class_docstr: Information about an operator is lazily computed.
  
  The information includes the exact 1-norm of the operator,
  in addition to estimates of 1-norms of powers of the operator.
  This uses the notation of Computing the Action (2011).
  This class is specialized enough to probably not be of general interest
  outside of this module.
class_docstr_tok: ["Information","about","an","operator","is","lazily","computed",".","The","information","includes","the","exact","1-norm","of","the","operator",",","in","addition","to","estimates","of","1-norms","of","powers","of","the","operator",".","This","uses","the","notation","of","Computing","the","Action","(","2011",")",".","This","class","is","specialized","enough","to","probably","not","be","of","general","interest","outside","of","this","module","."]
docstr: Set the scale parameter.
docstr_tok: ["Set","the","scale","parameter","."]
code: def set_scale(self, scale):
      """
      Set the scale parameter.
      """
      self._scale = scale
  
imports: from warnings import warn
  import numpy
  import scipy.linalg
  import scipy.sparse.linalg
  from scipy.linalg._decomp_qr import qr
  from scipy.sparse._sputils import is_pydata_spmatrix
  from scipy.sparse.linalg import aslinearoperator
  from scipy.sparse.linalg._interface import IdentityOperator
  from scipy.sparse.linalg._onenormest import onenormest
label_desc: Use image node_id 2 for calling the LazyOperatorNormInfo obj's underlying member method code with example usage: obj.set_scale(scale) without return types