generating random numbers between two numbers-CodePudding

Is it possible to generate random numbers that are almost equally spaced which shouldnot be exactly same as numpy.linspace output

I look into the numpy.random.uniform function but it doesnot give the required results.

Moreover the the summation of the values generated by the function should be same as the summation of the values generated by numpy.linspace function.

code

import random
import numpy as np
random.seed(42)
data=np.random.uniform(2,4,10)
print(data)

CodePudding user response：

Maybe this trick by combining numpy.linspace and numpy.random.uniform and random choice two indexes and increase one of them and decrease other help you: (You can change size=10, threshold=0.1 for how random numbers are bigger or smaller)

import numpy as np
size = 10
theroshold = 0.1
r = np.linspace(2,4,size) # r.sum()=30
# array([2.        , 2.22222222, 2.44444444, 2.66666667, 2.88888889,
#        3.11111111, 3.33333333, 3.55555556, 3.77777778, 4.        ])

c = np.random.uniform(0,theroshold,size)
# array([0.02246768, 0.08661081, 0.0932445 , 0.00360563, 0.06539992,
#        0.0107167 , 0.06490493, 0.0558159 , 0.00268924, 0.00070247])

s = np.random.choice(range(size), size 1)
# array([5, 5, 8, 3, 6, 4, 1, 8, 7, 1, 7])

for idx, (i,j) in enumerate(zip(s, s[1:])):
    r[i]  = c[idx]
    r[j] -= c[idx]

print(r)
print(r.sum())

Output:

[2.         2.27442369 2.44444444 2.5770278  2.83420567 3.19772192
 3.39512762 3.50172642 3.77532244 4.        ]

30

CodePudding user response：

You might consider drawing random samples around the output of numpy.linspace. Setting these numbers as the mean of the normal distribution and setting the variance not too high would generate numbers close to the output of numpy.linspace. For example,

>>> import numpy as np
>>> exact_numbers = np.linspace(2.0, 10.0, num=5)
>>> exact_numbers
array([ 2.,  4.,  6.,  8., 10.])
>>> approximate_numbers = np.random.normal(exact_numbers, np.ones(5) * 0.1)
>>> approximate_numbers
array([2.12950013, 3.9804745 , 5.80670316, 8.07868932, 9.85288221])