Add scripts and reqs

dial.py

+import matplotlib.pyplot as plt
+import mplcursors
+import numpy as np
+from numpy.fft import fft
+from scipy.io import wavfile
+
+
+def PowerSpectrum(y):
+    Y = np.abs(fft(y))
+    PS = Y[0:len(Y) // 2]
+    df = fs / len(Y)
+    f = np.arange(0, len(PS)) * df
+    return f, PS
+
+
+plt.clf()
+
+fs, data = wavfile.read('dial.wav')
+
+fig, axs = plt.subplots(2, num=1)
+
+y = data[:, 0]
+dt = 1 / fs
+t = np.arange(0, len(y)) * dt
+
+axs[0].plot(t, y)
+axs[0].set_xlabel('t [s]')
+axs[0].set_ylabel('y')
+
+limits = [0.1, 0.45, 0.8, 1.2]
+
+ss = limits[2]
+se = limits[3]
+
+to = t[(t > ss) & (t < se)]
+yo = y[(t > ss) & (t < se)]
+
+axs[0].plot(to, yo)
+
+f, PS = PowerSpectrum(y)
+
+fo, PSo = PowerSpectrum(yo)
+
+axs[1].plot(f, PS)
+axs[1].set_xlabel('f [Hz]')
+axs[1].set_ylabel('Y abs')
+axs[1].set_xlim(0, 1500)
+
+axs[1].plot(fo, PSo)
+
+plt.show()
+
+mplcursors.cursor()

fft.py

+import matplotlib.pyplot as plt
+import numpy as np
+from numpy.fft import fft, fftshift
+
+plt.clf()
+
+fs = 10  # sampling frequency
+
+dt = 1 / fs
+
+t = np.arange(0, 5, dt)  # start, end, step
+y = np.cos(2 * np.pi * 1 * t)
+
+t1 = np.arange(0, 5, dt / 1000)  # start, end, step
+y1 = np.cos(2 * np.pi * 9 * t1)
+
+N = len(y)
+
+fig, axs = plt.subplots(2, num=1)
+
+axs[0].plot(t, y, ':')
+axs[0].stem(t, y, '.')
+axs[0].set_xlabel('t [s]')
+axs[0].set_ylabel('y')
+axs[0].grid()
+
+axs[0].plot(t1, y1, 'r')
+
+Y = fftshift(fft(y) / N)
+df = fs / len(Y)
+f = np.arange(-fs / 2, fs / 2, df)
+
+axs[1].stem(f, np.abs(Y))
+axs[1].set_xlabel('f [Hz]')
+axs[1].set_ylabel('Y abs')
+axs[1].grid()
+
+# axs[1].stem(f, Y.real)
+# axs[1].set_xlabel('f [Hz]')
+# axs[1].set_ylabel('Y real')
+# axs[1].grid()
+
+# axs[2].stem(f, Y.imag)
+# axs[2].set_xlabel('f [Hz]')
+# axs[2].set_ylabel('Y imag')
+# axs[2].grid()
+
+fig.show()

requirements.txt

+numpy==1.19.4
+scipy==1.5.4
+matplotlib==3.3.2
+mplcursors==0.3