class_docstr: Add 'invisibility-reset' dimension to the path.
  
  This adds sensitivity to translation.
  
  Introduced by Yang et al.:
  https://arxiv.org/pdf/1707.03993.pdf
  : https: //arxiv.org/pdf/1707.03993.pdf
class_docstr_tok: ["Add","'invisibility-reset","'","dimension","to","the","path",".","This","adds","sensitivity","to","translation",".","Introduced","by","Yang","et","al",".",":","https",":","\/\/arxiv.org\/pdf\/1707.03993.pdf",":","https",":","\/\/arxiv.org\/pdf\/1707.03993.pdf"]
code: def _transform(self, X, y=None):
      X = np.swapaxes(X, 1, 2)
  
      # Batch, length, channels
      B, L, C = X.shape[0], X.shape[1], X.shape[2]
  
      # Add in a dimension of ones
      X_pendim = np.concatenate((np.ones(shape=(B, L, 1)), X), 2)
  
      # Add pen down to 0
      pen_down = X_pendim[:, [-1], :]
      pen_down[:, :, 0] = 0
      X_pendown = np.concatenate((X_pendim, pen_down), 1)
  
      # Add home
      home = np.zeros(shape=(B, 1, C + 1))
      X_penoff = np.concatenate((X_pendown, home), 1)
  
      Xt = np.swapaxes(X_penoff, 1, 2)
      return Xt
  
imports: import numpy
  from sklearn.pipeline import Pipeline
  from sktime.transformations.base import BaseTransformer
label_desc: Use image node_id 1 for calling the _InvisibilityReset obj's underlying member method code with example usage: obj._transform(X, y) and returns: Xt