U b/@sdZddlmZddlmZddlZddlmZddl m Z ddl m Z ddl mZd ZGd d d ZGd d d eZGdddeZGdddeZGdddeZGdddeZGdddeZGdddeZdS)zLIndexer objects for computing start/end window bounds for rolling operations) annotations) timedeltaN) calculate_variable_window_bounds)Appender)ensure_platform_int)Nanoa\ Computes the bounds of a window. Parameters ---------- num_values : int, default 0 number of values that will be aggregated over window_size : int, default 0 the number of rows in a window min_periods : int, default None min_periods passed from the top level rolling API center : bool, default None center passed from the top level rolling API closed : str, default None closed passed from the top level rolling API win_type : str, default None win_type passed from the top level rolling API Returns ------- A tuple of ndarray[int64]s, indicating the boundaries of each window c@sBeZdZdZddddddZeeddd d d d d ddZdS) BaseIndexerz*Base class for window bounds calculations.Nrnp.ndarray | Noneint index_array window_sizecKs.||_||_|D]\}}t|||qdS)z Parameters ---------- **kwargs : keyword arguments that will be available when get_window_bounds is called N)r r itemssetattr)selfr r kwargskeyvaluer@/tmp/pip-unpacked-wheel-xg7vt6ln/pandas/core/indexers/objects.py__init__+s zBaseIndexer.__init__ int | None bool | None str | Nonetuple[np.ndarray, np.ndarray] num_values min_periodscenterclosedreturncCstdSN)NotImplementedErrorrrrrrrrrget_window_bounds:s zBaseIndexer.get_window_bounds)Nr)rNNN)__name__ __module__ __qualname____doc__rrget_window_bounds_docr$rrrrr(src@s0eZdZdZeed dddddd d d ZdS) FixedWindowIndexerz3Creates window boundaries that are of fixed length.rNr rrrrrcCs|r|jdd}nd}tjd||d|dd}||j}|dkrN|d8}|dkr^|d8}t|d|}t|d|}||fS)Nrint64Zdtypeleftboth)r0Zneither)r nparangeZclip)rrrrroffsetendstartrrrr$Is  z$FixedWindowIndexer.get_window_bounds)rNNNr%r&r'r(rr)r$rrrrr*Fsr*c@s0eZdZdZeed dddddd d d ZdS) VariableWindowIndexerzNCreates window boundaries that are of variable length, namely for time series.rNr rrrrrcCst||j||||jSr!)rr r r#rrrr$gs z'VariableWindowIndexer.get_window_bounds)rNNNr7rrrrr8dsr8csJeZdZdZddddfdd Zeeddd d d d d ddZZS)VariableOffsetWindowIndexerzNCalculate window boundaries based on a non-fixed offset such as a BusinessDay.Nrr r r c s"tj||f|||_||_dSr!)superrindexr4)rr r r;r4r __class__rrrsz$VariableOffsetWindowIndexer.__init__rrrrrcCs~|dkr|jdk rdnd}|dk}|dk}|j|d|jdkrHd}nd}tj|dd }|dtj|dd } | dd|d<|rd| d<nd| d<td|D]} |j| } |j| ||j} |r| td8} | || <t|| d| D],} |j| | |tdkr| || <qq|j| | d| |tdkrP| d| | <n| | d| | <|s| | d8<q|| fS) Nrightr1)r>r1r/r+rr-r.)r;r2emptyfillranger4rr)rrrrrZ right_closedZ left_closedZindex_growth_signr6r5iZ end_boundZ start_boundjrrrr$s>      $z-VariableOffsetWindowIndexer.get_window_bounds)NrNN)rNNN) r%r&r'r(rrr)r$ __classcell__rrr<rr9~s r9c@s0eZdZdZeed dddddd d d ZdS) ExpandingIndexerz;Calculate expanding window bounds, mimicking df.expanding()rNr rrrrrcCs&tj|tjdtjd|dtjdfS)Nr.r+)r2zerosr-r3r#rrrr$s z"ExpandingIndexer.get_window_bounds)rNNNr7rrrrrFsrFc@s0eZdZdZeed dddddd d d ZdS) FixedForwardWindowIndexera Creates window boundaries for fixed-length windows that include the current row. Examples -------- >>> df = pd.DataFrame({'B': [0, 1, 2, np.nan, 4]}) >>> df B 0 0.0 1 1.0 2 2.0 3 NaN 4 4.0 >>> indexer = pd.api.indexers.FixedForwardWindowIndexer(window_size=2) >>> df.rolling(window=indexer, min_periods=1).sum() B 0 1.0 1 3.0 2 2.0 3 4.0 4 4.0 rNr rrrrrcCsR|r td|dk rtdtj|dd}||j}|jrJ|||j d<||fS)Nz.Forward-looking windows can't have center=TruezAForward-looking windows don't support setting the closed argumentr-r.) ValueErrorr2r3r )rrrrrr6r5rrrr$s  z+FixedForwardWindowIndexer.get_window_bounds)rNNNr7rrrrrHsrHcsZeZdZdZdddedfddddddfd d Zeedd d d dddddZZ S)GroupbyIndexerzMCalculate bounds to compute groupby rolling, mimicking df.groupby().rolling()Nrr zint | BaseIndexerz dict | Noneztype[BaseIndexer])r r groupby_indiceswindow_indexerindexer_kwargsc sH|pi|_||_|r|ni|_tjf||jd|d|dS)a4 Parameters ---------- index_array : np.ndarray or None np.ndarray of the index of the original object that we are performing a chained groupby operation over. This index has been pre-sorted relative to the groups window_size : int or BaseIndexer window size during the windowing operation groupby_indices : dict or None dict of {group label: [positional index of rows belonging to the group]} window_indexer : BaseIndexer BaseIndexer class determining the start and end bounds of each group indexer_kwargs : dict or None Custom kwargs to be passed to window_indexer **kwargs : keyword arguments that will be available when get_window_bounds is called r r N)rKrLcopyrMr:rpop)rr r rKrLrMrr<rrrs  zGroupbyIndexer.__init__r rrrrrcCs*g}g}d}|jD]\}} |jdk r:|jt| } n|j} |jf| |jd|j} | t | |||\} } | t j } | t j } t | t | kst dt ||t | }|t | 7}t ||ddgj t j dd}||t| ||t| qt |} t |} | | fS)Nrr z6these should be equal in length from get_window_boundsr?r+F)rN)rKrr ZtakerrLr rMr$lenZastyper2r-AssertionErrorr3appendZ concatenate)rrrrrZ start_arraysZ end_arraysZwindow_indices_startrindicesr Zindexerr6r5Zwindow_indicesrrrr$;sP        z GroupbyIndexer.get_window_bounds)rNNN) r%r&r'r(rrrr)r$rErrr<rrJs$rJc@s0eZdZdZeed dddddd d d ZdS) ExponentialMovingWindowIndexerz/Calculate ewm window bounds (the entire window)rNr rrrrrcCs$tjdgtjdtj|gtjdfS)Nrr.)r2arrayr-r#rrrr$qs z0ExponentialMovingWindowIndexer.get_window_bounds)rNNNr7rrrrrTnsrT)r( __future__rdatetimerZnumpyr2Zpandas._libs.window.indexersrZpandas.util._decoratorsrZpandas.core.dtypes.commonrZpandas.tseries.offsetsrr)rr*r8r9rFrHrJrTrrrrs       R2Z