所以我有两个变量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,我在变量mean上应用了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均值的pmfs的总和(从0开始的出现次数)并将它们与limit中的相应值进行比较。我需要获取pmfs之和大于或等于limit中相应值的出现次数。例如,对于平均值= 5.76,(pmf(0)+ pmf(1)... + pmf(9))* 100 = 93.2,其在9个出现的极限变量中超过90。 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round(sum(l),2)*100>=s
的最后一次出现的z时,我收到以下错误:
ERROR:root:Line magic function `%z` not found.
有人可以帮我纠正代码中的错误吗?非常感谢。
答案 0 :(得分:1)
%
是在IPython的交互式shell中调用魔术行函数的前缀,并且没有z
行魔术函数,因此您会收到此错误。
在IPython中输入%quickref
,您可以了解可用的魔术函数或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,然后在另一个步骤中累积:
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_)]
致电calc(mean, limit)
给出:
[(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])]