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testing.cpython-35.opt-1.pyc
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Z@ e8 jA ZB y e jC jD ZD Wn" eE k r�d d% l& mD ZD Yn Xy e8 jF ZG e8 jH ZI e8 jJ ZK Wn0 eE k r1e: ZG d& d' � ZI d( d) � ZK Yn Xy e8 jL ZM Wn! eE k rbd d* d+ � ZM Yn XeM ZN d d, d- � ZO d d. d/ � ZP d d0 d � ZQ d d1 d! � ZR d2 d3 � ZS d4 d5 � ZT d6 d7 � ZU d eV d8 d9 � ZW Gd: d; � d; eX � ZY y e8 jZ Z[ e8 j\ Z] Wn eE k r'eO Z[ eP Z] Yn Xd< d d= d> d? d@ � Z^ e_ e/ j` dA � rae/ j` ja Za n e^ Za dB dC � Zb d dD dE � Zc GdF dG � dG eX � Zd dH dI � Ze dJ dK � Zf dL dM dN dO dP dQ dR dS dT g Zg dU dV dW dX dY g Zh dZ d[ d\ d] d^ d_ d` da db dc dd de df dg dh di dj dk dl dm dn do dp dq dr ds dt du dv g Zi dw dw d dw dx dy � Zj d dz d{ � Zk d| d} � Zl d~ d � Zm d� d� d� d� � Zn d� d� � Zo d� d� � Zp d� d� � Zq d� d� � Zr dw d� d� � Zs Gd� d� � d� eX � Zt e' eq � Zu e' er � Zv Gd� d� � d� eX � Zw d S)�zTesting utilities.� N)�wraps)� itemgetter)�urlopen)� HTTPError)� BaseEstimator)�joblib)�raises)� with_setup)�assert_almost_equal)�assert_array_equal)�assert_array_almost_equal)�assert_array_less)�assert_approx_equal)�ClassifierMixin�RegressorMixin�TransformerMixin� ClusterMixin)�DBSCAN� assert_equal�assert_not_equal� assert_raises�assert_raises_regexpr r � assert_true� assert_falser r r r � assert_less�assert_less_equal�assert_greater�assert_greater_equalr �SkipTest�__init__)r c C s$ t | | k d d | | f �d S)N�msgz%r in %r)r )�x� container� r# � /testing.py� assert_ina s r% c C s$ t | | k d d | | f �d S)Nr z%r in %r)r )r! r" r# r# r$ � assert_not_ind s r& c O s� d } y | | | � d } Wn_ | k r~ } z? t | � } t j | � j | � sl t d | | f � � WYd d } ~ Xn X| r� t d | j | j f � � d S)z<Helper function to check for message patterns in exceptions.FTz3Error message should match pattern %r. %r does not.Nz%s not raised by %s)�str�re�compile�search�AssertionError�__name__)Zexpected_exceptionZexpected_regexpZ callable_obj�args�kwargsZ not_raised�e� error_messager# r# r$ �assert_raises_regexk s #r1 c C s. d | | f } | d k r* | d | 7} d S)Nz%r is not lower than %rz: r# )�a�br �messager# r# r$ � _assert_less� s r5 c C s. d | | f } | d k r* | d | 7} d S)Nz%r is not greater than %rz: r# )r2 r3 r r4 r# r# r$ �_assert_greater� s r6 c C s. d | | f } | d k r* | d | 7} d S)Nz#%r is not lower than or equal to %rz: r# )r2 r3 r r4 r# r# r$ r � s c C s. d | | f } | d k r* | d | 7} d S)Nz%%r is not greater than or equal to %rz: r# )r2 r3 r r4 r# r# r$ r � s c s� t � t j d d � �� } t j d � | | | � } t t d � rZ d d � | D� } t | � d k s t d | j � � t � f d d � | D� � } | s� t d | j � | f � � Wd QRX| S) a Test that a certain warning occurs. Parameters ---------- warning_class : the warning class The class to test for, e.g. UserWarning. func : callable Calable object to trigger warnings. *args : the positional arguments to `func`. **kw : the keyword arguments to `func` Returns ------- result : the return value of `func` �recordT�always�VisibleDeprecationWarningc S s( g | ] } | j t j k r | � q Sr# )�category�npr9 )�.0r/ r# r# r$ � <listcomp>� s z assert_warns.<locals>.<listcomp>r z!No warning raised when calling %sc 3 s | ] } | j � k Vq d S)N)r: )r< �warning)� warning_classr# r$ � <genexpr>� s z assert_warns.<locals>.<genexpr>z#%s did not give warning: %s( is %s)N) �clean_warning_registry�warnings�catch_warnings� simplefilter�hasattrr; �lenr+ r, �any)r? �funcr- �kw�w�result�foundr# )r? r$ � assert_warns� s rM c s� t � t j d d � �c} t j d � t t d � rK t j d t j � | | | � } t | � d k s t d | j � � � f d d � | D� } t | � s� t d | j � f � � d } x� d d � t | � D� D]u } | | j } t t | d � r| j d n | � } t � � r-� } n � f d d � } | | � r� d } Pq� W| sxt d � | j | f � � Wd QRX| S)ag Test that a certain warning occurs and with a certain message. Parameters ---------- warning_class : the warning class The class to test for, e.g. UserWarning. message : str | callable The entire message or a substring to test for. If callable, it takes a string as argument and will trigger an assertion error if it returns `False`. func : callable Calable object to trigger warnings. *args : the positional arguments to `func`. **kw : the keyword arguments to `func`. Returns ------- result : the return value of `func` r7 Tr8 r9 �ignorer z!No warning raised when calling %sc s" g | ] } t | j � � � q Sr# )� issubclassr: )r< r> )r? r# r$ r= � s z(assert_warns_message.<locals>.<listcomp>z&No warning raised for %s with class %sFc S s" g | ] \ } } | r | � q Sr# r# )r< �ir! r# r# r$ r= � s r- c s � | k S)Nr# )r )r4 r# r$ �<lambda> s z&assert_warns_message.<locals>.<lambda>zCDid not receive the message you expected ('%s') for <%s>, got: '%s'N)rA rB rC rD rE r; r9 rF r+ r, rG � enumerater4 r' r- �callable) r? r4 rH r- rI rJ rK rL Z message_found�indexr Zcheck_in_messager# )r4 r? r$ �assert_warns_message� s6 ( rU c O s� t � t j d d � �� } t j d � | | | � } t t d � rZ d d � | D� } t | � d k r� t d | j d j d d � | D� � f � � Wd QRX| S) Nr7 Tr8 r9 c S s( g | ] } | j t j k r | � q Sr# )r: r; r9 )r< r/ r# r# r$ r= s z&assert_no_warnings.<locals>.<listcomp>r z"Got warnings when calling %s: [%s]z, c s s | ] } t | � Vq d S)N)r' )r< r> r# r# r$ r@ % s z%assert_no_warnings.<locals>.<genexpr>) rA rB rC rD rE r; rF r+ r, �join)rH r- rI rJ rK r# r# r$ �assert_no_warnings s *rW c C s0 t | � r t d | � | � St d | � Sd S)av Context manager and decorator to ignore warnings. Note. Using this (in both variants) will clear all warnings from all python modules loaded. In case you need to test cross-module-warning-logging this is not your tool of choice. Parameters ---------- category : warning class, defaults to Warning. The category to filter. If Warning, all categories will be muted. Examples -------- >>> with ignore_warnings(): ... warnings.warn('buhuhuhu') >>> def nasty_warn(): ... warnings.warn('buhuhuhu') ... print(42) >>> ignore_warnings(nasty_warn)() 42 r: N)rS �_IgnoreWarnings)�objr: r# r# r$ �ignore_warnings) s rZ c @ sR e Z d Z d Z d d � Z d d � Z d d � Z d d � Z d d � Z d S) rX al Improved and simplified Python warnings context manager and decorator. This class allows to ignore the warnings raise by a function. Copied from Python 2.7.5 and modified as required. Parameters ---------- category : tuple of warning class, defaut to Warning The category to filter. By default, all the categories will be muted. c C s8 d | _ t j d | _ d | _ g | _ | | _ d S)NTrB F)�_record�sys�modules�_module�_entered�logr: )�selfr: r# r# r$ r T s z_IgnoreWarnings.__init__c s% t � � � � f d d � � } | S)z<Decorator to catch and hide warnings without visual nesting.c s? t � t j � �% t j d � j � � | | � SWd QRXd S)NrN )rA rB rC rD r: )r- r. )�fnra r# r$ �wrapper] s z)_IgnoreWarnings.__call__.<locals>.wrapper)r )ra rb rc r# )rb ra r$ �__call__[ s !z_IgnoreWarnings.__call__c C sl g } | j r | j d � | j t j d k rF | j d | j � t | � j } d | d j | � f S)Nz record=TruerB z module=%rz%s(%s)z, )r[ �appendr^ r\ r] �typer, rV )ra r- �namer# r# r$ �__repr__g s z_IgnoreWarnings.__repr__c C sw t � t j d | j � | j r3 t d | � � d | _ | j j | _ | j d d � | j _ | j j | _ d S)NrN zCannot enter %r twiceT) rA rB rD r: r_ � RuntimeErrorr^ �filters�_filters� showwarning� _showwarning)ra r# r# r$ � __enter__p s z_IgnoreWarnings.__enter__c G sU | j s t d | � � | j | j _ | j | j _ g | j d d � <t � d S)Nz%Cannot exit %r without entering first) r_ ri rk r^ rj rm rl r` rA )ra �exc_infor# r# r$ �__exit__z s z_IgnoreWarnings.__exit__N) r, � __module__� __qualname__�__doc__r rd rh rn rp r# r# r# r$ rX G s rX gH�����z>� Tc C sg t j | � t j | � } } t j | | d | d | �rA d Sd | | | | f } t | � � d S)N�rtol�atolzDArray not equal to tolerance rtol=%g, atol=%g: actual %s, desired %s)r; Z asanyarrayZallcloser+ )�actualZdesiredru rv �err_msg�verboser r# r# r$ �_assert_allclose� s rz �assert_allclosec O s� y | | | � WnS | k rf } z3 t | � } | | k rT t d | | f � � WYd d } ~ XnQ Xt | t � r� d j d d � | D� � } n | j } t d | | j f � � d S)aL Helper function to test error messages in exceptions. Parameters ---------- exceptions : exception or tuple of exception Name of the estimator function : callable Calable object to raise error *args : the positional arguments to `function`. **kw : the keyword arguments to `function` zRError message does not include the expected string: %r. Observed error message: %rNz or c s s | ] } | j Vq d S)N)r, )r< r/ r# r# r$ r@ � s z'assert_raise_message.<locals>.<genexpr>z%s not raised by %s)r' r+ � isinstance�tuplerV r, )� exceptionsr4 �functionr- r. r/ r0 �namesr# r# r$ �assert_raise_message� s # r� c C s� t | � } x | D] } | | j | | <q W| d k rR t t | j � � � } t j d t | � f d d �| d <x. t | � D] \ } } | | d d | f <q� Wt j j | | d d �d S) aS Create a fake mldata data set. Parameters ---------- columns_dict : dict, keys=str, values=ndarray Contains data as columns_dict[column_name] = array of data. dataname : string Name of data set. matfile : string or file object The file name string or the file-like object of the output file. ordering : list, default None List of column_names, determines the ordering in the data set. Notes ----- This function transposes all arrays, while fetch_mldata only transposes 'data', keep that into account in the tests. N� Zdtype�objectZmldata_descr_orderingr Zoned_as�column) �dict�T�sorted�list�keys�sp�emptyrF rR �scipy�ioZsavemat)Z columns_dictZdataname�matfile�ordering�datasetsrg rP r# r# r$ � fake_mldata� s r� c @ s( e Z d Z d d � Z d d � Z d S)�mock_mldata_urlopenc C s | | _ d S)aT Object that mocks the urlopen function to fake requests to mldata. `mock_datasets` is a dictionary of {dataset_name: data_dict}, or {dataset_name: (data_dict, ordering). `data_dict` itself is a dictionary of {column_name: data_array}, and `ordering` is a list of column_names to determine the ordering in the data set (see `fake_mldata` for details). When requesting a dataset with a name that is in mock_datasets, this object creates a fake dataset in a StringIO object and returns it. Otherwise, it raises an HTTPError. N)� mock_datasets)ra r� r# r# r$ r � s z mock_mldata_urlopen.__init__c C s� | j d � d } | | j k r� d | } d d l m } | � } | j | } d } t | t � rs | \ } } t | | | | � | j d � | St | d | d g d � � d S) N�/r� �_r )�BytesIOi� z is not available���) �splitr� r� r� r| r} r� �seekr )ra ZurlnameZ dataset_nameZ resource_namer� r� Zdatasetr� r# r# r$ rd � s z mock_mldata_urlopen.__call__N)r, rq rr r rd r# r# r# r$ r� � s r� c C s& d d l m } t | � | j _ d S)Nr )r� )�sklearnr� r� �mldatar )r� r� r# r# r$ �install_mldata_mock s r� c C s d d l m } t | j _ d S)Nr )r� )r� r� r r� )r� r# r# r$ �uninstall_mldata_mock s r� ZOneVsOneClassifierZMultiOutputEstimatorZMultiOutputRegressorZMultiOutputClassifierZOutputCodeClassifierZOneVsRestClassifierZRFEZRFECVZ BaseEnsembleZPipelineZ FeatureUnionZ GridSearchCVZRandomizedSearchCVZSelectFromModelZ SparseCoderZEllipticEnvelopeZDictVectorizerZLabelBinarizerZ LabelEncoderZMultiLabelBinarizerZTfidfTransformerZTfidfVectorizerZIsotonicRegressionZ OneHotEncoderZRandomTreesEmbeddingZ FeatureHasherZDummyClassifierZDummyRegressorZ TruncatedSVDZPolynomialFeaturesZ GaussianRandomProjectionHashZHashingVectorizerZCheckingClassifierZPatchExtractorZCountVectorizerZ ZeroEstimatorZScaledLogOddsEstimatorZQuantileEstimatorZ MeanEstimatorZLogOddsEstimatorZPriorProbabilityEstimatorZ_SigmoidCalibrationZVotingClassifierFc s d d � � g } t j } xx t j d | d d d d d � � D]R \ } } } d | k r^ q@ t | d d �} t j | t j � } | j | � q@ Wt | � } d d � | D� } � f d d � | D� } | s� d d � | D� } | s d d � | D� } | sd d � | D� } | d k r�t | t � s@| g } n t | � } g } d t d t d t d t i } xS | j � D]E \ } � | | k r}| j | � | j � f d d � | D� � q}W| } | r�t d t | � � � t t | � d t d � �S)a Get a list of all estimators from sklearn. This function crawls the module and gets all classes that inherit from BaseEstimator. Classes that are defined in test-modules are not included. By default meta_estimators such as GridSearchCV are also not included. Parameters ---------- include_meta_estimators : boolean, default=False Whether to include meta-estimators that can be constructed using an estimator as their first argument. These are currently BaseEnsemble, OneVsOneClassifier, OutputCodeClassifier, OneVsRestClassifier, RFE, RFECV. include_other : boolean, default=False Wether to include meta-estimators that are somehow special and can not be default-constructed sensibly. These are currently Pipeline, FeatureUnion and GridSearchCV include_dont_test : boolean, default=False Whether to include "special" label estimator or test processors. type_filter : string, list of string, or None, default=None Which kind of estimators should be returned. If None, no filter is applied and all estimators are returned. Possible values are 'classifier', 'regressor', 'cluster' and 'transformer' to get estimators only of these specific types, or a list of these to get the estimators that fit at least one of the types. Returns ------- estimators : list of tuples List of (name, class), where ``name`` is the class name as string and ``class`` is the actuall type of the class. c S s* t | d � s d St | j � s& d Sd S)N�__abstractmethods__FT)rE rF r� )�cr# r# r$ � is_abstractX s z#all_estimators.<locals>.is_abstract�path�prefixzsklearn.�onerrorc S s d S)Nr# )r! r# r# r$ rQ c s z all_estimators.<locals>.<lambda>z.tests.�fromlist�dummyc S s9 g | ]/ } t | d t � r | d d k r | � q S)r� r r )rO r )r< r� r# r# r$ r= l s z"all_estimators.<locals>.<listcomp>c s& g | ] } � | d � s | � q S)r� r# )r< r� )r� r# r$ r= p s c S s& g | ] } | d t k r | � q S)r )� DONT_TEST)r< r� r# r# r$ r= s s c S s& g | ] } | d t k r | � q S)r )�OTHER)r< r� r# r# r$ r= v s c S s& g | ] } | d t k r | � q S)r )�META_ESTIMATORS)r< r� r# r# r$ r= y s NZ classifierZ regressorZ transformerZclusterc s) g | ] } t | d � � r | � q S)r� )rO )r< Zest)�mixinr# r$ r= � s zbParameter type_filter must be 'classifier', 'regressor', 'transformer', 'cluster' or None, got %s.�keyr )r� �__path__�pkgutilZ walk_packages� __import__�inspectZ getmembersZisclass�extend�setr| r� r r r r �items�remove� ValueError�reprr� r )Zinclude_meta_estimatorsZ include_otherZ type_filterZinclude_dont_testZ all_classesr� Zimporter�modnameZispkg�module�classesZ estimatorsZfiltered_estimatorsrj rg r# )r� r� r$ �all_estimators1 sJ ' ( $r� c C s9 t | t � r d Sd | j � k r5 | j d | � d S)z�Set random state of an estimator if it has the `random_state` param. Classes for whom random_state is deprecated are ignored. Currently DBSCAN is one such class. N� random_state)r| r Z get_paramsZ set_params)Z estimatorr� r# r# r$ �set_random_state� s r� c s" t � � � f d d � � } | S)z;Test decorator that skips test if matplotlib not installed.c sn y< d d l } | j d d d �d d l j } | j � Wn t k r\ t d � � Yn X� | | � Sd S)Nr ZAgg�warnFzMatplotlib not available.)� matplotlibZuseZmatplotlib.pyplotZpyplotZfigure� ImportErrorr )r- r. r� Zplt)rH r# r$ �run_test� s z if_matplotlib.<locals>.run_test)r )rH r� r# )rH r$ � if_matplotlib� s r� c s" t � � � f d d � � } | S)z3Test decorator that skips tests on 32bit platforms.c s? d t j d � } | d k r. t d � � n � | | � Sd S)N� �P� z Test skipped on 32bit platforms.)�struct�calcsizer )r- r. �bits)rH r# r$ r� � s z skip_if_32bit.<locals>.run_test)r )rH r� r# )rH r$ � skip_if_32bit� s r� �10.7�10.8�10.9z6Multi-process bug in Mac OS X >= 10.7 (see issue #636)c sf t j d t � t j � \ } } } d j | j d � d d � � | k � � � f d d � } | S)zgTest decorator that skips test if OS is Mac OS X and its major version is one of ``versions``. z�if_not_mac_os is deprecated in 0.17 and will be removed in 0.19: use the safer and more generic if_safe_multiprocessing_with_blas instead�.N� c s( � r$ t | � � f d d � � } | S)Nc s t � � � d S)N)r )r- r. )r4 r# r$ rH � s z.if_not_mac_os.<locals>.decorator.<locals>.func)r )rH )r4 �skipr# r$ � decorator� s z if_not_mac_os.<locals>.decorator)rB r� �DeprecationWarning�platformZmac_verrV r� )Zversionsr4 Z mac_versionr� r� r# )r4 r� r$ � if_not_mac_os� s (r� c s" t � � � f d d � � } | S)a; Decorator for tests involving both BLAS calls and multiprocessing. Under POSIX (e.g. Linux or OSX), using multiprocessing in conjunction with some implementation of BLAS (or other libraries that manage an internal posix thread pool) can cause a crash or a freeze of the Python process. In practice all known packaged distributions (from Linux distros or Anaconda) of BLAS under Linux seems to be safe. So we this problem seems to only impact OSX users. This wrapper makes it possible to skip tests that can possibly cause this crash under OS X with. Under Python 3.4+ it is possible to use the `forkserver` start method for multiprocessing to avoid this issue. However it can cause pickling errors on interactively defined functions. It therefore not enabled by default. c s( t j d k r t d � � � | | � S)N�darwinz)Possible multi-process bug with some BLAS)r\ r� r )r- r. )rH r# r$ r� � s z3if_safe_multiprocessing_with_blas.<locals>.run_test)r )rH r� r# )rH r$ �!if_safe_multiprocessing_with_blas� s r� c C sk t j � d } xT t t j j � � D]= \ } } d | k rA q& t | | � r& t | | � j � q& Wd S)zSafe way to reset warnings.Z__warningregistry__z six.movesN) rB � resetwarningsr� r\ r] r� rE �getattr�clear)ZregZmod_name�modr# r# r$ rA � s " rA c C s+ t t j j d d � � r' t d � � d S)NZSKLEARN_SKIP_NETWORK_TESTSr z-Text tutorial requires large dataset download)�int�os�environ�getr r# r# r# r$ �check_skip_network� s r� c C s( t j j d � d k r$ t d � � d S)z!Skip test if being run on Travis.ZTRAVIS�truez'This test needs to be skipped on TravisN)r� r� r� r r# r# r# r$ �check_skip_travis s r� c C sS y# t j j | � r" t j | � Wn) t k rN | rJ t j d | � Yn Xd S)zuUtility function to cleanup a temporary folder if still existing. 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__init__.cpython-35.pyc
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linear_assignment_.cpython-35.pyc
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validation.cpython-35.pyc
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