很抱歉发布长代码。我已经提取了代码中生成和使用列表lower_lip_under_upper_list_plist的部分。链接使用此列表的函数时出错。 generate_t_u()函数在time()函数内部调用，但time()函数无法识别此列表，因为它未在那里传递。但是如果我在这个函数中传递它，那么我也必须在main中进行更改。我将再次得到同样的错误。
def time(transcriptionFile) :
""" This function changes the time values in secs from the transcription file and keeps a list of start time for each phoneme. """
with open("transcriptions.txt", "r") as tFile :
timeList = []
t_u = 0.0
for line in tFile :
li = line.split()
if li :
start_time = (int(li[0]) / 10000000.)
timeList.append(start_time)
#print timeList
generate_t_u(timeList, lower_lip_under_upper_list_plist)
def generate_t_u(timeList, lower_lip_under_upper_list_plist)
""" It generates the regular time intervals t(u) values for sampling. """
i = 0
while i < len(timeList) - 1 :
# if the number is in the range
# do the calculations and move to the next number
if t_u > timeList[i] and t_u < timeList[i + 1] :
#print "\n The t_u value:", t_u, 'is between',
#print "start:", timeList[i], " and end: ", timeList[i+1]
poly = poly_coeff(timeList[i], timeList[i + 1], t_u)
Newton(poly, lower_lip_under_upper_list_plist[i], lower_lip_under_upper_list_plist[i + 1])
t_u = t_u + 0.04 # regular time interval
# if the number is at the lower boundary of the range, no need of calculation as u = 0
elif t_u == timeList[i] :
#print "\n The t_u value:", t_u, 'is on the boundary of',
#print "start:", timeList[i], " and end: ", timeList[i+1]
#print "u : 0"
lower_lip_under_upper_list_bezier(0, lower_lip_under_upper_list_plist[i], lower_lip_under_upper_list_plist[i + 1])
t_u = t_u + 0.04 # regular time interval
# if the number is at the upper boundary of the range, no need of calculation as u = 1
elif t_u == timeList[i + 1] :
#print "\n The t_u value:", t_u, 'is on the boundary of',
#print "start:", timeList[i], " and end: ", timeList[i+1]
#print " u : 1"
lower_lip_under_upper_list_bezier(1, lower_lip_under_upper_list_plist[i], lower_lip_under_upper_list_plist[i + 1])
t_u = t_u + 0.04 # regular time interval
# if the number isn't in the range, move to the next range
else :
i += 1
def Newton(poly, p0, p3) :
""" Newton's method for finding the root of a polynomial. Here the root is the 'u' value"""
poly_diff = poly_differentiate(poly)
counter = 0
epsilon = 0.000000000001
x = 0.5 # initial guess value
while True:
x_n = x - (float(poly_substitute(poly, x)) / poly_substitute(poly_diff, x))
counter += 1
if abs(x_n - x) < epsilon :
break
x = x_n
#print "\tIteration " , counter , " : ", x_n
print "u:", (x_n)
lower_lip_under_upper_list_bezier(x_n, p0, p3)
def param_lists_separate(pList) :
""" Separating the parameter values of each feature into individual lists """
v = [[inner[1][i] for outer in pList for inner in outer]
for i in range(len(pList[0][0][1]))]
lower_lip_under_upper_list_plist = v[0]
lips_part_plist = v[1]
lips_spread_plist = v[2]
jaw_open_plist = v[3]
lips_round_plist = v[4]
return lower_lip_under_upper_list_plist
def lower_lip_under_upper_list_bezier(x_n, p0, p3) :
""" Calculating sampling points using rational bezier curve equation"""
u = x_n
p1 = p0
p2 = p3
lower_lip_under_upper_list_p_u = math.pow(1 - u, 3) * p0 + 3 * u * math.pow(1 - u, 2) * p1 \
+ 3 * (1 - u) * math.pow(u, 2) * p2 + math.pow(u, 3) * p3
lower_lip_under_upper_list_p_u = lower_lip_under_upper_list_p_u * w
d = math.pow(1 - u, 3) * w + 3 * u * w * math.pow(1 - u, 2) + 3 * (1 - u) * w * math.pow(u, 2) + math.pow(u, 3) * w
lower_lip_under_upper_list_p_u = lower_lip_under_upper_list_p_u / d
print "\n p(u) values for the feature lower lip under upper list \n"
print "p(u): ", lower_lip_under_upper_list_p_u
return lower_lip_under_upper_list_p_u
if __name__ == "__main__" :
time("transcriptions.txt")
错误是：
NameError：未定义全局名称“lower_lip_under_upper_list_plist”。
此错误位于lower_lip_under_upper_list_bezier(0, lower_lip_under_upper_list_plist[i], lower_lip_under_upper_list_plist[i + 1])函数的time()行。
答案 0 :(得分：2)
考虑time函数中的这一行：
def time(transcriptionFile) :
...
generate_t_u(timeList, lower_lip_under_upper_list_plist)
lower_lip_under_upper_list_plist，因此Python在全局范围内查找它。它也没有在那里定义，所以Python引发了NameError，说没有定义变量lower_lip_under_upper_list_plist。
顺便说一下，回溯错误消息包含一个行号，表示导致NameError的行。它将帮助您（和我们）将问题归结为包含行号。
答案 1 :(得分：2)
lower_lip_under_upper_list_plist应该是generate_t_u的返回值吗？尝试将generate_t_u更改为：
def generate_t_u(time_list):
lower_lip_under_upper_list_plist = []
# ... the function remains the same
return lower_lip_upper_list_plist
我不确定调用param_lists_separate的位置，但看起来它中的绑定也应该是全局的。 generate_t_u中存在类似的问题，因为t_u未绑定在那里 - 如果这引用t_u中的time，那么它应该作为参数传入。如果您有许多相关的绑定和方法对数据起作用，那么您应该考虑创建一个将数据和操作联系在一起的类。
请考虑采取以下措施：
class NewtonsMethod(object):
def __init__(self, file_name):
# change global names into properties of ``self``
self.lower_lip_under_upper_list_plist = []
self.lips_part_plist = []
self.lips_spread_plist = []
self.jaw_open_plist = []
self.lips_round_plist = []
self.t_u = 0.0
self.time_list = []
# initialize from the data file
with open(file_name) as file_ref:
for line in file_ref:
data = line.split()
if data:
start_time = (int(data[0]) / 10000000.0)
self.time_list.append(start_time)
def _lower_lip_under_upper_list_bezier(self, x_n, point):
(u, p1, p2) = (x_n, self.lower_lip_under_upper_list_plist[point],
self.lower_lip_under_upper_list_plist[point + 1])
# if lower_lip_under_upper_list_p_u is used elsewhere, then it
# might make sense to change it to a property
lower_lip_under_upper_list_p_u = ...
return lower_lip_under_upper_list_p_u
def _generate_t_u(self):
(i, t_u) = (0, 0.0)
while i < len(self.time_list) - 1:
if t_u > self.time_list[i] and t_u < time_list[i + 1]:
poly = poly_coeff(self.time_list[i], self.time_list[i + 1], t_u)
self._apply_newton(poly, i)
elif t_u == self.time_list[i]:
self._lower_lip_under_upper_list_bezier(0, i)
t_u += 0.04
elif t_u == self.time_list[i + 1]:
self._lower_lip_under_upper_list_bezier(1, i)
t_u += 0.04
else:
i += 1
def _apply_newton(self, poly, point):
poly_diff = poly_differentiate(poly)
(epsilon, x) = (0.0000000001, 0.5)
while True:
x_n = x - (...)
if abs(x_n - x) < epsilon:
break
x = x_n
self._lower_lip_under_upper_list_bezier(x_n, point)
面向对象编程的最基本原则之一是将算法与它们处理和/或需要的数据捆绑在一起。你可以在这里应用这个想法。您的全局绑定将成为对象的属性，因此它们始终可用作实例方法中self的属性。您可能已经注意到，不再需要传递lower_lip_under_upper_list_plist之类的值。您需要做的就是将索引传递到列表中，因为列表本身是对象的属性。
将算法重构为class应该不再需要全局变量。它还可以最大限度地减少参数的数量，让您专注于以干净和模块化的方式实现算法。