate
self.x, x, nu, bool(extrapolate), out, self.c.dtype)
File "_ppoly.pyx", line 846, in scipy.interpolate._ppoly.evaluate_bernstein
(scipy\interpolate\_ppoly.c:15014)
File "stringsource", line 622, in View.MemoryView.memoryview_cwrapper
(scipy\interpolate\_ppoly.c:23370)
File "stringsource", line 327, in View.MemoryView.memoryview.__cinit__
(scipy\interpolate\_ppoly.c:19922)
ValueError: buffer source array is read-only
statsmodels 0.5.0
=================
======================================================================
ERROR: statsmodels.emplike.tests.test_aft.Test_AFTModel.test_beta_vect
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File
"X:\Python27-x64\lib\site-packages\statsmodels\emplike\tests\test_aft.py", line
34, in test_beta_vect
assert_almost_equal(self.res1.test_beta([3.5, -.035], [0, 1]),
File "X:\Python27-x64\lib\site-packages\statsmodels\emplike\aft_el.py", line
481, in test_beta
llr, pval, new_weights = reg_model.el_test(b0_vals, param_nums,
return_weights=True) # Needs to be changed
File
"X:\Python27-x64\lib\site-packages\statsmodels\regression\linear_model.py",
line 1519, in el_test
stochastic_exog=stochastic_exog)
File "X:\Python27-x64\lib\site-packages\statsmodels\emplike\elregress.py",
line 58, in _opt_nuis_regress
params[nuis_param_index] = nuisance_params
ValueError: shape mismatch: value array of shape (2,) could not be broadcast to
indexing result of shape (0,)
======================================================================
ERROR: statsmodels.emplike.tests.test_origin.TestOrigin.test_ci_beta
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File
"X:\Python27-x64\lib\site-packages\statsmodels\emplike\tests\test_origin.py",
line 35, in test_ci_beta
ci = self.res1.conf_int_el(1)
File
"X:\Python27-x64\lib\site-packages\statsmodels\emplike\originregress.py", line
256, in conf_int_el
lowerl = optimize.brentq(f, lower_bound, self.params[param_num])
File "X:\Python27-x64\lib\site-packages\scipy\optimize\zeros.py", line 415,
in brentq
r = _zeros._brentq(f,a,b,xtol,rtol,maxiter,args,full_output,disp)
File
"X:\Python27-x64\lib\site-packages\statsmodels\emplike\originregress.py", line
255, in <lambda>
stochastic_exog=stochastic_exog)[0] - r0
File
"X:\Python27-x64\lib\site-packages\statsmodels\emplike\originregress.py", line
202, in el_test
return_weights=return_weights)
File
"X:\Python27-x64\lib\site-packages\statsmodels\regression\linear_model.py",
line 1519, in el_test
stochastic_exog=stochastic_exog)
File "X:\Python27-x64\lib\site-packages\statsmodels\emplike\elregress.py",
line 58, in _opt_nuis_regress
params[nuis_param_index] = nuisance_params
ValueError: shape mismatch: value array of shape (2,) could not be broadcast to
indexing result of shape (0,)
======================================================================
ERROR: statsmodels.emplike.tests.test_origin.TestOrigin.test_hypothesis_beta1
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File
"X:\Python27-x64\lib\site-packages\statsmodels\emplike\tests\test_origin.py",
line 31, in test_hypothesis_beta1
assert_almost_equal(self.res1.el_test([.0034],[1])[0],
File
"X:\Python27-x64\lib\site-packages\statsmodels\emplike\originregress.py", line
202, in el_test
return_weights=return_weights)
File
"X:\Python27-x64\lib\site-packages\statsmodels\regression\linear_model.py",
line 1519, in el_test
stochastic_exog=stochastic_exog)
File "X:\Python27-x64\lib\site-packages\statsmodels\emplike\elregress.py",
line 58, in _opt_nuis_regress
params[nuis_param_index] = nuisance_params
ValueError: shape mismatch: value array of shape (2,) could not be broadcast to
indexing result of shape (0,)
sklearn 0.14.1
==============
======================================================================
ERROR: sklearn.tests.test_common.test_regressors_train
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\sklearn\tests\test_common.py", line
798, in test_regressors_train
assert_raises(ValueError, regressor.fit, X, y[:-1])
File "X:\Python27-x64\lib\unittest\case.py", line 473, in assertRaises
callableObj(*args, **kwargs)
File "X:\Python27-x64\lib\site-packages\sklearn\linear_model\least_angle.py",
line 937, in fit
for train, test in cv)
File
"X:\Python27-x64\lib\site-packages\sklearn\externals\joblib\parallel.py", line
516, in __call__
for function, args, kwargs in iterable:
File "X:\Python27-x64\lib\site-packages\sklearn\linear_model\least_angle.py",
line 937, in <genexpr>
for train, test in cv)
IndexError: index 199 is out of bounds for axis 1 with size 199
======================================================================
FAIL: sklearn.utils.tests.test_extmath.test_random_weights
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\sklearn\utils\tests\test_extmath.py",
line 68, in test_random_weights
assert_true(np.all(score.ravel() == w[:, :5].sum(1)))
AssertionError: False is not true
skimage 0.10.0
==============
======================================================================
ERROR: test_join.test_relabel_sequential_offset1
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File
"X:\Python27-x64\lib\site-packages\skimage\segmentation\tests\test_join.py",
line 30, in test_relabel_sequential_offset1
ar_relab, fw, inv = relabel_sequential(ar)
File "X:\Python27-x64\lib\site-packages\skimage\segmentation\_join.py", line
127, in relabel_sequential
forward_map[labels0] = np.arange(offset, offset + len(labels0) + 1)
ValueError: shape mismatch: value array of shape (6,) could not be broadcast to
indexing result of shape (5,)
======================================================================
ERROR: test_join.test_relabel_sequential_offset5
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File
"X:\Python27-x64\lib\site-packages\skimage\segmentation\tests\test_join.py",
line 42, in test_relabel_sequential_offset5
ar_relab, fw, inv = relabel_sequential(ar, offset=5)
File "X:\Python27-x64\lib\site-packages\skimage\segmentation\_join.py", line
127, in relabel_sequential
forward_map[labels0] = np.arange(offset, offset + len(labels0) + 1)
ValueError: shape mismatch: value array of shape (6,) could not be broadcast to
indexing result of shape (5,)
======================================================================
ERROR: test_join.test_relabel_sequential_offset5_with0
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File
"X:\Python27-x64\lib\site-packages\skimage\segmentation\tests\test_join.py",
line 54, in test_relabel_sequential_offset5_with0
ar_relab, fw, inv = relabel_sequential(ar, offset=5)
File "X:\Python27-x64\lib\site-packages\skimage\segmentation\_join.py", line
127, in relabel_sequential
forward_map[labels0] = np.arange(offset, offset + len(labels0) + 1)
ValueError: shape mismatch: value array of shape (6,) could not be broadcast to
indexing result of shape (5,)
======================================================================
ERROR: test_join.test_relabel_sequential_dtype
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File
"X:\Python27-x64\lib\site-packages\skimage\segmentation\tests\test_join.py",
line 66, in test_relabel_sequential_dtype
ar_relab, fw, inv = relabel_sequential(ar, offset=5)
File "X:\Python27-x64\lib\site-packages\skimage\segmentation\_join.py", line
127, in relabel_sequential
forward_map[labels0] = np.arange(offset, offset + len(labels0) + 1)
ValueError: shape mismatch: value array of shape (6,) could not be broadcast to
indexing result of shape (5,)
tables 3.1.1
============
======================================================================
ERROR: test05b_modifyColumns (tables.tests.test_nestedtypes.WriteNoReopen)
Modifying two nested columns (modify_columns).
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\tables\tests\common.py", line 144, in
newmethod
return oldmethod(self, *args, **kwargs)
File "X:\Python27-x64\lib\site-packages\tables\tests\test_nestedtypes.py",
line 527, in test05b_modifyColumns
dtype=raCols.dtype)
File "D:\Build\Test\numpy-build\numpy\core\records.py", line 519, in
fromarrays
arrayList = [sb.asarray(x) for x in arrayList]
File "D:\Build\Test\numpy-build\numpy\core\numeric.py", line 461, in asarray
return array(a, dtype, copy=False, order=order)
File "X:\Python27-x64\lib\site-packages\tables\table.py", line 3549, in
__iter__
out=buf_slice)
File "X:\Python27-x64\lib\site-packages\tables\table.py", line 1975, in read
arr = self._read(start, stop, step, field, out)
File "X:\Python27-x64\lib\site-packages\tables\table.py", line 1879, in _read
bytes_required))
ValueError: output array size invalid, got 8 bytes, need 16 bytes
======================================================================
ERROR: test05b_modifyColumns (tables.tests.test_nestedtypes.WriteReopen)
Modifying two nested columns (modify_columns).
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\tables\tests\common.py", line 144, in
newmethod
return oldmethod(self, *args, **kwargs)
File "X:\Python27-x64\lib\site-packages\tables\tests\test_nestedtypes.py",
line 527, in test05b_modifyColumns
dtype=raCols.dtype)
File "D:\Build\Test\numpy-build\numpy\core\records.py", line 519, in
fromarrays
arrayList = [sb.asarray(x) for x in arrayList]
File "D:\Build\Test\numpy-build\numpy\core\numeric.py", line 461, in asarray
return array(a, dtype, copy=False, order=order)
File "X:\Python27-x64\lib\site-packages\tables\table.py", line 3549, in
__iter__
out=buf_slice)
File "X:\Python27-x64\lib\site-packages\tables\table.py", line 1975, in read
arr = self._read(start, stop, step, field, out)
File "X:\Python27-x64\lib\site-packages\tables\table.py", line 1879, in _read
bytes_required))
ValueError: output array size invalid, got 8 bytes, need 16 bytes
bottleneck 0.8.0
================
======================================================================
FAIL: Test nansum.
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\bottleneck\tests\func_test.py", line
80, in unit_maker
assert_array_equal(actual, desired, err_msg)
File "D:\Build\Test\numpy-build\numpy\testing\utils.py", line 734, in
assert_array_equal
verbose=verbose, header='Arrays are not equal')
File "D:\Build\Test\numpy-build\numpy\testing\utils.py", line 623, in
assert_array_compare
chk_same_position(x_isnan, y_isnan, hasval='nan')
File "D:\Build\Test\numpy-build\numpy\testing\utils.py", line 603, in
chk_same_position
raise AssertionError(msg)
AssertionError:
Arrays are not equal
func nansum | input a24 (float32) | shape (0L,) | axis -1
Input array:
[]
x and y nan location mismatch:
x: array(nan, dtype=float32)
y: array(0.0, dtype=float32)
======================================================================
FAIL: Test move_nansum.
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\bottleneck\tests\move_test.py", line
63, in unit_maker
err_msg)
File "D:\Build\Test\numpy-build\numpy\testing\utils.py", line 836, in
assert_array_almost_equal
precision=decimal)
File "D:\Build\Test\numpy-build\numpy\testing\utils.py", line 623, in
assert_array_compare
chk_same_position(x_isnan, y_isnan, hasval='nan')
File "D:\Build\Test\numpy-build\numpy\testing\utils.py", line 603, in
chk_same_position
raise AssertionError(msg)
AssertionError:
Arrays are not almost equal to 5 decimals
func move_nansum | window 1 | input a6 (float32) | shape (4L,) | axis -1
Input array:
[ nan 1. 2. 3.]
x and y nan location mismatch:
x: array([ nan, 1., 2., 3.], dtype=float32)
y: array([ 0., 1., 2., 3.], dtype=float32)
pyfits 3.2.4
============
======================================================================
ERROR: pyfits.tests.test_table.TestTableFunctions.test_mask_array
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\pyfits\tests\test_table.py", line
962, in test_mask_array
hdu.writeto(self.temp('newtable.fits'))
File "X:\Python27-x64\lib\site-packages\pyfits\hdu\base.py", line 1646, in
writeto
checksum=checksum)
File "X:\Python27-x64\lib\site-packages\pyfits\hdu\hdulist.py", line 644, in
writeto
hdu._prewriteto(checksum=checksum)
File "X:\Python27-x64\lib\site-packages\pyfits\hdu\table.py", line 384, in
_prewriteto
self.data._scale_back()
File "X:\Python27-x64\lib\site-packages\pyfits\fitsrec.py", line 1015, in
_scale_back
dummy[idx] = val + (pad * (itemsize - len(val)))
ValueError: assignment destination is read-only
milk 0.5.3
==========
======================================================================
FAIL: milk.tests.test_pdist.test_pdist
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\milk\tests\test_pdist.py", line 11,
in test_pdist
assert np.allclose(Dxx[i,j], np.sum((X[i]-X[j])**2))
AssertionError
======================================================================
FAIL: milk.tests.test_pdist.test_plike
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\milk\tests\test_pdist.py", line 27,
in test_plike
assert Lxx[0,0] == Lxx2[0,0]
AssertionError_______________________________________________
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