Sensor Data Noise Filtering | Dataford Interview Questions

Write a function that processes a stream of numerical sensor data and filters out noise using basic mathematical algorithms such as modulus math or moving averages.

Implement filter_sensor_noise(data, window_size, threshold). Return a new list where each reading that differs from the average of the previous up to window_size filtered readings by more than threshold is replaced by that average; otherwise, retain the reading. The first reading has no prior average and is retained unchanged. Process readings in order without changing the input list.

Constraints

1 <= data.length <= 100000
1 <= window_size <= data.length
0 <= threshold
-1000000000 <= data[i] <= 1000000000
Readings and output values may be integers or floating-point numbers

Function Signature

def filter_sensor_noise(data, window_size, threshold):

Your question is Sensor Data Noise Filtering. Start with the requirements in the Question tab.

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Problem

Write a function that processes a stream of numerical sensor data and filters out noise using basic mathematical algorithms such as modulus math or moving averages.

Constraints

1 <= data.length <= 100000
1 <= window_size <= data.length
0 <= threshold
-1000000000 <= data[i] <= 1000000000
Readings and output values may be integers or floating-point numbers

Function Signature

def filter_sensor_noise(data, window_size, threshold):

Your question is Sensor Data Noise Filtering. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.