ó áp7]c@ srdZddlmZddlZddlmZddd„Zd„Z d„Z d „Z d ddd „Z dS( s  BDS test for IID time series References ---------- Broock, W. A., J. A. Scheinkman, W. D. Dechert, and B. LeBaron. 1996. "A Test for Independence Based on the Correlation Dimension." Econometric Reviews 15 (3): 197-235. Kanzler, Ludwig. 1999. "Very Fast and Correctly Sized Estimation of the BDS Statistic". SSRN Scholarly Paper ID 151669. Rochester, NY: Social Science Research Network. LeBaron, Blake. 1997. "A Fast Algorithm for the BDS Statistic." Studies in Nonlinear Dynamics & Econometrics 2 (2) (January 1). iÿÿÿÿ(tdivisionN(tstatsgø?cC s±tj|ƒ}t|ƒ}|dk rF|dkrFtd|ƒ‚n|dkretd|ƒ‚n|dkrŠ||jddƒ}ntj|dd…df|ƒ|kS(s– Calculate all pairwise threshold distance indicators for a time series Parameters ---------- x : 1d array observations of time series for which heaviside distance indicators are calculated epsilon : scalar, optional the threshold distance to use in calculating the heaviside indicators distance : scalar, optional if epsilon is omitted, specifies the distance multiplier to use when computing it Returns ------- indicators : 2d array matrix of distance threshold indicators Notes ----- Since this can be a very large matrix, use np.int8 to save some space. isCThreshold distance must be positive if specified. Got epsilon of %fs?Threshold distance must be positive. Got distance multiplier %ftddofiN(tnptasarraytlentNonet ValueErrortstdtabs(txtepsilontdistancetnobs((s3lib/python2.7/site-packages/statsmodels/tsa/_bds.pytdistance_indicatorss     cC sà|jdkstdƒ‚n|jd|jdksGtdƒ‚n|dkr\|}nOt||dƒ\}}|dd…dd…f|dd…dd…f}t|ƒ}tj|tj|dƒƒ}||fS(s Calculate a correlation sum Useful as an estimator of a correlation integral Parameters ---------- indicators : 2d array matrix of distance threshold indicators embedding_dim : integer embedding dimension Returns ------- corrsum : float Correlation sum indicators_joint matrix of joint-distance-threshold indicators isIndicators must be a matrixiis+Indicator matrix must be symmetric (square)Niÿÿÿÿ(tndimRtshapetcorrelation_sumRRtmeant triu_indices(t indicatorst embedding_dimtindicators_jointtcorrsumR ((s3lib/python2.7/site-packages/statsmodels/tsa/_bds.pyREs  6 cC sktjd|fƒ}t|dƒ\|d<}x6td|ƒD]%}t|dƒ\|d|f<}q>W|S(s9 Calculate all correlation sums for embedding dimensions 1:max_dim Parameters ---------- indicators : 2d array matrix of distance threshold indicators max_dim : integer maximum embedding dimension Returns ------- corrsums : 1d array Correlation sums iii(ii(RtzerosRtrange(Rtmax_dimtcorrsumsti((s3lib/python2.7/site-packages/statsmodels/tsa/_bds.pytcorrelation_sumsjs #c C s;t|ƒ}t|dƒ\}}|jdƒdjƒd|jƒd|||d|d}tjd|dfƒ}x±td|dƒD]œ}d}x5td|ƒD]$} |||| |d| 7}q­Wd||d||dd|d||d||d|d|d|dfs , %  %