class_docstr: A computed beamformer.
  
  Notes
  -----
  .. versionadded:: 0.17
code: def __repr__(self):  # noqa: D105
      n_verts = sum(len(v) for v in self["vertices"])
      n_channels = len(self["ch_names"])
      if self["subject"] is None:
          subject = "unknown"
      else:
          subject = f'"{self["subject"]}"'
      out = "<Beamformer | {}, subject {}, {} vert, {} ch".format(
          self["kind"],
          subject,
          n_verts,
          n_channels,
      )
      if self["pick_ori"] is not None:
          out += f', {self["pick_ori"]} ori'
      if self["weight_norm"] is not None:
          out += f', {self["weight_norm"]} norm'
      if self.get("inversion") is not None:
          out += f', {self["inversion"]} inversion'
      if "rank" in self:
          out += f', rank {self["rank"]}'
      out += ">"
      return out
  
imports: from copy import deepcopy
  import numpy
  from .._fiff.proj import Projection, make_projector
  from ..cov import Covariance, make_ad_hoc_cov
  from ..forward.forward import _restrict_forward_to_src_sel, is_fixed_orient
  from ..minimum_norm.inverse import _get_vertno, _prepare_forward
  from ..source_space._source_space import label_src_vertno_sel
  from ..time_frequency.csd import CrossSpectralDensity
  from ..utils import _check_option, _check_src_normal, _import_h5io_funcs, _pl, _reg_pinv, _sym_mat_pow, check_fname, logger, verbose, warn
label_desc: Use image node_id 2 for calling the Beamformer obj's underlying member method code with example usage: obj.__repr__() and returns: out