Question

i want to create a program which calculates the average of N random numbers taken from a uniform random number distribution.The program must run for
Ν=10,100,1000,10000,100000,1000000 random numbers.Then,i have to plot the mean value as
a function of N.

I did this:

from scitools.std import *
import matplotlib.pyplot as plt


N=10

distribution=[]
for i in range(1,7):   
    N*=10
    random_numbers=[random.uniform(0,1,size=N)]   
    distribution.append(random_numbers)


plt.semilogx(array(range(N)),array(distribution).mean())
plt.xlabel('N')
plt.grid(True)
plt.show()

It gives me the error in the title in the line where i do the plot.
Also,if there is another ,more pythonic way of doing this i’ll appreciate it.

Thank you.

Answer 1

import scipy
import matplotlib.pyplot as plt

Ns=[10**i for i in range(1,7)]
means=[scipy.random.uniform(0,1,size=N).mean() for N in Ns]

plt.semilogx(Ns,means)
plt.xlabel('N')
plt.grid(True)
plt.show()

1. As has already been mentioned, distribution is a list of arrays,
   with the inner arrays having different shapes. You can’t form a numpy
   array out of such an object by calling np.array(distribution).
2. At least for plotting purposes, you don’t need to save the entire
   distribution. Just compute and store the means. A succinct way to do
   that is to use a list comprehension.
3. Don’t use from module import * in scripts. It makes it hard
   to trace where variables come from. The from module import * was
   made (mainly) for use in interactive sessions, but generally not recommended for scripts.