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()
