def test_show_vispy():
"""Some basic tests of show_vispy"""
if has_matplotlib():
n = 200
t = np.arange(n)
noise = np.random.RandomState(0).randn(n)
# Need, image, markers, line, axes, figure
plt.figure()
ax = plt.subplot(211)
ax.imshow(read_png(load_data_file('pyplot/logo.png')))
ax = plt.subplot(212)
ax.plot(t, noise, 'ko-')
plt.draw()
canvases = plt.show()
canvases[0].close()
else:
assert_raises(ImportError, plt.show)
noise = np.random.RandomState(0).randn(n)
signal = tone + noise
magnitude = np.abs(np.fft.fft(signal))
freqs = np.fft.fftfreq(n, 1. / fs)
flim = n // 2
# Signal
fig = plt.figure()
ax = plt.subplot(311)
ax.imshow(read_png(load_data_file('pyplot/logo.png')))
ax = plt.subplot(312)
ax.plot(t, signal, 'k-')
# Frequency content
ax = plt.subplot(313)
idx = np.argmax(magnitude[:flim])
ax.text(freqs[idx], magnitude[idx], 'Max: %s Hz' % freqs[idx],
verticalalignment='top')
ax.plot(freqs[:flim], magnitude[:flim], 'r-o')
plt.draw()
# NOTE: show() has currently been overwritten to convert to vispy format, so:
# 1. It must be called to show the results, and
# 2. Any plotting commands executed after this will not take effect.
# We are working to remove this limitation.
if __name__ == '__main__':
fig.show(True)
freqs = np.fft.fftfreq(n, 1. / fs)
flim = n // 2
# Signal
fig = plt.figure()
ax = plt.subplot(311)
ax.imshow(read_png(load_data_file('pyplot/logo.png')))
ax = plt.subplot(312)
ax.plot(t, signal, 'k-')
# Frequency content
ax = plt.subplot(313)
idx = np.argmax(magnitude[:flim])
ax.text(freqs[idx],
magnitude[idx],
'Max: %s Hz' % freqs[idx],
verticalalignment='top')
ax.plot(freqs[:flim], magnitude[:flim], 'k-o')
plt.draw()
# NOTE: show() has currently been overwritten to convert to vispy format, so:
# 1. It must be called to show the results, and
# 2. Any plotting commands executed after this will not take effect.
# We are working to remove this limitation.
block = False if sys.flags.interactive == 0 else True
if __name__ == '__main__':
plt.show(block)
#==============================================================================
k_bin = n_bins_FFT/2 # select middle FFT bin to display
fig3 = plt.figure(3)
ax3 = fig3.add_subplot(111)
ax3.plot(freqs, 20*log10(Pxx[:,k_bin]))
ax3.set_xlabel(f_label)
ax3.set_ylabel(H_label)
ax3.set_title(r'$|H(e^{j 2 \pi f / f_S},\, t)|$ bei $t=%0.1f$ s' %(bins[k_bin]))
ax3.set_ylim([DB_MIN, DB_MAX])
ax3.set_xlim([0,rate_o/2])
ax3.grid(True)
# fig3.tight_layout()
#-------------------------------------------
mem.append(memory_usage()) # 3
print("... plotted in %0.2f s using %0.2f MB" %((time.time()-t2), mem[-1]))
print("... total time: %0.2f s" %(time.time()-t0))
if VISPY: plt.draw()
else: plt.show()
# NOTE: show() has currently been overwritten to convert to vispy format, so:
# 1. It must be called to show the results, and
# 2. Any plotting commands executed after this will not take effect.
# We are working to remove this limitation.
# Missing: plt.legend()
# plt.tight_layout()
# plt.specgram()
if __name__ == '__main__':
fig1.show(True)
