class_docstr: Class to hold linear constraints information
  
  Affine constraints are defined as ``R b = q` where `R` is the constraints
  matrix and `q` are the constraints values and `b` are the parameters.
  
  This is in analogy to patsy's LinearConstraints class but can be pickled.
  
  Parameters
  ----------
  constraint_matrix : ndarray
      R matrix, 2-dim with number of columns equal to the number of
      parameters. Each row defines one constraint.
  constraint_values : ndarray
      1-dim array of constant values
  variable_names : list of strings
      parameter names, used only for display
  kwds : keyword arguments
      keywords are attached to the instance.
docstr: class method to create instance from patsy instance
  
  Parameters
  ----------
  lc : instance
      instance of patsy LinearConstraint, or other instances that have
      attributes ``lc.coefs, lc.constants, lc.variable_names``
  
  Returns
  -------
  instance of this class
docstr_tok: ["class","method","to","create","instance","from","patsy","instance","Parameters","--","--","--","--","--","lc",":","instance","instance","of","patsy","LinearConstraint",",","or","other","instances","that","have","attributes","``","lc.coefs",",","lc.constants",",","lc.variable_names","``","Returns","--","--","--","-","instance","of","this","class"]
code: def from_patsy(cls, lc):
      """class method to create instance from patsy instance
  
      Parameters
      ----------
      lc : instance
          instance of patsy LinearConstraint, or other instances that have
          attributes ``lc.coefs, lc.constants, lc.variable_names``
  
      Returns
      -------
      instance of this class
  
      """
      return cls(lc.coefs, lc.constants, lc.variable_names)
  
file_path: statsmodels/statsmodels/base/_constraints.py
imports: import numpy
label_desc: Use image node_id 5 for calling the LinearConstraints obj's underlying member method code with example usage: obj.from_patsy(cls, lc) and returns: cls