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B �5�g/ � @ s� d Z ddlmZ ddlmZ ddlZddlmZ ddl m Z ddl m Z ddl mZ d ZG d d � d �ZG d d � d e�ZG dd� de�ZG dd� de�ZG dd� de�ZG dd� de�ZG dd� de�ZG dd� de�ZdS )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 @ sB e Zd ZdZdddd�dd�Zee�ddd d d d d �dd��ZdS )� BaseIndexerz*Base class for window bounds calculations.Nr znp.ndarray | None�int)� index_array� window_sizec K s2 || _ || _x |�� D ]\}}t| ||� qW dS )z� Parameters ---------- **kwargs : keyword arguments that will be available when get_window_bounds is called N)r r �items�setattr)�selfr r �kwargs�key�value� r �Q/home/digitalm-up/venv/lib/python3.7/site-packages/pandas/core/window/indexers.py�__init__+ s zBaseIndexer.__init__z int | Nonez bool | Nonez str | Nonez tuple[np.ndarray, np.ndarray])� num_values� min_periods�center�closed�returnc C s t �d S )N)�NotImplementedError)r r r r r r r r �get_window_bounds: s z BaseIndexer.get_window_bounds)Nr )r NNN)�__name__� __module__� __qualname__�__doc__r r �get_window_bounds_docr r r r r r ( s r c @ s0 e Zd ZdZee�d dddddd �d d ��ZdS ) �FixedWindowIndexerz3Creates window boundaries that are of fixed length.r Nr z int | Nonez bool | Nonez str | Nonez tuple[np.ndarray, np.ndarray])r r r r r c C s� |r| j d d }nd}tjd| |d | dd�}|| j }|dkrN|d8 }|dkr^|d8 }t�|d|�}t�|d|�}||fS )N� � r �int64)�dtype)�left�both)r& Zneither)r �np�arangeZclip)r r r r r �offset�end�startr r r r I s z$FixedWindowIndexer.get_window_bounds)r NNN)r r r r r r r r r r r r! F s r! c @ s0 e Zd ZdZee�d dddddd �d d ��ZdS ) �VariableWindowIndexerzNCreates window boundaries that are of variable length, namely for time series.r Nr z int | Nonez bool | Nonez str | Nonez tuple[np.ndarray, np.ndarray])r r r r r c C s t || j|||| j�S )N)r r r )r r r r r r r r r g s z'VariableWindowIndexer.get_window_bounds)r NNN)r r r r r r r r r r r r- d s r- c sJ e Zd ZdZdddd�� fdd� Zee�ddd d d d d �dd��Z� ZS )�VariableOffsetWindowIndexerzMCalculate window boundaries based on a non-fixed offset such as a BusinessDayNr znp.ndarray | Noner )r r c s" t � j||f|� || _|| _d S )N)�superr �indexr* )r r r r0 r* r )� __class__r r r � s z$VariableOffsetWindowIndexer.__init__z int | Nonez bool | Nonez str | Nonez tuple[np.ndarray, np.ndarray])r r r r r c C s� |d kr| j d k rdnd}|dk}|dk}| j |d | j d k rHd}nd}tj|dd �}|�d� tj|dd �} | �d� d|d< |r�d| d< nd| d< x�td|�D ]�} | j | } | j | || j } |r�| td�8 } | || < x>t|| d | �D ](} | j | | | td�kr�| || < P q�W | j | | d | | td�k�rR| d | | < n| | d | | < |s�| | d8 < q�W || fS ) N�rightr' )r2 r' )r& r' r" r ���r$ )r% )r0 r( �empty�fill�ranger* r r )r r r r r Z right_closedZ left_closedZindex_growth_signr, r+ �iZ end_boundZ start_bound�jr r r r � s> $z-VariableOffsetWindowIndexer.get_window_bounds)Nr NN)r NNN) r r r r r r r r � __classcell__r r )r1 r r. ~ s r. c @ s0 e Zd ZdZee�d dddddd �d d ��ZdS ) �ExpandingIndexerz;Calculate expanding window bounds, mimicking df.expanding()r Nr z int | Nonez bool | Nonez str | Nonez tuple[np.ndarray, np.ndarray])r r r r r c C s& t j|t jd�t jd|d t jd�fS )N)r% r" )r( Zzerosr$ r) )r r r r r r r r r � s z"ExpandingIndexer.get_window_bounds)r NNN)r r r r r r r r r r r r: � s r: c @ s0 e Zd ZdZee�d 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 r Nr z int | Nonez bool | Nonez str | Nonez tuple[np.ndarray, np.ndarray])r r r r r c C sR |r t d��|d k r t d��tj|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% )� ValueErrorr( r) r )r r r r r r, r+ r r r r � s z+FixedForwardWindowIndexer.get_window_bounds)r NNN)r r r r r r r r r r r r; � s r; c sZ e Zd ZdZdddedfdddddd�� fd d � Zee�dd d d ddd�dd��Z� Z S )�GroupbyIndexerzMCalculate bounds to compute groupby rolling, mimicking df.groupby().rolling()Nr znp.ndarray | Nonezint | BaseIndexerz dict | Noneztype[BaseIndexer])r r �groupby_indices�window_indexer�indexer_kwargsc sH |pi | _ || _|r |�� ni | _t� jf || j�d|�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 r N)r> r? �copyr@ r/ r �pop)r r r r> r? r@ r )r1 r r r s zGroupbyIndexer.__init__r z int | Nonez bool | Nonez str | Nonez tuple[np.ndarray, np.ndarray])r r r r r c C s0 g }g }d}�x| j �� D ]�\}} | jd k r>| j�t| ��} n| j} | jf | | jd�| j��} | �t | �|||�\} } | � t j �} | � t j �} t | �t | �ks�t d��t �||t | � �}|t | �7 }t �||d d g�j t j dd�}|�|�t| ��� |�|�t| ��� qW t �|�} t �|�} | | fS )Nr )r r z6these should be equal in length from get_window_boundsr3 r" F)rA )r> r r Ztaker r? r r@ r �lenZastyper( r$ �AssertionErrorr) �appendZ concatenate)r r r r r Z start_arraysZ end_arraysZwindow_indices_startr �indicesr Zindexerr, r+ Zwindow_indicesr r r r ; s8 z GroupbyIndexer.get_window_bounds)r NNN) r r r r r r r r r r9 r r )r1 r r= s r= c @ s0 e Zd ZdZee�d dddddd �d d ��ZdS ) � ExponentialMovingWindowIndexerz/Calculate ewm window bounds (the entire window)r Nr z int | Nonez bool | Nonez str | Nonez tuple[np.ndarray, np.ndarray])r r r r r c C s$ t jdgt jd�t j|gt jd�fS )Nr )r% )r( �arrayr$ )r r r r r r r r r q s z0ExponentialMovingWindowIndexer.get_window_bounds)r NNN)r r r r r r r r r r r rG n s rG )r � __future__r �datetimer �numpyr( Z pandas._libs.window.indexersr Zpandas.util._decoratorsr Zpandas.core.dtypes.commonr Zpandas.tseries.offsetsr r r r! r- r. r: r; r= rG r r r r �<module> s R2Z
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