Module ImportFrom alias Import alias identifier ImportFrom alias ImportFrom alias ImportFrom alias alias ImportFrom alias ImportFrom alias ImportFrom alias ImportFrom alias ImportFrom alias FunctionDef arguments args NameParam defaults body Expr Str Assign NameStore Call NameLoad SubscriptLoad NameLoad Index Str Assign SubscriptStore NameLoad Index Str Num Assign SubscriptStore NameLoad Index Str SubscriptLoad NameLoad Index Str Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Expr Str Assign NameStore Call NameLoad SubscriptLoad SubscriptLoad NameLoad Index Str Index Str NameLoad Return SubscriptLoad NameLoad Index NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam NameParam NameParam NameParam defaults Str BinOpDiv Num Num NameLoad Str Num NameLoad body Expr Str Assign NameStore Call AttributeLoad NameLoad attr If CompareNotIn NameLoad ListLoad Str Str Str body Raise Call NameLoad BinOpMod Str NameLoad Expr Call AttributeLoad NameLoad attr BinOpMod Str Call NameLoad NameLoad Assign NameStore Call NameLoad NameLoad keyword NameLoad keyword NameLoad Assign NameStore Call NameLoad NameLoad Assign NameStore Call NameLoad SubscriptLoad SubscriptLoad SubscriptLoad NameLoad Index Str Index Str ExtSlice Slice Slice Num Num NameLoad SubscriptLoad NameLoad Index Str Assign NameStore ListLoad Assign NameStore ListLoad For NameStore NameLoad body Expr Call AttributeLoad NameLoad attr NameLoad If CompareEq AttributeLoad NameLoad attr Str body Assign NameStore SubscriptLoad AttributeLoad SubscriptLoad SubscriptLoad SubscriptLoad NameLoad Index Str Index Num Index Str attr Index Num Assign NameStore Num orelse If CompareEq AttributeLoad NameLoad attr Str body Assign NameStore Num Assign NameStore Num Assign NameStore Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr SubscriptLoad SubscriptLoad SubscriptLoad NameLoad Index Str Index NameLoad Index Str Assign NameStore Call AttributeLoad NameLoad attr SubscriptLoad SubscriptLoad SubscriptLoad NameLoad Index Str Index NameLoad Index Str NameLoad Assign NameStore SubscriptLoad NameLoad ExtSlice Slice Index BinOpAdd NameLoad NameLoad If CompareEq NameLoad Str body Expr Call AttributeLoad NameLoad attr Str Assign NameStore SubscriptLoad Call AttributeLoad NameLoad attr keyword Num ExtSlice Index AttributeLoad NameLoad attr Slice orelse If CompareEq NameLoad Str body Expr Call AttributeLoad NameLoad attr Str Assign NameStore SubscriptLoad Call AttributeLoad NameLoad attr keyword Num ExtSlice Index AttributeLoad NameLoad attr Slice orelse If CompareEq NameLoad Str body Expr Call AttributeLoad NameLoad attr BinOpMod Str NameLoad Assign TupleStore NameStore NameStore NameStore Call AttributeLoad NameLoad attr NameLoad keyword NameLoad keyword NameLoad Expr Call AttributeLoad NameLoad attr NameLoad Expr Call AttributeLoad NameLoad attr BinOpMod Str SubscriptLoad NameLoad Slice Num Num Expr Call AttributeLoad NameLoad attr Str Assign NameStore SubscriptLoad NameLoad Slice NameLoad Assign NameStore BinOpDiv BinOpMult Num Call AttributeLoad NameLoad attr BinOpMult NameLoad NameLoad Call AttributeLoad NameLoad attr BinOpMult NameLoad NameLoad Expr Call AttributeLoad NameLoad attr BinOpMod Str TupleLoad NameLoad NameLoad Assign NameStore BinOpMult SubscriptLoad NameLoad ExtSlice Slice Slice NameLoad SubscriptLoad SubscriptLoad NameLoad Slice NameLoad ExtSlice Index AttributeLoad NameLoad attr Slice Assign NameStore AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad keyword Num Assign NameStore AttributeLoad SubscriptLoad AttributeLoad NameLoad attr Index TupleLoad NameLoad SubscriptLoad Call AttributeLoad NameLoad attr keyword Num ExtSlice Index AttributeLoad NameLoad attr Slice attr Assign NameStore Call NameLoad NameLoad keyword NameLoad keyword Num Expr Call AttributeLoad NameLoad attr BinOpMod Str TupleLoad NameLoad NameLoad Assign NameStore Call NameLoad NameLoad NameLoad NameLoad keyword NameLoad keyword NameLoad Return TupleLoad NameLoad NameLoad decorator_list NameLoad FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad Str BinOpDiv Num Num Str Num body Expr Str Assign NameStore Call AttributeLoad NameLoad attr If UnaryOpNot SubscriptLoad NameLoad Index Str body Raise Call NameLoad Str If UnaryOpNot CompareEq SubscriptLoad NameLoad Index Str Num body Raise Call NameLoad Str If NameLoad body Expr Call AttributeLoad NameLoad attr BinOpMod Str Call NameLoad NameLoad orelse Expr Call AttributeLoad NameLoad attr Str Assign NameStore Call NameLoad NameLoad Assign NameStore Call AttributeLoad NameLoad attr Call NameLoad SubscriptLoad NameLoad Index Str Assign NameStore Call NameLoad NameLoad keyword NameLoad keyword Num Assign NameStore Num Assign NameStore BinOpDiv Num BinOpPow NameLoad Num Assign NameStore Call NameLoad NameLoad NameLoad keyword NameLoad keyword NameLoad keyword Str Expr Call AttributeLoad NameLoad attr BinOpMod Str Call NameLoad AttributeLoad NameLoad attr Assign NameStore AttributeLoad NameLoad attr Assign NameStore ListLoad Assign NameStore ListLoad If NameLoad body For NameStore NameLoad body If CompareEq AttributeLoad NameLoad attr Str body Assign NameStore SubscriptLoad AttributeLoad SubscriptLoad SubscriptLoad SubscriptLoad NameLoad Index Str Index Num Index Str attr Index Num Assign NameStore Num orelse If CompareEq AttributeLoad NameLoad attr Str body Assign NameStore Num Assign NameStore Num orelse Raise Call NameLoad Str Assign NameStore Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr SubscriptLoad SubscriptLoad SubscriptLoad NameLoad Index Str Index NameLoad Index Str Assign NameStore Call AttributeLoad NameLoad attr SubscriptLoad SubscriptLoad SubscriptLoad NameLoad Index Str Index NameLoad Index Str NameLoad Assign NameStore SubscriptLoad NameLoad 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AttributeLoad NameLoad attr BinOpMult NameLoad NameLoad Call AttributeLoad NameLoad attr BinOpMult NameLoad NameLoad Expr Call AttributeLoad NameLoad attr BinOpMod Str TupleLoad NameLoad NameLoad Assign NameStore BinOpMult AttributeLoad SubscriptLoad NameLoad ExtSlice Slice Slice NameLoad attr SubscriptLoad SubscriptLoad NameLoad Slice NameLoad ExtSlice Slice Index AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad keyword Num orelse Assign NameStore NameLoad Return TupleLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam NameParam NameParam NameParam defaults Str BinOpDiv Num Num NameLoad Str Num NameLoad body Expr Str Assign NameStore Call NameLoad NameLoad keyword NameLoad keyword NameLoad Assign NameStore Call NameLoad NameLoad NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword NameLoad Assign TupleStore NameStore NameStore NameLoad Assign NameStore Call NameLoad SubscriptLoad SubscriptLoad NameLoad Index Str Index Str NameLoad SubscriptLoad SubscriptLoad NameLoad Index Str Index Str Assign NameStore Call AttributeLoad NameLoad attr NameLoad NameLoad Assign NameStore Call AttributeLoad NameLoad attr TupleLoad NameLoad Call AttributeLoad NameLoad attr keyword Num If UnaryOpNot NameLoad body Assign NameStore Call AttributeLoad NameLoad attr NameLoad keyword NameLoad Assign NameStore ListComp SubscriptLoad NameLoad Index Str comprehension NameStore SubscriptLoad NameLoad Index Str Assign NameStore Call NameLoad AttributeLoad NameLoad attr NameLoad keyword Num keyword Num Assign AttributeStore NameLoad attr Call NameLoad NameLoad Return NameLoad decorator_list NameLoad
N/A copy deepcopy N/A numpy np scipy linalg io.pick pick_channels utils logger verbose forward convert_forward_solution evoked EvokedArray source_estimate SourceEstimate inverse _subject_from_inverse N/A apply_inverse _prepare_info N/A N/A inverse_operator N/A N/A N/A Helper to get a usable dict N/A info N/A deepcopy N/A inverse_operator N/A info N/A N/A info N/A sfreq 1000.0 N/A N/A info N/A projs N/A inverse_operator N/A projs N/A info N/A _pick_leadfield N/A N/A leadfield forward ch_names N/A N/A N/A Helper to pick out correct lead field components N/A picks_fwd N/A pick_channels N/A N/A forward N/A sol N/A row_names ch_names N/A N/A leadfield N/A picks_fwd N/A point_spread_function N/A N/A inverse_operator forward labels method lambda2 pick_ori mode n_svd_comp verbose N/A dSPM N/A 1 9.0 None mean 1 None N/A N/A Compute point-spread functions (PSFs) for linear estimators

    Compute point-spread functions (PSF) in labels for a combination of inverse
    operator and forward solution. PSFs are computed for test sources that are
    perpendicular to cortical surface.

    Parameters
    ----------
    inverse_operator : instance of InverseOperator
        Inverse operator.
    forward : dict
        Forward solution. Note: (Bad) channels not included in forward
        solution will not be used in PSF computation.
    labels : list of Label
        Labels for which PSFs shall be computed.
    method : 'MNE' | 'dSPM' | 'sLORETA'
        Inverse method for which PSFs shall be computed (for apply_inverse).
    lambda2 : float
        The regularization parameter (for apply_inverse).
    pick_ori : None | "normal"
        If "normal", rather than pooling the orientations by taking the norm,
        only the radial component is kept. This is only implemented
        when working with loose orientations (for apply_inverse).
    mode : 'mean' | 'sum' | 'svd' |
        PSFs can be computed for different summary measures with labels:
        'sum' or 'mean': sum or means of sub-leadfields for labels
        This corresponds to situations where labels can be assumed to be
        homogeneously activated.
        'svd': SVD components of sub-leadfields for labels
        This is better suited for situations where activation patterns are
        assumed to be more variable.
        "sub-leadfields" are the parts of the forward solutions that belong to
        vertices within invidual labels.
    n_svd_comp : integer
        Number of SVD components for which PSFs will be computed and output
        (irrelevant for 'sum' and 'mean'). Explained variances within
        sub-leadfields are shown in screen output.
    verbose : bool, str, int, or None
        If not None, override default verbose level (see mne.verbose).

    Returns
    -------
    stc_psf : SourceEstimate
        The PSFs for the specified labels
        If mode='svd': n_svd_comp components per label are created
        (i.e. n_svd_comp successive time points in mne_analyze)
        The last sample is the summed PSF across all labels
        Scaling of PSFs is arbitrary, and may differ greatly among methods
        (especially for MNE compared to noise-normalized estimates).
    evoked_fwd : Evoked
        Forward solutions corresponding to PSFs in stc_psf
        If mode='svd': n_svd_comp components per label are created
        (i.e. n_svd_comp successive time points in mne_analyze)
        The last sample is the summed forward solution across all labels
        (sum is taken across summary measures).
     N/A mode N/A N/A mode lower N/A N/A mode N/A mean sum svd N/A N/A N/A ValueError N/A mode must be 'svd', 'mean' or 'sum'. Got %s. mode N/A N/A N/A logger info N/A About to process %d labels N/A len labels N/A forward N/A convert_forward_solution forward force_fixed False surf_ori True N/A info N/A _prepare_info inverse_operator N/A leadfield N/A _pick_leadfield N/A N/A N/A forward N/A sol N/A data N/A N/A N/A 2 3 forward N/A info N/A ch_names N/A label_psf_summary N/A N/A label_singvals N/A N/A ll labels N/A N/A N/A N/A logger info ll N/A N/A N/A ll hemi rh N/A N/A offset N/A N/A N/A N/A N/A forward N/A src N/A 0 N/A vertno shape N/A 0 N/A this_hemi 1 N/A N/A N/A N/A ll hemi lh N/A N/A offset 0 N/A this_hemi 0 N/A idx N/A N/A np intersect1d N/A ll vertices N/A N/A N/A forward N/A src N/A this_hemi N/A vertno N/A fwd_idx N/A N/A np searchsorted N/A N/A N/A forward N/A src N/A this_hemi N/A vertno idx N/A sub_leadfield N/A leadfield N/A N/A N/A N/A fwd_idx offset N/A N/A mode sum N/A N/A N/A N/A logger info Computing sums within labels N/A this_label_psf_summary N/A N/A N/A sub_leadfield sum axis 1 N/A N/A N/A np newaxis N/A N/A N/A N/A mode mean N/A N/A N/A N/A logger info Computing means within labels N/A this_label_psf_summary N/A N/A N/A sub_leadfield mean axis 1 N/A N/A N/A np newaxis N/A N/A N/A N/A mode svd N/A N/A N/A N/A logger info N/A Computing SVD within labels, using %d component(s) n_svd_comp N/A N/A u_svd s_svd _ N/A N/A linalg svd sub_leadfield full_matrices False compute_uv True N/A N/A N/A label_singvals append s_svd N/A N/A N/A logger info N/A First 5 singular values: %s N/A s_svd N/A 0 5 N/A N/A N/A logger info (This tells you something about variability of forward solutions in sub-leadfield for label) N/A my_comps N/A s_svd N/A n_svd_comp N/A comp_var N/A N/A 100.0 N/A N/A np sum N/A my_comps my_comps N/A N/A np sum N/A s_svd s_svd N/A N/A N/A logger info N/A Your %d component(s) explain(s) %.1f%% variance in label. N/A n_svd_comp comp_var N/A this_label_psf_summary N/A N/A u_svd N/A N/A N/A n_svd_comp N/A N/A s_svd N/A n_svd_comp N/A N/A N/A np newaxis N/A N/A this_label_psf_summary N/A this_label_psf_summary T N/A N/A N/A label_psf_summary append this_label_psf_summary N/A label_psf_summary N/A N/A np concatenate label_psf_summary axis 0 N/A label_psf_summary N/A N/A N/A np r_ N/A N/A label_psf_summary N/A N/A N/A label_psf_summary sum axis 0 N/A N/A N/A np newaxis N/A T N/A evoked_fwd N/A EvokedArray label_psf_summary info info tmin 0.0 N/A N/A N/A logger info N/A About to apply inverse operator for method='%s' and lambda2=%s N/A method lambda2 N/A stc_psf N/A apply_inverse evoked_fwd inverse_operator lambda2 method method pick_ori pick_ori N/A N/A stc_psf evoked_fwd N/A verbose _get_matrix_from_inverse_operator N/A N/A inverse_operator forward labels method lambda2 mode n_svd_comp N/A None dSPM N/A 1.0 9.0 mean 1 N/A N/A Get inverse matrix from an inverse operator

    Currently works only for fixed/loose orientation constraints
    For loose orientation constraint, the CTFs are computed for the radial
    component (pick_ori='normal').

    Parameters
    ----------
    inverse_operator : instance of InverseOperator
        The inverse operator.
    forward : dict
        The forward operator.
    method : 'MNE' | 'dSPM' | 'sLORETA'
        Inverse methods (for apply_inverse).
    labels : list of Label | None
        Labels for which CTFs shall be computed. If None, inverse matrix for
        all vertices will be returned.
    lambda2 : float
        The regularization parameter (for apply_inverse).
    pick_ori : None | "normal"
        pick_ori : None | "normal"
        If "normal", rather than pooling the orientations by taking the norm,
        only the radial component is kept. This is only implemented
        when working with loose orientations (for apply_inverse).
        Determines whether whole inverse matrix G will have one or three rows
        per vertex. This will also affect summary measures for labels.
    mode : 'mean' | 'sum' | 'svd'
        CTFs can be computed for different summary measures with labels:
        'sum' or 'mean': sum or means of sub-inverse for labels
        This corresponds to situations where labels can be assumed to be
        homogeneously activated.
        'svd': SVD components of sub-inverse for labels
        This is better suited for situations where activation patterns are
        assumed to be more variable.
        "sub-inverse" is the part of the inverse matrix that belongs to
        vertices within invidual labels.
    n_svd_comp : int
        Number of SVD components for which CTFs will be computed and output
        (irrelevant for 'sum' and 'mean'). Explained variances within
        sub-inverses are shown in screen output.

    Returns
    -------
    invmat : ndarray
        Inverse matrix associated with inverse operator and specified
        parameters.
    label_singvals : list of ndarray
        Singular values of svd for sub-inverses.
        Provides information about how well labels are represented by chosen
        components. Explained variances within sub-inverses are shown in
        screen output.
     N/A mode N/A N/A mode lower N/A N/A N/A forward N/A surf_ori N/A N/A N/A RuntimeError Forward has to be surface oriented and force_fixed=True. N/A N/A N/A N/A forward N/A source_ori 1 N/A N/A N/A RuntimeError Forward has to be surface oriented and force_fixed=True. N/A labels N/A N/A N/A N/A logger info N/A About to process %d labels N/A len labels N/A N/A N/A N/A logger info Computing whole inverse operator. N/A info N/A _prepare_info inverse_operator N/A id_mat N/A N/A np eye N/A len N/A info N/A ch_names N/A ev_id N/A EvokedArray id_mat info info tmin 0.0 N/A snr 3.0 N/A lambda2 N/A 1.0 N/A snr 2 N/A invmat_mat_op N/A apply_inverse ev_id inverse_operator lambda2 lambda2 method method pick_ori normal N/A N/A N/A logger info N/A Dimension of inverse matrix: %s N/A str N/A invmat_mat_op shape N/A invmat_mat N/A invmat_mat_op data N/A invmat_summary N/A N/A label_singvals N/A N/A labels N/A N/A ll labels N/A N/A N/A N/A ll hemi rh N/A N/A offset N/A N/A N/A N/A N/A forward N/A src N/A 0 N/A vertno shape N/A 0 N/A this_hemi 1 N/A N/A N/A N/A ll hemi lh N/A N/A offset 0 N/A this_hemi 0 N/A N/A N/A RuntimeError Cannot determine hemisphere of label. N/A idx N/A N/A np intersect1d N/A ll vertices N/A N/A N/A forward N/A src N/A this_hemi N/A vertno N/A fwd_idx N/A N/A np searchsorted N/A N/A N/A forward N/A src N/A this_hemi N/A vertno idx N/A invmat_lbl N/A invmat_mat N/A N/A N/A fwd_idx offset N/A N/A N/A mode sum N/A N/A N/A N/A logger info Computing sums within labels N/A this_invmat_summary N/A N/A invmat_lbl sum axis 0 N/A this_invmat_summary N/A N/A N/A np vstack this_invmat_summary T N/A N/A N/A mode mean N/A N/A N/A N/A logger info Computing means within labels N/A this_invmat_summary N/A N/A invmat_lbl mean axis 0 N/A this_invmat_summary N/A N/A N/A np vstack this_invmat_summary T N/A N/A N/A mode svd N/A N/A N/A N/A logger info N/A Computing SVD within labels, using %d component(s) n_svd_comp N/A N/A u_svd s_svd _ N/A N/A linalg svd N/A invmat_lbl T full_matrices False compute_uv True N/A N/A N/A label_singvals append s_svd N/A N/A N/A logger info N/A First 5 singular values: %s N/A s_svd N/A 5 N/A N/A N/A logger info (This tells you something about variability of estimators in sub-inverse for label) N/A my_comps N/A s_svd N/A n_svd_comp N/A comp_var N/A N/A 100 N/A N/A np sum N/A my_comps my_comps N/A N/A np sum N/A s_svd s_svd N/A N/A N/A logger info N/A Your %d component(s) explain(s) %.1f%% variance in label. N/A n_svd_comp comp_var N/A this_invmat_summary N/A N/A N/A u_svd N/A N/A N/A n_svd_comp T N/A N/A s_svd N/A n_svd_comp N/A N/A N/A N/A np newaxis N/A N/A N/A invmat_summary append this_invmat_summary N/A invmat N/A N/A np concatenate invmat_summary axis 0 N/A N/A invmat invmat_mat N/A N/A invmat label_singvals N/A cross_talk_function N/A N/A inverse_operator forward labels method lambda2 signed mode n_svd_comp verbose N/A dSPM N/A 1 9.0 False mean 1 None N/A N/A Compute cross-talk functions (CTFs) for linear estimators

    Compute cross-talk functions (CTF) in labels for a combination of inverse
    operator and forward solution. CTFs are computed for test sources that are
    perpendicular to cortical surface.

    Parameters
    ----------
    inverse_operator : instance of InverseOperator
        Inverse operator.
    forward : dict
        Forward solution. Note: (Bad) channels not included in forward
        solution will not be used in CTF computation.
    labels : list of Label
        Labels for which CTFs shall be computed.
    method : 'MNE' | 'dSPM' | 'sLORETA'
        Inverse method for which CTFs shall be computed.
    lambda2 : float
        The regularization parameter.
    signed : bool
        If True, CTFs will be written as signed source estimates. If False,
        absolute (unsigned) values will be written
    mode : 'mean' | 'sum' | 'svd'
        CTFs can be computed for different summary measures with labels:
        'sum' or 'mean': sum or means of sub-inverses for labels
        This corresponds to situations where labels can be assumed to be
        homogeneously activated.
        'svd': SVD components of sub-inverses for labels
        This is better suited for situations where activation patterns are
        assumed to be more variable. "sub-inverse" is the part of the inverse
        matrix that belongs to vertices within invidual labels.
    n_svd_comp : int
        Number of SVD components for which CTFs will be computed and output
        (irrelevant for 'sum' and 'mean'). Explained variances within
        sub-inverses are shown in screen output.
    verbose : bool, str, int, or None
        If not None, override default verbose level (see mne.verbose).

    Returns
    -------
    stc_ctf : SourceEstimate
        The CTFs for the specified labels.
        If mode='svd': n_svd_comp components per label are created
        (i.e. n_svd_comp successive time points in mne_analyze)
        The last sample is the summed CTF across all labels.
     N/A forward N/A convert_forward_solution forward force_fixed True surf_ori True N/A out N/A _get_matrix_from_inverse_operator inverse_operator forward labels labels method method lambda2 lambda2 mode mode n_svd_comp n_svd_comp N/A N/A invmat label_singvals out N/A leadfield N/A _pick_leadfield N/A N/A forward N/A sol N/A data forward N/A N/A inverse_operator N/A info N/A ch_names N/A ctfs N/A N/A np dot invmat leadfield N/A ctfs N/A N/A np vstack N/A ctfs N/A N/A ctfs sum axis 0 N/A N/A signed N/A N/A ctfs N/A N/A np abs ctfs out ctfs N/A vertno N/A N/A ss N/A vertno N/A ss N/A inverse_operator N/A src N/A stc_ctf N/A SourceEstimate N/A ctfs T vertno tmin 0.0 tstep 1.0 N/A N/A stc_ctf subject N/A _subject_from_inverse inverse_operator N/A stc_ctf N/A verbose