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import math
def calculate_standard_error(window):
n = len(window)
if n == 0:
return 0
mean = sum(window) / n
variance = sum((x - mean) ** 2 for x in window) / n
std_dev = math.sqrt(variance)
return std_dev / math.sqrt(n)
def sliding_window_spikes(measurements, measurementsLength, m, tolerance):
if m > measurementsLength or m == 0:
return 0
sum_indices = 0
for i in range(measurementsLength - m + 1):
window = measurements[i:i + m]
se = calculate_standard_error(window)
if se > tolerance:
sum_indices += (i + 1) # 1-based index
return sum_indices
+1
Soti round 2 Code done ✅👨💻
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