将最后一次迭代存储在循环中(python)
Storing the last iteration in a loop(python)
所以我有 2 个变量 mean 和 service 由以下值组成:
mean=[5.76,6.5,7,5,4.5,6,9,2.5,3,5.5]
limit=[90,80,95,96,98,85,82,75,90,91]
现在,我对变量 mean 应用了 poisson
函数:
from scipy.stats import poisson
for m in mean:
r_v=poisson(m)
r_v1.append(r_v)
接下来我需要做的是获取所有mean值的pmfs之和(出现次数从0开始),并将它们与limit中对应的值进行比较。我需要获取pmfs之和大于或等于limit中对应值的出现次数。例如,对于均值 =5.76,(pmf(0)+pmf(1)...+pmf(9))*100=93.2,在极限变量中超过 90 的次数有 9 次。
我 运行 以下代码似乎工作正常:
for r,s in zip(r_v1, limit):
l=[]
z=0
while True:
y=r.pmf(z)
l.append(y)
z+=1
if round(sum(l),2)*100>=s:
break
Store=%z
问题是,当我尝试存储最后一次出现的 z round(sum(l),2)*100>=s
时,出现以下错误:
ERROR:root:Line magic function `%z` not found.
有人可以帮我改正代码中的错误吗?非常感谢。
%
是在 IPython 的交互式 shell 中调用魔法线函数的前缀,没有 z
线魔法函数,因此会出现此错误.
在 IPython 中键入 %quickref
,您将获得可用魔术函数或 readthedocs.
的概览
你的问题是你在一步中尝试了太多。尝试为一个输入获得正确的结果,然后在另一步中累积:
def calc(mean_, limit_):
def inner(m, s):
r = poisson(m)
l = []
z = 0
while True:
y = r.pmf(z)
l.append(y)
z += 1
if round(sum(l), 2) * 100 >= s:
return z, l
return [inner(*args) for args in zip(mean_, limit_)]
调用 calc(mean, limit)
得到:
[(10,
[0.0031511115984444414,
0.018150402807039979,
0.052273160084275148,
0.10036446736180832,
0.14452483300100394,
0.16649260761715656,
0.15983290331247035,
0.13151964615426115,
0.094694145231068075,
0.060604252947883679]),
(10,
[0.0015034391929775724,
0.009772354754354215,
0.031760152951651209,
0.068813664728577653,
0.11182220518393866,
0.14536886673912017,
0.1574829389673803,
0.14623415761256733,
0.11881525306021086,
0.08581101609904139]),
(12,
[0.00091188196555451624,
0.0063831737588816145,
0.022341108156085643,
0.052129252364199796,
0.091226191637349643,
0.1277166682922895,
0.14900277967433773,
0.14900277967433773,
0.1303774322150455,
0.10140466950059107,
0.070983268650413558,
0.045171170959354162]),
(10,
[0.006737946999085467,
0.033689734995427337,
0.084224337488568321,
0.1403738958142805,
0.17546736976785063,
0.17546736976785068,
0.1462228081398754,
0.10444486295705395,
0.065278039348158651,
0.036265577415643714]),
(10,
[0.011108996538242306,
0.049990484422090385,
0.11247858994970336,
0.168717884924555,
0.18980762054012446,
0.17082685848611215,
0.1281201438645839,
0.082362949627232548,
0.046329159165318316,
0.0231645795826592]),
(9,
[0.0024787521766663585,
0.014872513059998144,
0.044617539179994441,
0.089235078359988937,
0.13385261753998332,
0.16062314104797995,
0.16062314104798009,
0.13767697804112569,
0.10325773353084421]),
(13,
[0.00012340980408667956,
0.0011106882367801166,
0.0049980970655105232,
0.014994291196531574,
0.033737155192196056,
0.06072687934595293,
0.091090319018929264,
0.1171161244529091,
0.13175564000952278,
0.13175564000952278,
0.11858007600857066,
0.097020062188830414,
0.072765046641622894]),
(4,
[0.0820849986238988,
0.20521249655974699,
0.25651562069968376,
0.21376301724973648]),
(6,
[0.049787068367863944,
0.14936120510359185,
0.22404180765538775,
0.22404180765538775,
0.16803135574154085,
0.10081881344492458]),
(10,
[0.0040867714384640666,
0.02247724291155237,
0.06181241800676901,
0.1133227663457432,
0.15581880372539689,
0.17140068409793663,
0.15711729375644187,
0.12344930223720431,
0.084871395288077939,
0.051865852676047694])]
所以我有 2 个变量 mean 和 service 由以下值组成:
mean=[5.76,6.5,7,5,4.5,6,9,2.5,3,5.5]
limit=[90,80,95,96,98,85,82,75,90,91]
现在,我对变量 mean 应用了 poisson
函数:
from scipy.stats import poisson
for m in mean:
r_v=poisson(m)
r_v1.append(r_v)
接下来我需要做的是获取所有mean值的pmfs之和(出现次数从0开始),并将它们与limit中对应的值进行比较。我需要获取pmfs之和大于或等于limit中对应值的出现次数。例如,对于均值 =5.76,(pmf(0)+pmf(1)...+pmf(9))*100=93.2,在极限变量中超过 90 的次数有 9 次。 我 运行 以下代码似乎工作正常:
for r,s in zip(r_v1, limit):
l=[]
z=0
while True:
y=r.pmf(z)
l.append(y)
z+=1
if round(sum(l),2)*100>=s:
break
Store=%z
问题是,当我尝试存储最后一次出现的 z round(sum(l),2)*100>=s
时,出现以下错误:
ERROR:root:Line magic function `%z` not found.
有人可以帮我改正代码中的错误吗?非常感谢。
%
是在 IPython 的交互式 shell 中调用魔法线函数的前缀,没有 z
线魔法函数,因此会出现此错误.
在 IPython 中键入 %quickref
,您将获得可用魔术函数或 readthedocs.
你的问题是你在一步中尝试了太多。尝试为一个输入获得正确的结果,然后在另一步中累积:
def calc(mean_, limit_):
def inner(m, s):
r = poisson(m)
l = []
z = 0
while True:
y = r.pmf(z)
l.append(y)
z += 1
if round(sum(l), 2) * 100 >= s:
return z, l
return [inner(*args) for args in zip(mean_, limit_)]
调用 calc(mean, limit)
得到:
[(10, [0.0031511115984444414, 0.018150402807039979, 0.052273160084275148, 0.10036446736180832, 0.14452483300100394, 0.16649260761715656, 0.15983290331247035, 0.13151964615426115, 0.094694145231068075, 0.060604252947883679]), (10, [0.0015034391929775724, 0.009772354754354215, 0.031760152951651209, 0.068813664728577653, 0.11182220518393866, 0.14536886673912017, 0.1574829389673803, 0.14623415761256733, 0.11881525306021086, 0.08581101609904139]), (12, [0.00091188196555451624, 0.0063831737588816145, 0.022341108156085643, 0.052129252364199796, 0.091226191637349643, 0.1277166682922895, 0.14900277967433773, 0.14900277967433773, 0.1303774322150455, 0.10140466950059107, 0.070983268650413558, 0.045171170959354162]), (10, [0.006737946999085467, 0.033689734995427337, 0.084224337488568321, 0.1403738958142805, 0.17546736976785063, 0.17546736976785068, 0.1462228081398754, 0.10444486295705395, 0.065278039348158651, 0.036265577415643714]), (10, [0.011108996538242306, 0.049990484422090385, 0.11247858994970336, 0.168717884924555, 0.18980762054012446, 0.17082685848611215, 0.1281201438645839, 0.082362949627232548, 0.046329159165318316, 0.0231645795826592]), (9, [0.0024787521766663585, 0.014872513059998144, 0.044617539179994441, 0.089235078359988937, 0.13385261753998332, 0.16062314104797995, 0.16062314104798009, 0.13767697804112569, 0.10325773353084421]), (13, [0.00012340980408667956, 0.0011106882367801166, 0.0049980970655105232, 0.014994291196531574, 0.033737155192196056, 0.06072687934595293, 0.091090319018929264, 0.1171161244529091, 0.13175564000952278, 0.13175564000952278, 0.11858007600857066, 0.097020062188830414, 0.072765046641622894]), (4, [0.0820849986238988, 0.20521249655974699, 0.25651562069968376, 0.21376301724973648]), (6, [0.049787068367863944, 0.14936120510359185, 0.22404180765538775, 0.22404180765538775, 0.16803135574154085, 0.10081881344492458]), (10, [0.0040867714384640666, 0.02247724291155237, 0.06181241800676901, 0.1133227663457432, 0.15581880372539689, 0.17140068409793663, 0.15711729375644187, 0.12344930223720431, 0.084871395288077939, 0.051865852676047694])]