def plot_spectrum(f,
p,
cen=0.0,
span=None,
dbm=False,
filename=None,
title='Spectrum'):
"""Plot average power in dBm per Hz"""
if not span:
mask = (f != 0) | (f == 0)
else:
mask = (f <= span / 2) & (f >= -span / 2)
if dbm:
plt.plot(f[mask], IQBase.get_dbm(p[mask]))
else:
plt.plot(f[mask], p[mask])
plt.xlabel("Delta f [Hz] @ {}".format(get_eng_notation(cen, 'Hz')))
plt.title(title)
if dbm:
plt.ylabel('Power Spectral Density [dBm/Hz]')
else:
plt.ylabel('Power Spectral Density')
plt.grid(True)
if filename is not None:
plt.savefig(filename + '.png') # , bbox_inches='tight')
plt.close()
def plot_spectrogram(xx, yy, zz, cen=0.0, cmap=cm.jet, dpi=300, dbm=False, filename=None, title='Spectrogram'):
"""
Plot the calculated spectrogram
:param xx:
:param yy:
:param zz:
:param cen:
:return:
"""
delta_f = np.abs(np.abs(xx[0, 1]) - np.abs(xx[0, 0]))
delta_t = np.abs(np.abs(yy[1, 0]) - np.abs(yy[0, 0]))
if dbm:
sp = plt.pcolormesh(xx, yy, IQBase.get_dbm(zz), cmap=cmap)
else:
sp = plt.pcolormesh(xx, yy, zz, cmap=cmap)
cb = plt.colorbar(sp)
plt.xlabel(
"Delta f @ {} (resolution = {})".format(get_eng_notation(cen, unit='Hz'), get_eng_notation(delta_f, unit='Hz')))
plt.ylabel('Time [sec] (resolution = {})'.format(
get_eng_notation(delta_t, 's')))
plt.title(title)
if dbm:
cb.set_label('Power Spectral Density [dBm/Hz]')
else:
cb.set_label('Power Spectral Density')
if filename is not None:
plt.savefig(filename + '.png', dpi=dpi, bbox_inches='tight')
plt.close()
def write_spectrum_to_csv(ff, pp, filename, center=0):
a = np.concatenate((ff, pp, IQBase.get_dbm(pp)))
b = np.reshape(a, (3, -1)).T
np.savetxt(
filename,
b,
header='Delta f [Hz] @ {:.2e} [Hz]|Power [W]|Power [dBm]'.format(
center),
delimiter='|')
def plot_frame_power(yy, frame_power):
"""
Plot frame power, i.e. trapezoid along each time frame
:param yy:
:param frame_power:
:return:
"""
plt.plot(yy[:, 0], IQBase.get_dbm(frame_power))
plt.ylabel('Power [dBm]')
plt.xlabel('Time [sec]')
plt.title('Frame power')
def plot_frame_power(yy, frame_power):
"""
Plot frame power, i.e. trapezoid along each time frame
:param yy:
:param frame_power:
:return:
"""
plt.plot(yy[:, 0], IQBase.get_dbm(frame_power))
plt.ylabel('Power [dBm]')
plt.xlabel('Time [sec]')
plt.title('Frame power')
def plot_dbm_per_hz(f, p, cen=0.0, span=None, filename='', to_file=False):
"""Plot average power in dBm per Hz"""
if not span:
mask = (f != 0) | (f == 0)
else:
mask = (f <= span / 2) & (f >= -span / 2)
plt.plot(f[mask], IQBase.get_dbm(p[mask]))
plt.xlabel("Delta f [Hz] @ {}".format(get_eng_notation(cen, 'Hz')))
plt.title(filename)
plt.ylabel("Power Spectral Density [dBm/Hz]")
plt.grid(True)
if to_file:
plt.savefig(filename)
plt.close()
def plot_dbm_per_hz(f, p, cen=0.0, span=None, filename='', to_file=False):
"""Plot average power in dBm per Hz"""
if not span:
mask = (f != 0) | (f == 0)
else:
mask = (f <= span / 2) & (f >= -span / 2)
plt.plot(f[mask], IQBase.get_dbm(p[mask]))
plt.xlabel("Delta f [Hz] @ {}".format(get_eng_notation(cen, 'Hz')))
plt.title(filename)
plt.ylabel("Power Spectral Density [dBm/Hz]")
plt.grid(True)
if to_file:
plt.savefig(filename)
plt.close()
def plot_spectrogram(xx,
yy,
zz,
cen=0.0,
cmap=cm.jet,
dpi=300,
dbm=False,
filename=None,
title='Spectrogram'):
"""
Plot the calculated spectrogram
:param xx:
:param yy:
:param zz:
:param cen:
:return:
"""
delta_f = np.abs(np.abs(xx[0, 1]) - np.abs(xx[0, 0]))
delta_t = np.abs(np.abs(yy[1, 0]) - np.abs(yy[0, 0]))
if dbm:
sp = plt.pcolormesh(xx, yy, IQBase.get_dbm(zz), cmap=cmap)
else:
sp = plt.pcolormesh(xx, yy, zz, cmap=cmap)
cb = plt.colorbar(sp)
plt.xlabel("Delta f @ {} (resolution = {})".format(
get_eng_notation(cen, unit='Hz'), get_eng_notation(delta_f,
unit='Hz')))
plt.ylabel('Time [sec] (resolution = {})'.format(
get_eng_notation(delta_t, 's')))
plt.title(title)
if dbm:
cb.set_label('Power Spectral Density [dBm/Hz]')
else:
cb.set_label('Power Spectral Density')
if filename is not None:
plt.savefig(filename + '.png', dpi=dpi, bbox_inches='tight')
plt.close()