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8_��||�|d	kr��|jd��S)a�Prepare an empty-room recording for Maxwell filtering.16 17    Empty-room data by default lacks certain properties that are required to18    ensure running :func:`~mne.preprocessing.maxwell_filter` will process the19    empty-room recording the same way as the experimental data. This function20    preconditions an empty-room raw data instance accordingly so it can be used21    for Maxwell filtering. Please see the ``Notes`` section for details.22 23    Parameters24    ----------25    raw_er : instance of Raw26        The empty-room recording. It will not be modified.27    raw : instance of Raw28        The experimental recording, typically this will be the reference run29        used for Maxwell filtering.30    bads : 'from_raw' | 'union' | 'keep'31        How to populate the list of bad channel names to be injected into32        the empty-room recording. If ``'from_raw'`` (default) the list of bad33        channels will be overwritten with that of ``raw``. If ``'union'``, will34        use the union of bad channels in ``raw`` and ``raw_er``. Note that35        this may lead to additional bad channels in the empty-room in36        comparison to the experimental recording. If ``'keep'``, don't alter37        the existing list of bad channels.38 39        .. note::40           Non-MEG channels are silently dropped from the list of bads.41    annotations : 'from_raw' | 'union' | 'keep'42        Whether to copy the annotations over from ``raw`` (default),43        use the union of the annotations, or to keep them unchanged.44    meas_date : 'keep' | 'from_raw'45        Whether to transfer the measurement date from ``raw`` or to keep46        it as is (default). If you intend to manually transfer annotations47        from ``raw`` **after** running this function, you should set this to48        ``'from_raw'``.49    %(emit_warning)s50        Unlike :meth:`raw.set_annotations <mne.io.Raw.set_annotations>`, the51        default here is ``False``, as empty-room recordings are often shorter52        than raw.53    %(verbose)s54 55    Returns56    -------57    raw_er_prepared : instance of Raw58        A copy of the passed empty-room recording, ready for Maxwell filtering.59 60    Notes61    -----62    This function will:63 64    * Compile the list of bad channels according to the ``bads`` parameter.65    * Inject the device-to-head transformation matrix from the experimental66      recording into the empty-room recording.67    * Set the following properties of the empty-room recording to match the68      experimental recording:69 70      * Montage (required for the fiducials defining the head coordinate frame)71      * ``raw.first_time`` and ``raw.first_samp``72 73    * Adjust annotations according to the ``annotations`` parameter.74    * Adjust the measurement date according to the ``meas_date`` parameter.75 76    .. note::77 78        Note that in case of dual MEG/EEG acquisition, EEG channels should not be79        included in the empty room recording. If provided, they will be ignored.80 81    .. versionadded:: 1.182    �raw_er)�item�typesZ	item_name�rawrD)rB�unionrC)Z	parameter�valueZallowed_valuesrErFrBrCrLc�g|]}�j|�qS���ch_names��.0�pick)�raw_er_preparedrO��E:\DocsHouse\542 percep lab latest\PerceptionLab\PerceptionLab_Portable\python_embed\Lib\site-packages\mne/preprocessing/maxwell.py�83<listcomp>�s��z4maxwell_filter_prepare_emptyroom.<locals>.<listcomp>T��meg�excludecsg|]}|�vr|�qSrOrO)rS�ch_name)�meg_ch_namesrOrVrW���84dev_head_tN)r<r%�strr7�copy�info�sorted�setrZget_montageZset_montagerE�onsetZ85first_time�
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set_meas_date)	rHrKrDrErFrGr@ZmontageZer_annotrO)r\rUrV� maxwell_filter_prepare_emptyroomDsdO86��87�8889�9091�rm�auto���\���(\�?�head�in�errorT�Y@��edgeZbad_acq_skiprO�hanncCs�t�d�tdid|�d|�d|�d|�d|�d|�d|�d	|�d92|�d|	�d|93�d
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�d|�d|�d|�d|�d|�d|�d|��}t|fi|��}t|fi|d��t�d�|S)u�"Maxwell filter data using multipole moments.94 95    Parameters96    ----------97    raw : instance of Raw98        Data to be filtered.99 100        .. warning:: It is critical to mark bad channels in101                     ``raw.info['bads']`` prior to processing in order to102                     prevent artifact spreading. Manual inspection and use103                     of :func:`~find_bad_channels_maxwell` is recommended.104    %(origin_maxwell)s105    %(int_order_maxwell)s106    %(ext_order_maxwell)s107    %(calibration_maxwell_cal)s108    %(cross_talk_maxwell)s109    st_duration : float | None110        If not None, apply spatiotemporal SSS with specified buffer duration111        (in seconds). MaxFilter™'s default is 10.0 seconds in v2.2.112        Spatiotemporal SSS acts as implicitly as a high-pass filter where the113        cut-off frequency is 1/st_duration Hz. For this (and other) reasons,114        longer buffers are generally better as long as your system can handle115        the higher memory usage. To ensure that each window is processed116        identically, choose a buffer length that divides evenly into your data.117        Any data at the trailing edge that doesn't fit evenly into a whole118        buffer window will be lumped into the previous buffer.119    st_correlation : float120        Correlation limit between inner and outer subspaces used to reject121        overlapping intersecting inner/outer signals during spatiotemporal SSS.122    %(coord_frame_maxwell)s123    %(destination_maxwell_dest)s124    %(regularize_maxwell_reg)s125    %(ignore_ref_maxwell)s126    %(bad_condition_maxwell_cond)s127    %(head_pos_maxwell)s128 129        .. versionadded:: 0.12130    %(st_fixed_maxwell_only)s131    %(mag_scale_maxwell)s132 133        .. versionadded:: 0.13134    %(skip_by_annotation_maxwell)s135 136        .. versionadded:: 0.17137    %(extended_proj_maxwell)s138    st_overlap : bool139        If True (default in 1.11), tSSS processing will use a constant140        overlap-add method. If False, then non-overlapping windows will be used.141 142        .. versionadded:: 1.10143    %(maxwell_mc_interp)s144    %(verbose)s145 146    Returns147    -------148    raw_sss : instance of Raw149        The raw data with Maxwell filtering applied.150 151    See Also152    --------153    mne.preprocessing.annotate_amplitude154    mne.preprocessing.find_bad_channels_maxwell155    mne.chpi.filter_chpi156    mne.chpi.read_head_pos157    mne.epochs.average_movements158 159    Notes160    -----161    .. versionadded:: 0.11162 163    Some of this code was adapted and relicensed (with BSD form) with164    permission from Jussi Nurminen. These algorithms are based on work165    from :footcite:`TauluKajola2005` and :footcite:`TauluSimola2006`.166    It will likely use multiple CPU cores, see the :ref:`FAQ <faq_cpu>`167    for more information.168 169    .. warning:: Maxwell filtering in MNE is not designed or certified170                 for clinical use.171 172    Compared to the MEGIN MaxFilter™ 2.2.11 software, the MNE Maxwell filtering173    routines currently provide the following features:174 175    .. table::176       :widths: auto177 178       +-----------------------------------------------------------------------------+-----+-----------+179       | Feature                                                                     | MNE | MaxFilter |180       +=============================================================================+=====+===========+181       | Maxwell filtering software shielding                                        | ✓   | ✓         |182       +-----------------------------------------------------------------------------+-----+-----------+183       | Bad channel reconstruction                                                  | ✓   | ✓         |184       +-----------------------------------------------------------------------------+-----+-----------+185       | Cross-talk cancellation                                                     | ✓   | ✓         |186       +-----------------------------------------------------------------------------+-----+-----------+187       | Fine calibration correction (1D)                                            | ✓   | ✓         |188       +-----------------------------------------------------------------------------+-----+-----------+189       | Fine calibration correction (3D)                                            | ✓   |           |190       +-----------------------------------------------------------------------------+-----+-----------+191       | Spatio-temporal SSS (tSSS)                                                  | ✓   | ✓         |192       +-----------------------------------------------------------------------------+-----+-----------+193       | Coordinate frame translation                                                | ✓   | ✓         |194       +-----------------------------------------------------------------------------+-----+-----------+195       | Regularization using information theory                                     | ✓   | ✓         |196       +-----------------------------------------------------------------------------+-----+-----------+197       | Movement compensation (raw)                                                 | ✓   | ✓         |198       +-----------------------------------------------------------------------------+-----+-----------+199       | Movement compensation (:func:`epochs <mne.epochs.average_movements>`)       | ✓   |           |200       +-----------------------------------------------------------------------------+-----+-----------+201       | :func:`cHPI subtraction <mne.chpi.filter_chpi>`                             | ✓   | ✓         |202       +-----------------------------------------------------------------------------+-----+-----------+203       | Double floating point precision                                             | ✓   |           |204       +-----------------------------------------------------------------------------+-----+-----------+205       | Seamless processing of split (``-1.fif``) and concatenated files            | ✓   |           |206       +-----------------------------------------------------------------------------+-----+-----------+207       | Automatic bad channel detection (:func:`~find_bad_channels_maxwell`)        | ✓   | ✓         |208       +-----------------------------------------------------------------------------+-----+-----------+209       | Head position estimation (:func:`~mne.chpi.compute_head_pos`)               | ✓   | ✓         |210       +-----------------------------------------------------------------------------+-----+-----------+211       | Overlap-add processing for spatio-temporal projections                      | ✓   |           |212       +-----------------------------------------------------------------------------+-----+-----------+213       | Smooth interpolation in movement compensation                               | ✓   |           |214       +-----------------------------------------------------------------------------+-----+-----------+215       | Certified for clinical use                                                  |     | ✓         |216       +-----------------------------------------------------------------------------+-----+-----------+217       | Extended external basis (eSSS)                                              | ✓   |           |218       +-----------------------------------------------------------------------------+-----+-----------+219 220    Epoch-based movement compensation is described in :footcite:`TauluKajola2005`.221 222    Use of Maxwell filtering routines with non-Neuromag systems is currently223    **experimental**. Worse results for non-Neuromag systems are expected due224    to (at least):225 226    * Missing fine-calibration and cross-talk cancellation data for227      other systems.228    * Processing with reference sensors has not been vetted.229    * Regularization of components may not work well for all systems.230    * Coil integration has not been optimized using Abramowitz/Stegun231      definitions.232 233    .. note:: Various Maxwell filtering algorithm components are covered by234              patents owned by MEGIN. These patents include, but may not be235              limited to:236 237              - US2006031038 (Signal Space Separation)238              - US6876196 (Head position determination)239              - WO2005067789 (DC fields)240              - WO2005078467 (MaxShield)241              - WO2006114473 (Temporal Signal Space Separation)242 243              These patents likely preclude the use of Maxwell filtering code244              in commercial applications. Consult a lawyer if necessary.245 246    Currently, in order to perform Maxwell filtering, the raw data must not247    have any projectors applied. During Maxwell filtering, the spatial248    structure of the data is modified, so projectors are discarded (unless249    in ``st_only=True`` mode).250 251    References252    ----------253    .. footbibliography::254    zMaxwell filtering raw datarK�origin�	int_order�	ext_order�calibration�255cross_talk�st_duration�st_correlation�coord_frame�destination�256regularize�257ignore_ref�
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Smaller values will690        find more bad channels at increased risk of including good ones. This691        value can be interpreted as the standard score of differences between692        the original and Maxwell-filtered data. See the ``Notes`` section for693        details.694 695        .. note:: This setting only concerns *noisy* channel detection.696                  The limit for *flat* channel detection currently cannot be697                  controlled by the user. Flat channel detection is always run698                  before noisy channel detection.699    duration : float700        Duration of the segments into which to slice the data for processing,701        in seconds. Default is 5.702    min_count : int703        Minimum number of times a channel must show up as bad in a chunk.704        Default is 5.705    return_scores : bool706        If ``True``, return a dictionary with scoring information for each707        evaluated segment of the data. Default is ``False``.708 709        .. warning:: This feature is experimental and may change in a future710                     version of MNE-Python without prior notice. Please711                     report any problems and enhancement proposals to the712                     developers.713 714        .. versionadded:: 0.21715    %(origin_maxwell)s716    %(int_order_maxwell)s717    %(ext_order_maxwell)s718    %(calibration_maxwell_cal)s719    %(cross_talk_maxwell)s720    %(coord_frame_maxwell)s721    %(regularize_maxwell_reg)s722    %(ignore_ref_maxwell)s723    %(bad_condition_maxwell_cond)s724    %(head_pos_maxwell)s725    %(mag_scale_maxwell)s726    %(skip_by_annotation_maxwell)s727    h_freq : float | None728        The cutoff frequency (in Hz) of the low-pass filter that will be729        applied before processing the data. This defaults to ``40.``, which730        should provide similar results to MaxFilter. If you do not wish to731        apply a filter, set this to ``None``.732    %(extended_proj_maxwell)s733    %(maxwell_mc_interp)s734    %(verbose)s735 736    Returns737    -------738    noisy_chs : list739        List of bad MEG channels that were automatically detected as being740        noisy among the good MEG channels.741    flat_chs : list742        List of MEG channels that were detected as being flat in at least743        ``min_count`` segments.744    scores : dict745        A dictionary with information produced by the scoring algorithms.746        Only returned when ``return_scores`` is ``True``. It contains the747        following keys:748 749        - ``ch_names`` : ndarray, shape (n_meg,)750            The names of the MEG channels. Their order corresponds to the751            order of rows in the ``scores`` and ``limits`` arrays.752        - ``ch_types`` : ndarray, shape (n_meg,)753            The types of the MEG channels in ``ch_names`` (``'mag'``,754            ``'grad'``).755        - ``bins`` : ndarray, shape (n_windows, 2)756            The inclusive window boundaries (start and stop; in seconds) used757            to calculate the scores.758        - ``scores_flat`` : ndarray, shape (n_meg, n_windows)759            The scores for testing whether MEG channels are flat. These values760            correspond to the standard deviation of a segment.761            See the ``Notes`` section for details.762        - ``limits_flat`` : ndarray, shape (n_meg, 1)763            The score thresholds (in standard deviation) above which a segment764            was classified as "flat".765        - ``scores_noisy`` : ndarray, shape (n_meg, n_windows)766            The scores for testing whether MEG channels are noisy. These values767            correspond to the standard score of a segment.768            See the ``Notes`` section for details.769        - ``limits_noisy`` : ndarray, shape (n_meg, 1)770            The score thresholds (in standard scores) above which a segment was771            classified as "noisy".772 773        .. note:: The scores and limits for channels marked as ``bad`` in the774                  input data will be set to ``np.nan``.775 776    See Also777    --------778    annotate_amplitude779    maxwell_filter780 781    Notes782    -----783    All arguments after ``raw``, ``limit``, ``duration``, ``min_count``, and784    ``return_scores`` are the same as :func:`~maxwell_filter`, except that the785    following are not allowed in this function because they are unused:786    ``st_duration``, ``st_correlation``, ``destination``, ``st_fixed``, and787    ``st_only``.788 789    This algorithm, for a given chunk of data:790 791    1. Runs SSS on the data, without removing external components.792    2. Excludes channels as *flat* that have had low variability793       (standard deviation < 0.01 fT or fT/cm in a 30 ms window) in the given794       or any previous chunk.795    3. For each channel :math:`k`, computes the *range* or peak-to-peak796       :math:`d_k` of the difference between the reconstructed and original797       data.798    4. Computes the average :math:`\mu_d` and standard deviation799       :math:`\sigma_d` of the differences (after scaling magnetometer data800       to roughly match the scale of the gradiometer data using ``mag_scale``).801    5. Marks channels as bad for the chunk when802       :math:`d_k > \mu_d + \textrm{limit} \times \sigma_d`. Note that this803       expression can be easily transformed into804       :math:`(d_k - \mu_d) / \sigma_d > \textrm{limit}`, which is equivalent805       to :math:`z(d_k) > \textrm{limit}`, with :math:`z(d_k)` being the806       standard or z-score of the difference.807 808    Data are processed in chunks of the given ``duration``, and channels that809    are bad for at least ``min_count`` chunks are returned.810 811    Channels marked as *flat* in step 2 are excluded from all subsequent steps812    of noisy channel detection.813 814    This algorithm gives results similar to, but not identical with,815    MaxFilter. 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a8Compute the SSS basis for a given measurement info structure.849 850    Parameters851    ----------852    %(info_not_none)s853    %(origin_maxwell)s854    %(int_order_maxwell)s855    %(ext_order_maxwell)s856    %(calibration_maxwell_cal)s857    %(coord_frame_maxwell)s858    %(regularize_maxwell_reg)s859    %(ignore_ref_maxwell)s860    %(bad_condition_maxwell_cond)s861    %(mag_scale_maxwell)s862    %(extended_proj_maxwell)s863    %(verbose)s864 865    Returns866    -------867    S : ndarray, shape (n_meg, n_moments)868        The basis that can be used to reconstruct the data.869    pS : ndarray, shape (n_moments, n_good_meg)870        The (stabilized) pseudoinverse of the S array.871    reg_moments : ndarray, shape (n_moments,)872        The moments that were kept after regularization.873    n_use_in : int874        The number of kept moments that were in the internal space.875 876    Notes877    -----878    This outputs variants of :math:`\mathbf{S}` and :math:`\mathbf{S^\dagger}`879    from equations 27 and 37 of :footcite:`TauluKajola2005` with the coil scale880    for magnetometers already factored in so that the resulting denoising881    transform of the data to obtain :math:`\hat{\phi}_{in}` from equation882    38 would be::883 884        phi_in = S[:, :n_use_in] @ pS[:n_use_in] @ data_meg_good885 886    .. versionadded:: 0.23887 888    References889    ----------890    .. footbibliography::891    rarQr�Fr�zComputing Maxwell basisN)rKryrzr{r|r�r�r�r�r�r�r�r�r^r�r)892r<rr&rgr�rir`r>rar�)raryrzr{r|r�r�r�r�r�r�r@rKr�r3r(r)r�r*rOrOrV�compute_maxwell_basisks.;$893���rQ)rnrorpNNNrqrrNrsFrtNTFrurvrOTrxN)rnrorpNNNrqrrNrsFrtNTFrurvrOrsTrxN)TrV)FN)rur�)TTTT)Fru)Nru)r+r,r-FrnrorpNNrrrsFrtNrurvr.rOrxN)rnrorpNrrrsTrtrurON)��collectionsr�	functoolsr�mathr�osrr�pathlibr�numpyrgZscipyrZ
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Aluode/PerceptionLabPortable · CoolFace