forked from UNN/2026-rff_mp
35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
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import pandas as pd
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import matplotlib.pyplot as plt
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from matplotlib.ticker import AutoMinorLocator
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import numpy as np
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from scipy.interpolate import interp1d, CubicSpline
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from scipy.optimize import curve_fit
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from numpy.polynomial import Polynomial
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df = pd.read_csv("timedata_500.csv")
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print(df)
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# построение графика
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# fig, ax = plt.subplots(figsize=(8, 5))
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# ax.set_title("График зависимости фазы от частоты(сх5)")
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# ax.set_xlabel("v, Hz")
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# ax.set_ylabel("phi, rad")
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# ax.grid(which="major", linewidth=1.5)
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# ax.grid(which="minor", color="gray", linewidth=0.5)
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# ax.xaxis.set_minor_locator(AutoMinorLocator())
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# ax.yaxis.set_minor_locator(AutoMinorLocator())
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# ax.axhline(y=0, color='black', linewidth=1, linestyle='-', alpha=0.7) # Ось X (U=0)
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# ax.axvline(x=0, color='black', linewidth=1, linestyle='-', alpha=0.7) # Ось Y (B=0)
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# ax.plot(1, 0, ">k", transform=ax.get_yaxis_transform(), clip_on=False)
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# ax.plot(0, 1, "^k", transform=ax.get_xaxis_transform(), clip_on=False)
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# ax.legend()
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# plt.savefig('graphics\zadanie3.png', dpi=200)
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# plt.savefig('graphics\zadanie3.eps', dpi=200)
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# plt.show()
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