B 2c @sddlZddlZddlZddlmZmZmZmZddl m Z ddl m Zejddddgddgd d d Zd d ZejdejdejdgdddZddejejejgDZeddejejgDeddejejejgDeejdejdgedddgejedddZejeejdddeejdddeejdddedgdd 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)Zautousescopeparamsidsccs tj}|jt_|jV|t_dS)N)expr _MIN_ELEMENTSparam)requestr rD/tmp/pip-install-v41xt_bg/pandas/pandas/tests/arithmetic/conftest.pyswitch_numexpr_min_elementssrcCs>t|tr4t|dkst|djdt|dS|jSdS)Nr-) isinstancetuplelenAssertionError__name__str)xrrrid_funcs rr)dtype)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') )r)rrrrone(srcCs4g|],}tjtjtjgD]}|dgd|dqqS)r)r)npint64uint64float64).0box_clsrrrr @sr'cCs g|]}|dgdtjdqS)gr )r)r!r$)r%r&rrrr'EscCsg|]}tjd|dqS)r)r)r!array)r%rrrrr'GsggcCs|jS)a Several types of scalar zeros and length 5 vectors of zeros. This fixture can be used to check that numeric-dtype indexes handle division by any zero numeric-dtype. Uses vector of length 5 for broadcasting with `numeric_idx` fixture, which creates numeric-dtype vectors also of length 5. Examples -------- >>> arr = RangeIndex(5) >>> arr / zeros Float64Index([nan, inf, inf, inf, inf], dtype='float64') )r)rrrrzeroLsr)r r$r"r#cCs t|jS)N)typer)rrrrkr+)r r cCs|jS)z7 Several types of numeric-dtypes Index objects )r)rrrr numeric_idxds r-Z5m4scCs t|jS)N)r*r)rrrrr+~r,cCs|jS)zT Several variants of Timedelta scalars representing 5 minutes and 4 seconds )r)rrrr scalar_tdxs r.H)daysz72:00:00DhcCs t|jS)N)r*r)rrrrr+r,cCs|jS)za Several timedelta-like and DateOffset objects that each represent a 3-day timedelta )r)rrrr three_dayssr4rx)hoursi )secondsmcCs t|jS)N)r*r)rrrrr+r,cCs|jS)zb Several timedelta-like and DateOffset objects that each represent a 2-hour timedelta )r)rrrr two_hourssr9)minutesscCs|jS)zp Several timedelta-like and DateOffset instances that are _not_ compatible with Hourly frequencies. )r)rrrr not_hourlys r=z23:00:00cCs|jS)zo Several timedelta-like and DateOffset instances that are _not_ compatible with Daily frequencies. )r)rrrr not_dailys r@imcCs|jS)z{ Several timedelta-like and DateOffset instances that are _not_ compatible with Monthly or Annual frequencies. )r)rrrrmismatched_freqs rAcCs|jS)z] Fixture to test behavior for Index, Series, DataFrame, and pandas Array classes )r)rrrrbox_with_arraysrBcCs|jS)zc Fixture to test behavior for Index, Series, tm.to_array, numpy Array and list classes )r)rrrr box_1d_arraysrC)5Znumpyr!ZpytestZpandaspdrrrrZpandas._testingZ_testingtmZpandas.core.computationrr Zfixturerrr(r"rZIndexzerosextendr#r$r)Zaranger-Z TimedeltaZto_pytimedeltaZto_timedelta64r.offsetsZDayZHourZ timedelta64r4ZMinuter9Z YearBeginZ MonthBeginZ_common_mismatchr=r@rAZSeriesZ DataFramerBZto_arraylistrCZbox_with_array2rrrrs    $                          & (