U f»{j ã@s>ddlZddlZdd„Zd dd„Zejfdd„Zd d d „ZdS)éNcCs*ddlm}t ||ƒ¡tjdtjS)a.Compute normalized phase angles. Parameters ---------- data : ndarray, shape (n_epochs, n_sources, n_times) The data to compute the phase angles for. Returns ------- phase_angles : ndarray, shape (n_epochs, n_sources, n_times) The normalized phase angles. r)Úhilberté)Z scipy.signalrÚnpZangleÚpi)Údatar©rúV/var/www/html/bwave/python/venv/lib/python3.8/site-packages/mne/preprocessing/ctps_.pyÚ_compute_normalized_phase s r Tc Cs¤|jdkstd|jƒ‚|r&t|ƒ}n|}t |d¡}t |d¡}tt |dddg¡ƒD]4\}}t|ƒ\}}|||dd…f<|||dd…f<q\|||rž|ndfS)aÕCompute cross-trial-phase-statistics [1]. Note. It is assumed that the sources are already appropriately filtered Parameters ---------- data: ndarray, shape (n_epochs, n_channels, n_times) Any kind of data of dimensions trials, traces, features. is_raw : bool If True it is assumed that data haven't been transformed to Hilbert space and phase angles haven't been normalized. Defaults to True. Returns ------- ks_dynamics : ndarray, shape (n_sources, n_times) The kuiper statistics. pk_dynamics : ndarray, shape (n_sources, n_times) The normalized kuiper index for ICA sources and time slices. phase_angles : ndarray, shape (n_epochs, n_sources, n_times) | None The phase values for epochs, sources and time slices. If ``is_raw`` is False, None is returned. References ---------- [1] Dammers, J., Schiek, M., Boers, F., Silex, C., Zvyagintsev, M., Pietrzyk, U., Mathiak, K., 2008. Integration of amplitude and phase statistics for complete artifact removal in independent components of neuromagnetic recordings. Biomedical Engineering, IEEE Transactions on 55 (10), 2353-2362. éz$Data must have 3 dimensions, not %i.rérN)ÚndimÚ ValueErrorr rZ zeros_likeÚ enumerateZ transposeÚkuiper) rZis_rawZ phase_anglesZ ks_dynamicsZ pk_dynamicsÚiiÚsourceÚksÚpkrrrÚctpss!   rc CsÄtj|dd |¡}|j}t|ƒ}|d}tj||ddt|ƒ}tj||dt|ƒ}|dkr†|dd…tjf}|dd…tjf}||jdd}||jdd}|} ||} | t | | |dfS)awKuiper's test of uniform distribution. Parameters ---------- data : ndarray, shape (n_sources,) | (n_sources, n_times) Empirical distribution. dtype : str | obj The data type to be used. Returns ------- ks : ndarray Kuiper's statistic. pk : ndarray Normalized probability of Kuiper's statistic [0, 1]. r)Úaxis)Údtypeçð?r N) rÚsortZastypeÚshapeÚlenÚarangeÚfloatZnewaxisÚmaxÚ _prob_kuiper) rrrZn_dimZn_trialsZj1Új2Zd1Zd2Ún_effÚdrrrrPsrÚf8cCsÈddlm}t |¡}d}t |¡}|dd||}|d}t |¡dd} |  |¡ ||¡} d | |d } d | |} d| } || | dd  d|} t  |d kd| ¡} t  | d kd | ¡} | S)a•Test for statistical significance against uniform distribution. Parameters ---------- d : float The kuiper distance value. n_eff : int The effective number of elements. dtype : str | obj The data type to be used. Defaults to double precision floats. Returns ------- pk_norm : float The normalized Kuiper value such that 0 < ``pk_norm`` < 1. References ---------- [1] Stephens MA 1970. Journal of the Royal Statistical Society, ser. B, vol 32, pp 115-122. [2] Kuiper NH 1962. Proceedings of the Koninklijke Nederlands Akademie van Wetenschappen, ser Vol 63 pp 38-47 r)Ú logsumexpédg×£p= ×Ã?g¸…ëQ¸Î?g@r rg@rgÀ)Úbrgš™™™™™Ù?g) Z scipy.specialr#rÚsizeÚmathÚsqrtrÚrepeatZreshapeÚwhere)r!r rr#Z n_time_slicesZn_pointsÚenZk_lambdaÚl2rZfactÚar%Zpk_normrrrrws    r)T)r")r'Únumpyrr rZfloat64rrrrrrÚs  6'