optimizer.py 文件源码

def init(self, init_points, return_log):
                '''A function to perform all initialization and clear the optimize methods - To be constructed'''

                if self.randomstate != None:
                        numpy.random.seed(self.randomstate)

                print('Optimization procedure is initializing at %i random points.' % init_points)

                #Sampling some points are random to define xtrain.
                xtrain = numpy.asarray([numpy.random.uniform(x[0], x[1], size = init_points) for x in self.log_bounds]).T
                ytrain = []
                for x in xtrain : 
                    ytrain.append(self.f(dict(zip(self.keys, return_log(x)))))
                    print('%d points initialized.' % len(ytrain))

                ytrain = numpy.asarray(ytrain)

                print('Optimization procedure is done initializing.')

                return xtrain, ytrain

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