code: def prob_larger_continuous(distr1, distr2):
      """
      Probability indicating that distr1 is stochastically larger than distr2.
  
      This computes
  
          p = P(x1 > x2)
  
      for two continuous distributions, where `distr1` and `distr2` are the
      distributions of random variables x1 and x2 respectively.
  
      Parameters
      ----------
      distr1, distr2 : distributions
          Two instances of scipy.stats.distributions. The required methods are
          cdf of the second distribution and expect of the first distribution.
  
      Returns
      -------
      p : probability x1 is larger than x2
  
  
      Notes
      -----
      This is a one-liner that is added mainly as reference.
  
      Examples
      --------
      >>> from scipy import stats
      >>> prob_larger_continuous(stats.norm, stats.t(5))
      0.4999999999999999
  
      # which is the same as
      >>> stats.norm.expect(stats.t(5).cdf)
      0.4999999999999999
  
      # distribution 1 with smaller mean (loc) than distribution 2
      >>> prob_larger_continuous(stats.norm, stats.norm(loc=1))
      0.23975006109347669
  
      """
  
      return distr1.expect(distr2.cdf)
  
file_path: statsmodels/statsmodels/stats/nonparametric.py
imports: import numpy
  from scipy import stats
  from scipy.stats import rankdata
  from statsmodels.stats.base import HolderTuple
  from statsmodels.stats.weightstats import _tconfint_generic, _tstat_generic, _zconfint_generic, _zstat_generic
label_desc: Use image node_id 4 for calling a global function with example usage: prob_larger_continuous(distr1, distr2) and returns: distr1