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Bug#966712: statsmodels: debci tests fail

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  Bug#966712: statsmodels: debci tests fail Drew Parsons <dparsons@debian.org> - 2020-08-02 13:30 +0200
    Bug#966712: statsmodels: debci tests fail "Rebecca N. Palmer" <rebecca_palmer@zoho.com> - 2020-08-02 18:00 +0200

#1020131 — Bug#966712: statsmodels: debci tests fail

Source: statsmodels
Severity: normal

Three statsmodels debci tests (autopkgtest) are failing against
scipy 1.5.2:

../../../../usr/lib/python3/dist-packages/statsmodels/base/tests/test_optimize.py::test_full_output_false FAILED [  1%]
../../../../usr/lib/python3/dist-packages/statsmodels/base/tests/test_optimize.py::test_full_output FAILED [  1%]
../../../../usr/lib/python3/dist-packages/statsmodels/regression/tests/test_rolling.py::test_plot FAILED [ 30%]


Error traces:

=================================== FAILURES ===================================
____________________________ test_full_output_false ____________________________

reset_randomstate = None

    @pytest.mark.smoke
    def test_full_output_false(reset_randomstate):
        # newton needs f, score, start, fargs, kwargs
        # bfgs needs f, score start, fargs, kwargs
        # nm needs ""
        # cg ""
        # ncg ""
        # powell ""
        for method in fit_funcs:
            func = fit_funcs[method]
            if method == "newton":
                xopt, retvals = func(dummy_func, dummy_score, [1], (), {},
                        hess=dummy_hess, full_output=False, disp=0)
    
            else:
                xopt, retvals = func(dummy_func, dummy_score, [1], (), {},
                    full_output=False, disp=0)
            assert_(retvals is None)
            if method == "powell":
                #NOTE: I think I reported this? Might be version/optimize API
                # dependent
>               assert_(xopt.shape == () and xopt.size == 1)
E               AssertionError

/usr/lib/python3/dist-packages/statsmodels/base/tests/test_optimize.py:53: AssertionError
_______________________________ test_full_output _______________________________

reset_randomstate = None

    def test_full_output(reset_randomstate):
        for method in fit_funcs:
            func = fit_funcs[method]
            if method == "newton":
                xopt, retvals = func(dummy_func, dummy_score, [1], (), {},
                                     hess=dummy_hess, full_output=True, disp=0)
    
            else:
                xopt, retvals = func(dummy_func, dummy_score, [1], (), {},
                                     full_output=True, disp=0)
    
            assert_(retvals is not None)
            assert_('converged' in retvals)
    
            if method == "powell":
                #NOTE: I think I reported this? Might be version/optimize API
                # dependent
>               assert_(xopt.shape == () and xopt.size == 1)
E               AssertionError

/usr/lib/python3/dist-packages/statsmodels/base/tests/test_optimize.py:75: AssertionError
__________________________________ test_plot ___________________________________

    @pytest.mark.matplotlib
    def test_plot():
        import matplotlib.pyplot as plt
    
        y, x, w = gen_data(250, 3, True, pandas=True)
        fmla = 'y ~ 1 + x0 + x1 + x2'
        data = pd.concat([y, x], axis=1)
        mod = RollingWLS.from_formula(fmla, window=100, data=data, weights=w)
        res = mod.fit()
        fig = res.plot_recursive_coefficient()
        assert isinstance(fig, plt.Figure)
        res.plot_recursive_coefficient(variables=2, alpha=None,
                                       figsize=(30, 7))
        res.plot_recursive_coefficient(variables='x0', alpha=None,
                                       figsize=(30, 7))
        res.plot_recursive_coefficient(variables=[0, 2], alpha=None,
                                       figsize=(30, 7))
        res.plot_recursive_coefficient(variables=['x0'], alpha=None,
                                       figsize=(30, 7))
        res.plot_recursive_coefficient(variables=['x0', 'x1', 'x2'], alpha=None,
                                       figsize=(30, 7))
        with pytest.raises(ValueError, match='variable x4 is not an integer'):
            res.plot_recursive_coefficient(variables='x4')
    
        fig = plt.Figure()
        with pytest.warns(UserWarning, match="tight_layout"):
>           out = res.plot_recursive_coefficient(fig=fig)
E           Failed: DID NOT WARN. No warnings of type (<class 'UserWarning'>,) matching ('tight_layout') was emitted. The list of emitted warnings is: [MatplotlibDeprecationWarning('savefig() got unexpected keyword argument "dpi" which is no longer supported as of 3.3 and will become an error two minor releases later')].

/usr/lib/python3/dist-packages/statsmodels/regression/tests/test_rolling.py:260: Failed






-- System Information:
Debian Release: bullseye/sid
  APT prefers unstable
  APT policy: (500, 'unstable'), (1, 'experimental')
Architecture: amd64 (x86_64)
Foreign Architectures: i386

Kernel: Linux 5.7.0-2-amd64 (SMP w/8 CPU threads)
Locale: LANG=en_AU.UTF-8, LC_CTYPE=en_AU.UTF-8 (charmap=UTF-8), LANGUAGE=en_AU:en
Shell: /bin/sh linked to /usr/bin/dash
Init: systemd (via /run/systemd/system)
LSM: AppArmor: enabled

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#1020162

Control: severity -1 serious
Control: tags -1 fixed-upstream patch

test_full_output*:
https://github.com/statsmodels/statsmodels/issues/6771
test_plot:
https://github.com/statsmodels/statsmodels/commit/fa8739e9d2822fe985bc96cd31bb3eb568fd9dc7

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