On Sat, Nov 29, 2014 at 02:11:48PM +0100, Michael Banck wrote: > Hi, > > On Wed, Nov 26, 2014 at 11:57:41PM +0100, Michael Banck wrote: > > On Wed, Nov 26, 2014 at 05:47:57PM -0500, Yaroslav Halchenko wrote: > > > Upload it without delay, and let's hope none off those doesn't veil > > > the actual problem in the code :-) > > > > OK, I will sponsor that upload as well tomorrow. > > Unfortunately, I did not get around to that yet, but was looking now. > > The problem is: As -1.1 has already been uploaded and accepted in the > archive, what we need is -1.2 patch on top of that with a new changelog > and everything. > > Tomasz, I will try to extract that from your two NMU diffs later today > if you don't get around sending a new patch until then.
I've uploaded the attached debdiff now. Michael
diff -Nru statsmodels-0.4.2/debian/changelog statsmodels-0.4.2/debian/changelog --- statsmodels-0.4.2/debian/changelog 2014-11-23 18:56:37.000000000 +0100 +++ statsmodels-0.4.2/debian/changelog 2014-11-29 16:33:12.000000000 +0100 @@ -1,3 +1,15 @@ +statsmodels (0.4.2-1.2) testing; urgency=medium + + * Non-maintainer upload, incorporating changes by Tomasz Buchert. + * debian/patches/scipy-rvs-interface.patch: Removed again and ... + * debian/patches/testsuite-fixes.patch: ... folded into this patch, just + raising a nose.SkipTest() for the problematic test case. + * debian/patches/testsuite-fixes.patch: Amended for test_discrete.py, also + skipping this test case via raising a nose.SkipTest(), as it leads to a + FTBFS error on i386 (Closes: #768695). + + -- Michael Banck <mba...@debian.org> Sat, 29 Nov 2014 16:19:51 +0100 + statsmodels (0.4.2-1.1) testing; urgency=medium * Non-maintainer upload. diff -Nru statsmodels-0.4.2/debian/patches/scipy-rvs-interface.patch statsmodels-0.4.2/debian/patches/scipy-rvs-interface.patch --- statsmodels-0.4.2/debian/patches/scipy-rvs-interface.patch 2014-11-23 18:56:37.000000000 +0100 +++ statsmodels-0.4.2/debian/patches/scipy-rvs-interface.patch 1970-01-01 01:00:00.000000000 +0100 @@ -1,128 +0,0 @@ -Description: remove tests that use uncompatible scipy interface - The tests use an "rvs" method which has an incompatible - interface. We remove these failing tests altogether. - ---- statsmodels-0.4.2.orig/statsmodels/sandbox/tests/test_gam.py -+++ statsmodels-0.4.2/statsmodels/sandbox/tests/test_gam.py -@@ -187,121 +187,3 @@ class TestAdditiveModel(BaseAM, CheckAM) - const = res_gam.alpha + sum([ss.params[1] for ss in m.smoothers]) - #print const, slopes - res1.params = np.array([const] + slopes) -- -- --class BaseGAM(BaseAM, CheckGAM): -- -- def init(self): -- nobs = self.nobs -- y_true, x, exog = self.y_true, self.x, self.exog -- if not hasattr(self, 'scale'): -- scale = 1 -- else: -- scale = self.scale -- -- f = self.family -- -- self.mu_true = mu_true = f.link.inverse(y_true) -- -- np.random.seed(8765993) -- #y_obs = np.asarray([stats.poisson.rvs(p) for p in mu], float) -- y_obs = self.rvs(mu_true, scale=scale, size=nobs) #this should work -- m = GAM(y_obs, x, family=f) #TODO: y_obs is twice __init__ and fit -- m.fit(y_obs, maxiter=100) -- res_gam = m.results -- self.res_gam = res_gam #attached for debugging -- self.mod_gam = m #attached for debugging -- -- res_glm = GLM(y_obs, exog, family=f).fit() -- -- #Note: there still are some naming inconsistencies -- self.res1 = res1 = Dummy() #for gam model -- #res2 = Dummy() #for benchmark -- self.res2 = res2 = res_glm #reuse existing glm results, will add additional -- -- #eta in GLM terminology -- res2.y_pred = res_glm.model.predict(res_glm.params, exog, linear=True) -- res1.y_pred = res_gam.predict(x) -- res1.y_predshort = res_gam.predict(x[:10]) #, linear=True) -- -- #mu -- res2.mu_pred = res_glm.model.predict(res_glm.params, exog, linear=False) -- res1.mu_pred = res_gam.mu -- -- #parameters -- slopes = [i for ss in m.smoothers for i in ss.params[1:]] -- const = res_gam.alpha + sum([ss.params[1] for ss in m.smoothers]) -- res1.params = np.array([const] + slopes) -- -- --class TestGAMPoisson(BaseGAM): -- -- def __init__(self): -- super(self.__class__, self).__init__() #initialize DGP -- -- self.family = family.Poisson() -- self.rvs = stats.poisson.rvs -- -- self.init() -- --class TestGAMBinomial(BaseGAM): -- -- def __init__(self): -- super(self.__class__, self).__init__() #initialize DGP -- -- self.family = family.Binomial() -- self.rvs = stats.bernoulli.rvs -- -- self.init() -- --class _estGAMGaussianLogLink(BaseGAM): -- #test failure, but maybe precision issue, not far off -- #>>> np.mean(np.abs(tt.res2.mu_pred - tt.mu_true)) -- #0.80409736263199649 -- #>>> np.mean(np.abs(tt.res2.mu_pred - tt.mu_true))/tt.mu_true.mean() -- #0.023258245077813208 -- #>>> np.mean((tt.res2.mu_pred - tt.mu_true)**2)/tt.mu_true.mean() -- #0.022989403735692578 -- -- def __init__(self): -- super(self.__class__, self).__init__() #initialize DGP -- -- self.family = family.Gaussian(links.log) -- self.rvs = stats.norm.rvs -- self.scale = 5 -- -- self.init() -- -- --class TestGAMGamma(BaseGAM): -- -- def __init__(self): -- super(self.__class__, self).__init__() #initialize DGP -- -- self.family = family.Gamma(links.log) -- self.rvs = stats.gamma.rvs -- -- self.init() -- --class _estGAMNegativeBinomial(BaseGAM): -- #rvs generation doesn't work, nbinom needs 2 parameters -- -- def __init__(self): -- super(self.__class__, self).__init__() #initialize DGP -- -- self.family = family.NegativeBinomial() -- self.rvs = stats.nbinom.rvs -- -- self.init() -- --if __name__ == '__main__': -- t1 = TestAdditiveModel() -- t1.test_predict() -- t1.test_params() -- -- for tt in [TestGAMPoisson, TestGAMBinomial, TestGAMGamma, -- _estGAMGaussianLogLink]: #, TestGAMNegativeBinomial]: -- tt = tt() -- tt.test_predict() -- tt.test_params() -- tt.test_mu diff -Nru statsmodels-0.4.2/debian/patches/series statsmodels-0.4.2/debian/patches/series --- statsmodels-0.4.2/debian/patches/series 2014-11-23 18:56:37.000000000 +0100 +++ statsmodels-0.4.2/debian/patches/series 2014-11-29 16:40:05.000000000 +0100 @@ -1,3 +1,2 @@ sphinx-ipython.patch -scipy-rvs-interface.patch testsuite-fixes.patch diff -Nru statsmodels-0.4.2/debian/patches/testsuite-fixes.patch statsmodels-0.4.2/debian/patches/testsuite-fixes.patch --- statsmodels-0.4.2/debian/patches/testsuite-fixes.patch 2014-11-23 18:56:37.000000000 +0100 +++ statsmodels-0.4.2/debian/patches/testsuite-fixes.patch 2014-11-29 14:08:36.000000000 +0100 @@ -1,17 +1,22 @@ Description: Fix various testsuite problems The testsuite depends on version-specific functionality - of various dependencies like numpy, scipy. This patches fixes + of various dependencies like numpy or scipy. This patch fixes problems caused by versions in jessie release of these dependencies. . statsmodels/tools/tools.py: - => unexisting attribute in numpy object + => unexisting attribute in numpy object statsmodels/sandbox/distributions/tests/testtransf.py: statsmodels/tsa/filters/tests/test_filters.py: - => scipy interface incompatibilities + => scipy interface incompatibilities statsmodels/tsa/base/tests/test_datetools.py: - => DateRange class is not present in jessie pandas + => DateRange class is not present in jessie pandas statsmodels/sandbox/distributions/extras.py: - => a mistake fixed in newer releases of statsmodels + => a mistake fixed in newer releases of statsmodels + statsmodels/sandbox/tests/test_gam.py: + => incompatible scipy interface for rvs method + statsmodels/discrete/tests/test_discrete.py: + => failures due to differences between architectures, see + https://github.com/statsmodels/statsmodels/commit/ca701e7a --- a/statsmodels/tools/tools.py +++ b/statsmodels/tools/tools.py @@ -55,14 +60,13 @@ assert_almost_equal(self.res1.B, self.res2.B, DECIMAL_4) --- a/statsmodels/tsa/vector_ar/tests/test_var.py +++ b/statsmodels/tsa/vector_ar/tests/test_var.py -@@ -502,7 +502,7 @@ - def have_pandas(): - try: - import pandas as _ -- return True -+ return hasattr(_, "DateRange") - except ImportError: - return False +@@ -494,6 +494,7 @@ + resultspath = basepath + '/tsa/vector_ar/tests/results/' + + def get_lutkepohl_data(name='e2'): ++ raise nose.SkipTest("Skipped because of missing DateRange") + lut_data = basepath + '/tsa/vector_ar/data/' + path = lut_data + '%s.dat' % name --- a/statsmodels/tsa/base/tests/test_datetools.py +++ b/statsmodels/tsa/base/tests/test_datetools.py @@ -130,3 +134,32 @@ extradoc = ''' Skewed T distribution by Azzalini, A. & Capitanio, A. (2003)_ +--- a/statsmodels/sandbox/tests/test_gam.py ++++ b/statsmodels/sandbox/tests/test_gam.py +@@ -85,7 +85,7 @@ + from statsmodels.genmod.families import family, links + from statsmodels.genmod.generalized_linear_model import GLM + from statsmodels.regression.linear_model import OLS +- ++import nose + + class Dummy(object): + pass +@@ -192,6 +192,7 @@ + class BaseGAM(BaseAM, CheckGAM): + + def init(self): ++ raise nose.SkipTest("Incompatible scipy interface") + nobs = self.nobs + y_true, x, exog = self.y_true, self.x, self.exog + if not hasattr(self, 'scale'): +--- a/statsmodels/discrete/tests/test_discrete.py ++++ b/statsmodels/discrete/tests/test_discrete.py +@@ -244,6 +244,7 @@ + class TestProbitCG(CheckModelResults): + @classmethod + def setupClass(cls): ++ raise SkipTest("This method does not converge on some architectures") + if iswindows: # does this work with classmethod? + raise SkipTest("fmin_cg sometimes fails to converge on windows") + data = sm.datasets.spector.load()
