x\c @ sQ ddlmZddlmZddlmZddlmZddlZddlZddl Z ddl m Z ddl Z ddl Z ddlZddlZddlZddlZddlZddlmZmZddlmZddljZdd lmZmZmZmZm Z m!Z!m"Z"m#Z#m$Z$m%Z%m&Z&m'Z'm(Z(m)Z)m*Z*m+Z+dd l,m-Z-m.Z.m/Z/m0Z0m1Z1m2Z2m3Z3m4Z4m5Z5m6Z6m7Z7m8Z8m9Z9m:Z:dd l;m<Z<ddl=Z>dd l=m?Z?m@Z@mAZAmBZBmCZCmDZDmEZEmFZFmGZGmHZHmIZIdd lJmKZKddlLmMZMmNZNmOZOmPZPmQZQmRZRddlSjTjUZVddlWmXZXddlYmZZZdZ[dZ\e]Z^e_ej`fZadZbdZcebdZdddZfddZgddZhedZiddZjde]dZkdZlemdZndd d!Zoejpeqe jre jsd"ejtd#fZuejpeqe)d$jve%e*e#d%de jsd"ejwd#fZxd'd(Zyd'd)Zzd*Z{d+Z|dd,Z}d-Z~d.Zdemed/Zeejd0Zejd1Zd2Zed3Zd4Zd5Zd6Zede]d7Zed8Zed9Zd:Zdeme]ememd;d<Zemd=d>Zd?d@ZdAZdBZdCZememdDdEZddFdGZdHdIZdJdKZdLdMZddNZe]emdddOdPZeme]e]dQZemdeme]eme]e]emdRdS Zemddeme]eme]e]e]eme]dTdU Zeme]e]e]e]dVdWZdXZemdYZdZZemememe]d[Zememememememe]d\d]Zemememememe]d^d_Zd`ZdaZdbZdcdddZdcddeZdcdfddgZdcddhZdcddiZdcddjZdcddkZdcddlZdcddmZdcdnddoZdcdpddqZdcddrZdcddsZdcdtZduZdcdvZddwZddxZddyZdzZddndd{Zddd|Zddnd}Zdd~ZddndZdZdZdZddZddZddZde]dddZememd#d#ddddddd ZddZddememd#d#ddddddd ZdddZdZdefdYZdZdZdZee!jfZereef7ZnedZede^e]eeedZeZddZdefdYZeeddemdZdefdYZedZeddZdddZdeHfdYZdeAfdYZde>jfdYZde>jfdYZde?fdYZedZddZdZdS(i(tdivision(tcontextmanager(tdatetime(twrapsN(trmtree(trandtrandn(ttesting(tPY2tPY3tCountertcallabletfilterthttplibtlmaptlrangetlziptmaptraise_with_tracebacktranget string_typestutunichrtzip(tis_booltis_categorical_dtypetis_datetime64_dtypetis_datetime64tz_dtypetis_datetimelike_v_numerictis_datetimelike_v_objecttis_extension_array_dtypetis_interval_dtypet is_list_liket is_numbertis_period_dtypet is_sequencetis_timedelta64_dtypetneeds_i8_conversion(tarray_equivalent( t CategoricaltCategoricalIndext DataFramet DatetimeIndextIndext IntervalIndext MultiIndextPanelt RangeIndextSeriest bdate_range(ttake_1d(t DatetimeArraytExtensionArrayt IntervalArrayt PeriodArraytTimedeltaArrayt period_array(turlopen(t pprint_thingiicC s8tjjdd}d|kr4tjdtndS(NtPANDAS_TESTING_MODEtNonet deprecatetalways(tostenvirontgettwarningst simplefiltert_testing_mode_warnings(t testing_mode((s2lib/python2.7/site-packages/pandas/util/testing.pytset_testing_mode6s cC s8tjjdd}d|kr4tjdtndS(NR;R<R=tignore(R?R@RARBRCRD(RE((s2lib/python2.7/site-packages/pandas/util/testing.pytreset_testing_mode=s cC stjddtdS(sJ Reset the display options for printing and representing objects. s ^display.tsilentN(tpdt reset_optiontTrue(((s2lib/python2.7/site-packages/pandas/util/testing.pytreset_display_optionsGscC sc|dkr-tdjdtd}nt|$}tj||tj|SWdQXdS(s Pickle an object and then read it again. Parameters ---------- obj : pandas object The object to pickle and then re-read. path : str, default None The path where the pickled object is written and then read. Returns ------- round_trip_pickled_object : pandas object The original object that was pickled and then re-read. s__{random_bytes}__.picklet random_bytesi N(R<Rtformattrandst ensure_cleanRJt to_picklet read_pickle(tobjtpath((s2lib/python2.7/site-packages/pandas/util/testing.pytround_trip_pickleOs  !cC snddl}|jdj}|dkr3d}nt|)}||||||}WdQX|S(s Write an object to file specified by a pathlib.Path and read it back Parameters ---------- writer : callable bound to pandas object IO writing function (e.g. DataFrame.to_csv ) reader : callable IO reading function (e.g. pd.read_csv ) path : str, default None The path where the object is written and then read. Returns ------- round_trip_object : pandas object The original object that was serialized and then re-read. iNtpathlibt ___pathlib___(tpytestt importorskiptPathR<RQ(twritertreaderRURYR[RT((s2lib/python2.7/site-packages/pandas/util/testing.pytround_trip_pathlibgs   cC snddl}|jdj}|dkr3d}nt|)}||||||}WdQX|S(s Write an object to file specified by a py.path LocalPath and read it back Parameters ---------- writer : callable bound to pandas object IO writing function (e.g. DataFrame.to_csv ) reader : callable IO reading function (e.g. pd.read_csv ) path : str, default None The path where the object is written and then read. Returns ------- round_trip_object : pandas object The original object that was serialized and then re-read. iNspy.patht___localpath___(RYRZtlocalR<RQ(R\R]RURYt LocalPathRT((s2lib/python2.7/site-packages/pandas/util/testing.pytround_trip_localpaths   c c si|dkrt|d}n|dkrKddl}|j|d}n|dkrxddl}|j|d}n|dkrtj}|j|d}n|dkrddl}|j |}|j }t |dkr|j|j }q5t d j|nd j|} t | z |VWd|j|dkrd|jnXdS( s  Open a compressed file and return a file object Parameters ---------- path : str The path where the file is read from compression : {'gzip', 'bz2', 'zip', 'xz', None} Name of the decompression to use Returns ------- f : file object trbtgzipiNtbz2txzRis)ZIP file {} error. Only one file per ZIP.s!Unrecognized compression type: {}(R<topenRdRetBZ2Filetcompatt import_lzmatLZMAFiletzipfiletZipFiletnamelisttlentpopt ValueErrorROtclose( RUt compressiontfRdRetlzmaRltzip_filet zip_namestmsg((s2lib/python2.7/site-packages/pandas/util/testing.pytdecompress_files4               ttestcC s|dkr$ddl}|j}n|dkrHddl}|j}nc|dkrlddl}|j}n?|dkrtj}|j}ndj |} t | |dkrd} ||f} d } nd } |f} d } ||d | } t | | | WdQXdS( s Write data to a compressed file. Parameters ---------- compression : {'gzip', 'bz2', 'zip', 'xz'} The compression type to use. path : str The file path to write the data. data : str The data to write. dest : str, default "test" The destination file (for ZIP only) Raises ------ ValueError : An invalid compression value was passed in. RiNRdReRfs!Unrecognized compression type: {}twtwritestrtwbtwritetmode( RlRmRdtGzipFileReRhRiRjRkRORqtgetattr(RsRUtdatatdestRltcompress_methodRdReRuRxRtargstmethodRt((s2lib/python2.7/site-packages/pandas/util/testing.pytwrite_to_compresseds.                 tequivc K sDt|tjr4t||dtd|d||St|tjrht||dtd|d||St|tjrt||dtd|d||S|r!t |rt |rq!t |rt |rq!t|t j st|t j rd}nd}t ||d|ntj||d|d||SdS( sw Check that the left and right objects are approximately equal. By approximately equal, we refer to objects that are numbers or that contain numbers which may be equivalent to specific levels of precision. Parameters ---------- left : object right : object check_dtype : bool / string {'equiv'}, default 'equiv' Check dtype if both a and b are the same type. If 'equiv' is passed in, then `RangeIndex` and `Int64Index` are also considered equivalent when doing type checking. check_less_precise : bool or int, default False Specify comparison precision. 5 digits (False) or 3 digits (True) after decimal points are compared. If int, then specify the number of digits to compare. When comparing two numbers, if the first number has magnitude less than 1e-5, we compare the two numbers directly and check whether they are equivalent within the specified precision. Otherwise, we compare the **ratio** of the second number to the first number and check whether it is equivalent to 1 within the specified precision. t check_exacttexacttcheck_less_preciset check_dtypes numpy arraytInputRTN(t isinstanceRJR+tassert_index_equaltFalseR0tassert_series_equalR)tassert_frame_equalR!Rtnptndarraytassert_class_equalt_testingtassert_almost_equal(tlefttrightRRtkwargsRT((s2lib/python2.7/site-packages/pandas/util/testing.pyRsB     c C sd}|j}t||sKt|jd|d|dt|nt||st|jd|d|dt|ndS(s Helper method for our assert_* methods that ensures that the two objects being compared have the right type before proceeding with the comparison. Parameters ---------- left : The first object being compared. right : The second object being compared. cls : The class type to check against. Raises ------ AssertionError : Either `left` or `right` is not an instance of `cls`. s9{name} Expected type {exp_type}, found {act_type} insteadtnametexp_typetact_typeN(t__name__RtAssertionErrorROttype(RRtclsterr_msgtcls_name((s2lib/python2.7/site-packages/pandas/util/testing.pyt_check_isinstanceKs cC s&t||ttj||d|S(Nt compare_keys(RtdictRtassert_dict_equal(RRR((s2lib/python2.7/site-packages/pandas/util/testing.pyRgsg?cC st||kS(N(R(tsizetp((s2lib/python2.7/site-packages/pandas/util/testing.pytrandboolmstdtypeitiitOcC satjjtd|tj|jtj|fj|}|dkrP|S|j |SdS(s"Generate an array of byte strings.RN( Rtrandomtchoicet RANDS_CHARStprodtviewtstr_treshapeR<tastype(tncharsRRtretval((s2lib/python2.7/site-packages/pandas/util/testing.pyt rands_arrayws % cC satjjtd|tj|jtj|fj|}|dkrP|S|j |SdS(s%Generate an array of unicode strings.RN( RRRt RANDU_CHARSRRtunicode_RR<R(RRRR((s2lib/python2.7/site-packages/pandas/util/testing.pyt randu_arrays % cC sdjtjjt|S(st Generate one random byte string. See `rands_array` if you want to create an array of random strings. R(tjoinRRRR(R((s2lib/python2.7/site-packages/pandas/util/testing.pyRPscC sdjtjjt|S(s Generate one random unicode string. See `randu_array` if you want to create an array of random unicode strings. R(RRRRR(R((s2lib/python2.7/site-packages/pandas/util/testing.pytranduscC sQddlm}m}|dkrCx(|D]}||q,Wn ||dS(Ni(t get_fignumsRr(tmatplotlib.pyplotRRrR<(tfignumRt_close((s2lib/python2.7/site-packages/pandas/util/testing.pyRrs  cO sd|krtdntjdtjdtj||}|j\}}|j}|r|jd}|dkr|d}ntj||d|n|S(sRun command with arguments and return its output as a byte string. If the exit code was non-zero it raises a CalledProcessError. The CalledProcessError object will have the return code in the returncode attribute and output in the output attribute. The arguments are the same as for the Popen constructor. Example: >>> check_output(["ls", "-l", "/dev/null"]) 'crw-rw-rw- 1 root root 1, 3 Oct 18 2007 /dev/null\n' The stdout argument is not allowed as it is used internally. To capture standard error in the result, use stderr=STDOUT. >>> check_output(["/bin/sh", "-c", ... "ls -l non_existent_file ; exit 0"], ... stderr=STDOUT) 'ls: non_existent_file: No such file or directory\n' tstdouts3stdout argument not allowed, it will be overridden.tstderrRitoutputN( Rqt subprocesstPopentPIPEt communicatetpollRAR<tCalledProcessError(t popenargsRtprocessRt unused_errtretcodetcmd((s2lib/python2.7/site-packages/pandas/util/testing.pyt check_outputs     cC sTytdgdt}Wn4tjk rO}t|djd|nX|S(Ns locale -atshellsC{exception}, the 'locale -a' command cannot be found on your systemt exception(RRLRRRRO(t raw_localeste((s2lib/python2.7/site-packages/pandas/util/testing.pyt_default_locale_getters cC sy |}Wntk r!dSXyh|jd}g}xL|D]D}trr|jt|dtjjj qA|jt|qAWWnt k rnX|dkrt ||St j djd|}|jdj|}t ||S(sGet all the locales that are available on the system. Parameters ---------- prefix : str If not ``None`` then return only those locales with the prefix provided. For example to get all English language locales (those that start with ``"en"``), pass ``prefix="en"``. normalize : bool Call ``locale.normalize`` on the resulting list of available locales. If ``True``, only locales that can be set without throwing an ``Exception`` are returned. locale_getter : callable The function to use to retrieve the current locales. This should return a string with each locale separated by a newline character. Returns ------- locales : list of strings A list of locale strings that can be set with ``locale.setlocale()``. For example:: locale.setlocale(locale.LC_ALL, locale_string) On error will return None (no locale available, e.g. Windows) s tencodings {prefix}.*tprefixN(t ExceptionR<tsplitR tappendtstrRJtoptionstdisplayRt TypeErrort_valid_localestretcompileROtfindallR(Rt normalizet locale_getterRt out_localestxtpatterntfound((s2lib/python2.7/site-packages/pandas/util/testing.pyt get_localess&       cc sitj}zEtj||tj}tj|rKdj|Vn|VWdtj||XdS(s@Context manager for temporarily setting a locale. Parameters ---------- new_locale : str or tuple A string of the form .. For example to set the current locale to US English with a UTF8 encoding, you would pass "en_US.UTF-8". lc_var : int, default `locale.LC_ALL` The category of the locale being set. Notes ----- This is useful when you want to run a particular block of code under a particular locale, without globally setting the locale. This probably isn't thread-safe. t.N(tlocalet getlocalet setlocaletcomt _all_not_noneR(t new_localetlc_vartcurrent_localetnormalized_locale((s2lib/python2.7/site-packages/pandas/util/testing.pyt set_locales   cC sCyt|d|WdQXWnttjfk r:tSXtSdS(su Check to see if we can set a locale, and subsequently get the locale, without raising an Exception. Parameters ---------- lc : str The locale to attempt to set. lc_var : int, default `locale.LC_ALL` The category of the locale being set. Returns ------- is_valid : bool Whether the passed locale can be set RN(RRqRtErrorRRL(tlcR((s2lib/python2.7/site-packages/pandas/util/testing.pytcan_set_locale3s cC s7|rd}n d}tttt||S(smReturn a list of normalized locales that do not throw an ``Exception`` when set. Parameters ---------- locales : str A string where each locale is separated by a newline. normalize : bool Whether to call ``locale.normalize`` on each locale. Returns ------- valid_locales : list A list of valid locales. cS stj|jS(N(RRtstrip(R((s2lib/python2.7/site-packages/pandas/util/testing.pyt`scS s |jS(N(R(R((s2lib/python2.7/site-packages/pandas/util/testing.pyRbs(tlistR RR(tlocalesRt normalizer((s2lib/python2.7/site-packages/pandas/util/testing.pyROs  cc sVtstdntj}tttj|z dVWdtj|XdS(s Set default encoding (as given by sys.getdefaultencoding()) to the given encoding; restore on exit. Parameters ---------- encoding : str s:set_defaultencoding context is only available in Python 2.N(RRqtsystgetdefaultencodingtreloadtsetdefaultencoding(Rtorig((s2lib/python2.7/site-packages/pandas/util/testing.pytset_defaultencodingjs     cO srddlm}y#ddlm}tdd}Wntk rR|}i}nX||}|j|||S(Ni(tPdbt color_schemetLinux(tpdbRtIPython.core.debuggerRt ImportErrortruncall(RtRRtOldPdbRtkwR((s2lib/python2.7/site-packages/pandas/util/testing.pytdebugs   cO sddl}|j|||S(Ni(tpudbR (RtRRR ((s2lib/python2.7/site-packages/pandas/util/testing.pytpudebugs cC stddlm}y#|ddjtjjWn:tk roddlm}|jtjjnXdS(Ni(RRR(RRt set_traceRt _getframetf_backRR(RR ((s2lib/python2.7/site-packages/pandas/util/testing.pyRs # cc sN|p d}d}|rDtjd|}z |VWd|jXnttjj|rktdnytj d|\}}Wn*t k rddl }|j dnXz |VWdytj|Wn(t k rdjd|d |GHnXy&tjj|r!tj|nWn$t k rH}d jd |GHnXXdS( sGets a temporary path and agrees to remove on close. Parameters ---------- filename : str (optional) if None, creates a temporary file which is then removed when out of scope. if passed, creates temporary file with filename as ending. return_filelike : bool (default False) if True, returns a file-like which is *always* cleaned. Necessary for savefig and other functions which want to append extensions. RtsuffixNs-Can't pass a qualified name to ensure_clean()is$no unicode file names on this systems7Couldn't close file descriptor: {fdesc} (file: {fname})tfdesctfnames#Exception on removing file: {error}terror(R<ttempfilet TemporaryFileRrRoR?RUtdirnameRqtmkstemptUnicodeEncodeErrorRYtskipRROtexiststremove(tfilenametreturn_fileliketfdRtRYR((s2lib/python2.7/site-packages/pandas/util/testing.pyRQs4       cc sEtjdd}z |VWdyt|Wntk r?nXXdS(s{ Get a temporary directory path and agrees to remove on close. Yields ------ Temporary directory path RRN(RtmkdtempRR(tdirectory_name((s2lib/python2.7/site-packages/pandas/util/testing.pytensure_clean_dirs   cc s=ttj}z dVWdtjjtjj|XdS(s Get a context manager to safely set environment variables All changes will be undone on close, hence environment variables set within this contextmanager will neither persist nor change global state. N(RR?R@tcleartupdate(t saved_environ((s2lib/python2.7/site-packages/pandas/util/testing.pyt!ensure_safe_environment_variabless   cC st|t|kS(sJChecks if the set of unique elements of arr1 and arr2 are equivalent. (t frozenset(tarr1tarr2((s2lib/python2.7/site-packages/pandas/util/testing.pyt equalContentssR+c s|t}dfd} d} t||t| ||d||j|jkrdjd|} djd|jd|} d jd|jd |} t|| | | nt|t|kr3d jd|} d jd t|d|} djd t|d |} t|| | | n|jdkrxt|jD]}| ||}| ||}djd|}t||dd|d|d|d|| |j ||j |d|qRWn|rere|j |st j |j |j kjtdt|}djd|dt j|d}t||||qn4tj|j |j d|dd|d|d||rtd||d|nt|tjst|tjrtd||d|nt|tjst|tjr/t|j |j nrxt|sMt|rxt|j |j ddjd|qxnd S(!sCheck that left and right Index are equal. Parameters ---------- left : Index right : Index exact : bool / string {'equiv'}, default 'equiv' Whether to check the Index class, dtype and inferred_type are identical. If 'equiv', then RangeIndex can be substituted for Int64Index as well. check_names : bool, default True Whether to check the names attribute. check_less_precise : bool or int, default False Specify comparison precision. Only used when check_exact is False. 5 digits (False) or 3 digits (True) after decimal points are compared. If int, then specify the digits to compare check_exact : bool, default True Whether to compare number exactly. check_categorical : bool, default True Whether to compare internal Categorical exactly. obj : str, default 'Index' Specify object name being compared, internally used to show appropriate assertion message R+c sr~t||dd|r>td||d|n|jdkre|jdks{tq~td||d|ndS( NRRTRtstringtunicodet inferred_type(R,R-(R,R-(Rtassert_attr_equalR.R(tltrRT(tcheck_categoricalR(s2lib/python2.7/site-packages/pandas/util/testing.pyt _check_typesscS sU|j|}|j|}t|j|d|j}|j|d|j|}|S(Nt fill_valueR(tlevelstcodesR2tvaluest _na_valuet _shallow_copytnames(tindextleveltuniquetlabelstfilledR7((s2lib/python2.7/site-packages/pandas/util/testing.pyt_get_ilevel_values)s   RTs{obj} levels are differents{nlevels}, {left}tnlevelsRs{nlevels}, {right}Rs{obj} length are differents{length}, {left}tlengths{length}, {right}isMultiIndex level [{level}]R<Rt check_namesRRgY@s${obj} values are different ({pct} %)tpctiRtlobjtrobjR:tfreqs{obj} categoryN(RLRR+RAROtraise_assert_detailRoRRR5tequalsRtsumR7RtinttroundRRR/RRJt PeriodIndexR,tassert_interval_array_equalRtassert_categorical_equal(RRRRCRRR2RTt__tracebackhide__R3R@tmsg1tmsg2tmsg3R<tlleveltrlevelREtdiffRx((R2Rs2lib/python2.7/site-packages/pandas/util/testing.pyRs\    ( 2 $RcC st}d}|dkrt|t|krt|jt|jh}t|ddhrdjd|}t||||||qqnU|rt|t|krdjd|}t||||||qndS( schecks classes are equal.cS sFt|tr|Sy|jjSWntk rAtt|SXdS(N(RR+t __class__RtAttributeErrortreprR(R((s2lib/python2.7/site-packages/pandas/util/testing.pyt repr_classus  Rt Int64IndexR/s {obj} classes are not equivalentRTs{obj} classes are differentN(RLRRRoRORH(RRRRTRPRZttypesRx((s2lib/python2.7/site-packages/pandas/util/testing.pyRqs t Attributesc C st}t||}t||}||kr4tSt|rntj|rnt|rntj|rntSy||k}Wntk rt}nXt|ts|j }n|rtSdj d|}t ||||dS(sKchecks attributes are equal. Both objects must have attribute. Parameters ---------- attr : str Attribute name being compared. left : object right : object obj : str, default 'Attributes' Specify object name being compared, internally used to show appropriate assertion message s Attribute "{attr}" are differenttattrN( RLRR!RtisnanRRRtbooltallRORH( R^RRRTRPt left_attrt right_attrtresultRx((s2lib/python2.7/site-packages/pandas/util/testing.pyR/s$    cC sddlj}t|tjtjfrx|jD]B}djd|j j }t||j t fs7t |q7Wn9t||jtt fst djd|j j dS(NisJone of 'objs' is not a matplotlib Axes instance, type encountered {name!r}Rsqobjs is neither an ndarray of Artist instances nor a single Artist instance, tuple, or dict, "objs" is a {name!r}(RtpyplotRRJR0RRtravelRORWRtAxesRRtArtistttuple(tobjstplttelRx((s2lib/python2.7/site-packages/pandas/util/testing.pyt"assert_is_valid_plot_return_objects + cC s t|dS(Nt__iter__(thasattr(RT((s2lib/python2.7/site-packages/pandas/util/testing.pyt isiterablescC s@t|ttfr!|j}nt|tjtj|S(N(RR+R0R7tassert_numpy_array_equalRtsorttarray(tseq((s2lib/python2.7/site-packages/pandas/util/testing.pyt is_sorteds R'c C st||t|rit|j|jddjd|t|j|jd|ddjd|nnt|jj|jjddjd|t|jj|j|jj|jddjd|t d||d|dS(svTest that Categoricals are equivalent. Parameters ---------- left : Categorical right : Categorical check_dtype : bool, default True Check that integer dtype of the codes are the same check_category_order : bool, default True Whether the order of the categories should be compared, which implies identical integer codes. If False, only the resulting values are compared. The ordered attribute is checked regardless. obj : str, default 'Categorical' Specify object name being compared, internally used to show appropriate assertion message RTs{obj}.categoriesRs {obj}.codess {obj}.valuestorderedN( RR'Rt categoriesRORqR6t sort_valuesttakeR/(RRRtcheck_category_orderRT((s2lib/python2.7/site-packages/pandas/util/testing.pyROsR5c C st||tt|j|jd|ddjd|t|j|jd|ddjd|td||d|dS(sTest that two IntervalArrays are equivalent. Parameters ---------- left, right : IntervalArray The IntervalArrays to compare. exact : bool / string {'equiv'}, default 'equiv' Whether to check the Index class, dtype and inferred_type are identical. If 'equiv', then RangeIndex can be substituted for Int64Index as well. obj : str, default 'IntervalArray' Specify object name being compared, internally used to show appropriate assertion message RRTs {obj}.lefttclosedN(RR5RRRORR/(RRRRT((s2lib/python2.7/site-packages/pandas/util/testing.pyRNs R6cC sOt||tt|j|jddjd|td||d|dS(NRTs {obj}.valuesRG(RR6Rqt_dataROR/(RRRT((s2lib/python2.7/site-packages/pandas/util/testing.pytassert_period_array_equalsR3cC skt}t||tt|j|jddjd|td||d|td||d|dS(NRTs {obj}._dataRGttz(RLRR3RqR|ROR/(RRRTRP((s2lib/python2.7/site-packages/pandas/util/testing.pytassert_datetime_array_equals R7cC sUt}t||tt|j|jddjd|td||d|dS(NRTs {obj}._dataRG(RLRR7RqR|ROR/(RRRTRP((s2lib/python2.7/site-packages/pandas/util/testing.pytassert_timedelta_array_equal s c C s%t}t|tjr't|}nt|rBt|}ntrit|tri|j d}nt|tjrt|}nt|rt|}ntrt|tr|j d}ndj d|d|d|d|}|dk r|dj d|7}nt |dS( Nsutf-8s?{obj} are different {message} [left]: {left} [right]: {right}RTtmessageRRs [diff]: {diff}RV( RLRRRR:RRYRRtencodeROR<R(RTRRRRVRPRx((s2lib/python2.7/site-packages/pandas/util/testing.pyRH(s"  $ s numpy arrayc  sUt}t||dt||tjd}||} ||} |dkr| | k rdjd| d| } t| qnB|dkr| | krdjd| d| } t| qnfd } t||d s | |||n|rQt|tjrQt|tjrQt d ||dqQntS( s Checks that 'np.ndarray' is equivalent Parameters ---------- left : np.ndarray or iterable right : np.ndarray or iterable strict_nan : bool, default False If True, consider NaN and None to be different. check_dtype: bool, default True check dtype if both a and b are np.ndarray err_msg : str, default None If provided, used as assertion message check_same : None|'copy'|'same', default None Ensure left and right refer/do not refer to the same memory area obj : str, default 'numpy array' Specify object name being compared, internally used to show appropriate assertion message RTcS s#t|dddk r|jS|S(Ntbase(RR<R(RT((s2lib/python2.7/site-packages/pandas/util/testing.pyt _get_basefstsames{left!r} is not {right!r}RRtcopys{left!r} is {right!r}c s|dkr|j|jkrFtdjd|j|jnd}x?t||D].\}}t||ds\|d7}q\q\W|d|j}djddtj|d }t|||nt |dS( Ns{obj} shapes are differentRTit strict_nanigY@s${obj} values are different ({pct} %)RDi( R<tshapeRHRORR&RRRLR(RRRRVR0R1Rx(RTR(s2lib/python2.7/site-packages/pandas/util/testing.pyt_raisews  RR( RLRRRRRORR&RR/( RRRRRt check_sameRTRPRt left_baset right_baseRxR((RTRs2lib/python2.7/site-packages/pandas/util/testing.pyRqIs.         $c C sLt|tstdt|ts6td|rUtd||ddnt|drt|t|krt|j|jdStj |j }tj |j }t||ddtj ||j t }tj ||j t }|r&t||ddn"t j||d |d |dddS( s;Check that left and right ExtensionArrays are equal. Parameters ---------- left, right : ExtensionArray The two arrays to compare check_dtype : bool, default True Whether to check if the ExtensionArray dtypes are identical. check_less_precise : bool or int, default False Specify comparison precision. Only used when check_exact is False. 5 digits (False) or 3 digits (True) after decimal points are compared. If int, then specify the digits to compare. check_exact : bool, default False Whether to compare number exactly. Notes ----- Missing values are checked separately from valid values. A mask of missing values is computed for each and checked to match. The remaining all-valid values are cast to object dtype and checked. sleft is not an ExtensionArraysright is not an ExtensionArrayRRTR4tasi8NsExtensionArray NA maskRR(RR4RR/RoRRqRRtasarraytisnaRtobjectRR( RRRRRtleft_natright_nat left_validt right_valid((s2lib/python2.7/site-packages/pandas/util/testing.pytassert_extension_array_equals$'R0c C spt} t||t|r:t|t|s:tnt|t|krdjdt|d|j} djdt|d|j} t | d| | nt |j|jd|d|d |d |d | d d jd | |r(t |rt |r| rq(t d||n|rbt |j|jd|d djd | n|rt||st||st|st|rt|jjt|jsdjd|jd|j}t|qqt |j|jd|nt|s)t|r?t|j|jnt|jrt|jrt|jsrtt|j|jSt|rt | rt|rt | rt|j|jStj|j|jd |d|d djd | |r#t d||d | n| rlt |sAt |rlt|j|jd djd | qlndS(sCheck that left and right Series are equal. Parameters ---------- left : Series right : Series check_dtype : bool, default True Whether to check the Series dtype is identical. check_index_type : bool / string {'equiv'}, default 'equiv' Whether to check the Index class, dtype and inferred_type are identical. check_series_type : bool, default True Whether to check the Series class is identical. check_less_precise : bool or int, default False Specify comparison precision. Only used when check_exact is False. 5 digits (False) or 3 digits (True) after decimal points are compared. If int, then specify the digits to compare. check_names : bool, default True Whether to check the Series and Index names attribute. check_exact : bool, default False Whether to compare number exactly. check_datetimelike_compat : bool, default False Compare datetime-like which is comparable ignoring dtype. check_categorical : bool, default True Whether to compare internal Categorical exactly. obj : str, default 'Series' Specify object name being compared, internally used to show appropriate assertion message. s {len}, {left}RoRs{len}, {right}RsSeries length are differentRRCRRR2RTs {obj}.indexRRs{obj}s:[datetimelike_compat=True] {left} is not equal to {right}.Rs{obj} categoryN( RLRR0RRRRoROR;RHRRR/Rqt get_valuesRRR%R+R7RIRRNRsRRRRt_valuesRRRO(RRRtcheck_index_typetcheck_series_typeRRCRtcheck_datetimelike_compatR2RTRPRQRRRx((s2lib/python2.7/site-packages/pandas/util/testing.pyRsj&!!  !  R)cC sut}t||t|r:t|t|s:tn|j|jkrt| ddjd|jdjd|jn| r|j ||}}nt |j |j d|d|d|d| d| d d jd | t |j |j d|d|d|d| d| d d jd | |r|j }|j }x+ttt|jt|jD]K}||kst||kstt||||d |d d qrWnxt|j D]\}}||kst|jdd|f}|jdd|f}t||d |d|d|d| d|d| d| d djd|qWdS(s Check that left and right DataFrame are equal. This function is intended to compare two DataFrames and output any differences. Is is mostly intended for use in unit tests. Additional parameters allow varying the strictness of the equality checks performed. Parameters ---------- left : DataFrame First DataFrame to compare. right : DataFrame Second DataFrame to compare. check_dtype : bool, default True Whether to check the DataFrame dtype is identical. check_index_type : bool / string {'equiv'}, default 'equiv' Whether to check the Index class, dtype and inferred_type are identical. check_column_type : bool / string {'equiv'}, default 'equiv' Whether to check the columns class, dtype and inferred_type are identical. Is passed as the ``exact`` argument of :func:`assert_index_equal`. check_frame_type : bool, default True Whether to check the DataFrame class is identical. check_less_precise : bool or int, default False Specify comparison precision. Only used when check_exact is False. 5 digits (False) or 3 digits (True) after decimal points are compared. If int, then specify the digits to compare. check_names : bool, default True Whether to check that the `names` attribute for both the `index` and `column` attributes of the DataFrame is identical, i.e. * left.index.names == right.index.names * left.columns.names == right.columns.names by_blocks : bool, default False Specify how to compare internal data. If False, compare by columns. If True, compare by blocks. check_exact : bool, default False Whether to compare number exactly. check_datetimelike_compat : bool, default False Compare datetime-like which is comparable ignoring dtype. check_categorical : bool, default True Whether to compare internal Categorical exactly. check_like : bool, default False If True, ignore the order of index & columns. Note: index labels must match their respective rows (same as in columns) - same labels must be with the same data. obj : str, default 'DataFrame' Specify object name being compared, internally used to show appropriate assertion message. See Also -------- assert_series_equal : Equivalent method for asserting Series equality. DataFrame.equals : Check DataFrame equality. Examples -------- This example shows comparing two DataFrames that are equal but with columns of differing dtypes. >>> from pandas.util.testing import assert_frame_equal >>> df1 = pd.DataFrame({'a': [1, 2], 'b': [3, 4]}) >>> df2 = pd.DataFrame({'a': [1, 2], 'b': [3.0, 4.0]}) df1 equals itself. >>> assert_frame_equal(df1, df1) df1 differs from df2 as column 'b' is of a different type. >>> assert_frame_equal(df1, df2) Traceback (most recent call last): AssertionError: Attributes are different Attribute "dtype" are different [left]: int64 [right]: float64 Ignore differing dtypes in columns with check_dtype. >>> assert_frame_equal(df1, df2, check_dtype=False) sDataFrame shape mismatchs {shape!r}RRRCRRR2RTs {obj}.indexs {obj}.columnsRsDataFrame.blocksNRRsDataFrame.iloc[:, {idx}]tidx(RLRR)RRRRRHROt reindex_likeRR;tcolumnst_to_dict_of_blocksRtsettkeysRt enumeratetilocR(RRRRtcheck_column_typetcheck_frame_typeRRCt by_blocksRRR2t check_likeRTRPtrblockstlblocksRtitcoltlcoltrcol((s2lib/python2.7/site-packages/pandas/util/testing.pyREsV]  5 R.cC s|rt||d|nxB|jD]7}t||} t||} t| | d|q&W|r|j} |j} xKttt| jt| jD]E} | | kst| | kstt | | j | | j qWnxt |j dD]i\}}dj d|}||ksFt||j|}|j|}t||d|d|qWxMt |j dD]6\}}dj d|}||kst|qWdS( sCheck that left and right Panels are equal. Parameters ---------- left : Panel (or nd) right : Panel (or nd) check_dtype : bool, default True Whether to check the Panel dtype is identical. check_panel_type : bool, default False Whether to check the Panel class is identical. check_less_precise : bool or int, default False Specify comparison precision. Only used when check_exact is False. 5 digits (False) or 3 digits (True) after decimal points are compared. If int, then specify the digits to compare check_names : bool, default True Whether to check the Index names attribute. by_blocks : bool, default False Specify how to compare internal data. If False, compare by columns. If True, compare by blocks. obj : str, default 'Panel' Specify the object name being compared, internally used to show the appropriate assertion message. RTRCis"non-matching item (right) '{item}'titemRs!non-matching item (left) '{item}'N(Rt _AXIS_ORDERSRRRRRRRR&R7Rt _get_axisRORR(RRRtcheck_panel_typeRRCRRTtaxistleft_indt right_indRRRRRRxtlitemtritem((s2lib/python2.7/site-packages/pandas/util/testing.pytassert_panel_equals0  5""    "cK sZt}t|tjr+t|||n+t|tjrPt|||nt|tjrut|||nt|t rt |||nt|t rt |||nt|t rt|||n{t|trt|||nYt|trt|||n7t|tjrDt|||ntt|dS(s Wrapper for tm.assert_*_equal to dispatch to the appropriate test function. Parameters ---------- left : Index, Series, DataFrame, ExtensionArray, or np.ndarray right : Index, Series, DataFrame, ExtensionArray, or np.ndarray **kwargs N(RLRRJR+RR0RR)RR5RNR6R}R3RR7RR4RRRRqtNotImplementedErrorR(RRRRP((s2lib/python2.7/site-packages/pandas/util/testing.pyt assert_equal s( cC s|tjkr!tj|}n|tjkrBtj|}n|tjkr{tj|j}|r|j}qn|tkrt|}n~|tkrt|}nc|t krt |}nH|t j krt j |}n'|t krt |}n t||S(s Helper function to wrap the expected output of a test in a given box_class. Parameters ---------- expected : np.ndarray, Index, Series box_cls : {Index, Series, DataFrame} Returns ------- subclass of box_cls (RJR+R0R)tto_frametTR6R8R3R7RRRstto_arrayR(texpectedtbox_clst transpose((s2lib/python2.7/site-packages/pandas/util/testing.pyt box_expectedBs(      cC set|rt|St|s.t|r;tj|St|rTtj|Stj |SdS(N( R"R8RRR3t_from_sequenceR$R7RRs(RT((s2lib/python2.7/site-packages/pandas/util/testing.pyRjs     cC sWt||tjt|j|jd|t|jtjjj sMt t|jtjjj snt |s|jj }|jj }n|j}|j}|r|j dkr|j j }|j j }n|j|stdd||n|r!td||n|r:td||nt|j|jd|dS(s#Check that the left and right SparseArray are equal. Parameters ---------- left : SparseArray right : SparseArray check_dtype : bool, default True Whether to check the data dtype is identical. check_kind : bool, default True Whether to just the kind of the sparse index for each column. check_fill_value : bool, default True Whether to check that left.fill_value matches right.fill_value consolidate_block_indices : bool, default False Whether to consolidate contiguous blocks for sparse arrays with a BlockIndex. Some operations, e.g. concat, will end up with block indices that could be consolidated. Setting this to true will create a new BlockIndex for that array, with consolidated block indices. RtblocksSparseArray.indexsindex are not equalR4RN(RRJt SparseArrayRqt sp_valuesRtsp_indext_libstsparset SparseIndexRtto_block_indextkindt to_int_indexRIRHR/R7(RRRt check_kindtcheck_fill_valuetconsolidate_block_indicest left_indext right_index((s2lib/python2.7/site-packages/pandas/util/testing.pytassert_sp_array_equalzs,!!    t SparseSeriesc C st||tj|r/t||d| nt|j|jddjd| t|j|jd|d|d||rt d||n|rt d||nt t j |jt j |jdS( sCheck that the left and right SparseSeries are equal. Parameters ---------- left : SparseSeries right : SparseSeries check_dtype : bool, default True Whether to check the Series dtype is identical. exact_indices : bool, default True check_series_type : bool, default True Whether to check the SparseSeries class is identical. check_names : bool, default True Whether to check the SparseSeries name attribute. check_kind : bool, default True Whether to just the kind of the sparse index for each column. check_fill_value : bool, default True Whether to check that left.fill_value matches right.fill_value consolidate_block_indices : bool, default False Whether to consolidate contiguous blocks for sparse arrays with a BlockIndex. Some operations, e.g. concat, will end up with block indices that could be consolidated. Setting this to true will create a new BlockIndex for that array, with consolidated block indices. obj : str, default 'SparseSeries' Specify the object name being compared, internally used to show the appropriate assertion message. RTs {obj}.indexRRRRRN( RRJRRRR;RORR7R/RqRR( RRRt exact_indicesRRCRRRRT((s2lib/python2.7/site-packages/pandas/util/testing.pytassert_sp_series_equals!tSparseDataFramec C sFt||tj|r/t||d|nt|j|jddjd|t|j|jddjd||rtd||d|nxt j |D]s\} } | |kst |rt | || d|d|d|d|qt | j|| jd|qWx |D]} | |ks&t q&Wd S( sCheck that the left and right SparseDataFrame are equal. Parameters ---------- left : SparseDataFrame right : SparseDataFrame check_dtype : bool, default True Whether to check the Series dtype is identical. exact_indices : bool, default True SparseSeries SparseIndex objects must be exactly the same, otherwise just compare dense representations. check_frame_type : bool, default True Whether to check the SparseDataFrame class is identical. check_kind : bool, default True Whether to just the kind of the sparse index for each column. check_fill_value : bool, default True Whether to check that left.fill_value matches right.fill_value consolidate_block_indices : bool, default False Whether to consolidate contiguous blocks for sparse arrays with a BlockIndex. Some operations, e.g. concat, will end up with block indices that could be consolidated. Setting this to true will create a new BlockIndex for that array, with consolidated block indices. obj : str, default 'SparseDataFrame' Specify the object name being compared, internally used to show the appropriate assertion message. RTs {obj}.indexs {obj}.columnstdefault_fill_valueRRRRN(RRJRRRR;RORR/Rit iteritemsRRRtto_dense( RRRRRRRRRTRtseries((s2lib/python2.7/site-packages/pandas/util/testing.pytassert_sp_frame_equals,     cC s9x2|D]*}||kstdjd|qWdS(NsDid not contain item: '{key!r}'tkey(RRO(titerabletdictk((s2lib/python2.7/site-packages/pandas/util/testing.pytassert_contains_all3s cK spxit||D]X\}}t|||djdt|dt|}||k st|qWdS(s iter1, iter2: iterables that produce elements comparable with assert_almost_equal Checks that the elements are equal, but not the same object. (Does not check that items in sequences are also not the same object) sdExpected object {obj1!r} and object {obj2!r} to be different objects, but they were the same object.tobj1tobj2N(RRRORR(titer1titer2t eql_kwargstelem1telem2Rx((s2lib/python2.7/site-packages/pandas/util/testing.pyt assert_copy8s  cC s tj| S(N(R,tascii_uppercase(R((s2lib/python2.7/site-packages/pandas/util/testing.pytgetColsIsi cC sttddd|d|S(NRi RR(R+R(RR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeStringIndexNscC sttddd|d|S(NRi RR(R+R(RR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeUnicodeIndexRsicK s7tddd|}ttjj||d||S(s' make a length k index or n categories RiRR(RR(RRR(RtnRRR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeCategoricalIndexVscK s2tjddd|d}tj|d||S(s make a length k IntervalIndex iidtnumiR(RtlinspaceR,t from_breaks(RRRR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeIntervalIndex\scC sf|dkrttgd|S|dkrAtttgd|Stttgtg|dd|S(NiRi(R+RLR(RR((s2lib/python2.7/site-packages/pandas/util/testing.pyt makeBoolIndexbs   cC stt|d|S(NR(R+R(RR((s2lib/python2.7/site-packages/pandas/util/testing.pyt makeIntIndexjscC s-tgt|D]}d|^qd|S(Nii?Rl(R+R(RRR((s2lib/python2.7/site-packages/pandas/util/testing.pyt makeUIntIndexnscK std|dd||S(NiiR(R/(RRR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeRangeIndexrscC sOttjj|tjjd}t|dtjjddd|S(Nii ii R(tsortedRRt random_sampleR+trandint(RRR7((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeFloatIndexvs(tBcK sCtddd}t|d|d|d|}t|d||S(NiitperiodsRGR(RR1R*(RRGRRtdttdr((s2lib/python2.7/site-packages/pandas/util/testing.pyt makeDateIndex{stDc K s%tjddd|d|d||S(Ntstarts1 dayRRGR(RJttimedelta_range(RRGRR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeTimedeltaIndexsc K s=tddd}tjd|d|ddd||}|S(NiiRRRGRR(RRJt period_range(RRRRR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakePeriodIndexs'cK stjddfd||S(NtfootbariiR:(RR(ii(R-t from_product(RR:R((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeMultiIndexsc c sJtttttttttt t g }x|D]}|d|Vq.WdS(sGenerator which can be iterated over to get instances of all the various index classes. Parameters ---------- k: length of each of the index instances RN( RRRRRRRRRRR(Rtall_make_index_funcstmake_index_func((s2lib/python2.7/site-packages/pandas/util/testing.pytall_index_generators     cc s5tttttttg}x|D] }|Vq"WdS(N(RRRRRRR(tmake_index_funcsR ((s2lib/python2.7/site-packages/pandas/util/testing.pytindex_subclass_makers_generators   cc s2tttg}x|D]}|d|VqWdS(sGenerator which can be iterated over to get instances of all the classes which represent time-seires. Parameters ---------- k: length of each of the index instances RN(RRR(RR R ((s2lib/python2.7/site-packages/pandas/util/testing.pytall_timeseries_index_generators cC s(tt}tttd|d|S(NR;R(RtNR0R(RR;((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeFloatSeriess cC s(tt}tttd|d|S(NR;R(RRR0R(RR;((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeStringSeriess cC s@tt}t|dt}tt}t|d|d|S(NRR;R(RRR+RRR0(Rt dateIndexR;((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeObjectSeriess  c s&ttfdttDS(Nc s+i|]!}tttd|qS(R;(R0RR(t.0tc(R;(s2lib/python2.7/site-packages/pandas/util/testing.pys s (RRRtK(((R;s2lib/python2.7/site-packages/pandas/util/testing.pyt getSeriesDatas cC s=|dkrt}ntt|dt|d|d|S(NR;RGR(R<RR0RR(tnperRGR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeTimeSeriess  cC s7|dkrt}ntt|dt|d|S(NR;R(R<RR0RR(RR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakePeriodSeriess  c sfdttDS(Nc s"i|]}t|qS((R(RR(RGR(s2lib/python2.7/site-packages/pandas/util/testing.pys s (RR(RRG((RGRs2lib/python2.7/site-packages/pandas/util/testing.pytgetTimeSeriesDatasc sfdttDS(Nc si|]}t|qS((R(RR(R(s2lib/python2.7/site-packages/pandas/util/testing.pys s (RR(R((Rs2lib/python2.7/site-packages/pandas/util/testing.pyt getPeriodDatascC st||}t|S(N(RR)(RRGR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeTimeDataFramescC st}t|S(N(RR)(R((s2lib/python2.7/site-packages/pandas/util/testing.pyt makeDataFrames cC stdddddg}idddd d gd 6dddddgd 6d ddddgd6tdddd6}||fS(NtatbRtdRgg?g@g@g@tARtfoo1tfoo2tfoo3tfoo4tfoo5tCs1/1/2009RiR(R+R1(R;R((s2lib/python2.7/site-packages/pandas/util/testing.pytgetMixedTypeDictscC sttdS(Ni(R)R((((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeMixedDataFramescC st|}t|S(N(RR)(RR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakePeriodFrames c s{tjdtctjddtgtjtd D]}d|^q8}fd|D}tj |SWdQXdS(NtrecordRGs\nPanelitItemc si|]}t|qS((R(RR(R(s2lib/python2.7/site-packages/pandas/util/testing.pys s ( RBtcatch_warningsRLtfilterwarningst FutureWarningR,RRR.tfromDict(RRtcolsR((Rs2lib/python2.7/site-packages/pandas/util/testing.pyt makePanels (c s{tjdtctjddtgtjtd D]}d|^q8}fd|D}tj |SWdQXdS(NR+RGs\nPaneliR,c si|]}t|qS((R*(RR(R(s2lib/python2.7/site-packages/pandas/util/testing.pys s ( RBR-RLR.R/R,RRR.R0(RRR1R((Rs2lib/python2.7/site-packages/pandas/util/testing.pytmakePeriodPanels (t#cC s[|dkrdg|}nt|r:t||ks@t|dks||tks||tks|t||ks|t|dks|dkr|dkst|tkrgt|D]}|t|^q}n|tkrd}nt|t j r|dkr|g}nt dt dt dtdtdtdtdtj|}|r||}|r|d |_n|S|dk rtd jd |nt||kr|jdg|t|nt||ksttd |Dstg} xt|D]}d } |||d} t} x@t| D]2} djd|d|d| }||| | 1 produces multindex) prefix - a string prefix for labels names - (Optional), bool or list of strings. if True will use default names, if false will use no names, if a list is given, the name of each level in the index will be taken from the list. ndupe_l - (Optional), list of ints, the number of rows for which the label will repeated at the corresponding level, you can specify just the first few, the rest will use the default ndupe_l of 1. len(ndupe_l) <= nlevels. idx_type - "i"/"f"/"s"/"u"/"dt"/"p"/"td". If idx_type is not None, `idx_nlevels` must be 1. "i"/"f" creates an integer/float index, "s"/"u" creates a string/unicode index "dt" create a datetime index. "td" create a datetime index. if unspecified, string labels will be generated. iRRttsRRRttdisT"{idx_type}" is not a legal value for `idx_type`, use "i"/"f"/"s"/"u"/"dt/"p"/"td".tidx_typecs s|]}|dkVqdS(iN((RR((s2lib/python2.7/site-packages/pandas/util/testing.pys VscS s7ddl}|jdd|jd}tt|S(Nis[^\d_]_?Rt_(RtsubRRRK(RRt numeric_tuple((s2lib/python2.7/site-packages/pandas/util/testing.pytkeyfuncZs s{prefix}_l{i}_g{j}RtjRRcs s|]}|dVqdS(iN((RR((s2lib/python2.7/site-packages/pandas/util/testing.pys qsR:N(RRtR5RRRR6("R<R#RoRRRLRRRRiRRRRRRRRRRARRqROtextendRaR RRtelementsRRR+R-t from_tuples(tnentriesRARR:tndupe_lR7Rtidx_funcRttuplesR;t div_factortcntR<tlabelRdR;R((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeCustomIndexs` $$  ,        !  "   c  C s;|dkst|dks$t| dksN| dkrH|d ksNt| dksx| dkrr|d ksxtt|d |d d d |d|d| } t|d |d dd |d|d| } |dkrd}ngt|D].}gt|D]}|||^q^q}t|| | d| S(s nrows, ncols - number of data rows/cols c_idx_names, idx_names - False/True/list of strings, yields No names , default names or uses the provided names for the levels of the corresponding index. You can provide a single string when c_idx_nlevels ==1. c_idx_nlevels - number of levels in columns index. > 1 will yield MultiIndex r_idx_nlevels - number of levels in rows index. > 1 will yield MultiIndex data_gen_f - a function f(row,col) which return the data value at that position, the default generator used yields values of the form "RxCy" based on position. c_ndupe_l, r_ndupe_l - list of integers, determines the number of duplicates for each label at a given level of the corresponding index. The default `None` value produces a multiplicity of 1 across all levels, i.e. a unique index. Will accept a partial list of length N < idx_nlevels, for just the first N levels. If ndupe doesn't divide nrows/ncol, the last label might have lower multiplicity. dtype - passed to the DataFrame constructor as is, in case you wish to have more control in conjuncion with a custom `data_gen_f` r_idx_type, c_idx_type - "i"/"f"/"s"/"u"/"dt"/"td". If idx_type is not None, `idx_nlevels` must be 1. "i"/"f" creates an integer/float index, "s"/"u" creates a string/unicode index "dt" create a datetime index. "td" create a timedelta index. if unspecified, string labels will be generated. Examples: # 5 row, 3 columns, default names on both, single index on both axis >> makeCustomDataframe(5,3) # make the data a random int between 1 and 100 >> mkdf(5,3,data_gen_f=lambda r,c:randint(1,100)) # 2-level multiindex on rows with each label duplicated # twice on first level, default names on both axis, single # index on both axis >> a=makeCustomDataframe(5,3,r_idx_nlevels=2,r_ndupe_l=[2]) # DatetimeIndex on row, index with unicode labels on columns # no names on either axis >> a=makeCustomDataframe(5,3,c_idx_names=False,r_idx_names=False, r_idx_type="dt",c_idx_type="u") # 4-level multindex on rows with names provided, 2-level multindex # on columns with default labels and default names. >> a=makeCustomDataframe(5,3,r_idx_nlevels=4, r_idx_names=["FEE","FI","FO","FAM"], c_idx_nlevels=2) >> a=mkdf(5,3,r_idx_nlevels=2,c_idx_nlevels=4) iRRtR5RRRR6iRARR'R:RAR7tRcS sdjd|d|S(NsR{rows}C{cols}trowsR1(RO(R1R((s2lib/python2.7/site-packages/pandas/util/testing.pyRsRN(RRtR5RRRR6(RRtR5RRRR6(RR<RGRR)(tnrowstncolst c_idx_namest r_idx_namest c_idx_nlevelst r_idx_nlevelst data_gen_ft c_ndupe_lt r_ndupe_lRt c_idx_typet r_idx_typeRR;R1RR((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeCustomDataframews$;        Ac  s|dkrtj}ntjj|}ttjd|d}d}t||}fd}|||}x,|jkr|d9}|||}qWtj|dj t} || j t} | j | j fS(NiigRQ?c s7|jt|}tjtj| S(N(RRKRR=tfloor(trngt _extra_sizetind(RKRJR(s2lib/python2.7/site-packages/pandas/util/testing.pyt_gen_unique_randsg?g?( R<RRt RandomStateRKRLtminRRVRttolist( RJRKtdensityt random_statetmin_rowstfact extra_sizeRZRYR<R((RKRJRs2lib/python2.7/site-packages/pandas/util/testing.pyt_create_missing_idxs  !  g?cC st||d|d|d|d|d|d| d| d| d | d |  }t||||\}}tj|j||f<|S( s[ Parameters ---------- Density : float, optional Float in (0, 1) that gives the percentage of non-missing numbers in the DataFrame. random_state : {np.random.RandomState, int}, optional Random number generator or random seed. See makeCustomDataframe for descriptions of the rest of the parameters. RLRMRNRORPRQRRRRSRT(RURcRtnanR7(RJRKR^R_RLRMRNRORPRQRRRRSRTtdfRR<((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeMissingCustomDataframes   cC sDt}td|d||j\}}tj|j||f<|S(NR^R_(RRcRRRdR7(R^R_ReRR<((s2lib/python2.7/site-packages/pandas/util/testing.pytmakeMissingDataframe s   c C su|j\}}}x\t|jD]K\}}||}x2t|jD]!\}}tj||||*qHWq"W|S(N(RRtitemsRRtNaN( tpaneltItJRRRtdmR<R((s2lib/python2.7/site-packages/pandas/util/testing.pytadd_nans s  t TestSubDictcB seZdZRS(cO stj|||dS(N(Rt__init__(tselfRR((s2lib/python2.7/site-packages/pandas/util/testing.pyRp s(Rt __module__Rp(((s2lib/python2.7/site-packages/pandas/util/testing.pyRo sc stfd}|S(s8allows a decorator to take optional positional and keyword arguments. Assumes that taking a single, callable, positional argument means that it is decorating a function, i.e. something like this:: @my_decorator def function(): pass Calls decorator with decorator(f, *args, **kwargs)c sffd} o;tdko;td}|r^d}g||S|SdS(Nc s|S(N((Rt(Rt decoratorR(s2lib/python2.7/site-packages/pandas/util/testing.pytdec( sii(RoR (RRRtt is_decoratingRt(Rs(RRs2lib/python2.7/site-packages/pandas/util/testing.pytwrapper& s)  (R(RsRv((Rss2lib/python2.7/site-packages/pandas/util/testing.pyt optional_args s  s timed outs Server Hangups#HTTP Error 503: Service Unavailables502: Proxy ErrorsHTTP Error 502: internal errorsHTTP Error 502sHTTP Error 503sHTTP Error 403sHTTP Error 400s$Temporary failure in name resolutionsName or service not knownsConnection refusedscertificate verifyieioinihi6i<cC s4yt|WdQXWn|k r+tSXtSdS(s;Try to connect to the given url. True if succeeds, False if IOError raised Parameters ---------- url : basestring The URL to try to connect to Returns ------- connectable : bool Return True if no IOError (unable to connect) or URLError (bad url) was raised N(R9RRL(turlt error_classes((s2lib/python2.7/site-packages/pandas/util/testing.pyt can_connect` s    shttp://www.google.comc  sPddlmt_tjfd}|S(s^ Label a test as requiring network connection and, if an error is encountered, only raise if it does not find a network connection. In comparison to ``network``, this assumes an added contract to your test: you must assert that, under normal conditions, your test will ONLY fail if it does not have network connectivity. You can call this in 3 ways: as a standard decorator, with keyword arguments, or with a positional argument that is the url to check. Parameters ---------- t : callable The test requiring network connectivity. url : path The url to test via ``pandas.io.common.urlopen`` to check for connectivity. Defaults to 'http://www.google.com'. raise_on_error : bool If True, never catches errors. check_before_test : bool If True, checks connectivity before running the test case. error_classes : tuple or Exception error classes to ignore. If not in ``error_classes``, raises the error. defaults to IOError. Be careful about changing the error classes here. skip_errnos : iterable of int Any exception that has .errno or .reason.erno set to one of these values will be skipped with an appropriate message. _skip_on_messages: iterable of string any exception e for which one of the strings is a substring of str(e) will be skipped with an appropriate message. Intended to suppress errors where an errno isn't available. Notes ----- * ``raise_on_error`` supercedes ``check_before_test`` Returns ------- t : callable The decorated test ``t``, with checks for connectivity errors. Example ------- Tests decorated with @network will fail if it's possible to make a network connection to another URL (defaults to google.com):: >>> from pandas.util.testing import network >>> from pandas.io.common import urlopen >>> @network ... def test_network(): ... with urlopen("rabbit://bonanza.com"): ... pass Traceback ... URLError: You can specify alternative URLs:: >>> @network("http://www.yahoo.com") ... def test_something_with_yahoo(): ... raise IOError("Failure Message") >>> test_something_with_yahoo() Traceback (most recent call last): ... IOError: Failure Message If you set check_before_test, it will check the url first and not run the test on failure:: >>> @network("failing://url.blaher", check_before_test=True) ... def test_something(): ... print("I ran!") ... raise ValueError("Failure") >>> test_something() Traceback (most recent call last): ... Errors not related to networking will always be raised. i(Rc sgr) r)ts)q)ny||SWn&tk rb}t|dd}| rt|drt|jdd}n|krdjd|nytj|Wntk rt |nXt fdDrdjd|nt |s.nsCtrIqcdjd|nXdS(Nterrnotreasons2Skipping test due to known errno and error {error}Rc3 s'|]}|jjkVqdS(N(tlower(Rtm(te_str(s2lib/python2.7/site-packages/pandas/util/testing.pys ssBSkipping test because exception message is known and error {error}s;Skipping test due to lack of connectivity and error {error}( RzRRR<RoR|ROt tracebackt format_excRtanyR(RRRR{(t_skip_on_messagestcheck_before_testRytraise_on_errorRt skip_errnosttRx(Rs2lib/python2.7/site-packages/pandas/util/testing.pyRv s2         (RYRRLtnetworkRiR(RRxRRRyRRRv((RRRyRRRRRxs2lib/python2.7/site-packages/pandas/util/testing.pyRx sZ 3"cO s\tjdtddtd|d|}|dk rT||||WdQXn|SdS(s Check that the specified Exception is raised and that the error message matches a given regular expression pattern. This may be a regular expression object or a string containing a regular expression suitable for use by `re.search()`. This is a port of the `assertRaisesRegexp` function from unittest in Python 2.7. .. deprecated:: 0.24.0 Use `pytest.raises` instead. Examples -------- >>> assert_raises_regex(ValueError, 'invalid literal for.*XYZ', int, 'XYZ') >>> import re >>> assert_raises_regex(ValueError, re.compile('literal'), int, 'XYZ') If an exception of a different type is raised, it bubbles up. >>> assert_raises_regex(TypeError, 'literal', int, 'XYZ') Traceback (most recent call last): ... ValueError: invalid literal for int() with base 10: 'XYZ' >>> dct = dict() >>> assert_raises_regex(KeyError, 'pear', dct.__getitem__, 'apple') Traceback (most recent call last): ... AssertionError: "pear" does not match "'apple'" You can also use this in a with statement. >>> with assert_raises_regex(TypeError, r'unsupported operand type\(s\)'): ... 1 + {} >>> with assert_raises_regex(TypeError, 'banana'): ... 'apple'[0] = 'b' Traceback (most recent call last): ... AssertionError: "banana" does not match "'str' object does not support \ item assignment" stassert_raises_regex has been deprecated and will be removed in the next release. Please use `pytest.raises` instead.t stackleveliRtregexpN(RBtwarnR/t_AssertRaisesContextmanagerR<(t _exceptiont_regexpt _callableRRtmanager((s2lib/python2.7/site-packages/pandas/util/testing.pytassert_raises_regex s)   RcB s5eZdZddZdZdZdZRS(s7 Context manager behind `assert_raises_regex`. cC sJ||_|dk r=t|d r=tj|tj}n||_dS(s Initialize an _AssertRaisesContextManager instance. Parameters ---------- exception : class The expected Exception class. regexp : str, default None The regex to compare against the Exception message. tsearchN(RR<RoRRtDOTALLR(RqRR((s2lib/python2.7/site-packages/pandas/util/testing.pyRp7 s cC s|S(N((Rq((s2lib/python2.7/site-packages/pandas/util/testing.pyt __enter__J scC sU|j}|sBt|dt|}tdjd|n|j|||S(NRs{name} not raised.R(RRRRROtexception_matches(Rqtexc_typet exc_valuet trace_backRtexp_name((s2lib/python2.7/site-packages/pandas/util/testing.pyt__exit__M s  cC st||jr|jdk r|t|}|jj|s|djd|jjd|}t|}t ||q|nt St SdS(s Check that the Exception raised matches the expected Exception and expected error message regular expression. Parameters ---------- exc_type : class The type of Exception raised. exc_value : Exception The instance of `exc_type` raised. trace_back : stack trace object The traceback object associated with `exc_value`. Returns ------- is_matched : bool Whether or not the Exception raised matches the expected Exception class and expected error message regular expression. Raises ------ AssertionError : The error message provided does not match the expected error message regular expression. s"{pat}" does not match "{val}"tpattvalN( t issubclassRRR<RRRORRRRLR(RqRRRRRxR((s2lib/python2.7/site-packages/pandas/util/testing.pyRV s   N(RRrt__doc__R<RpRRR(((s2lib/python2.7/site-packages/pandas/util/testing.pyR2 s    R>c c st}tjdt}|dk rxt|s?|g}nx6|D]+}y|jjWqFtk rpqFXqFWnt}tj ||Vg}x|D]} |rWt | j |rWt}|rt | j t t frddlm} m} | | dd} djd| jd| jd | j} | j| jksTt| qq|j| j j| j| j| jfqW|rd jd |j} |st| n| std jd |WdQXdS(sB Context manager for running code expected to either raise a specific warning, or not raise any warnings. Verifies that the code raises the expected warning, and that it does not raise any other unexpected warnings. It is basically a wrapper around ``warnings.catch_warnings``. Parameters ---------- expected_warning : {Warning, False, None}, default Warning The type of Exception raised. ``exception.Warning`` is the base class for all warnings. To check that no warning is returned, specify ``False`` or ``None``. filter_level : str, default "always" Specifies whether warnings are ignored, displayed, or turned into errors. Valid values are: * "error" - turns matching warnings into exceptions * "ignore" - discard the warning * "always" - always emit a warning * "default" - print the warning the first time it is generated from each location * "module" - print the warning the first time it is generated from each module * "once" - print the warning the first time it is generated clear : str, default None If not ``None`` then remove any previously raised warnings from the ``__warningsregistry__`` to ensure that no warning messages are suppressed by this context manager. If ``None`` is specified, the ``__warningsregistry__`` keeps track of which warnings have been shown, and does not show them again. check_stacklevel : bool, default True If True, displays the line that called the function containing the warning to show were the function is called. Otherwise, the line that implements the function is displayed. Examples -------- >>> import warnings >>> with assert_produces_warning(): ... warnings.warn(UserWarning()) ... >>> with assert_produces_warning(False): ... warnings.warn(RuntimeWarning()) ... Traceback (most recent call last): ... AssertionError: Caused unexpected warning(s): ['RuntimeWarning']. >>> with assert_produces_warning(UserWarning): ... warnings.warn(RuntimeWarning()) Traceback (most recent call last): ... AssertionError: Did not see expected warning of class 'UserWarning'. ..warn:: This is *not* thread-safe. R+i(t getframeinfotstackiiswWarning not set with correct stacklevel. File where warning is raised: {actual} != {caller}. Warning message: {message}tactualtcallerRs/Did not see expected warning of class {name!r}.Rs(Caused unexpected warning(s): {extra!r}.textraN(RLRBR-R<R t__warningregistry__R$RRRCRtcategoryR/tDeprecationWarningtinspectRRRORRRRRtlineno(texpected_warningt filter_levelR$tcheck_stacklevelRPR{R~t saw_warningtextra_warningstactual_warningRRRRx((s2lib/python2.7/site-packages/pandas/util/testing.pytassert_produces_warning sL<              $  t RNGContextcB s)eZdZdZdZdZRS(s- Context manager to set the numpy random number generator speed. Returns to the original value upon exiting the context manager. Parameters ---------- seed : int Seed for numpy.random.seed Examples -------- with RNGContext(42): np.random.randn() cC s ||_dS(N(tseed(RqR((s2lib/python2.7/site-packages/pandas/util/testing.pyRp scC s)tjj|_tjj|jdS(N(RRt get_statet start_stateR(Rq((s2lib/python2.7/site-packages/pandas/util/testing.pyR scC stjj|jdS(N(RRt set_stateR(RqRRR((s2lib/python2.7/site-packages/pandas/util/testing.pyR s(RRrRRpRR(((s2lib/python2.7/site-packages/pandas/util/testing.pyR s  ck s\ddl}dddh}||kr6tdn|j||dV|j|dS(su Context manager to temporarily register a CSV dialect for parsing CSV. Parameters ---------- name : str The name of the dialect. kwargs : mapping The parameters for the dialect. Raises ------ ValueError : the name of the dialect conflicts with a builtin one. See Also -------- csv : Python's CSV library. iNtexcels excel-tabtunixs Cannot override builtin dialect.(tcsvRqtregister_dialecttunregister_dialect(RRRt_BUILTIN_DIALECTS((s2lib/python2.7/site-packages/pandas/util/testing.pytwith_csv_dialect s  cc soddlm}|dkr(|j}n|j}|j}|j|||_dV||_|j|dS(Ni(t expressions(tpandas.core.computationRR<t _MIN_ELEMENTSt _USE_NUMEXPRtset_use_numexpr(tuset min_elementstexprtoldusetoldmin((s2lib/python2.7/site-packages/pandas/util/testing.pyt use_numexpr, s       ic sgdkstdk r?tks?tnddlfd}|S(sDecorator to run the same function multiple times in parallel. Parameters ---------- num_threads : int, optional The number of times the function is run in parallel. kwargs_list : list of dicts, optional The list of kwargs to update original function kwargs on different threads. Notes ----- This decorator does not pass the return value of the decorated function. Original from scikit-image: https://github.com/scikit-image/scikit-image/pull/1519 iiNc s+tfd}|S(Nc srfd}nfd}g}xKtD]=}||}jdd|d|}|j|q=Wx|D]}|jqWx|D]}|jqWdS(Nc st|S(N(R(R(Rt kwargs_list(s2lib/python2.7/site-packages/pandas/util/testing.pyRY sc sS(N((R(R(s2lib/python2.7/site-packages/pandas/util/testing.pyR[ sttargetRR(RtThreadRRR(RRt update_kwargstthreadsRtupdated_kwargstthread(tfuncthas_kwargs_listRt num_threadst threading(Rs2lib/python2.7/site-packages/pandas/util/testing.pytinnerV s    (R(RR(RRRR(Rs2lib/python2.7/site-packages/pandas/util/testing.pyRvU s'(RR<RoR(RRRv((RRRRs2lib/python2.7/site-packages/pandas/util/testing.pyt test_parallel; s  tSubclassedSeriescB s2eZddgZedZedZRS(ttestattrRcC stS(N(R(Rq((s2lib/python2.7/site-packages/pandas/util/testing.pyt _constructorm scC stS(N(tSubclassedDataFrame(Rq((s2lib/python2.7/site-packages/pandas/util/testing.pyt_constructor_expanddimq s(RRrt _metadatatpropertyRR(((s2lib/python2.7/site-packages/pandas/util/testing.pyRj s RcB s/eZdgZedZedZRS(RcC stS(N(R(Rq((s2lib/python2.7/site-packages/pandas/util/testing.pyRy scC stS(N(R(Rq((s2lib/python2.7/site-packages/pandas/util/testing.pyt_constructor_sliced} s(RRrRRRR(((s2lib/python2.7/site-packages/pandas/util/testing.pyRv s tSubclassedSparseSeriescB s/eZdgZedZedZRS(RcC stS(N(R(Rq((s2lib/python2.7/site-packages/pandas/util/testing.pyR scC stS(N(tSubclassedSparseDataFrame(Rq((s2lib/python2.7/site-packages/pandas/util/testing.pyR s(RRrRRRR(((s2lib/python2.7/site-packages/pandas/util/testing.pyR s RcB s/eZdgZedZedZRS(RcC stS(N(R(Rq((s2lib/python2.7/site-packages/pandas/util/testing.pyR scC stS(N(R(Rq((s2lib/python2.7/site-packages/pandas/util/testing.pyR s(RRrRRRR(((s2lib/python2.7/site-packages/pandas/util/testing.pyR s tSubclassedCategoricalcB seZedZRS(cC stS(N(R(Rq((s2lib/python2.7/site-packages/pandas/util/testing.pyR s(RRrRR(((s2lib/python2.7/site-packages/pandas/util/testing.pyR sc# saddlddlfd}jjd}||z dVWd||XdS(sContext manager for temporarily setting a timezone. Parameters ---------- tz : str A string representing a valid timezone. Examples -------- >>> from datetime import datetime >>> from dateutil.tz import tzlocal >>> tzlocal().tzname(datetime.now()) 'IST' >>> with set_timezone('US/Eastern'): ... tzlocal().tzname(datetime.now()) ... 'EDT' iNc sL|dkr1yjd=WqHtk r-qHXn|jd<jdS(NtTZ(R<R@tKeyErrorttzset(R~(R?ttime(s2lib/python2.7/site-packages/pandas/util/testing.pytsetTZ s   R(R?RR@RA(R~Rtorig_tz((R?Rs2lib/python2.7/site-packages/pandas/util/testing.pyt set_timezone s     c s+rfd}nfd}|S(slCreate a function for calling on an array. Parameters ---------- alternative : function The function to be called on the array with no NaNs. 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Returns ------- expected : string Expected output of to_csv() in current OS (R?tlinesepR(t rows_listtsepR((s2lib/python2.7/site-packages/pandas/util/testing.pytconvert_rows_list_to_csv_str s (i( s timed outs Server Hangups#HTTP Error 503: Service Unavailables502: Proxy ErrorsHTTP Error 502: internal errorsHTTP Error 502sHTTP Error 503sHTTP Error 403sHTTP Error 400s$Temporary failure in name resolutionsName or service not knownsConnection refusedscertificate verify(ieioinihi6i<(t __future__Rt contextlibRRt functoolsRRR?RtshutilRR,RRRRRBtnumpyRt numpy.randomRRt pandas._libsRRt pandas.compatRiRR R R R R RRRRRRRRRRtpandas.core.dtypes.commonRRRRRRRRR R!R"R#R$R%tpandas.core.dtypes.missingR&tpandasRJR'R(R)R*R+R,R-R.R/R0R1tpandas.core.algorithmsR2tpandas.core.arraysR3R4R5R6R7R8tpandas.core.commontcoretcommonRtpandas.io.commonR9tpandas.io.formats.printingR:RRRt_RAISE_NETWORK_ERROR_DEFAULTRtResourceWarningRDRFRHRMR<RVR^RbRyRRRRLRRRsRt ascii_letterstdigitsRRRRRRRRPRRrRRRtLC_ALLRRRRR RRRQR#R'R+RRR/RmRpRuRORNR}RRRHRqRRRRRRRRRRRRRRRRRRRRRRRRRRR R R RRRRRRRRRRR(R)R*R2R3RGRURcRfRgRnRRoRwt_network_error_messagest_network_errno_valstIOErrort HTTPExceptiont_network_error_classest TimeoutErrorRzRtwith_connectivity_checkRRRtWarningRRRRRRRRRRRRRRR(((s2lib/python2.7/site-packages/pandas/util/testing.pyts          j^ L.      2 1 G  -  #  9   / q (   %    !J 0 v  9 " (  9 2 C                 `  Q      | 5Nm/    ,