angr/exploration_techniques/unique.py
def update_average(state, new, mem=1.0):
            """
            param state: The state to update the average for.
            param new:   The new value to be accumulated into the average.
            param mem:   Memory parameter to determine how to weight the past average.
            """
            prev, size = self.uniqueness[state]
            new_average = float(prev * (size ** mem) + new) / ((size ** mem) + 1)
            self.uniqueness[state] = new_average, size + 1

            param state: The state to update the average for.
            param new:   The new value to be accumulated into the average.
            param mem:   Memory parameter to determine how to weight the past average.
            
param state: The state to update the average for.
param new:   The new value to be accumulated into the average.
param mem:   Memory parameter to determine how to weight the past average.
param state : The state to update the average for . param new : The new value to be accumulated into the average . param mem : Memory parameter to determine how to weight the past average .
def update_average(state, new, mem=1.0):
            prev, size = self.uniqueness[state]
            new_average = float(prev * (size ** mem) + new) / ((size ** mem) + 1)
            self.uniqueness[state] = new_average, size + 1
def update_average ( state , new , mem = 1.0 ) : prev , size = self . uniqueness [ state ] new_average = float ( prev * ( size ** mem ) + new ) / ( ( size ** mem ) + 1 ) self . uniqueness [ state ] = new_average , size + 1
param state: The state to update the average for.
param state : The state to update the average for .
"""
            param state: The state to update the average for.
            param new:   The new value to be accumulated into the average.
            param mem:   Memory parameter to determine how to weight the past average.
            """
state
new
mem