example_3.py

import numpy as np
import matplotlib.pyplot as plt
import csv
from datetime import datetime
from utilities import create_folder
from plot_utilities import set_font_size

save_folder = "./images/example_3/"
create_folder(save_folder)

set_font_size(18)

# Load data from csv file
csv_path = "data/GCMT_Catalog.csv"

# Example line from the csv file:
# ,Lon,Lat,Depth,Time,Mag
# 0,-177.64,-28.61,59000.0,1976-01-01T01:29:39.600000Z,7.25
with open(csv_path, newline="") as csvfile:
    reader = csv.DictReader(csvfile)
    time = []
    magnitude = []
    for row in reader:
        time_str = row["Time"]
        time_float = datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S.%f%z").timestamp()
        time.append(time_float)
        magnitude.append(float(row["Mag"]))
time = np.array(time)
time_0 = time[0]
time -= time_0  # Normalize time to start from zero
# time /= 365.25 * 24 * 3600  # Convert time to years
magnitude = np.array(magnitude)


def time_to_string(time_float):
    time_float += time_0  # Add back the original time offset
    dt = datetime.fromtimestamp(time_float)
    return dt.strftime("%Y-%m-%d %H:%M:%S")


assert len(time) == len(magnitude)
n = len(time)
n = n // 20
time = time[:n]
magnitude = magnitude[:n]
print(f"Number of samples: {n}")
print(f"Time range: {time_to_string(time[0])} to {time_to_string(time[-1])}")

plt.figure()
plt.plot(time, magnitude, marker="o", linestyle="-")
plt.xlabel("Time (seconds)")
plt.ylabel("$s$")
plt.tight_layout()
plt.savefig(f"{save_folder}/signal.pdf")