Mailman 3 January 2011 - SciPy-Dev

kde evaluate and dtypes, atleast_float ?
by josef.pktd＠gmail.com Jan. 15, 2011

Jan. 15, 2011

http://projects.scipy.org/scipy/ticket/1181 the dtypes in kde evaluate only makes sense if we have at least float integer input produces nonsense evaluate has points = atleast_2d(points).astype(self.dataset.dtype) .... result = zeros((m,), points.dtype) .... result += exp(-energy) I don't know which dtypes kde is supposed to handle, but what's the best way to guarantee that the result is "atleast_float", so that a probability makes sense. I don't know what a complex probability is, but handling complex is useful for complex derivatives. Thanks, Josef

1 0

one failure in scipy trunk
by josef.pktd＠gmail.com Jan. 14, 2011

Jan. 14, 2011

compiled against numpy 1.5.1 Josef ====================================================================== FAIL: Test singular pair ---------------------------------------------------------------------- Traceback (most recent call last): File "c:\programs\python25\lib\site-packages\nose-0.11.1-py2.5.egg\nose\case.p y", line 183, in runTest self.test(*self.arg) File "C:\Josef\_progs\Subversion\scipy_trunk_g09\dist\scipy-0.10.0.dev7027.win 32\Programs\Python25\Lib\site-packages\scipy\linalg\tests\test_decomp.py", line 200, in test_singular self._check_gen_eig(A, B) File "C:\Josef\_progs\Subversion\scipy_trunk_g09\dist\scipy-0.10.0.dev7027.win 32\Programs\Python25\Lib\site-packages\scipy\linalg\tests\test_decomp.py", line 189, in _check_gen_eig err_msg=msg) File "C:\Programs\Python25\Lib\site-packages\numpy\testing\utils.py", line 774 , in assert_array_almost_equal header='Arrays are not almost equal') File "C:\Programs\Python25\Lib\site-packages\numpy\testing\utils.py", line 618 , in assert_array_compare raise AssertionError(msg) AssertionError: Arrays are not almost equal array([[22, 34, 31, 31, 17], [45, 45, 42, 19, 29], [39, 47, 49, 26, 34], [27, 31, 26, 21, 15], [38, 44, 44, 24, 30]]) array([[13, 26, 25, 17, 24], [31, 46, 40, 26, 37], [26, 40, 19, 25, 25], [16, 25, 27, 14, 23], [24, 35, 18, 21, 22]]) (mismatch 50.0%) x: array([ 3.57527348e-16 -2.30736377e-08j, 3.57527348e-16 +2.30736377e-08j, 2.86330799e-01 +0.00000000e+00j, 2.00000000e+00 +0.00000000e+00j]) y: array([ -1.31566605e-01+0.j, -3.23644701e-08+0.j, 3.23644694e-08+0.j, 2.00000000e+00+0.j]) ---------------------------------------------------------------------- Ran 4810 tests in 277.406s FAILED (KNOWNFAIL=12, SKIP=35, failures=1) <nose.result.TextTestResult run=4810 errors=0 failures=1>

3 6

speed of nosetests scipy.stats
by josef.pktd＠gmail.com Jan. 13, 2011

Jan. 13, 2011

nosetests scipy.stats includes the "slow" tests, but if I remember correctly they ran in around 7 minutes on my computer. Now I get: Ran 1572 tests in 2479.594s Is it slow for anyone else, or is it just because my computer is busy with other things also. I gave up running my fit tests after about an hour or so. scipy 0.9b1, numpy 1.5.1 official installers and what kind of operation produces "Warning: invalid value encountered in subtract" ? I get hundreds of these Josef

6 9

review request - test noise clean up
by Ralf Gommers Jan. 13, 2011

Jan. 13, 2011

Hi, I cleaned most of the noise in the test output (only stats module and a few random ones left): https://github.com/rgommers/scipy/tree/testnoise Can someone please check this and confirm that this can go into trunk as well as 0.9.x? Especially for the scipy.special commit. There are a few warnings that I'll only silence in 0.9.x because they indicate actual problems or should be fixed elsewhere (like astype() in numpy: http://projects.scipy.org/numpy/ticket/1709). For the ComplexWarning filter, is it preferable to be really granular with linenos like warnings.filterwarnings('ignore', category=np.ComplexWarning, lineno=98) or just filter it out of the whole module? Thanks, Ralf

6 9

Bug in KDTree
by Benjamin Root Jan. 11, 2011

Jan. 11, 2011

Hello, I came across an issue using KDTree. I searched the bug list, and it appears that there has already been a patch submitted for review. I have added comments to the bug report and I think the patch is good to go. I am not an expert in KDTree myself, but I think the logic is sound. http://projects.scipy.org/scipy/ticket/1052 If the first node of the tree is a leafnode, then query_pairs() will fail if the points are closer than the distance threshold. This is because the algorithm is assuming that the first node will always be an innernode. By rearranging the if-statements so that a check for a leafnode is done first, you protect against such a situation. At least, that is my understanding. I welcome comments on this. Thanks, Ben Root

2 5