U b@s\dZddlZddlZddlmZmZmZddlm Z ddZ ej ej ddd Z d d Z dS) aP Missing data handling for arithmetic operations. In particular, pandas conventions regarding division by zero differ from numpy in the following ways: 1) np.array([-1, 0, 1], dtype=dtype1) // np.array([0, 0, 0], dtype=dtype2) gives [nan, nan, nan] for most dtype combinations, and [0, 0, 0] for the remaining pairs (the remaining being dtype1==dtype2==intN and dtype==dtype2==uintN). pandas convention is to return [-inf, nan, inf] for all dtype combinations. Note: the numpy behavior described here is py3-specific. 2) np.array([-1, 0, 1], dtype=dtype1) % np.array([0, 0, 0], dtype=dtype2) gives precisely the same results as the // operation. pandas convention is to return [nan, nan, nan] for all dtype combinations. 3) divmod behavior consistent with 1) and 2). N)is_float_dtypeis_integer_dtype is_scalar) roperatorcCst|jr|St|d}t|}|s,|s,|S|r:t|}t|jr|dk}|r|t|@}|j ddd}t ||tj |S)z If this is a reversed op, then flip x,y If we have an integer value (or array in y) and we have 0's, fill them with np.nan, return the result. Mask the nan's from x. dtyperfloat64Fcopy) rrhasattrrnparrayranyisnanastypeZputmasknan)resultxyZis_variable_typeZis_scalar_typeZymaskmaskr;/tmp/pip-unpacked-wheel-ck39h295/pandas/core/ops/missing.py _fill_zeros%s    r)rreturnc Cst|dst|}t|ds(t|}|dk}|r|t|@}||@}|dk}|dk}||dk@}tjdd&||@||@B} ||@||@B} W5QRX|s| s| r|jddd}tj||<tj|| <tj || <|S)am Set results of 0 // 0 to np.nan, regardless of the dtypes of the numerator or the denominator. Parameters ---------- x : ndarray y : ndarray result : ndarray Returns ------- ndarray The filled result. Examples -------- >>> x = np.array([1, 0, -1], dtype=np.int64) >>> x array([ 1, 0, -1]) >>> y = 0 # int 0; numpy behavior is different with float >>> result = x // y >>> result # raw numpy result does not fill division by zero array([0, 0, 0]) >>> mask_zero_div_zero(x, y, result) array([ inf, nan, -inf]) rrignore)invalidrFr) r r r r ZsignbitZerrstaterrinf) rrrZzmaskZ zneg_maskZ zpos_maskZx_lt0Zx_gt0Znan_maskZ neginf_maskZ posinf_maskrrrmask_zero_div_zeroLs(         rcCs|tkr*t|||dt|d||f}n|tjkrVt|||dt|d||f}n^|tjkrnt|||}nF|tjkrt|||}n.|tjkrt|||}n|tj krt|||}|S)a Call _fill_zeros with the appropriate fill value depending on the operation, with special logic for divmod and rdivmod. Parameters ---------- op : function (operator.add, operator.div, ...) left : object (np.ndarray for non-reversed ops) right : object (np.ndarray for reversed ops) result : ndarray Returns ------- result : np.ndarray Notes ----- For divmod and rdivmod, the `result` parameter and returned `result` is a 2-tuple of ndarray objects. r) divmodrrrZrdivmodoperatorfloordivZ rfloordivmodZrmod)opleftrightrrrrdispatch_fill_zeross"      r%)__doc__rZnumpyr Zpandas.core.dtypes.commonrrrZpandas.core.opsrrZndarrayrr%rrrrs '>