I want to create, pseudo-randomly, an array of transaction values from half-open intervals, for example [1,5), [5,10), [10,25)
and so on. Each number in the interval has the same chance to be picked, but I want to adjust the probability of getting some intervals over others. The flow should look like this way:
1: Pick any of the defined intervals > Pick a random number in the interval > Append number in array
2: Pick any of the defined intervals > Pick a random number in the interval > Append number in array
...
n: Pick any of the defined intervals > Pick a random number in the interval > Append number in array
My code is:
import numpy as np
# set interval limits
a,b,c,d,e,f,g,h,i,j = 1,5,10,25,50,100,200,300,500,1000
# start picking random numbers
np.random.seed(33)
trx_value = np.random.choice([np.random.uniform(a,b),
np.random.uniform(b,c),
np.random.uniform(c,d),
np.random.uniform(d,e),
np.random.uniform(e,f),
np.random.uniform(f,g),
np.random.uniform(g,h),
np.random.uniform(h,i),
np.random.uniform(i,j)], 20,
p=[0.1, 0.15, 0.2, 0.2, 0.15, 0.1, 0.05, 0.03, 0.02])
trx_value
It seems that it is working in a different way, as the result is not displaying the uniqueness in the values I was expecting:
> array([ 8.22611761, 8.22611761, 127.05325134, 8.22611761,
> 266.53172436, 35.43526485, 35.43526485, 88.57366253,
> 127.05325134, 12.38946805, 266.53172436, 127.05325134,
> 12.38946805, 35.43526485, 127.05325134, 12.38946805,
> 266.53172436, 8.22611761])
It seems it is doing something like this:
1: For each interval, pick a random number > Store this number in a pool
2: Pick a random number from the pool > Append number in array
...
n: Pick a random number from the pool > Append number in array
I am sure it is a thinking-problem, but I want to know if this is possible without using a for
loop
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