U f/e @sddlZddlZddlZddlmZmZmZmZddl m Z ddl m Zejddddgddgd d d Zd d ZejdejdejdgdddZddejejejfDZeddejejfDeddejejejfDeejdejdgedddgejedddZejeejdddeejdddeejdddedgdd d!d"d#Zejed$ed$ed$gd%d d!d&d'Z ejej!"d(ej!#d)ejd(d*ed+e$d(d,e$d)d-gd.d d!d/d0Z%ejej!#d1ej!&d2ejd1d3ejd4d5e$d1d-e$d2d6gd7d d!d8d9Z'ej!(d1ej!)dej!&gZ*ejejd:d;e$d:d<ejd:d5ge*dd=d>Z+eje$d?d-ejd@d3edAge*ddBdCZ,eje$dDd,ejdDd*ejdDd*ge*ddEdFZ-ejejej.ej/ejged!dGdHZ0ejejej.e j1eje2ged!dIdJZ3e0Z4dS)KN) Float64Index Int64Index RangeIndex UInt64Index) expressionsTmodulei@BZnumexprpython)ZautouseZscopeparamsidsccs tj}|jt_|jV|t_dSN)expr _MIN_ELEMENTSparam)requestr rD/tmp/pip-unpacked-wheel-tiezk1ph/pandas/tests/arithmetic/conftest.pyswitch_numexpr_min_elementssrcCs>t|tr4t|dkst|djdt|dS|jSdS)Nr-) isinstancetuplelenAssertionError__name__strxrrrid_funcs rrdtype)r cCs|jS)aL Several variants of integer value 1. The zero-dim integer array behaves like an integer. This fixture can be used to check that datetimelike indexes handle addition and subtraction of integers and zero-dimensional arrays of integers. Examples -------- >>> dti = pd.date_range('2016-01-01', periods=2, freq='H') >>> dti DatetimeIndex(['2016-01-01 00:00:00', '2016-01-01 01:00:00'], dtype='datetime64[ns]', freq='H') >>> dti + one DatetimeIndex(['2016-01-01 01:00:00', '2016-01-01 02:00:00'], dtype='datetime64[ns]', freq='H') rrrrrone(sr#cCs4g|],}tjtjtjfD]}|dgd|dqqS)rr)npint64uint64float64).0box_clsr rrr ?sr+cCs g|]}|dgdtjdqS)r$r)r%r()r)r*rrrr+EscCsg|]}tjd|dqS)rr)r%array)r)r rrrr+Gsr,gcCs|jS)a Several types of scalar zeros and length 5 vectors of zeros. This fixture can be used to check that numeric-dtype indexes handle division by any zero numeric-dtype. Uses vector of length 5 for broadcasting with `numeric_idx` fixture, which creates numeric-dtype vectors also of length 5. Examples -------- >>> arr = RangeIndex(5) >>> arr / zeros Float64Index([nan, inf, inf, inf, inf], dtype='float64') r!r"rrrzeroLsr.r$r(r&r'cCs t|jSr typerrrrrkr1)r r cCs|jS)z7 Several types of numeric-dtypes Index objects r!r"rrr numeric_idxds r3Z5m4scCs t|jSr r/rrrrr1~r2cCs|jS)zT Several variants of Timedelta scalars representing 5 minutes and 4 seconds r!r"rrr scalar_tdxs r4H)daysz72:00:00DhcCs t|jSr r/rrrrr1r2cCs|jS)za Several timedelta-like and DateOffset objects that each represent a 3-day timedelta r!r"rrr three_dayssr:rx)hoursi )secondsmcCs t|jSr r/rrrrr1r2cCs|jS)zb Several timedelta-like and DateOffset objects that each represent a 2-hour timedelta r!r"rrr two_hourssr?)minutesscCs|jS)zp Several timedelta-like and DateOffset instances that are _not_ compatible with Hourly frequencies. r!r"rrr not_hourlys rCz23:00:00cCs|jS)zo Several timedelta-like and DateOffset instances that are _not_ compatible with Daily frequencies. r!r"rrr not_dailys rFimcCs|jS)z{ Several timedelta-like and DateOffset instances that are _not_ compatible with Monthly or Annual frequencies. r!r"rrrmismatched_freqs rGcCs|jS)z] Fixture to test behavior for Index, Series, DataFrame, and pandas Array classes r!r"rrrbox_with_arraysrHcCs|jS)zc Fixture to test behavior for Index, Series, tm.to_array, numpy Array and list classes r!r"rrr box_1d_arraysrI)5Znumpyr%ZpytestZpandaspdrrrrZpandas._testingZ_testingtmZpandas.core.computationrr Zfixturerrr-r&r#ZIndexzerosextendr'r(r.Zaranger3Z TimedeltaZto_pytimedeltaZto_timedelta64r4offsetsZDayZHourZ timedelta64r:ZMinuter?Z YearBeginZ MonthBeginZ_common_mismatchrCrFrGZSeriesZ DataFramerHZto_arraylistrIZbox_with_array2rrrrs