original_docstring: ADFQ posterior update using both ADFQ and ADFQ-V2
      Parameters
      ----------
          trigger : threshold value to start ADFQ-V2 update
      
docstring: ADFQ posterior update using both ADFQ and ADFQ-V2
  Parameters
  
  trigger : threshold value to start ADFQ-V2 update
docstring_tokens: ADFQ posterior update using both ADFQ and ADFQ - V2 Parameters trigger : threshold value to start ADFQ - V2 update
code: def posterior_hypbrid(n_means, n_vars, c_mean, c_var, reward, discount, terminal, varTH=1e-20, 
          logEps=-1e+20,  scale_factor = 1.0, trigger = 1e-4, batch=False, noise=0.0):
      """ADFQ posterior update using both ADFQ and ADFQ-V2
      Parameters
      ----------
          trigger : threshold value to start ADFQ-V2 update
      """
      if (c_var*scale_factor <= trigger).all() and (c_var*scale_factor<=trigger).all():
          mean_new, var_new, stats = posterior_adfq_v2(n_means, n_vars, c_mean, c_var, reward, discount, terminal, varTH=varTH, 
          logEps=logEps,  scale_factor = scale_factor,  batch=batch, noise=noise)
      else:
          mean_new, var_new, stats = posterior_adfq(n_means, n_vars, c_mean, c_var, reward, discount, terminal, varTH=varTH, 
          scale_factor = scale_factor,  batch=batch, noise=noise)
  
      return mean_new, var_new, stats
code_tokens: def posterior_hypbrid ( n_means , n_vars , c_mean , c_var , reward , discount , terminal , varTH = 1e-20 , logEps = - 1e+20 , scale_factor = 1.0 , trigger = 1e-4 , batch = False , noise = 0.0 ) : if ( c_var * scale_factor <= trigger ) . all ( ) and ( c_var * scale_factor <= trigger ) . all ( ) : mean_new , var_new , stats = posterior_adfq_v2 ( n_means , n_vars , c_mean , c_var , reward , discount , terminal , varTH = varTH , logEps = logEps , scale_factor = scale_factor , batch = batch , noise = noise ) else : mean_new , var_new , stats = posterior_adfq ( n_means , n_vars , c_mean , c_var , reward , discount , terminal , varTH = varTH , scale_factor = scale_factor , batch = batch , noise = noise ) return mean_new , var_new , stats
short_docstring: ADFQ posterior update using both ADFQ and ADFQ-V2
  Parameters
short_docstring_tokens: ADFQ posterior update using both ADFQ and ADFQ - V2 Parameters
comment: """ADFQ posterior update using both ADFQ and ADFQ-V2
      Parameters
      ----------
          trigger : threshold value to start ADFQ-V2 update
      """