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)))
def peak_impose(ax, frequency, peaklist):
x = list(range(len(peaklist)))
ax2 = ax.twinx()
gf.std_graph(ax2, frequency[x], peaklist, c='b')
peaksdex = peak_assign(peaklist)
gf.button_grapher(ax2, frequency, peaksdex, peaklist)
def plotdots(ax, i, detect):
colored = 'r'
if detect:
colored = 'b'
gf.std_graph(ax, [i, i + 1], [0, 0], c=colored, lw=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',
label='Power')
# ax.axvspan(4, 21, alpha=0.5, color='b')
# ax.axvspan(30, 51, alpha=0.5, color='b')
# ax.axvspan(65, 72, alpha=0.5, color='b')
# ax.axvspan(3, 16, alpha=0.5, color='b')
# ax.axvspan(33, 54, alpha=0.5, color='b')
# ax.axvspan(11, 36, alpha=0.5, color='b')
# ax.axvspan(55, 72, alpha=0.5, color='b')
ax2 = gf.get_twinx(ax, ylabel='Matches')
gf.std_graph(ax2, np.arange(len(result)), result[:, 3], c='r', label='Matches')
ax.legend(loc=2)
ax2.legend(loc=1)
gf.show()
background = sys.argv[1]
audio = sys.argv[2]
fs = 44100
if len(sys.argv) > 3:
fs = int(sys.argv[3])
# Build image
background = aa.load_npy(background)
audio = aa.load_npy(audio)
ax = gf.init_image()
# Set double scale
ax2 = ax.twinx()
# Run spectrum analysis
freq, curve = aa.spectrum(background, fs)
_, bluecurve = aa.spectrum(audio, fs)
# bluecurve = bluecurve * curve[2]/bluecurve[2]
snratio = bluecurve / curve
# Graph ax
gf.semi_graph(ax, freq, curve, label='background')
gf.semi_graph(ax, freq, bluecurve, 'b', 'recording')
gf.std_graph(ax2, freq, snratio, label='S/N ratio')
maxdex = aa.max_range(bluecurve, 10)
print_maxdex(freq, snratio, maxdex)
gf.pin_grapher(ax, freq, maxdex, curve, bluecurve)
ax.legend(loc=2)
ax2.legend(loc=0)
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)))
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()
