import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.ticker import AutoMinorLocator
import numpy as np
from scipy.interpolate import interp1d, CubicSpline
from scipy.optimize import curve_fit
from numpy.polynomial import Polynomial


df = pd.read_csv("timedata_500.csv")
print(df)



# построение графика
# fig, ax = plt.subplots(figsize=(8, 5))




# ax.set_title("График зависимости фазы от частоты(сх5)")
# ax.set_xlabel("v, Hz")        
# ax.set_ylabel("phi, rad")
# ax.grid(which="major", linewidth=1.5)
# ax.grid(which="minor", color="gray", linewidth=0.5)
# ax.xaxis.set_minor_locator(AutoMinorLocator())
# ax.yaxis.set_minor_locator(AutoMinorLocator())
# ax.axhline(y=0, color='black', linewidth=1, linestyle='-', alpha=0.7)  # Ось X (U=0)
# ax.axvline(x=0, color='black', linewidth=1, linestyle='-', alpha=0.7)  # Ось Y (B=0)
# ax.plot(1, 0, ">k", transform=ax.get_yaxis_transform(), clip_on=False)
# ax.plot(0, 1, "^k", transform=ax.get_xaxis_transform(), clip_on=False)
# ax.legend()
# plt.savefig('graphics\zadanie3.png', dpi=200)
# plt.savefig('graphics\zadanie3.eps', dpi=200)
# plt.show()