検索: fill_between matplot
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matplotlib.collections — Matplotlib 3.6.0 documentation
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# https://helve-blog.com/posts/python/numpy-fast-fourier-transform/
# https://sabopy.com/py/matplotlib-110/
import numpy as np
import matplotlib.pyplot as plt
N = 1024 # サンプル数
dt = 0.001 # サンプリング周期 [s]
f1, f2 = 50, 120 # 周波数 [Hz]
def func(t):
return 1.5*np.sin(2*np.pi*f1*t) + np.sin(2*np.pi*f2*t) + 3 # 信号
t = np.arange(0, N*dt, dt) # 時間 [s]
print(t)
#x = 1.5*np.sin(2*np.pi*f1*t) + np.sin(2*np.pi*f2*t) + 3 # 信号
x =func(t)
fig, ax = plt.subplots()
ax.plot(t, x)
# ax.set_xlim(0, 0.1)
ax.set_xlabel("Time [s]")
ax.set_ylabel("Signal")
ax.grid()
#t_ = np.arange(0.04, 0.6, dt)
#ax.fill_between(t_,func(t_),fc="0.8",ec="0.5")
plt.show()
F = np.fft.fft(x) # 変換結果
freq = np.fft.fftfreq(N, d=dt) # 周波数
fig, ax = plt.subplots(nrows=3, sharex=True, figsize=(6,6))
ax[0].plot(F.real, label="Real part")
ax[0].legend()
ax[1].plot(F.imag, label="Imaginary part")
ax[1].legend()
ax[2].plot(freq, label="Frequency")
ax[2].legend()
ax[2].set_xlabel("Number of data")
plt.show()
Amp = np.abs(F/(N/2)) # 振幅
fig, ax = plt.subplots()
ax.plot(freq[1:int(N/2)], Amp[1:int(N/2)])
ax.set_xlabel("Freqency [Hz]")
ax.set_ylabel("Amplitude")
ax.grid()
#ax.fill_between(freq[1:int(N/2)],Amp[1:int(N/2)])
ax.fill_between(freq[5:50],Amp[5:50],fc="tab:blue")
plt.show()
もしくはstemをつかう。
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