U f{ją@sDddlZddlmZmZmZddlmZmZm Z m Z ddl m Z ddl mZddlmZddlmZmZmZmZmZmZmZmZdd lmZd d lmZmZmZm Z m!Z!m"Z"m#Z#m$Z$d d Z%ddZ&d2ddZ'ddZ(ddZ)ed3ddZ*ddZ+ed4ddZ,ed5ddZ-ed6d'd(Z.d)d*Z/ed7d.d/Z0ed0d1Z1dS)8N)SourceEstimate_BaseSourceEstimate _make_stc) combine_xyz_prepare_forward_check_reference _log_exp_var)is_fixed_orient)pick_channels_evoked)deactivate_proj)loggerverbose _check_depth _check_option sum_squared_validate_typecheck_random_statewarn)Dipole)mixed_norm_solveriterative_mixed_norm_solver_Phitf_mixed_norm_solveriterative_tf_mixed_norm_solver norm_l2infnorm_epsilon_inf groups_norm2cCs,td|ddg|dkr(t|r(tddS)zCheck pick_ori.pick_oriNvectorzOpick_ori="vector" cannot be combined with a fixed orientation forward solution.)rr ValueError)rforwardr#^/var/www/html/bwave/python/venv/lib/python3.8/site-packages/mne/inverse_sparse/mxne_inverse.py _check_orisr%c Cs2d}t|tr$tjt|jdd}t|}||krFtd||f||}||}t|rbdnd}tt ||dgj }t ||j dkrtdt ||j dft |j dkr||9}n||dddf9}||dddf9}|dk r(||k}|dd|f}t ||}td||||fS)Nraxisz#weights_min > weights_max (%s > %s)z5weights do not have the correct dimension (%d != %d)z#Reducing source space to %d sources) isinstancernpmaxabsdatar!r ravelZtileTlenshapesumr info) r"gainsource_weightingweights weights_minmaskZ weights_max n_dip_per_pos n_sourcesr#r#r$_prepare_weightss4    r;c  Cspt|d}t|||d|||fddi|\ }} } } } } } } } |dkrJd}nt|| | ||\} } }|| | | | |fS)NZ depth_sparseautoZuse_cpsT)rrr;)r"r3 noise_covpcadepthlooserankr6r7 gain_infor4_r5whitenerr8r#r#r$ _prepare_gain=s"  rEcCs|||dddf9}|SNr#)Xr5 active_setr#r#r$_reapply_source_weightingMsrIc sfdd|dD}|}t||dd}|}tdd|ddfdd|f||_t}t} |jdD]"} | dr|| qz| | qzt|d kr|j t |d d d |jd<W5QRX|j d d |j | d d d|j|j8_|S)Ncsg|]}dd|qS)solZ row_namesindex).0cr"r#r$ Tsz%_compute_residual..ch_names)includerJr-ZprojsZactiverTF)copyr)r)Zremove_existingr) rSr r*dotr-listr3appendr0Z_unlockr Z apply_projZadd_proj) r"evokedrGrHr3selresidualZr_tmpZ active_projsZnon_active_projspr#rOr$_compute_residualRs(.     r[Fc Cs|d}d} t|s@|dkr0tdt|}nd} t|d}|sTt|d} n|} t|rddnd } | dkr~t| | } |d } g} d}| D]J}|t|d }| || k| |k@}||8}|d |}|}| |q|| }t || | j ||| dd | |d S)N source_nnFr z#combining the current components...T)r(r(rrr(srcvertnoZsubject_his_id)r r\) r r r3rr*Zreshapewhereuniquer0rVrkind)rGrHr"tmintstep active_is_idxrrr\r active_idxr9r^verticesZn_points_so_farZthis_srcZthis_n_points_so_farZthis_active_idxZ this_vertnor#r#r$_make_sparse_stcpsJ      rhcCs|j|jkr$|jkr$dks:nt|j|j|jf|j|jd|jdfksXt|jd|jdkspt||jjddd}tj||dk<||}|j|jkst||}|jd|jdkst|j|jftjj |dd\}}}|jddkr|dd||ddkf}|j |} |j |} |j |ddddtj f|} tjj | ddd } d | | dk<| | } tjj | ddtj f| dd d} tjj | ddtj f| dd d}d | ||}|j|jkst|j|jf|S) NrrrT)keepdimsFZ full_matricesgư>)r'ri?r&d) ndimAssertionErrorr1Zconjrealr2r*inflinalgsvdr/newaxisnorm)MrGr4rtZM_estresUsrCZfit_orthZres_orthwZw_normZfit_backZres_backZgof_backr#r#r$ _split_gofs.:$  " &&rzc  Cs||t|jd} |s,t|d} n|} |j|jdt| fksLt|jdt| krp|jdksvntt|||} | jt| t| fkst|jdt| dt| fkstt|rdnd} | dkr2| | } tj| dd\} }| | |} t| | t| f| _| d} | dk s2t| jt| t| fksNtg}t | D]$\}}|d|tj ddf}|jt| dd}||| |d| }| dkr|d}|d |tj ddf}|jt| dd}n||d rt|d || |d| j|}tjj|dd}tt| df}|dd|d kf||d kj||d k<|t| |||| |qZ|S) Nrrr(T)Z return_indexrl source_rrr&r\Zsurf_ori)r*Zaranger1r`r0rnrzr rasortr2all enumeratersrepeatrTr/rqrtzerosrVr)rGrHr"rcrdru gain_activerertimesrfZ gof_splitr9rCZkeepdipoleskZi_dipZi_posZX_ amplitudeZi_orir#r#r$_make_dipoles_sparsesT* "       rcCstdt|tr|g}t|ts4tdt||djd}|djd|}t t |t |djf}tj dd|Ddd}t |dd}t}t} t t |D]} t || j|| jdkstd || j|| <tj ||| jdkdd} t| dd} | |kr8||dd| q| |dd| |qt|tt| tg} t|| |||jd } td | S) ayConvert a list of spatio-temporal dipoles into a SourceEstimate. Parameters ---------- dipoles : Dipole | list of instances of Dipole The dipoles to convert. src : instance of SourceSpaces The source space used to generate the forward operator. %(verbose)s Returns ------- stc : SourceEstimate The source estimate. z)Converting dipoles into a SourceEstimate.zODipoles must be an instance of Dipole or a list of instances of Dipole. Got %s!rrcSs$g|]}|d|dddfqS)Zrrr_Nr#)rMZ_srcr#r#r$rP sz)make_stc_from_dipoles..r&r_z9Only dipoles with fixed position over time are supported!)rgrcrdsubject[done])r r3r)rrUr!typerr*rr0 concatenateranger~posrr`rVarrayastypeintrZ_subject)rr^rrcrdrGr{Z n_lh_pointsZ lh_vertnoZ rh_vertnoiidxrgZstcr#r#r$make_stc_from_dipolessB      rsurer<皙? -C6? Tr|c4sddlm}t|dtfdt|tr4td|dn"d|krHdksVntd||d krjtd ||dkr~td |t|tjt fs|d kstd t |t|tr|d krt|tr|dkrt d|d}tt sgt ddj tfddtd tDs,t dt|dj|||||| | \}}}}}}t||fdd|dDtjfddDd d}tdt||}| r|j|dd\}} }!t| tst| tr|ddd| f}| d| } |!d| }!|| }|t|9}t|r(d nd}"tt|j||"dd}#|#d9}#||#}||#}|dkr|}$t|tr|d krtjdd d!d"}$t|||$d |||||"|| | ||d#\}%}&}'td$|'nV|d krt |||||||"| | ||d% \}%}&}(n&t!|||||||"|| | ||d& \}%}&}(| r>t|%|!}%t||!}|dd|&f})|dk rxtj"t|td'}*|&|*|<|*}&~*|&#dkrt$d(t%|}+n2t&|%||&}%d ||dk<|)||&})~t|)|%}+t },t }-d}.D]}/|/j'd}0d)|/jd*}1|%dd|.|.t|/j'f}2|rPt(|2|&||0|1|dd|.|.t|/j'f|)}3nt)|2|&||0|1|d+}3|,*|3|.t|/j'7}.|r|-*t+||/|2|&|qt,||+d,d-td.t|,d kr|,d}3|r|-d}-n|,}3|r|3|-f}3|3S)/a Mixed-norm estimate (MxNE) and iterative reweighted MxNE (irMxNE). Compute L1/L2 mixed-norm solution :footcite:`GramfortEtAl2012` or L0.5/L2 :footcite:`StrohmeierEtAl2016` mixed-norm solution on evoked data. Parameters ---------- evoked : instance of Evoked or list of instances of Evoked Evoked data to invert. forward : dict Forward operator. noise_cov : instance of Covariance Noise covariance to compute whitener. alpha : float | str Regularization parameter. If float it should be in the range [0, 100): 0 means no regularization, 100 would give 0 active dipole. If ``'sure'`` (default), the SURE method from :footcite:`DeledalleEtAl2014` will be used. .. versionchanged:: 0.24 The default was changed to ``'sure'``. %(loose)s %(depth)s maxit : int Maximum number of iterations. tol : float Tolerance parameter. active_set_size : int | None Size of active set increment. If None, no active set strategy is used. debias : bool Remove coefficient amplitude bias due to L1 penalty. time_pca : bool or int If True the rank of the concatenated epochs is reduced to its true dimension. If is 'int' the rank is limited to this value. weights : None | array | SourceEstimate Weight for penalty in mixed_norm. Can be None, a 1d array with shape (n_sources,), or a SourceEstimate (e.g. obtained with wMNE, dSPM, or fMRI). weights_min : float Do not consider in the estimation sources for which weights is less than weights_min. solver : 'cd' | 'bcd' | 'auto' The algorithm to use for the optimization. 'cd' uses coordinate descent, and 'bcd' applies block coordinate descent. 'cd' is only available for fixed orientation. n_mxne_iter : int The number of MxNE iterations. If > 1, iterative reweighting is applied. return_residual : bool If True, the residual is returned as an Evoked instance. return_as_dipoles : bool If True, the sources are returned as a list of Dipole instances. dgap_freq : int or np.inf The duality gap is evaluated every dgap_freq iterations. Ignored if solver is 'cd'. %(rank_none)s .. versionadded:: 0.18 %(pick_ori)s sure_alpha_grid : array | str If ``'auto'`` (default), the SURE is evaluated along 15 uniformly distributed alphas between alpha_max and 0.1 * alpha_max. If array, the grid is directly specified. Ignored if alpha is not "sure". .. versionadded:: 0.24 random_state : int | None The random state used in a random number generator for delta and epsilon used for the SURE computation. Defaults to None. .. versionadded:: 0.24 %(verbose)s Returns ------- stc : SourceEstimate | list of SourceEstimate Source time courses for each evoked data passed as input. residual : instance of Evoked The residual a.k.a. data not explained by the sources. Only returned if return_residual is True. See Also -------- tf_mixed_norm References ---------- .. footbibliography:: r)rqnumericalpha)rr|rlz@If not equal to "sure" alpha must be in [0, 100). Got alpha = %srzJMxNE has to be computed at least 1 time. Requires n_mxne_iter >= 1, got %d8dgap_freq must be a positive integer. Got dgap_freq = %sr<z?If not equal to "auto" sure_alpha_grid must be an array. Got %srzFIf sure_alpha_grid is manually specified, alpha must be "sure". Got %sTc3s|]}|jkVqdSrF)rQ)rMr) all_ch_namesrWr#r$ szmixed_norm..z2All the datasets must have the same good channels.csg|]}|qSr#rKrMnamerr#r$rPszmixed_norm..rQcsg|]}|jqSr#)r-)rMe)rXr#r$rPsr&Whitening data matrix.FrjNr()rS{Gz?r)num) sigma random_state n_mxne_itermaxittoln_orientactive_set_sizedebiassolver dgap_freqrzSelected alpha: %s)rrrrrrrr)rrrrrrrrZdtypez*No active dipoles found. alpha is too big.rksfreqr)prefixr)-Zscipyrqrstrr)rr!r*ZndarrayrUr ExceptionrrQr~rr0rEr3r%rr rTrrboolrrr rr/Z geomspace_compute_mxne_surerrrr2rZ zeros_likerIrrrhrVr[r )4rWr"r=rr@r?rrrrZtime_pcar6r7rrreturn_residualreturn_as_dipolesrrArZsure_alpha_gridrrrqr>r4rBrDr5r8rurwrxZVhr9 alpha_max alpha_gridrGrH best_alpha_Eractive_set_tmpZ M_estimateZoutsrYZcntrrcrdZXeoutr#)rrWrXr$ mixed_norm!s^_                             rcCst|ttfrt|}}n|\}}|}t|jd}t||}t||}t|dd|}t|d| d}tj|tt |j |||f}|j |dddf9_ |S)z Window evoked (size in seconds).rrN) r)floatrrSr3r*ZhanningZr_Zonesr0rr-)rWsizeZlsizeZrsizerZlhannZrhannwindowr#r#r$_window_evokeds  $r@{Gz?c.st||j|j}d|kr(dks6ntd|d|krJdksXntd||d|}||}|dkrtd||dkrtd|t| } t| } t| t| krtd | | ft||j|| ||||| \}}}}}}t||t |rdnd }| d k rt || }fd d |dD} |j | }!t dt ||!}!t|!jd| tt}"| dd}#|"|#}$t| | |$|j jd}%|t|!9}t||!|%||}&|&d9}&||&}||&}|dkrt|!|||| | |||||| d \}'}(})n(t|!|||| | ||||||| d \}'}(})|(dkrBtd|d d |(f}*|d k r|tjt|td}+|(|+|<|+}(~+t|'||(}'|*||(}*|rt|||'|(|},|rt|'|(||jdd|d|!|*}-n"t |'|(||jdd|d|d}-t d|r|-|,f}-|-S)am Time-Frequency Mixed-norm estimate (TF-MxNE). Compute L1/L2 + L1 mixed-norm solution on time-frequency dictionary. Works with evoked data :footcite:`GramfortEtAl2013b,GramfortEtAl2011`. Parameters ---------- evoked : instance of Evoked Evoked data to invert. forward : dict Forward operator. noise_cov : instance of Covariance Noise covariance to compute whitener. %(loose)s %(depth)s maxit : int Maximum number of iterations. tol : float Tolerance parameter. weights : None | array | SourceEstimate Weight for penalty in mixed_norm. Can be None or 1d array of length n_sources or a SourceEstimate e.g. obtained with wMNE or dSPM or fMRI. weights_min : float Do not consider in the estimation sources for which weights is less than weights_min. pca : bool If True the rank of the data is reduced to true dimension. debias : bool Remove coefficient amplitude bias due to L1 penalty. wsize : int or array-like Length of the STFT window in samples (must be a multiple of 4). If an array is passed, multiple TF dictionaries are used (each having its own wsize and tstep) and each entry of wsize must be a multiple of 4. See :footcite:`BekhtiEtAl2016`. tstep : int or array-like Step between successive windows in samples (must be a multiple of 2, a divider of wsize and smaller than wsize/2) (default: wsize/2). If an array is passed, multiple TF dictionaries are used (each having its own wsize and tstep), and each entry of tstep must be a multiple of 2 and divide the corresponding entry of wsize. See :footcite:`BekhtiEtAl2016`. window : float or (float, float) Length of time window used to take care of edge artifacts in seconds. It can be one float or float if the values are different for left and right window length. return_residual : bool If True, the residual is returned as an Evoked instance. return_as_dipoles : bool If True, the sources are returned as a list of Dipole instances. alpha : float in [0, 100) or None Overall regularization parameter. If alpha and l1_ratio are not None, alpha_space and alpha_time are overridden by alpha * alpha_max * (1. - l1_ratio) and alpha * alpha_max * l1_ratio. 0 means no regularization, 100 would give 0 active dipole. l1_ratio : float in [0, 1] or None Proportion of temporal regularization. If l1_ratio and alpha are not None, alpha_space and alpha_time are overridden by alpha * alpha_max * (1. - l1_ratio) and alpha * alpha_max * l1_ratio. 0 means no time regularization a.k.a. MxNE. dgap_freq : int or np.inf The duality gap is evaluated every dgap_freq iterations. %(rank_none)s .. versionadded:: 0.18 %(pick_ori)s n_tfmxne_iter : int Number of TF-MxNE iterations. If > 1, iterative reweighting is applied. %(verbose)s Returns ------- stc : instance of SourceEstimate Source time courses. residual : instance of Evoked The residual a.k.a. data not explained by the sources. Only returned if return_residual is True. See Also -------- mixed_norm References ---------- .. footbibliography:: r|gY@z)alpha must be in [0, 100). Got alpha = %srkz3l1_ratio must be in range [0, 1]. Got l1_ratio = %srzOTF-MxNE has to be computed at least 1 time. Requires n_tfmxne_iter >= 1, got %srzWThe same number of window sizes and steps must be passed. Got tstep = %s and wsize = %sr(Ncsg|]}|qSr#rKrrr#r$rPsz!tf_mixed_norm..rQrrr)wsizerdrrrrrr) rrd n_tfmxne_iterrrrrrrrzrrrdrrrrZl1_ratiorrArrrr3Z alpha_spaceZ alpha_timer4rBrDr5r8r9rXruZn_stepsZn_freqsZn_coefsphirrGrHrrrrYrr#rr$ tf_mixed_norm"s_                    rc s< fdd fddd fdd  fdd }d d }tt}t| }d ||jd d}|j|j}||||\}}}tdtt ||D]B\}\}}|||||||||<| rtd|||fqt |}|t |}|t |}||ddf}|||fS)aStein Unbiased Risk Estimator (SURE). Implements the finite-difference Monte-Carlo approximation of the SURE for Multi-Task LASSO. See reference :footcite:`DeledalleEtAl2014`. Parameters ---------- M : array, shape (n_sensors, n_times) The data. gain : array, shape (n_sensors, n_dipoles) The gain matrix a.k.a. lead field. alpha_grid : array, shape (n_alphas,) The grid of alphas used to evaluate the SURE. sigma : float The true or estimated noise level in the data. Usually 1 if the data has been previously whitened using MNE whitener. n_mxne_iter : int The number of MxNE iterations. If > 1, iterative reweighting is applied. maxit : int Maximum number of iterations. tol : float Tolerance parameter. n_orient : int The number of orientation (1 : fixed or 3 : free or loose). active_set_size : int Size of active set increase at each iteration. debias : bool Debias source estimates. solver : 'cd' | 'bcd' | 'auto' The algorithm to use for the optimization. dgap_freq : int or np.inf The duality gap is evaluated every dgap_freq iterations. random_state : int | None The random state used in a random number generator for delta and epsilon used for the SURE computation. Returns ------- X : array, shape (n_active, n_times) Coefficient matrix. active_set : array, shape (n_dipoles,) Array of indices of non-zero coefficients. best_alpha_ : float Alpha that minimizes the SURE. References ---------- .. footbibliography:: csttt|SrF)r*sqrtrrSry)rr#r$g$sz_compute_mxne_sure..gcsdt|S)Ng@)r*rr.r)rrr#r$gprime'sz"_compute_mxne_sure..gprimeNc sb|dkr2t||||dd \}}}n(t||||dd \}}}||fS)NrF) rrrrrrrZactive_set_initX_initr) rrrrrrrZ weight_initr)rr) rrurZas_initrw_initrGrHrC)rrrr4rrrrr#r$ _run_solver*s@ z'_compute_mxne_sure.._run_solvercstt|jd|jdf}tt|jd|jdf}gg}}|||}tdtD]r\} } td| | |d\} } | |d\} }| || | ddf<| || |ddf<|| ||qhdkr|||fS|}|}tdtD]\} } td| ||  dkrx|| }| |d|d\} } | || | ddf<| || <||  dkr|| }| |d|d\} }| || |ddf<||| <q|||fSdS)NrzWarm starting...z alpha: %szFitting SURE on grid.r)r) r*rr0r1r r3rrVrSr2)r4ruepsdeltaZcoefs_grid_1_0Zcoefs_grid_2_0 active_setsZactive_sets_epsZM_epsjrrGZa_setZX_epsZ a_set_eps coefs_grid_1 coefs_grid_2ryZw_eps)rrrrr#r$ _fit_on_grid:sH               z(_compute_mxne_sure.._fit_on_gridc Ssr|jd|jd}}|||||} tj|||d} | |||d} | d| |d7} | S)Nrrr)r1r2r*rqrt) coef1coef2r4rurrrZ n_sensorsZn_timesZdofZdf_termrr#r#r$_compute_sure_valbs z-_compute_mxne_sure.._compute_sure_valrrg333333?zComputing SURE values on grid.zalpha %s :: sure %s)NNN) r*emptyr0rr1Zrandnr r3rzipZargmin)rur4rrrrrrrrrrrrrrZ sure_pathrngrrrrrrrrrrGrHr#) rrrrrrr4rrrrrrr$rs<8 (  r)NN)FNN)FN)N)rr<rrrrTTNr|r<rFFrNNr<NN)r<rrrNr|TTrrrFFNNrNNrN)2numpyr*Zsource_estimaterrrZminimum_norm.inverserrrr r"r Zio.pickr Zio.projr utilsr rrrrrrrZdipolerZ mxne_optimrrrrrrrrr%r;rErIr[rhrzrrrrrrr#r#r#r$s   ( (  &# 3 2 p J