Hi David,
On Tue, Oct 15, 2013 at 12:46 PM, David Cournapeau <courn...@gmail.com>wrote: > 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 > > Not going to fix these, nanarg{max, min} now raises an exception for this case. > 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) > Iarry problem, the proper form here is xi[x,...] Chuck
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