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Failed

dariah_topics.postprocessing._show_gensim_topics (from nosetests)

Failing for the past 1 build (Since Failed#383 )
Took 2 ms.

Error Message

Failed doctest test for dariah_topics.postprocessing._show_gensim_topics
  File "/mnt/data/jenkins/workspace/DARIAH-Topics/dariah_topics/postprocessing.py", line 329, in _show_gensim_topics

----------------------------------------------------------------------
File "/mnt/data/jenkins/workspace/DARIAH-Topics/dariah_topics/postprocessing.py", line 352, in dariah_topics.postprocessing._show_gensim_topics
Failed example:
    isinstance(gensim2dataframe(model, 4), pd.DataFrame)
Exception raised:
    Traceback (most recent call last):
      File "/usr/lib/python3.5/doctest.py", line 1321, in __run
        compileflags, 1), test.globs)
      File "<doctest dariah_topics.postprocessing._show_gensim_topics[6]>", line 1, in <module>
        isinstance(gensim2dataframe(model, 4), pd.DataFrame)
    NameError: name 'gensim2dataframe' is not defined

-------------------- >> begin captured logging << --------------------
gensim.corpora.dictionary: INFO: adding document #0 to Dictionary(0 unique tokens: [])
gensim.corpora.dictionary: INFO: built Dictionary(4 unique tokens: ['test', 'corpus', 'testing', 'for']) from 2 documents (total 4 corpus positions)
gensim.models.ldamodel: INFO: using symmetric alpha at 1.0
gensim.models.ldamodel: INFO: using symmetric eta at 0.25
gensim.models.ldamodel: INFO: using serial LDA version on this node
gensim.models.ldamodel: INFO: running online (single-pass) LDA training, 1 topics, 1 passes over the supplied corpus of 2 documents, updating model once every 2 documents, evaluating perplexity every 2 documents, iterating 1x with a convergence threshold of 0.001000
gensim.models.ldamodel: WARNING: too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
gensim.models.ldamodel: DEBUG: bound: at document #0
gensim.models.ldamodel: INFO: -1.686 per-word bound, 3.2 perplexity estimate based on a held-out corpus of 2 documents with 4 words
gensim.models.ldamodel: INFO: PROGRESS: pass 0, at document #2/2
gensim.models.ldamodel: DEBUG: performing inference on a chunk of 2 documents
gensim.models.ldamodel: DEBUG: 0/2 documents converged within 1 iterations
gensim.models.ldamodel: DEBUG: updating topics
gensim.models.ldamodel: INFO: topic #0 (1.000): 0.250*"test" + 0.250*"corpus" + 0.250*"for" + 0.250*"testing"
gensim.models.ldamodel: INFO: topic diff=0.252138, rho=1.000000
--------------------- >> end captured logging << ---------------------

Stacktrace

  File "/usr/lib/python3.5/unittest/case.py", line 59, in testPartExecutor
    yield
  File "/usr/lib/python3.5/unittest/case.py", line 601, in run
    testMethod()
  File "/usr/lib/python3.5/doctest.py", line 2190, in runTest
    raise self.failureException(self.format_failure(new.getvalue()))
Failed doctest test for dariah_topics.postprocessing._show_gensim_topics
  File "/mnt/data/jenkins/workspace/DARIAH-Topics/dariah_topics/postprocessing.py", line 329, in _show_gensim_topics

----------------------------------------------------------------------
File "/mnt/data/jenkins/workspace/DARIAH-Topics/dariah_topics/postprocessing.py", line 352, in dariah_topics.postprocessing._show_gensim_topics
Failed example:
    isinstance(gensim2dataframe(model, 4), pd.DataFrame)
Exception raised:
    Traceback (most recent call last):
      File "/usr/lib/python3.5/doctest.py", line 1321, in __run
        compileflags, 1), test.globs)
      File "<doctest dariah_topics.postprocessing._show_gensim_topics[6]>", line 1, in <module>
        isinstance(gensim2dataframe(model, 4), pd.DataFrame)
    NameError: name 'gensim2dataframe' is not defined

-------------------- >> begin captured logging << --------------------
gensim.corpora.dictionary: INFO: adding document #0 to Dictionary(0 unique tokens: [])
gensim.corpora.dictionary: INFO: built Dictionary(4 unique tokens: ['test', 'corpus', 'testing', 'for']) from 2 documents (total 4 corpus positions)
gensim.models.ldamodel: INFO: using symmetric alpha at 1.0
gensim.models.ldamodel: INFO: using symmetric eta at 0.25
gensim.models.ldamodel: INFO: using serial LDA version on this node
gensim.models.ldamodel: INFO: running online (single-pass) LDA training, 1 topics, 1 passes over the supplied corpus of 2 documents, updating model once every 2 documents, evaluating perplexity every 2 documents, iterating 1x with a convergence threshold of 0.001000
gensim.models.ldamodel: WARNING: too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
gensim.models.ldamodel: DEBUG: bound: at document #0
gensim.models.ldamodel: INFO: -1.686 per-word bound, 3.2 perplexity estimate based on a held-out corpus of 2 documents with 4 words
gensim.models.ldamodel: INFO: PROGRESS: pass 0, at document #2/2
gensim.models.ldamodel: DEBUG: performing inference on a chunk of 2 documents
gensim.models.ldamodel: DEBUG: 0/2 documents converged within 1 iterations
gensim.models.ldamodel: DEBUG: updating topics
gensim.models.ldamodel: INFO: topic #0 (1.000): 0.250*"test" + 0.250*"corpus" + 0.250*"for" + 0.250*"testing"
gensim.models.ldamodel: INFO: topic diff=0.252138, rho=1.000000
--------------------- >> end captured logging << ---------------------