ó ˜í Yc @sdZddlZddlZddddddd d d d g Zddd „Zddd„Zdddd„Zdddd„Z ddd„Z ddd„Z ddd„Z ddd„Z ddd„Zddd„Zddd„Zd„Zdd„ZdS(s<Alternative methods of calculating moving window statistics.iÿÿÿÿNtmove_sumt move_meantmove_stdtmove_vartmove_mintmove_maxt move_argmint move_argmaxt move_mediant move_rankcCsttj|||d|ƒS(s%Slow move_sum for unaccelerated dtypetaxis(t move_functnptnansum(tatwindowt min_countR ((s3lib/python2.7/site-packages/bottleneck/slow/move.pyR scCsttj|||d|ƒS(s&Slow move_mean for unaccelerated dtypeR (R R tnanmean(RRRR ((s3lib/python2.7/site-packages/bottleneck/slow/move.pyRsic Cs"ttj|||d|d|ƒS(s%Slow move_std for unaccelerated dtypeR tddof(R R tnanstd(RRRR R((s3lib/python2.7/site-packages/bottleneck/slow/move.pyRsc Cs"ttj|||d|d|ƒS(s%Slow move_var for unaccelerated dtypeR R(R R tnanvar(RRRR R((s3lib/python2.7/site-packages/bottleneck/slow/move.pyRscCsttj|||d|ƒS(s%Slow move_min for unaccelerated dtypeR (R R tnanmin(RRRR ((s3lib/python2.7/site-packages/bottleneck/slow/move.pyR!scCsttj|||d|ƒS(s%Slow move_max for unaccelerated dtypeR (R R tnanmax(RRRR ((s3lib/python2.7/site-packages/bottleneck/slow/move.pyR&scCs"d„}t||||d|ƒS(s(Slow move_argmin for unaccelerated dtypecSstj|dtƒ}tdƒg|j}tdddƒ||<||}ytj|d|ƒ}Wn£tk r |jƒ}tj |ƒ}tj |tj d|ƒtj |d|ƒj tjƒ}|jdkrätj}q tj|d|ƒ}tj||Generic moving window function implemented with a python loop.Rs1min_count (%d) cannot be greater than window (%d)is&`min_count` must be greater than zero.s(moving window functions require ndim > 0s)An `axis` value of None is not supported.is`window` must be at least 1.s`window` is too long.tignoreR N(R RRRRRtshapet issubclasstdtypettypetinexactt empty_liketemptyRtlisttwarningstcatch_warningst simplefiltertrangetmint_maskR&(tfuncRRRR tkwargstmctmsgtytidx1tidx2titwinR)((s3lib/python2.7/site-packages/bottleneck/slow/move.pyR gs@          ' c Csì||kj|ƒ}tdƒg|j}tdƒg|j}tdƒg|j}t|dƒ||>> y1 = larry([1, 2, 3]) What is the rank of the last element (the value 3 in this example)? It is the largest element so the rank is 1.0: >>> import numpy as np >>> from la.afunc import lastrank >>> x1 = np.array([1, 2, 3]) >>> lastrank(x1) 1.0 Now let's try an example where the last element has the smallest value: >>> x2 = np.array([3, 2, 1]) >>> lastrank(x2) -1.0 Here's an example where the last element is not the minimum or maximum value: >>> x3 = np.array([1, 3, 4, 5, 2]) >>> lastrank(x3) -0.5 RiR2iiÿÿÿÿgð?g@gà?N(R RRRtsizeR7R0tpopR6R2tfillR&RRR tsumtputmask( RR RR0trtindlasttindlast2RIt a_indlasttgte((s3lib/python2.7/site-packages/bottleneck/slow/move.pyR.Ÿs:5        #(t__doc__R8tnumpyR t__all__RRRRRRRRRRR R R=R.(((s3lib/python2.7/site-packages/bottleneck/slow/move.pyts$    &