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How to improve efficiency of this while loop?

I am trying to write a while loop which would iterate 50 times and take the value of each element from a large dataset. Each time it checks for the equality of the sum of the elements of the current row with the sum of the previous row. If the difference is less than a chosen tolerance, then it makes a change, if not the change isn’t made. I have a strong suspicion that this could be more efficient. Can anyone help me out here?
There are four parameters to the problem, tolerance, delay, speed and iterations.
I know that currently I can get something that works but it is very inefficient.
Any help would be greatly appreciated.
import numpy as np
import time
import random
import datetime

tol = 1.0E-10 # tolerance for matching
time_delay = 10 # delay to wait before changing the variable’s value (seconds)
time_loop = 50 # time to repeat loop 50 times
time_end = 5 # end time

random.seed()
t = np.array([random.rand(50) for i in range(50)])
print(t)
x = sum(t[1::2])
print(x)
for i in range(50):
x = sum(t[1::2])
if x — x[i-1] > tol:
x[i-1] = x — 1.0E-10 # tolerance for matching
x[i] = x + 1.0E-10 # tolerance for matching
x = x + 1.0E-10
y = sum(t[1::2])
z = x — y
if z > tol:
y = y + 1.0E-10

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What is the source code for using JSON.parse in Jquery Mobile?

I tried searching for this on google to see if anyone has already created a parser for this yet. I will create one if nobody does.
I got the code to help parse the API response from the JSON.parse function I am using from the following web page

When I use this code, my drop down list is not populated
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