Extracting wrapped column data

For a special case with the known wrap_line number and the matching timestamps:

p1 = np.loadtxt(file_name, max_rows=wrap_line-1)
p2 = np.loadtxt(file_name, skiprows=wrap_line, usecols=[1,2])
p = np.concatenate((p1,p2),axis=1)

I have created a sample file and tried the simulated the same situation,

Input File:

0.0 1.23 2.34 3.45 4.56
↑
0.0 5.67 6.78
0.1 2.34 3.45 4.56 5.67
↑
0.1 6.78 7.89
0.2 3.45 4.56 5.67 6.78
↑
0.2 7.89 8.90
0.3 4.56 5.67 6.78 7.89
↑
0.3 8.90 9.01

Python code:

import numpy as np


def load_wrapped_data(filename, num_columns):
    data = []
    current_row = []
    time = None

    with open(filename, 'r') as file:
        for line in file:
            values = line.strip().split()

            if len(values) == 1 and values[0] == '↑':
                continue

            if len(current_row) == 0:
                time = float(values[0])
                current_row.extend(map(float, values[1:]))
            else:
                current_row.extend(map(float, values[1:]))

            if len(current_row) == num_columns - 1:
                data.append([time] + current_row)
                current_row = []
                time = None

    return np.array(data)


filename = 'temp_59324.dat'
num_columns = 7

data = load_wrapped_data(filename, num_columns)

print(data)

This gives the below output,

[[0.   1.23 2.34 3.45 4.56 5.67 6.78]
 [0.1  2.34 3.45 4.56 5.67 6.78 7.89]
 [0.2  3.45 4.56 5.67 6.78 7.89 8.9 ]
 [0.3  4.56 5.67 6.78 7.89 8.9  9.01]]