import os
import pandas as pd

# Path settings
input_file = r'G:\Users\Chipistil\Desktop\High-throughput-T2NP-Memristor-based-Dual-clock-edge-sampling-TRNG\Data Conversion\tdelay+tr.txt'
output_file = r'G:\Users\Chipistil\Desktop\High-throughput-T2NP-Memristor-based-Dual-clock-edge-sampling-TRNG\Data Conversion\tr.xlsx'

data = []
with open(input_file, 'r') as f:
    for line in f:
        line = line.strip()
        if line:
            cols = line.split()
            if len(cols) >= 3:
                col1 = round(float(cols[0]), 4)
                col2 = round(float(cols[1]), 4)
                col3 = round(float(cols[2]), 4)
                data.append((col1, col2, col3))

tr_list = []
n = len(data)
i = 0

def find_rg_cluster(start_idx):
    in_cluster = False
    consecutive_230 = 0
    
    for j in range(start_idx, n):
        current = data[j][2]
        
        if not in_cluster:
            if current == 2.30:
                if j + 10 <= n:
                    next_10_values = [data[k][2] for k in range(j+1, j+11)]
                    if all(val < 2.30 for val in next_10_values):
                        in_cluster = True
                        rg0 = j
                        consecutive_230 = 0
        else:
            if current == 2.30:
                consecutive_230 += 1
                if consecutive_230 >= 6:
                    cluster_end = j - consecutive_230 + 1
                    return (rg0, cluster_end), cluster_end + 1
            else:
                consecutive_230 = 0
    
    if in_cluster:
        return (rg0, n-1), n
    return None, n

def locate_key_points(start, end):
    rg0 = start
    
    rg1 = None
    for j in range(rg0 + 1, min(n, end + 1000)):
        if data[j][2] == 0.00:
            rg1 = j
            break
    
    if rg1 is None:
        return None, None
    
    t1 = (data[rg1][0] + data[rg0][0]) / 2
    
    rg2 = None
    rg3 = None
    started = False
    for j in range(rg0 + 1, min(n, end + 1000)):
        if not started:
            if data[j][1] > 2.9:
                started = True
                rg2 = j
        else:
            if data[j][1] > 2.9:
                rg2 = j
            elif data[j][1] < 0.5:
                rg3 = j
                break
    
    if rg2 is None or rg3 is None:
        return t1, None
    
    t2 = (data[rg3][0] + data[rg2][0]) / 2
    
    return t1, t2

while i < n:
    rg_range, new_i = find_rg_cluster(i)
    
    if rg_range:
        start, end = rg_range
        
        t1, t2 = locate_key_points(start, end)
        
        if all([t1, t2]):
            tr = round(t2 - t1, 4)
            tr_list.append((tr, round(t1, 4), round(t2, 4)))
        
        i = new_i
    else:
        i += 1

if tr_list:
    df = pd.DataFrame(tr_list, columns=['tr', 't1', 't2'])
    df.to_excel(output_file, index=False)
    print(f"Processing completed, found {len(tr_list)} valid tr values, written to Excel file")
else:
    print("No valid tr values found")