Details
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Type:
Bug
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Status: Done
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Resolution: Done
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Fix Version/s: None
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Component/s: meas_modelfit
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Labels:None
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Templates:customfield_11800 22777
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Story Points:0.25
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Epic Link:
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Sprint:Science Pipelines DM-W16-6
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Team:Data Release Production
Description
I recently upgraded my Anaconda to version 2.5 on Mac OS X El Capitan. Rebuilding lsst_apps triggers a new test failure in meas_modelfit:
F.....
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FAIL: testDerivatives (__main__.MixtureTestCase)
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Traceback (most recent call last):
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File "tests/testMixture.py", line 172, in testDerivatives
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doTest(g, x)
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File "tests/testMixture.py", line 168, in doTest
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self.assertClose(analyticGradient, numericGradient, rtol=1E-6)
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File "/Users/timj/work/lsstsw/stack/DarwinX86/utils/2016_01.0+0b596edbb3/python/lsst/utils/tests.py", line 368, in assertClose
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testCase.assertFalse(failed, msg="\n".join(msg))
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AssertionError: 1/3 elements differ with rtol=1e-06, atol=2.22044604925e-16
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-7.41146749152e-07 != -7.41145697331e-07 (diff=1.05182109542e-12/7.41146749152e-07=1.41918060981e-06)
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Switching to the previous anaconda (2.4 I think) the numbers above are:
-7.41146749152e-07 != -7.41146239432e-07 (diff=5.0971982368e-13/7.41146749152e-07=6.87744801233e-07)
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The following patch fixes it:
diff --git a/tests/testMixture.py b/tests/testMixture.py
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index a070748..804495e 100755
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--- a/tests/testMixture.py
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+++ b/tests/testMixture.py
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@@ -165,7 +165,7 @@ class MixtureTestCase(lsst.utils.tests.TestCase):
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analyticGradient = numpy.zeros(n, dtype=float)
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analyticHessian = numpy.zeros((n,n), dtype=float)
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mixture.evaluateDerivatives(point, analyticGradient, analyticHessian)
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- self.assertClose(analyticGradient, numericGradient, rtol=1E-6)
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+ self.assertClose(analyticGradient, numericGradient, rtol=1.5E-6)
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self.assertClose(analyticHessian, numericHessian, rtol=1E-6)
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for x in numpy.random.randn(10, g.getDimension()): |
but I have no idea how reasonable that is. It is obviously disconcerting that updating the numerical library can change our tests again.