英文:
Porting algorithm from Python to Go
问题
我正在尝试将这段Python代码转换为Go代码，但是在math包中找不到**beta()**函数。我应该在哪里找到beta和其他所需的函数？
from numpy import *
from scipy.stats import beta
class BetaBandit(object):
def __init__(self, num_options=2, prior=(1.0,1.0)):
self.trials = zeros(shape=(num_options,), dtype=int)
self.successes = zeros(shape=(num_options,), dtype=int)
self.num_options = num_options
self.prior = prior
def add_result(self, trial_id, success):
self.trials[trial_id] = self.trials[trial_id] + 1
if (success):
self.successes[trial_id] = self.successes[trial_id] + 1
def get_recommendation(self):
sampled_theta = []
for i in range(self.num_options):
#Construct beta distribution for posterior
dist = beta(self.prior[0]+self.successes[i],
self.prior[1]+self.trials[i]-self.successes[i])
#Draw sample from beta distribution
sampled_theta += [ dist.rvs() ]
# Return the index of the sample with the largest value
return sampled_theta.index( max(sampled_theta) )
这段代码使用了numpy和scipy.stats库中的beta函数。如果你想在Go中实现相同的功能，你可以尝试使用Go的数学库或者寻找第三方库来提供beta分布的函数。
英文:
I am trying to port this python code to Go but there is no beta() in math package. Where can i find beta and other functions required for this?
from numpy import *
from scipy.stats import beta
class BetaBandit(object):
def __init__(self, num_options=2, prior=(1.0,1.0)):
self.trials = zeros(shape=(num_options,), dtype=int)
self.successes = zeros(shape=(num_options,), dtype=int)
self.num_options = num_options
self.prior = prior
def add_result(self, trial_id, success):
self.trials[trial_id] = self.trials[trial_id] + 1
if (success):
self.successes[trial_id] = self.successes[trial_id] + 1
def get_recommendation(self):
sampled_theta = []
for i in range(self.num_options):
#Construct beta distribution for posterior
dist = beta(self.prior[0]+self.successes[i],
self.prior[1]+self.trials[i]-self.successes[i])
#Draw sample from beta distribution
sampled_theta += [ dist.rvs() ]
# Return the index of the sample with the largest value
return sampled_theta.index( max(sampled_theta) )
答案1
得分: 7
如果你在谈论 numpy.random.beta，它是Dirichlet分布的特例，与Gamma分布有关，你可以查看项目 gostat。
它有一个 beta.go 源代码 实现了该函数。
英文:
If you are talking about numpy.random.beta, the Beta distribution which is a special case of the Dirichlet distribution, and is related to the Gamma distribution, you can check the project gostat.
It has a beta.go source code which implements that function.
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