fig = pl.figure(figsize=(24,18)) # x(t) tao = 0.5 dt = 0.001 Ts = dt fs = 1/Ts t = np.arange(0,tao,dt) x_t = np.sin(2*np.pi*50*t)+np.sin(2*np.pi*100*t) ax1 = fig.add_subplot(3,2,1) ax1.stem(t,x_t) ax1.set_xlabel('t') ax1.set_ylabel('x(t)') ax1.set_title('x(t)') ax1.set_xlim([0,0.05]) # x(f) N = dsp.get_fft_len(x_t) x_f = np.fft.fftshift(np.abs(np.fft.fft(x_t,n=N))) f = np.linspace(-fs/2,fs/2,N) ax2 = fig.add_subplot(3,2,2) ax2.stem(f,x_f) ax2.set_xlabel('f') ax2.set_ylabel('x(f)') ax2.set_title('x(f)') # ax2.set_xlim([-120,120]) # x'(t) t_intp = np.linspace(0,max(t),len(t)*L,endpoint='False') x_intp_t = np.asarray([]) for i in range(len(x_t)): temp = np.asarray([x_t[i],0,0,0]) x_intp_t = np.hstack([x_intp_t,temp]) ax3 = fig.add_subplot(3,2,3)
import numpy as np import matplotlib.pylab as pl import scipy.signal as signal import dsp L = 4 fig = pl.figure(figsize=(12,9)) # x(t) tao = 0.5 dt = 0.001 Ts = dt fs = 1/Ts t = np.arange(0,tao,dt) x_t = np.sin(2*np.pi*50*t)+np.sin(2*np.pi*100*t) ax1 = fig.add_subplot(1,2,1) ax1.stem(t,x_t) ax1.set_xlabel('t') ax1.set_ylabel('x(t)') ax1.set_title('x(t)') ax1.set_xlim([0,0.05]) # x(f) N = dsp.get_fft_len(x_t) x_f = np.fft.fftshift(np.abs(np.fft.fft(x_t,n=N))) f = np.linspace(-fs/2,fs/2,N) ax2 = fig.add_subplot(1,2,2) ax2.stem(f,x_f) ax2.set_xlabel('f') ax2.set_ylabel('x(f)') ax2.set_title('x(f)') fig.savefig('up_1.jpg')