def key_0(self):
fig = plt.figure()
ax = plt.subplot(111)
self.current_ionogram.plot(ax=ax, overplot_digitization=False, vmin=self.vmin, vmax=self.vmax, overplot_model=False)
fname = 'Ionogram-O%d_%s.png' % (mex.orbits[float(self.current_ionogram.time)].number,
celsius.spiceet_to_utcstr(self.current_ionogram.time, fmt='C'))
plt.title(celsius.spiceet_to_utcstr(self.current_ionogram.time,
fmt='C'))
plt.savefig(fname.replace(':',''))
plt.close(fig)
def update(self):
""" This redraws the various axes """
plt.sca(self.ig_ax)
plt.cla()
if debug:
print('DEBUG: Plotting ionogram...')
alpha = 0.5
self.current_ionogram.interpolate_frequencies() # does nothing if not required
self.current_ionogram.plot(ax=self.ig_ax, colorbar=False,
vmin=self.vmin, vmax=self.vmax,
color='white', verbose=debug,
overplot_digitization=True,alpha=alpha,errors=False,
overplot_model=False, overplot_expected_ne_max=True)
if debug:
print('DEBUG: ... done')
plt.colorbar(cax=self.cbar_ax, orientation='horizontal',
ticks=mpl.ticker.MultipleLocator())
plt.sca(self.cbar_ax)
plt.xlabel(r'spec. dens. / $V^2m^{-2}Hz^{-1}$')
plt.sca(self.ig_ax)
# Plasma and cyclotron lines
if len(self.selected_plasma_lines) > 0:
extent = plt.ylim()
for v in self.selected_plasma_lines:
plt.vlines(v, extent[0], extent[1], 'red',alpha=alpha)
if len(self.selected_cyclotron_lines) > 0:
extent = plt.xlim()
for v in self.selected_cyclotron_lines:
plt.hlines(v, extent[0], extent[1], 'red',alpha=alpha)
f = self.current_ionogram.digitization.morphology_fp_local
if np.isfinite(f):
plt.vlines(
np.arange(1., 5.) * f / 1E6, plt.ylim()[0],
plt.ylim()[1],
color='red', lw=1.,alpha=alpha)
# If current digitization is invertible, do it and plot it
if self.current_ionogram.digitization:
if debug:
print('DEBUG: Inverting, computing model...')
d = self.current_ionogram.digitization
plt.sca(self.ne_ax)
plt.cla()
if d.is_invertible():
winning = d.invert()
if winning & np.all(d.density > 0.) & np.all(d.altitude > 0.):
plt.plot(d.density, d.altitude, color='k')
plt.xlim(5.E1, 5E5)
plt.ylim(0,499)
alt = np.arange(0., 499., 5.)
if self.current_ionogram.sza < 89.9:
plt.plot(self.ionospheric_model(alt,
np.deg2rad(self.current_ionogram.sza)), alt, color='green')
plt.grid()
plt.xscale('log')
plt.xlabel(r'$n_e / cm^{-3}$')
plt.ylabel('alt. / km')
fname = self.digitization_db.filename
if len(fname) > 30: fname = fname[:10] + '...' + fname[-20:]
plt.title('Database: ' + fname)
if debug:
print('DEBUG: Plotting timeseries....')
# Timeseries integrated bar
plt.sca(self.tser_ax)
plt.cla()
plt.imshow(self.tser_arr[::-1,:], vmin=self.vmin, vmax=self.vmax,
interpolation='Nearest', extent=self.extent, origin='upper',aspect='auto')
plt.xlim(self.extent[0], self.extent[1])
plt.ylim(self.extent[2], self.extent[3])
plt.ylim(0., 5.5)
plt.vlines(self.current_ionogram.time,
self.extent[2], self.extent[3], self.stored_color)
plt.hlines(self.timeseries_frequency, self.extent[0], self.extent[1],
self.stored_color, 'dashed')
plt.ylabel('f / MHz')
# Frequency bar
plt.sca(self.freq_ax)
plt.cla()
freq_extent = (self.extent[0], self.extent[1],
ais.ais_max_delay*1E3, ais.ais_min_delay*1E3)
inx = 1.0E6 * (self.current_ionogram.frequencies.shape[0] *
self.timeseries_frequency) /\
(self.current_ionogram.frequencies[-1] - self.current_ionogram.frequencies[0])
self._freq_bar_data = self.tser_arr_all[:,int(inx),:]
plt.imshow(self.tser_arr_all[:,int(inx),:], vmin=self.vmin, vmax=self.vmax,
interpolation='Nearest', extent=freq_extent, origin='upper',aspect='auto')
plt.xlim(freq_extent[0], freq_extent[1])
plt.ylim(freq_extent[2], freq_extent[3])
plt.vlines(self.current_ionogram.time,
freq_extent[2],freq_extent[3], self.stored_color)
plt.ylabel(r'$\tau_D / ms$')
title = "AISTool v%s, Orbit = %d, Ionogram=%s " % (__version__,
self.orbit, celsius.spiceet_to_utcstr(self.current_ionogram.time,
fmt='C'))
if self.browsing:
title += '[Browsing] '
if self.minimum_interaction_mode:
title += '[Quick] '
if self._digitization_saved == False:
title += 'UNSAVED '
if self.get_status() is not None:
title += '[Status = %s] ' % self.get_status()
pos, sza = mex.mso_r_lat_lon_position(float(self.current_ionogram.time),
sza=True)
title += '\nMSO: Altitude = %.1f km, Elevation = %.1f, Azimuth = %.1f deg, SZA = %.1f' % (pos[0] - mex.mars_mean_radius_km, mex.modpos(pos[1]), mex.modpos(pos[2]), sza)
pos = mex.iau_pgr_alt_lat_lon_position(float(self.current_ionogram.time))
title += '\nIAU: Altitude = %.1f km, Latitude = %.1f, Longitude = %.1f deg' % (
pos[0], pos[1], mex.modpos(pos[2]))
plt.sca(self.tser_ax)
plt.title(title)
# Message history:
if len(self._messages):
txt = ''
for i, s in enumerate(self._messages):
txt += str(i + self._message_counter) + ': ' + s + '\n'
plt.annotate(txt, (0.05, 0.995), xycoords='figure fraction',
fontsize=8, horizontalalignment='left', verticalalignment='top')
# Axis formatters need redoing after each cla()
nf = mpl.ticker.NullFormatter
loc_f = celsius.SpiceetLocator()
loc_t = celsius.SpiceetLocator()
self.freq_ax.xaxis.set_major_formatter(celsius.SpiceetFormatter(loc_f))
self.tser_ax.xaxis.set_major_formatter(nf())
self.freq_ax.xaxis.set_major_locator(loc_f)
self.tser_ax.xaxis.set_major_locator(loc_t)
if debug:
print('DEBUG: drawing...')
self.figure.canvas.draw()
return self
def main(self, fname=None, show=False,
figurename=None, save=False, along_orbit=False, set_cmap=True):
# if len(a.digitization_list) < 100:
# return
if set_cmap:
plt.hot()
fig = plt.figure(figsize=(8.27, 11.69), dpi=70)
n = 8 + 4 + 1 + 1 + 1
hr = np.ones(n)
hr[-4:] = 0.5
g = mpl.gridspec.GridSpec(n,1, hspace=0.1, height_ratios=hr,
bottom=0.06, right=0.89)
axes = []
prev = None
for i in range(n):
axes.append(plt.subplot(g[i], sharex=prev))
axes[i].set_xlim(self.extent[0], self.extent[1])
axes[i].yaxis.set_major_locator(
mpl.ticker.MaxNLocator(prune='upper', nbins=5,
steps=[1,2,5,10]))
l = celsius.SpiceetLocator()
axes[i].xaxis.set_major_locator(l)
axes[i].xaxis.set_major_formatter(
celsius.SpiceetFormatter(locator=l))
prev = axes[-1]
axit = iter(axes)
self.plot_aspera_ima(ax=next(axit), inverted=False)
self.plot_aspera_els(ax=next(axit))
self.plot_mod_b(ax=next(axit))
self.plot_ne(ax=next(axit))
self.plot_timeseries(ax=next(axit))
self.plot_frequency_range(ax=next(axit), f_min=0.0, f_max=0.2,
colorbar=True)
# self.plot_frequency_range(ax=axit.next(), f_min=0.2, f_max=0.5)
self.plot_frequency(ax=next(axit), f=0.5)
# self.plot_frequency(ax=axit.next(), f=0.75)
self.plot_frequency(ax=next(axit), f=1.)
# self.plot_frequency(ax=axit.next(), f=1.52)
self.plot_frequency(ax=next(axit), f=2.)
self.plot_tec(ax=next(axit))
# twx = plt.twinx()
# t = mex.sub_surface.read_tec(self.start_time, self.finish_time)
# good = t['FLAG'] == 1
# plt.plot(t['EPHEMERIS_TIME'][good], t['TEC'][good], 'k.', mew=0.)
# plt.ylabel(r'$TEC / m^{-2}$')
# plt.yscale('log')
# plt.ylim(3E13, 2E16)
# self.plot_profiles(ax=axit.next())
# self.plot_profiles_delta(ax=axit.next())
# self.plot_peak_altitude(ax=axit.next())
# self.plot_peak_density(ax=axit.next())
self.plot_profiles(ax=next(axit))
# self.plot_tec(ax=axit.next())
self.plot_altitude(ax=next(axit))
self.plot_lat(ax=next(axit))
self.plot_lon(ax=next(axit))
self.plot_sza(ax=next(axit))
# axes[-1].xaxis.set_major_formatter(celsius.SpiceetFormatter())
for i in range(n-1):
plt.setp( axes[i].get_xticklabels(), visible=False )
axes[i].set_xlim(self.extent[0], self.extent[1])
l = celsius.SpiceetLocator()
axes[i].xaxis.set_major_locator(l)
axes[i].xaxis.set_major_formatter(
celsius.SpiceetFormatter(locator=l))
plt.annotate("Orbit %d, plot start: %s, newest digitization: %s" % (
self.orbit,
celsius.spiceet_to_utcstr(self.extent[0],fmt='C')[0:17], self._newest),
(0.5, 0.93), xycoords='figure fraction', ha='center')
if save:
if figurename is None:
fname = mex.locate_data_directory() + ('ais_plots/v0.9/%05d/%d.pdf' % ((self.orbit // 1000) * 1000, self.orbit))
else:
fname = figurename
print('Writing %s' % fname)
d = os.path.dirname(fname)
if not os.path.exists(d) and d:
os.makedirs(d)
plt.savefig(fname)
if show:
plt.show()
else:
plt.close(fig)
plt.close('all')
if along_orbit:
# fig = plt.figure()
fig, ax = plt.subplots(2, 1, squeeze=True, figsize=(4,4), dpi=70, num=plt.gcf().number + 1)
plt.subplots_adjust(hspace=0.3,wspace=0.0, right=0.85)
self.density_along_orbit(ax[0], vmax=4.)
self.modb_along_orbit(ax[1], vmax=100.)
if save:
fname = mex.locate_data_directory() + ('ais_plots/A0_v0.9/%05d/%d.pdf' % ((self.orbit // 1000) * 1000, self.orbit))
print('Writing %s' % fname)
d = os.path.dirname(fname)
if not os.path.exists(d):
os.makedirs(d)
plt.savefig(fname)
if show:
plt.show()
else:
plt.close(fig)
plt.close('all')
def stacked_f_plots(start=7894, finish=None, show=True,
frequencies=[0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 2.0, 3.0]):
gc.enable()
if finish is None:
finish = start + 1
plt.close("all")
fig = plt.figure(figsize = celsius.paper_sizes['A4'])
orbits = list(range(start, finish))
if len(orbits) > 1:
show = False
# plt.hot()
for o in orbits:
plt.clf()
gc.collect()
fname = mex.locate_data_directory() + 'marsis/ais_digitizations/%05d/%05d.dig' % ((o // 1000) * 1000, o)
try:
a = AISReview(o, debug=True, db_filename=fname)
except Exception as e:
print(e)
continue
n = len(frequencies) + 4
hr = np.ones(n)
hr[0] = 2.
g = mpl.gridspec.GridSpec(n,1, hspace=0.1, height_ratios=hr)
axes = []
prev = None
for i in range(n):
axes.append(plt.subplot(g[i], sharex=prev))
axes[i].set_xlim(a.extent[0], a.extent[1])
axes[i].yaxis.set_major_locator(mpl.ticker.MaxNLocator(prune='upper', nbins=5, steps=[1,2,5,10]))
axes[i].xaxis.set_major_locator(celsius.SpiceetLocator())
axes[i].xaxis.set_major_formatter(celsius.SpiceetFormatter())
prev = axes[-1]
ax = iter(axes)
a.plot_timeseries(ax=next(ax))
a.plot_frequency_range(ax=next(ax), f_min=0.0, f_max=0.2)
for i, f in enumerate(frequencies):
a.plot_frequency_altitude(ax=next(ax), f=f)
plt.sca(next(ax))
b = a.quick_field_model(a.t)
plt.plot(a.t, np.sqrt(np.sum(b**2., 0)), 'k-')
plt.plot(a.t, b[0], 'r-')
plt.plot(a.t, b[1], 'g-')
plt.plot(a.t, b[2], 'b-')
celsius.ylabel(r'$B_{SC} / nT$')
plt.sca(next(ax))
ion_pos = a.iau_pos
ion_pos[0,:] = 150.0 + mex.mars_mean_radius_km
bion = a.field_model(ion_pos)
plt.plot(a.t, np.sqrt(np.sum(bion**2., 0)), 'k-')
plt.plot(a.t, bion[0], 'r-')
plt.plot(a.t, bion[1], 'g-')
plt.plot(a.t, bion[2], 'b-')
celsius.ylabel(r'$B_{150} / nT$')
for i in range(n-1):
ax = axes[i]
plt.setp( ax.get_xticklabels(), visible=False )
ax.xaxis.set_major_formatter(celsius.SpiceetFormatter())
plt.annotate("Orbit %d, plot start: %s" % (o, celsius.spiceet_to_utcstr(a.extent[0])[0:14]),
(0.5, 0.93), xycoords='figure fraction', ha='center')
if show:
plt.show()
gc.collect()
