Hi, On Thu, Apr 24, 2014 at 5:26 PM, <josef.pktd@gmail.com> wrote:
On Thu, Apr 24, 2014 at 7:29 PM, <josef.pktd@gmail.com> wrote:
On Thu, Apr 24, 2014 at 7:20 PM, Charles R Harris <charlesr.harris@gmail.com> wrote:
On Thu, Apr 24, 2014 at 5:08 PM, <josef.pktd@gmail.com> wrote:
On Thu, Apr 24, 2014 at 7:00 PM, Charles R Harris <charlesr.harris@gmail.com> wrote:
Hi Matthew,
On Thu, Apr 24, 2014 at 3:56 PM, Matthew Brett <matthew.brett@gmail.com> wrote:
Hi,
Thanks to Cark Kleffner's toolchain and some help from Clint Whaley (main author of ATLAS), I've built 64-bit windows numpy and scipy wheels for testing.
The build uses Carl's custom mingw-w64 build with static linking.
There are two harmless test failures on scipy (being discussed on the list at the moment) - tests otherwise clean.
Wheels are here:
https://nipy.bic.berkeley.edu/scipy_installers/numpy-1.8.1-cp27-none-win_amd...
https://nipy.bic.berkeley.edu/scipy_installers/scipy-0.13.3-cp27-none-win_am...
You can test with:
pip install -U pip # to upgrade pip to latest pip install -f https://nipy.bic.berkeley.edu/scipy_installers numpy scipy
Please do send feedback.
ATLAS binary here:
https://nipy.bic.berkeley.edu/scipy_installers/atlas_builds/atlas-64-full-ss...
Many thanks for Carl in particular for doing all the hard work,
Cool. After all these long years... Now all we need is a box running tests for CI.
Chuck
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I get two test failures with numpy
Josef
> np.test() Running unit tests for numpy NumPy version 1.8.1 NumPy is installed in C:\Python27\lib\site-packages\numpy Python version 2.7.3 (default, Apr 10 2012, 23:24:47) [MSC v.1500 64 bit (AMD64)] nose version 1.1.2
====================================================================== FAIL: test_iterator.test_iter_broadcasting_errors ---------------------------------------------------------------------- Traceback (most recent call last): File "C:\Python27\lib\site-packages\nose\case.py", line 197, in runTest self.test(*self.arg) File "C:\Python27\lib\site-packages\numpy\core\tests\test_iterator.py", line 657, in test_iter_broadcasting_errors '(2)->(2,newaxis)') % msg) File "C:\Python27\lib\site-packages\numpy\testing\utils.py", line 44, in assert_ raise AssertionError(msg) AssertionError: Message "operands could not be broadcast together with remapped shapes [original->remapped]: (2,3)->(2,3) (2,)->(2,newaxis) and requested shape (4,3)" doesn't contain remapped operand shape(2)->(2,newaxis)
====================================================================== FAIL: test_iterator.test_iter_array_cast ---------------------------------------------------------------------- Traceback (most recent call last): File "C:\Python27\lib\site-packages\nose\case.py", line 197, in runTest self.test(*self.arg) File "C:\Python27\lib\site-packages\numpy\core\tests\test_iterator.py", line 836, in test_iter_array_cast assert_equal(i.operands[0].strides, (-96,8,-32)) File "C:\Python27\lib\site-packages\numpy\testing\utils.py", line 255, in assert_equal assert_equal(actual[k], desired[k], 'item=%r\n%s' % (k, err_msg), verbose) File "C:\Python27\lib\site-packages\numpy\testing\utils.py", line 317, in assert_equal raise AssertionError(msg) AssertionError: Items are not equal: item=0
ACTUAL: 96L DESIRED: -96
---------------------------------------------------------------------- Ran 4828 tests in 46.306s
FAILED (KNOWNFAIL=10, SKIP=8, failures=2) <nose.result.TextTestResult run=4828 errors=0 failures=2>
Strange. That second one looks familiar, at least the "-96" part. Wonder why this doesn't show up with the MKL builds.
ok tried again, this time deleting the old numpy directories before installing
Ran 4760 tests in 42.124s
OK (KNOWNFAIL=10, SKIP=8) <nose.result.TextTestResult run=4760 errors=0 failures=0>
so pip also seems to be reusing leftover files.
all clear.
Running the statsmodels test suite, I get a failure in test_discrete.TestProbitCG where fmin_cg converges to something that differs in the 3rd decimal.
I usually only test the 32-bit version, so I don't know if this is specific to this scipy version, but we haven't seen this in a long time. I used our nightly binaries http://statsmodels.sourceforge.net/binaries/
That's interesting, you saw also we're getting failures on the tests for powell optimization because of small unit-at-last-place differences in the exp function in mingw-w64. Is there any chance you can track down where the optimization path is diverging and why? It's just that - if this is also the exp function maybe we can see if the error is exceeding reasonable bounds and then feed back to mingw-w64 and fall back to the numpy default implementation in the meantime. Cheers, Matthew