def runfromfft(f, psd): ax = gf.init_image() gf.semi_graph(ax, f, psd) maxdex = aa.max_range(psd, 20) # gf.button_grapher(ax, f, maxdex, psd) peaklist = aa.peak_map(psd) aa.peak_impose(ax, f, peaklist) plt.show()
def runfromfft_graph(f, psd): peaklist = aa.peak_map(psd) peaksdex = aa.peak_assign(peaklist) output = guesswork(f, psd, peaklist, peaksdex) ax = gf.init_image(ylabel='POWER') gf.std_graph(ax, output[:, 0], output[:, 1]) ax2 = gf.get_twinx(ax) gf.std_graph(ax2, output[:, 0], output[:, 2], c='r') plt.show() print(aa.print_identify(aa.identify(output)))
peaksdex = peak_assign(peaklist) gf.button_grapher(ax2, frequency, peaksdex, peaklist) def runfromfft(f, psd): ax = gf.init_image() gf.semi_graph(ax, f, psd) maxdex = aa.max_range(psd, 20) # gf.button_grapher(ax, f, maxdex, psd) peaklist = aa.peak_map(psd) aa.peak_impose(ax, f, peaklist) plt.show() if __name__ == '__main__': filename = sys.argv[1] bandpass = [] if len(sys.argv) > 3: lowerbound = int(sys.argv[2]) upperbound = int(sys.argv[3]) bandpass = [lowerbound, upperbound] audio = aa.load_npy(filename) bandpass = [80, 10000] f, psd = aa.spectrum(audio, bandpass=bandpass) ax = gf.init_image() gf.semi_graph(ax, f, psd, label=filename) # maxdex = aa.max_range(psd, 20) # peaklist = aa.peak_map(psd) # plt.savefig('%s.png' % filename.split('.')[0]) plt.show()
result.append(intervaldata) result = np.asarray(result) print(result) def plotdots(ax, i, detect): colored = 'r' if detect: colored = 'b' gf.std_graph(ax, [i, i + 1], [0, 0], c=colored, lw=3) print(np.average(result[:, 2]) - 120) print(np.average(result[:, 3])) ax = gf.init_image(xlabel='Intervals', ylabel='Power Rating', title='') ax.set_ylim(-10, 200) i = 0 tot = 0 for each in result: print(each) print(aa.detect(each)) if aa.detect(each): tot += 1 plotdots(ax, i, aa.detect(each)) i += 1 print(tot) gf.std_graph(ax, np.arange(len(result)), result[:, 2] - 120, c='g',
def runfromfft_graph(f, psd): peaklist = aa.peak_map(psd) peaksdex = aa.peak_assign(peaklist) output = guesswork(f, psd, peaklist, peaksdex) ax = gf.init_image(ylabel='POWER') gf.std_graph(ax, output[:, 0], output[:, 1]) ax2 = gf.get_twinx(ax) gf.std_graph(ax2, output[:, 0], output[:, 2], c='r') plt.show() print(aa.print_identify(aa.identify(output))) if __name__ == '__main__': filename = sys.argv[1] parts = 1 if len(sys.argv) > 2: parts = int(sys.argv[2]) au = aa.load_npy(filename) # Get the shorter audio pack audiolist = np.array_split(au, parts) for audio in audiolist: output = run(audio) # for each in output: # print(each) ax = gf.init_image(ylabel='POWER') gf.std_graph(ax, output[:, 0], output[:, 1] - 120) ax2 = gf.get_twinx(ax) gf.std_graph(ax2, output[:, 0], output[:, 2], c='r') plt.show()