3 pd] @sVddlZddlZddlZddljZddZej dFdGdHgdd d Z ej d ej d ej d gdd dZ ddejej gDZejddejej gDejddej ejejgDejej dIejd gejdddJgej edddZej ejejddd ejejddd ejejddd ejdgdddddZej ejdjejdejdjgd ddd!d"Zej ejjd#ejj d$ejd#d%jejd&ej!d#d'ej!d$d(gd)ddd*d+Z"ej ejj d,ejj#d-ejd,d.jejdKd0ej!d,d(ej!d-d1gd2ddd3d4Z$ejj%d,ejj&d ejj#gZ'ej ejd5d6jej!d5d7ejd5d0ge'dd8d9Z(ej ej!d:d(ejd;d.jejd<ge'dd=d>Z)ej ej!d?d'ejd?d%jejd?d%ge'dd@dAZ*ej ejej+ej,geddBdCZ-ej ejej+ej,ej.geddDdEZ/e/Z0dS)LNcCs>t|tr4t|dkst|djdt|dS|jSdS)Nr-) isinstancetuplelenAssertionError__name__str)xr B/tmp/pip-build-7vycvbft/pandas/pandas/tests/arithmetic/conftest.pyid_func s rfooEgonVenkmanNCC1701D)paramscCs|jS)zP A 3-tuple of names, the first two for operands, the last for a result. )param)requestr r r namess rr)dtypecCs|jS)aL Several variants of integer value 1. The zero-dim integer array behaves like an integer. This fixture can be used to check that datetimelike indexes handle addition and subtraction of integers and zero-dimensional arrays of integers. Examples -------- >>> dti = pd.date_range('2016-01-01', periods=2, freq='H') >>> dti DatetimeIndex(['2016-01-01 00:00:00', '2016-01-01 01:00:00'], dtype='datetime64[ns]', freq='H') >>> dti + one DatetimeIndex(['2016-01-01 01:00:00', '2016-01-01 02:00:00'], dtype='datetime64[ns]', freq='H') )r)rr r r one"srcCs4g|],}tjtjtjgD]}|dgd|dqqS)r)r)npint64uint64float64).0box_clsrr r r :sr cCs g|]}|dgdtjdqS)gr)rg)rr)rrr r r r ?scCsg|]}tjd|dqS)r)r)rarray)rrr r r r AsgcCs|jS)a Several types of scalar zeros and length 5 vectors of zeros. This fixture can be used to check that numeric-dtype indexes handle division by any zero numeric-dtype. Uses vector of length 5 for broadcasting with `numeric_idx` fixture, which creates numeric-dtype vectors also of length 5. Examples -------- >>> arr = pd.RangeIndex(5) >>> arr / zeros Float64Index([nan, inf, inf, inf, inf], dtype='float64') )r)rr r r zeroFsr"rrrrcCs t|jS)N)typer )r r r r esr$)ridscCs|jS)z7 Several types of numeric-dtypes Index objects )r)rr r r numeric_idx^s r&Z5m4scCs t|jS)N)r#r )r r r r r$xscCs|jS)zT Several variants of Timedelta scalars representing 5 minutes and 4 seconds )r)rr r r scalar_tdrs r'H)daysz72:00:00DhcCs t|jS)N)r#r )r r r r r$scCs|jS)za Several timedelta-like and DateOffset objects that each represent a 3-day timedelta )r)rr r r three_dayssr-rx)hoursi)secondsmcCs t|jS)N)r#r )r r r r r$scCs|jS)zb Several timedelta-like and DateOffset objects that each represent a 2-hour timedelta )r)rr r r two_hourssr2)minutesscCs|jS)zp Several timedelta-like and DateOffset instances that are _not_ compatible with Hourly frequencies. )r)rr r r not_hourlys r6z23:00:00cCs|jS)zo Several timedelta-like and DateOffset instances that are _not_ compatible with Daily frequencies. )r)rr r r not_dailys r9imcCs|jS)z{ Several timedelta-like and DateOffset instances that are _not_ compatible with Monthly or Annual frequencies. )r)rr r r mismatched_freqs r:cCs|jS)z Several array-like containers that should have effectively identical behavior with respect to arithmetic operations. )r)rr r r boxsr;cCs|jS)z] Fixture to test behavior for Index, Series, DataFrame, and pandas Array classes )r)rr r r box_with_arraysr<)rNN)rrN)rrrggi )1numpyrZpytestZpandaspdZpandas._testingZ_testingtmrZfixturerr!rrIndexzerosextendrrr"Z Float64IndexZarangeZ Int64IndexZ UInt64IndexZ RangeIndexr&Z TimedeltaZto_pytimedeltaZto_timedelta64r'offsetsZDayZHourZ timedelta64r-ZMinuter2Z YearBeginZ MonthBeginZ_common_mismatchr6r9r:ZSeriesZ DataFramer;Zto_arrayr<Zbox_with_array2r r r r s   $                           " &