用python实现概率质量函数Possion
原理如下：
方法一：用scipy库的poisson
import scipy.stats as stats
plt.figure(figsize=(12.5,4))
a = np.arange(16)
poi = stats.poisson
lambda_ = [1.5,4.25]
colors = ['#348ABD','#A60628']
plt.bar(a,poi.pmf(a,lambda_[0])#第一个参数是K，第二个参数是lambda的值
,color = colors[0],label="$lambda = %.lf$"%lambda_[0],
alpha=0.60,edgecolor=colors[0],lw="3")
plt.bar(a,poi.pmf(a,lambda_[1]),color = colors[1],label="$lambda = %.lf$"%lambda_[1],
alpha=0.60,edgecolor=colors[1],lw="3")
第二种方法是我自己写了Possion函数，结果跟上面一样：
def poissons(k,lambdas):
p = np.zeros((1,len(k)))
for i in range(len(k)):
if i == 0:
p[0,i] = math.pow(lambdas,k[i]) * math.exp(-lambdas)
else:
sum_k = 1
a = k[i].astype('float64')
while a != 0:
sum_k = sum_k * a
a = a - 1
p[0,i] = math.pow(lambdas,k[i]) * math.exp(-lambdas) / sum_k
return p