Your message dated Fri, 01 Mar 2019 23:51:43 +0000
with message-id <[email protected]>
and subject line Bug#917754: fixed in statsmodels 0.8.0-8
has caused the Debian Bug report #917754,
regarding statsmodels: FTBFS: Could not import extension
matplotlib.sphinxext.only_directives (exception: No module named
'matplotlib.sphinxext.only_directives')
to be marked as done.
This means that you claim that the problem has been dealt with.
If this is not the case it is now your responsibility to reopen the
Bug report if necessary, and/or fix the problem forthwith.
(NB: If you are a system administrator and have no idea what this
message is talking about, this may indicate a serious mail system
misconfiguration somewhere. Please contact [email protected]
immediately.)
--
917754: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=917754
Debian Bug Tracking System
Contact [email protected] with problems
--- Begin Message ---
Source: statsmodels
Version: 0.8.0-7
Severity: serious
Justification: FTBFS on amd64
Tags: buster sid
Usertags: ftbfs-20181229 ftbfs-buster
Hi,
During a rebuild of all packages in sid, your package failed to build
on amd64.
Relevant part (hopefully):
> make[2]: Entering directory '/<<PKGBUILDDIR>>/docs'
> Make static directory for images
> mkdir -p build/html/_static
> # generate the examples rst files
> Generating reST from examples folder
> #../tools/examples_rst.py
> Generating datasets from installed statsmodels.datasets
> python3 ../tools/dataset_rst.py
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.7_statsmodels/build/statsmodels/compat/pandas.py:56:
> FutureWarning: The pandas.core.datetools module is deprecated and will be
> removed in a future version. Please use the pandas.tseries module instead.
> from pandas.core import datetools
> Generating notebooks from examples/notebooks folder
> python3 ../tools/nbgenerate.py --execute=True --allow_errors=True
> RUNNING THE L-BFGS-B CODE
>
> * * *
>
> Machine precision = 2.220D-16
> N = 4 M = 10
> This problem is unconstrained.
>
> At X0 0 variables are exactly at the bounds
>
> At iterate 0 f= 4.23082D+00 |proj g|= 4.24640D-03
>
> At iterate 5 f= 4.23081D+00 |proj g|= 4.05724D-04
>
> At iterate 10 f= 4.23081D+00 |proj g|= 1.30108D-04
>
> At iterate 15 f= 4.23080D+00 |proj g|= 1.31695D-03
>
> * * *
>
> Tit = total number of iterations
> Tnf = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip = number of BFGS updates skipped
> Nact = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F = final function value
>
> * * *
>
> N Tit Tnf Tnint Skip Nact Projg F
> 4 19 23 1 0 0 3.347D-06 4.231D+00
> F = 4.2308031361514127
>
> CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
>
> Cauchy time 0.000E+00 seconds.
> Subspace minimization time 0.000E+00 seconds.
> Line search time 0.000E+00 seconds.
>
> Total User time 0.000E+00 seconds.
>
> RUNNING THE L-BFGS-B CODE
>
> * * *
>
> Machine precision = 2.220D-16
> N = 5 M = 10
> This problem is unconstrained.
>
> At X0 0 variables are exactly at the bounds
>
> At iterate 0 f= 4.22237D+00 |proj g|= 5.01920D-03
>
> At iterate 5 f= 4.22236D+00 |proj g|= 2.92744D-04
>
> At iterate 10 f= 4.22235D+00 |proj g|= 2.35973D-04
>
> At iterate 15 f= 4.22234D+00 |proj g|= 1.81119D-03
>
> At iterate 20 f= 4.22234D+00 |proj g|= 4.50080D-05
>
> * * *
>
> Tit = total number of iterations
> Tnf = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip = number of BFGS updates skipped
> Nact = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F = final function value
>
> * * *
>
> N Tit Tnf Tnint Skip Nact Projg F
> 5 20 23 1 0 0 4.501D-05 4.222D+00
> F = 4.2223359703293983
>
> CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
>
> Cauchy time 0.000E+00 seconds.
> Subspace minimization time 0.000E+00 seconds.
> Line search time 0.000E+00 seconds.
>
> Total User time 0.000E+00 seconds.
>
> RUNNING THE L-BFGS-B CODE
>
> * * *
>
> Machine precision = 2.220D-16
> N = 3 M = 12
> This problem is unconstrained.
>
> At X0 0 variables are exactly at the bounds
>
> At iterate 0 f= 4.23082D+00 |proj g|= 8.41904D-04
>
> At iterate 5 f= 4.23082D+00 |proj g|= 2.53486D-04
>
> At iterate 10 f= 4.23080D+00 |proj g|= 3.19123D-04
>
> At iterate 15 f= 4.23080D+00 |proj g|= 0.00000D+00
>
> * * *
>
> Tit = total number of iterations
> Tnf = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip = number of BFGS updates skipped
> Nact = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F = final function value
>
> * * *
>
> N Tit Tnf Tnint Skip Nact Projg F
> 3 15 19 1 0 0 0.000D+00 4.231D+00
> F = 4.2308031360254565
>
> CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
>
> Cauchy time 0.000E+00 seconds.
> Subspace minimization time 0.000E+00 seconds.
> Line search time 0.000E+00 seconds.
>
> Total User time 0.000E+00 seconds.
>
> RUNNING THE L-BFGS-B CODE
>
> * * *
>
> Machine precision = 2.220D-16
> N = 4 M = 12
> This problem is unconstrained.
>
> At X0 0 variables are exactly at the bounds
>
> At iterate 0 f= 4.22237D+00 |proj g|= 1.77725D-03
>
> At iterate 5 f= 4.22236D+00 |proj g|= 1.28875D-04
>
> At iterate 10 f= 4.22234D+00 |proj g|= 9.76019D-04
>
> At iterate 15 f= 4.22234D+00 |proj g|= 8.88178D-07
>
> * * *
>
> Tit = total number of iterations
> Tnf = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip = number of BFGS updates skipped
> Nact = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F = final function value
>
> * * *
>
> N Tit Tnf Tnint Skip Nact Projg F
> 4 17 26 1 0 0 2.665D-07 4.222D+00
> F = 4.2223359687650603
>
> CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
>
> Cauchy time 0.000E+00 seconds.
> Subspace minimization time 0.000E+00 seconds.
> Line search time 0.000E+00 seconds.
>
> Total User time 0.000E+00 seconds.
>
> RUNNING THE L-BFGS-B CODE
>
> * * *
>
> Machine precision = 2.220D-16
> N = 3 M = 12
> This problem is unconstrained.
>
> At X0 0 variables are exactly at the bounds
>
> At iterate 0 f= 2.46776D+00 |proj g|= 8.52900D-03
>
> At iterate 5 f= 2.46684D+00 |proj g|= 6.99796D-04
>
> At iterate 10 f= 2.46684D+00 |proj g|= 4.44089D-08
>
> * * *
>
> Tit = total number of iterations
> Tnf = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip = number of BFGS updates skipped
> Nact = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F = final function value
>
> * * *
>
> N Tit Tnf Tnint Skip Nact Projg F
> 3 11 21 1 0 0 4.441D-08 2.467D+00
> F = 2.4668361847172697
>
> CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
>
> Cauchy time 0.000E+00 seconds.
> Subspace minimization time 0.000E+00 seconds.
> Line search time 0.000E+00 seconds.
>
> Total User time 0.000E+00 seconds.
>
> RUNNING THE L-BFGS-B CODE
>
> * * *
>
> Machine precision = 2.220D-16
> N = 6 M = 12
> This problem is unconstrained.
>
> At X0 0 variables are exactly at the bounds
>
> At iterate 0 f= 2.31550D+00 |proj g|= 1.76959D-02
>
> At iterate 5 f= 2.31296D+00 |proj g|= 5.41003D-03
>
> At iterate 10 f= 2.31191D+00 |proj g|= 4.70468D-04
>
> At iterate 15 f= 2.31191D+00 |proj g|= 1.77636D-07
>
> * * *
>
> Tit = total number of iterations
> Tnf = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip = number of BFGS updates skipped
> Nact = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F = final function value
>
> * * *
>
> N Tit Tnf Tnint Skip Nact Projg F
> 6 17 21 1 0 0 4.441D-08 2.312D+00
> F = 2.3119057684972777
>
> CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
>
> Cauchy time 0.000E+00 seconds.
> Subspace minimization time 0.000E+00 seconds.
> Line search time 0.000E+00 seconds.
>
> Total User time 0.000E+00 seconds.
>
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_sarimax_stata.ipynb
> to /<<PKGBUILDDIR>>/examples/executed/statespace_sarimax_stata.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_sarimax_stata.ipynb
> to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_sarimax_stata.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/gls.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/gls.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/gls.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/gls.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/tsa_filters.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/tsa_filters.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/tsa_filters.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/tsa_filters.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/recursive_ls.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/recursive_ls.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/recursive_ls.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/recursive_ls.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/predict.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/predict.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/predict.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/predict.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/pca_fertility_factors.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/pca_fertility_factors.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/pca_fertility_factors.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/pca_fertility_factors.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/tsa_dates.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/tsa_dates.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/tsa_dates.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/tsa_dates.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/regression_diagnostics.ipynb
> to /<<PKGBUILDDIR>>/examples/executed/regression_diagnostics.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/regression_diagnostics.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/regression_diagnostics.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_cycles.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/statespace_cycles.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_cycles.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_cycles.html
> Executeing
> /<<PKGBUILDDIR>>/examples/notebooks/statespace_local_linear_trend.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/statespace_local_linear_trend.ipynb
> Converting
> /<<PKGBUILDDIR>>/examples/executed/statespace_local_linear_trend.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_local_linear_trend.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/tsa_arma_0.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/tsa_arma_0.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/tsa_arma_0.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/tsa_arma_0.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/glm.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/glm.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/glm.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/glm.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/formulas.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/formulas.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/formulas.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/formulas.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/tsa_arma_1.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/tsa_arma_1.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/tsa_arma_1.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/tsa_arma_1.html
> Executeing
> /<<PKGBUILDDIR>>/examples/notebooks/statespace_sarimax_internet.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/statespace_sarimax_internet.ipynb
> Converting
> /<<PKGBUILDDIR>>/examples/executed/statespace_sarimax_internet.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_sarimax_internet.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/interactions_anova.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/interactions_anova.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/interactions_anova.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/interactions_anova.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/markov_regression.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/markov_regression.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/markov_regression.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/markov_regression.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/robust_models_1.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/robust_models_1.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/robust_models_1.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/robust_models_1.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/generic_mle.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/generic_mle.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/generic_mle.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/generic_mle.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/glm_formula.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/glm_formula.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/glm_formula.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/glm_formula.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_varmax.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/statespace_varmax.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_varmax.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_varmax.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/quantile_regression.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/quantile_regression.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/quantile_regression.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/quantile_regression.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_arma_0.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/statespace_arma_0.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_arma_0.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_arma_0.html
> Executeing
> /<<PKGBUILDDIR>>/examples/notebooks/statespace_structural_harvey_jaeger.ipynb
> to
> /<<PKGBUILDDIR>>/examples/executed/statespace_structural_harvey_jaeger.ipynb
> Converting
> /<<PKGBUILDDIR>>/examples/executed/statespace_structural_harvey_jaeger.ipynb
> to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_structural_harvey_jaeger.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/discrete_choice_overview.ipynb
> to /<<PKGBUILDDIR>>/examples/executed/discrete_choice_overview.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/discrete_choice_overview.ipynb
> to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/discrete_choice_overview.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/ols.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/ols.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/ols.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/ols.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/plots_boxplots.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/plots_boxplots.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/plots_boxplots.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/plots_boxplots.html
> Executeing
> /<<PKGBUILDDIR>>/examples/notebooks/statespace_dfm_coincident.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/statespace_dfm_coincident.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_dfm_coincident.ipynb
> to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_dfm_coincident.html
> Executeing
> /<<PKGBUILDDIR>>/examples/notebooks/categorical_interaction_plot.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/categorical_interaction_plot.ipynb
> Converting
> /<<PKGBUILDDIR>>/examples/executed/categorical_interaction_plot.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/categorical_interaction_plot.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/chi2_fitting.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/chi2_fitting.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/chi2_fitting.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/chi2_fitting.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/discrete_choice_example.ipynb
> to /<<PKGBUILDDIR>>/examples/executed/discrete_choice_example.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/discrete_choice_example.ipynb
> to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/discrete_choice_example.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/markov_autoregression.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/markov_autoregression.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/markov_autoregression.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/markov_autoregression.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/contrasts.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/contrasts.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/contrasts.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/contrasts.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/wls.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/wls.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/wls.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/wls.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/mixed_lm_example.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/mixed_lm_example.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/mixed_lm_example.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/mixed_lm_example.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/robust_models_0.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/robust_models_0.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/robust_models_0.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/robust_models_0.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/kernel_density.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/kernel_density.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/kernel_density.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/kernel_density.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/regression_plots.ipynb to
> /<<PKGBUILDDIR>>/examples/executed/regression_plots.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/regression_plots.ipynb to
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/regression_plots.html
> Finished
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_sarimax_stata.html
> Finished
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_arma_0.html
> Finished /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/gls.html
> Finished
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_structural_harvey_jaeger.html
> Finished
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/tsa_filters.html
> Finished
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/discrete_choice_overview.html
> Finished
> /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/recursive_ls.html
> Finished /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/ols.html
> Finished
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> Running sphinx-build
> sphinx-build -b html -d build/doctrees source build/html
> Running Sphinx v1.7.9
> WARNING: sphinx.ext.pngmath has been deprecated. Please use
> sphinx.ext.imgmath instead.
>
> Extension error:
> Could not import extension matplotlib.sphinxext.only_directives (exception:
> No module named 'matplotlib.sphinxext.only_directives')
> make[2]: *** [Makefile:72: html] Error 2
The full build log is available from:
http://aws-logs.debian.net/2018/12/29/statsmodels_0.8.0-7_unstable.log
A list of current common problems and possible solutions is available at
http://wiki.debian.org/qa.debian.org/FTBFS . You're welcome to contribute!
About the archive rebuild: The rebuild was done on EC2 VM instances from
Amazon Web Services, using a clean, minimal and up-to-date chroot. Every
failed build was retried once to eliminate random failures.
--- End Message ---
--- Begin Message ---
Source: statsmodels
Source-Version: 0.8.0-8
We believe that the bug you reported is fixed in the latest version of
statsmodels, which is due to be installed in the Debian FTP archive.
A summary of the changes between this version and the previous one is
attached.
Thank you for reporting the bug, which will now be closed. If you
have further comments please address them to [email protected],
and the maintainer will reopen the bug report if appropriate.
Debian distribution maintenance software
pp.
Rebecca N. Palmer <[email protected]> (supplier of updated statsmodels
package)
(This message was generated automatically at their request; if you
believe that there is a problem with it please contact the archive
administrators by mailing [email protected])
-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA256
Format: 1.8
Date: Fri, 01 Mar 2019 22:49:09 +0000
Source: statsmodels
Binary: python-statsmodels python-statsmodels-lib python-statsmodels-doc
python3-statsmodels python3-statsmodels-lib
Architecture: source
Version: 0.8.0-8
Distribution: unstable
Urgency: medium
Maintainer: Debian Science Maintainers
<[email protected]>
Changed-By: Rebecca N. Palmer <[email protected]>
Description:
python-statsmodels - Python module for the estimation of statistical models
python-statsmodels-doc - documentation and examples for statsmodels
python-statsmodels-lib - low-level implementations and bindings for statsmodels
python3-statsmodels - Python3 module for the estimation of statistical models
python3-statsmodels-lib - Python3 low-level implementations and bindings for
statsmodels
Closes: 687301 860449 882641 917754
Changes:
statsmodels (0.8.0-8) unstable; urgency=medium
.
* Team upload.
* Remove outdated information from description.
* Use sphinx.ext.mathjax rather than no-longer-existing pngmath.
This also fixes equation display Closes: #687301
* Fix spelling.
* Fix remote -> local requirejs substitution.
* Use text instead of fetching a logo.
* Make dataset caching work in Python 3.
* Extend use_cached_datasets to build more of the examples.
* Fix path and data layout exceptions in examples.
* Re-enable build-time tests, and clean up files they leave behind.
* Use upstream tests as autopkgtest.
* Move metadata to d/u/metadata, update and extend it.
* Update d/copyright.
* Fix exceptions due to newer versions of dependencies:
- "no attribute 'chisqprob'" in discrete_model
- "shape mismatch...could not be broadcast" in imputation
- "ufunc 'gammaln' not supported" in discrete_model
- "object arrays are not supported" in tsa.statespace
- "module 'pandas' has no attribute 'ols'" in tsa.vector_ar
- various IndexErrors in KaplanMeier Closes: #860449
- "unexpected keyword argument 'format'" in datasets.co2
- UnicodeDecodeError in parse_lutkepohl_data
- various issues within test and example code
* Backport the following from experimental:
.
[ Julian Taylor ]
* Use python3 also for fold_toc.py
* Use fixed locale for documentation build
.
[ Andreas Tille ]
* hardening=+all
* Use libjs-mathjax
* Extend description of -doc package
* Remove matplotlib.sphinxext.only_directives option which is
not used. Closes: #917754
* Do not try to access remote locations on buildtime test
Closes: #882641
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