Model_runs
Add some functions for the implementation of the model_runs
@@ -282,6 +282,22 @@ def print_x_iters( list_of_res):
for i in range( len(list_of_res) ):
print( list_of_res[i].x_iters )
+def median_number( lista ):
+ """
+ Given a list it
+ return the median
+
+ Parameters
+ ----------
+ lista : [list] List of numbers
+
+ Returns
+ -------
+ val : The median of the numbers
+ """
+ val = statistics.median( lista )
+ return val
+
def median( list_of_res):
"""
Given a Bayesian_optimization result
@@ -984,3 +1000,4 @@ def load_BO( lista_dump ):
res_loaded = load( lista_dump[n] )
lista_res_loaded.append( res_loaded )
return lista_res_loaded
+
