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NumPy can compute the sum of numbers that are in the vicinity of a given number using the numpy.sum function along with boolean indexing. Here is an example:

import numpy as np

# generate an array of random numbers
arr = np.random.rand(10)

# choose a central number
center = 0.5

# define the vicinity range
vicinity = 0.1

# boolean indexing to select numbers within the vicinity range
selected = (arr >= center - vicinity) & (arr <= center + vicinity)

# compute the sum of selected numbers
sum = np.sum(arr[selected])

print(sum)

In this example, we first generate an array arr of 10 random numbers. We then choose a center number and define a vicinity range around it. We use boolean indexing to select the numbers in arr that are within the vicinity range of the center number. Finally, we use the numpy.sum function to compute the sum of the selected numbers.