parameters: (y)
return_statement: return linkage(y, method='ward', metric='euclidean')
docstring: Performs Ward's linkage on a condensed distance matrix.
  
      See linkage for more information on the return structure
      and algorithm.
  
      The following are common calling conventions:
  
      1. ``Z = ward(y)``
         Performs Ward's linkage on the condensed distance matrix ``Z``. See
         linkage for more information on the return structure and
         algorithm.
  
      2. ``Z = ward(X)``
         Performs Ward's linkage on the observation matrix ``X`` using
         Euclidean distance as the distance metric. See linkage for more
         information on the return structure and algorithm.
  
      Parameters
      ----------
      y : ndarray
          A condensed distance matrix. A condensed
          distance matrix is a flat array containing the upper
          triangular of the distance matrix. This is the form that
          ``pdist`` returns. Alternatively, a collection of
          m observation vectors in n dimensions may be passed as
          a m by n array.
  
      Returns
      -------
      Z : ndarray
          The hierarchical clustering encoded as a linkage matrix.
  
      See Also
      --------
      linkage: for advanced creation of hierarchical clusterings.
docstring_summary: Performs Ward's linkage on a condensed distance matrix.
docstring_tokens: Performs Ward s linkage on a condensed distance matrix .
function: def ward(y):
      """
      Performs Ward's linkage on a condensed distance matrix.
  
      See linkage for more information on the return structure
      and algorithm.
  
      The following are common calling conventions:
  
      1. ``Z = ward(y)``
         Performs Ward's linkage on the condensed distance matrix ``Z``. See
         linkage for more information on the return structure and
         algorithm.
  
      2. ``Z = ward(X)``
         Performs Ward's linkage on the observation matrix ``X`` using
         Euclidean distance as the distance metric. See linkage for more
         information on the return structure and algorithm.
  
      Parameters
      ----------
      y : ndarray
          A condensed distance matrix. A condensed
          distance matrix is a flat array containing the upper
          triangular of the distance matrix. This is the form that
          ``pdist`` returns. Alternatively, a collection of
          m observation vectors in n dimensions may be passed as
          a m by n array.
  
      Returns
      -------
      Z : ndarray
          The hierarchical clustering encoded as a linkage matrix.
  
      See Also
      --------
      linkage: for advanced creation of hierarchical clusterings.
  
      """
      return linkage(y, method='ward', metric='euclidean')
function_tokens: def ward ( y ) : return linkage ( y , method = 'ward' , metric = 'euclidean' )