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Calculating time between high state

In python I want calculations of high / low states of a signal in chunks of a given size (samples_to_process).

The two required calculations are number index between rising edges (length_between_high_states) and number of index's the signal is high for (high_state_length).

The calculations must be stateful across chunnks.

example

Lets take a small reproduceable example:

data = np.array([0,1,1,0,1,1,1,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,0])

If this array is read 8 items at a time, the first iteration is

high_state_length = 2 
length_between_high_states = 4

then

high_state_length = 3
length_between_high_states = 9

I believe I have the correct logic to read in the first state of the array and signal changes, but subsequent state changes in the signal and carrying the state across chunks are not yet implemented:

import numpy as np
#total array size = 25
data = np.array([0,1,1,0,1,1,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,0])
#size of samples of data array to process in each read
samples_to_process = 8
samples = np.zeros(samples_to_process, dtype=np.complex64)
threshold = 0.5

index = 0
#slice(index, index+samples_to_process)
for index in range(0, data.size, samples_to_process):
    samples=data[index:index+samples_to_process]
    print(samples)
    while True
        start_index = np.argmax(samples > threshold)
        stop_index = np.argmax(samples[start_index:] < threshold) + start_index
        next_start_index = np.argmax(samples[stop_index:] > threshold) + stop_index
        length_between_high_states = next_start_index - start_index
        high_state_length = stop_index - start_index
        # how to calculate remainder state and pass into next itr
        start_index = next_start_index
        print("next loop")

The question is how to pass the signal state between iterations to be included in subsequent calculations.



source https://stackoverflow.com/questions/77592555/calculating-time-between-high-state

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