code: def _row_cosine_similarities(self, X, F):
      # Active
      X_act = X.loc[self.active_rows_]
      X_act = X_act / X_act.sum().sum()
      marge_col = X_act.sum(axis=0)
      Tc = (
          X_act.div(X_act.sum(axis=1), axis=0).div(marge_col, axis=1)
          - 1
      )
      dist2_row = (Tc**2).mul(marge_col, axis=1).sum(axis=1)
  
      # Supplementary
      X_sup = X.loc[X.index.difference(self.active_rows_, sort=False)]
      X_sup = X_sup.div(X_sup.sum(axis=1), axis=0)
      dist2_row_sup = (
          ((X_sup - marge_col) ** 2).div(marge_col, axis=1).sum(axis=1)
      )
  
      dist2_row = pd.concat((dist2_row, dist2_row_sup))
  
      # Can't use pandas.div method because it doesn't support duplicate indices
      return F**2 / dist2_row.to_numpy()[:, None]
  
imports: from __future__ import annotations
  import functools
  import altair
  import numpy
  import pandas
  from scipy import sparse
  from sklearn.utils import check_array
  from prince import svd, utils
label_desc: Use image node_id 6 for calling the CA obj's underlying member method code with example usage: obj._row_cosine_similarities(X, F) and returns: unknown