code: def _get_densest(A, eligibleRows):
      """
      Returns the index of the densest row of A. Ignores rows that are not
      eligible for consideration.
  
      Parameters
      ----------
      A : 2-D array
          An array representing a matrix
      eligibleRows : 1-D logical array
          Values indicate whether the corresponding row of A is eligible
          to be considered
  
      Returns
      -------
      i_densest : int
          Index of the densest row in A eligible for consideration
  
      """
      rowCounts = _row_count(A)
      return np.argmax(rowCounts * eligibleRows)
  
file_path: catboost/contrib/python/scipy/py3/scipy/optimize/_remove_redundancy.py
imports: import numpy
  from scipy.linalg import svd
  from scipy.linalg.interpolative import interp_decomp
  import scipy
  from scipy.linalg.blas import dtrsm
label_desc: Use image node_id 2 for calling a global function with example usage: _get_densest(A, eligibleRows) and returns: np