class_docstr: Custom time series aligner. todo: write docstring.
  
  todo: describe your custom time series aligner here
  
  Hyper-parameters
  ----------------
  parama : int
      descriptive explanation of parama
  paramb : string, optional (default='default')
      descriptive explanation of paramb
  paramc : boolean, optional (default= whether paramb is not the default)
      descriptive explanation of paramc
  and so on
  
  Components
  ----------
  est : sktime.estimator, BaseEstimator descendant
      descriptive explanation of est
  est2: another estimator
      descriptive explanation of est2
  and so on
docstr: Return distance matrix of alignment.
  
      core logic
  
  Behaviour: returns pairwise distance matrix of alignment distances
      not all aligners will return or implement this (optional)
  
  Accesses in self:
      Fitted model attributes ending in "_".
  
  Returns
  -------
  distmat: an (n x n) np.array of floats, where n is length of X passed to fit
      [i,j]-th entry is alignment distance between X[i] and X[j] passed to fit
docstr_tok: ["Return","distance","matrix","of","alignment",".","core","logic","Behaviour",":","returns","pairwise","distance","matrix","of","alignment","distances","not","all","aligners","will","return","or","implement","this","(","optional",")","Accesses","in","self",":","Fitted","model","attributes","ending","in","``","_","''",".","Returns","--","--","--","-","distmat",":","an","(","n","x","n",")","np.array","of","floats",",","where","n","is","length","of","X","passed","to","fit","[","i",",","j","]","-th","entry","is","alignment","distance","between","X","[","i","]","and","X","[","j","]","passed","to","fit"]
code: def _get_distance_matrix(self):
      """Return distance matrix of alignment.
  
          core logic
  
      Behaviour: returns pairwise distance matrix of alignment distances
          not all aligners will return or implement this (optional)
  
      Accesses in self:
          Fitted model attributes ending in "_".
  
      Returns
      -------
      distmat: an (n x n) np.array of floats, where n is length of X passed to fit
          [i,j]-th entry is alignment distance between X[i] and X[j] passed to fit
      """
  
file_path: sktime/extension_templates/alignment.py
imports: from sktime.alignment.base import BaseAligner
label_desc: Use image node_id 5 for calling the MyAligner obj's underlying member method code with example usage: obj._get_distance_matrix() without return types