python - 如果可能的话，如何使用函数参数作为 npy 方法

Question

我正在尝试创建一个函数，它将采用 numpy dstr 名称作为参数，并绘制该分布中的随机数据点的直方图。

如果它仅适用于需要 1 个参数的 npy 发行版，那就没问题。只是真的坚持尝试创建 np.random.distribution()...\

# import libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline 

#Define a function (Fnc) that produces random numpy distributions (dstr)
#Fnc args: [npy dstr name as lst of str], [num of data pts]
def get_rand_dstr(dstr_name):
  npdstr = dstr_name
  dstr = np.random.npdstr(user.input("How many datapoints?"))
  #here pass each dstr from dstr_name through for loop
  #for loop will prompt user for required args of dstr (nbr of desired datapoints)
  return plt.hist(df)

get_rand_dstr('chisquare')

Answer 1

使用这个代码，它可能会对你有帮助

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline 

def get_rand_dstr(dstr_name):
#     npdstr = dstr_name  
    dstr = 'np.random.{}({})'.format(dstr_name, (input("How many datapoints?"))) # for using any distribution need to manipulate here 
                                                                                 # cause number of args are diffrent for diffrent distibutions           
    print(dstr)
    df = eval(dstr)
    print(df)
#     dstr1 = np.random.chisquare(int(input("How many datapoints?")))
#     print(dstr1)
    return plt.hist(df)

# get_rand_dstr('geometric')  
get_rand_dstr('chisquare')