Thanks for your answers. DBSCAN has the correct doc because the fit_predict method is not inherited, but it has its own implementation (because of the additional parameter sample_weight).
I have forked the sklearn repo. I work in a virtualenv (virtualenv venv3 --no-site-packages --python python3.5). *python3 setup.py install* completes, but *make test-code* and *make doc-noplot* fail. Do you have any idea about the origin of these errors ? I intend to install work on the python3 version. When I run make test-code, I am surprise that there are references to /usr/lib/python2.7/. Thanks for your help, Anaël Beaugnon * **make doc-noplot* Exception occurred: File "/usr/lib/python3.5/zipfile.py", line 1435, in write st = os.stat(filename) FileNotFoundError: [Errno 2] No such file or directory: '/<dir>/scikit-learn/doc/auto_examples/plot_digits_pipe.ipynb' The full traceback has been saved in /tmp/sphinx-err-ivjeif0v.log, if you want to report the issue to the developers. Please also report this if it was a user error, so that a better error message can be provided next time. A bug report can be filed in the tracker at <https://github.com/sphinx-doc/sphinx/issues>. Thanks! File /tmp/sphinx-err-ivjeif0v.log # Sphinx version: 1.7.4 # Python version: 3.5.3 (CPython) # Docutils version: 0.14 # Jinja2 version: 2.10 # Last messages: # Loaded extensions: Traceback (most recent call last): File "/<dir>/scikit-learn/venv3/lib/python3.5/site-packages/sphinx/cmdline.py", line 303, in main args.warningiserror, args.tags, args.verbosity, args.jobs) File "/<dir>/scikit-learn/venv3/lib/python3.5/site-packages/sphinx/application.py", line 233, in __init__ self._init_builder() File "/<dir>/scikit-learn/venv3/lib/python3.5/site-packages/sphinx/application.py", line 311, in _init_builder self.emit('builder-inited') File "/<dir>/scikit-learn/venv3/lib/python3.5/site-packages/sphinx/application.py", line 444, in emit return self.events.emit(event, self, *args) File "/<dir>/scikit-learn/venv3/lib/python3.5/site-packages/sphinx/events.py", line 79, in emit results.append(callback(*args)) File "/<dir>/scikit-learn/venv3/lib/python3.5/site-packages/sphinx_gallery/gen_gallery.py", line 247, in generate_gallery_rst download_fhindex = generate_zipfiles(gallery_dir) File "/<dir>/scikit-learn/venv3/lib/python3.5/site-packages/sphinx_gallery/downloads.py", line 115, in generate_zipfiles jy_zipfile = python_zip(listdir, gallery_dir, ".ipynb") File "/<dir>/scikit-learn/venv3/lib/python3.5/site-packages/sphinx_gallery/downloads.py", line 69, in python_zip zipf.write(file_src, os.path.relpath(file_src, gallery_path)) File "/usr/lib/python3.5/zipfile.py", line 1435, in write st = os.stat(filename) FileNotFoundError: [Errno 2] No such file or directory: '/<dir>/scikit-learn/doc/auto_examples/plot_digits_pipe.ipynb' *make test-code* ======================================================================= ERRORS ======================================================================= _________________________________________________________________ ERROR collecting __________________________________________________________________ /usr/lib/python2.7/dist-packages/py/_path/common.py:366: in visit for x in Visitor(fil, rec, ignore, bf, sort).gen(self): /usr/lib/python2.7/dist-packages/py/_path/common.py:405: in gen if p.check(dir=1) and (rec is None or rec(p))]) /usr/lib/python2.7/dist-packages/_pytest/main.py:682: in _recurse ihook = self.gethookproxy(path) /usr/lib/python2.7/dist-packages/_pytest/main.py:587: in gethookproxy my_conftestmodules = pm._getconftestmodules(fspath) /usr/lib/python2.7/dist-packages/_pytest/config.py:339: in _getconftestmodules mod = self._importconftest(conftestpath) /usr/lib/python2.7/dist-packages/_pytest/config.py:364: in _importconftest raise ConftestImportFailure(conftestpath, sys.exc_info()) E ConftestImportFailure: ImportError('No module named _check_build\n___________________________________________________________________________\nContents of /<dir>/scikit-learn/sklearn/__check_build:\n__pycache__ setup.py __init__.pyc\n_check_build.pyx _check_build.cpython-35m-x86_64-linux-gnu.so_check_build.c\n__init__.py\n___________________________________________________________________________\nIt seems that scikit-learn has not been built correctly.\n\nIf you have installed scikit-learn from source, please do not forget\nto build the package before using it: run `python setup.py install` or\n`make` in the source directory.\n\nIf you have used an installer, please check that it is suited for your\nPython version, your operating system and your platform.',) E File "/<dir>/scikit-learn/sklearn/__init__.py", line 63, in <module> E from . import __check_build E File "/<dir>/scikit-learn/sklearn/__check_build/__init__.py", line 46, in <module> E raise_build_error(e) E File "/<dir>/scikit-learn/sklearn/__check_build/__init__.py", line 41, in raise_build_error E %s""" % (e, local_dir, ''.join(dir_content).strip(), msg)) !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Interrupted: 1 errors during collection !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ============================================================== 1 error in 0.27 seconds =============================================================== Le 23/05/2018 à 18:09, Andreas Mueller a écrit : > > +1 for a PR on fit_predict docs. This is probably due to the > inheritance structure. > Though it's weird that DBSCAN has the correct docs. > > I'm not sure about renaming affinity, but we can discuss that. I agree > it's misleading. > > > On 5/23/18 8:01 AM, Tom DLT wrote: >> Hi Anaël, >> >> Thanks for spotting these inconsistencies. >> You are very welcome to open pull-requests and/or issues on the >> GitHub tracker >> (cf. >> http://scikit-learn.org/stable/developers/contributing.html#contributing-code) >> The documentation issue should be straightforward. >> The parameter renaming would need a proper deprecation cycle (cf >> http://scikit-learn.org/stable/developers/contributing.html#deprecation). >> >> See you on GitHub, >> >> Tom >> >> 2018-05-23 11:50 GMT+02:00 Beaugnon Anael <anael.beaug...@ssi.gouv.fr >> <mailto:anael.beaug...@ssi.gouv.fr>>: >> >> Dear all, >> >> Three clustering algorithms can take as input distance or >> similarity matrices instead of the observations >> (AgglomerativeClustering >> >> <http://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html#sklearn.cluster.AgglomerativeClustering>, >> AffinityPropagation >> >> <http://scikit-learn.org/stable/modules/generated/sklearn.cluster.AffinityPropagation.html#sklearn.cluster.AffinityPropagation>, >> and DBSCAN >> >> <http://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html#sklearn.cluster.DBSCAN>), >> but there are inconsistencies in their documentations. >> >> >> *DBSCAN :* >> The documentation explains clearly how to run DBSCAN with a >> precomputed distance matrix. >> Constructor:/ >> metric: If metric is “precomputed”, X is assumed to be a >> distance matrix and must be square. >> / >> fit / fit_predict /: >> X: A feature array, or array of distances between samples >> if |metric='precomputed'|. >> >> >> / >> *AffinityPropagation : >> * >> Constructor: >> affinity: /Which affinity to use. At the moment >> |precomputed| and |euclidean| are supported. |euclidean| uses the >> negative squared euclidean distance between points. >> / >> fit : / >> X: //Data matrix or, if affinity is |precomputed|, matrix >> of similarities / affinities. >> / >> fit_predict :/ >> / >> / X: Input data. / >> X can also be a matrix of similarities ? fit and >> fit_predict should share the same documentation for the input X ?/ >> >> >> / >> *AgglomerativeClustering : >> * Constructor: >> /affinity: Metric used to compute the linkage. Can be >> “euclidean”, “l1”, “l2”, “manhattan”, “cosine”, or ‘precomputed’. >> If linkage is “ward”, only “euclidean” is accepted/. >> The name of the parameter 'affinity' seems misleading, >> since it does not correspond to similarity functions, but to >> distance functions. >> fit : / >> X: //The samples a.k.a. observations./ >> fit_predict :/ >> // X: //Input data. >> / The documentation of fit and fit_predict does not >> specify that X can also be a matrix of distances. >> >> The user may be confused whether he/she should provide a distance >> or a similarity matrix to AgglomerativeClustering. >> The documentation of fit and fit_predict can be easily updated. >> As for the name of the 'affinity' parameter, it is more difficult >> since it involves an API change. >> >> >> What do you think of these potential updates of the documentation ? >> >> Cheers, >> >> Anaël Beaugnon >> // >>
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