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请你帮我弄清楚我的代码有什么问题。我正在尝试编写一个程序，该程序在二维中生成随机行走，并确定行走次数为 1000、最大步长为 0.9、两个位置之间的间隔为 500 步后步行者位置的统计信息0.001。

import math
import random
import time

print "RANDOM WALKS ANALYSIS IN ONE DIMENSION"
NOFW_ = 1000 #The number of walks 
NOFS_= 500 #The number of steps in each walk
MSS_ = 0.9 # The maximum step size[m]
SOFP_ = 0.001  # The separation of positions considered equal[m]

print "                         Number of walks: %3g"% NOFW_
print "            Number of steps in each Walk: %3g"% NOFS_
print "                       Maximum step size: %3g"% MSS_,"m"
print "Separation of positions considered equal: %3g"% SOFP_,"m"
print
print "Please wait while random walks are generated and analyzed..."
print "Date:" + time.ctime()
print

def initialPosition():
    return (0.0, 0.0)

def distance(posA, posB):
    """Calculates the distance between two positions posA and posB"""
    distance = math.sqrt((posB[0] - posA[0])**2 + (posB[1] - posA[1])**2)
    return distance

def printstats(description, numbers):
    minimum_value_ = min(numbers) 
    numbers.sort()
    Tenth_percentile = abs(0.10*len(numbers) + 0.5)
    Mean_value_ = (1./float(len(numbers))*sum(numbers))
    A = 0
    for values in numbers:
        B = distance(values, Mean_value_)
        B = B**2
        A = B + A
    Standard_deviation = math.sqrt((1./(len(numbers)-1))*A)
    Newposition_ = int(0.90*(len(numbers) + 0.5))
    Ninetieth_percentile =numbers[Newposition_]
    maximum_value_ = max(numbers)

    print "Analysis for"""+ description
    print "Minimum value: %9.1f" % minimum_value_
    print "10th percentile: %7.1f" % Tenth_percentile
    print "Mean value: %12.1f" % Mean_value_
    print "Standard deviation: %4.1f" % Standard_deviation
    print "90th percentile: %7.1f" % Ninetieth_percentile
    print "Maximum value: %9.1f" % maximum_value_


    list_1 = [minimum_value_, Tenth_percentile, Mean_value_, Standard_deviation, Ninetieth_percentile,maximum_value_]
    return list_1

def takeStep(prevPosition, maxStep):
    x = random.random()
    y = random.random() 
    minStep = -maxStep
    Z = random.random()*2*math.pi
    stepsize_ = random.random()*0.9
    Stepx= stepsize_*math.cos(Z)
    Stepy= stepsize_*math.sin(Z)
    New_positionx = prevPosition[0] + Stepx
    New_positiony = prevPosition[1] + Stepy
    return (New_positionx, New_positiony) 

Step_100 = []
Step_500 = []
count_list = []
for walk in range(NOFW_):
    Step1 = []
    Position = (0.0,0.0)
    count = 0
    for step in range(NOFS_):
        Next_Step_ = takeStep(Position, MSS_)
        for word in Step1:
            if distance(Next_Step_, word) <= SOFP_:
                count +=1 
        position = Next_Step_
        Step1.append(Next_Step_)
    Step_100.append(Step1[-1])
    Step_500.append(Step1[-1])
    count_list.append(count)

Step_100 = printstats("distance from start at step 100 [m]", Step_100)
Step_500 = printstats("distance from start at step 500 [m]", Step_500)
count_list = printstats("times position revisited", count_list)
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1 回答 1

0

你的问题在这里

Mean_value_ = (1./float(len(numbers))*sum(numbers))

sum()应该得到一些数字，但您的变量numbers实际上包含一些 2 个值的元组

您可能希望为 2 个数字的元组定义自己的 sum 函数，或者分别对第一个值和第二个值求和

于 2013-03-06T03:41:36.613 回答