Method build_program

_program.py:215–298

Build a naive random program. ## edited by Yan: every time we append a function node to the program, we append the type list of the function to the para_stack, when a teriminal is needed, we append check the type needed(0 for constant, 1 for variable)

(self, random_state)

        self._indices_state = None

    def build_program(self, random_state):
        """Build a naive random program. 
        
        ## edited by Yan:
        every time we append a function node to the program, we append the 
        type list of the function to the para_stack, when a teriminal is 
        needed, we append check the type needed(0 for constant, 1 for variable)
        
    
        Parameters
        ----------
        random_state : RandomState instance
            The random number generator.
    
        Returns
        -------
        program : list
            The flattened tree representation of the program.
    
        """
        if self.init_method == 'half and half':
            method = ('full' if random_state.randint(2) else 'grow')
        else:
            method = self.init_method
        max_depth = random_state.randint(*self.init_depth)
    
        # Start a program with a function to avoid degenerative programs
        probs = np.array(list(function_weights.values()))
        probs = np.cumsum(probs) / np.sum(probs)
        func = np.searchsorted(probs, random_state.uniform())
        function = list(function_weights.keys())[func]
        #function = random_state.randint(len(self.function_set))
        #function = self.function_set[function]
        if function.para == None:
            func_para = [0,1] if random_state.uniform() < 0.5 else [1,1]
        else:
            func_para = function.para.copy()
        program = [function]
        terminal_stack = [function.arity]
        para_stack = [func_para]
    
        while terminal_stack:
            depth = len(terminal_stack)                      
            choice = self.n_features + len(self.function_set)
            choice = random_state.randint(choice)
            # Determine if we are adding a function or terminal
            if (depth < max_depth) and (method == 'full' or
                                        choice <= len(self.function_set)) and para_stack[-1][-1]:        
                
                probs = np.array(list(function_weights.values()))
                probs = np.cumsum(probs) / np.sum(probs)
                func = np.searchsorted(probs, random_state.uniform())
                function = list(function_weights.keys())[func]                
                #function = random_state.randint(len(self.function_set))
                #function = self.function_set[function]
                if function.para == None:
                    func_para = [0,1] if random_state.uniform() < 0.5 else [1,1]
                else: