def __call__(self, time, force=False):
t = np.atleast_1d(time)
t0 = mex.orbits[np.amin(t)].number
t1 = mex.orbits[np.amax(t)].number + 1
if t1 > (t0 + 2):
if force and (((t1 - t0) / time.shape[0]) < 50):
raise ValueError("%d orbits, but not many points requested? force=True disables this check")
chunks = []
compute_count = 0
for o in range(t0, t1):
try:
chunk = np.load(self.directory + '%05d/%05d.npy' % (o/1000 * 1000, o))
except IOError as e:
compute_count+= 1
print('Computing for orbit %d' % o)
o_t = np.arange(-40. * 60., 40. * 60., 5.) + mex.orbits[o].periapsis
pos = mex.iau_r_lat_lon_position(o_t)
field = self.field_model(pos)
# for i in range(o_t.shape[0]):
# print o_t[i], field[i,:]
chunk = np.vstack((o_t, field))
all_dirs = self.directory + '%05d/' % (o/1000 * 1000)
if not os.path.exists(all_dirs):
os.makedirs(all_dirs)
np.save(all_dirs + '%05d.npy' % o, chunk)
chunks.append(chunk)
data = np.hstack(chunks)
output = np.empty((3,t.shape[0]))
for i in (0,1,2):
output[i,:] = np.interp(t, data[0,:], data[i+1,:], left=np.nan, right=np.nan)
return output
def generate_position(self):
if not hasattr(self, 't'):
print("Generating position information...")
self.t = np.arange(float(self.extent[0]), float(self.extent[1]), ais_code.ais_spacing_seconds)
if self.debug: print("%d points..." % self.t.size)
self.pos, self.mso_pos, self.sza = mex.mso_r_lat_lon_position(self.t, sza=True, mso=True)
if self.debug: print("...stage 2")
self.iau_pos = mex.iau_r_lat_lon_position(self.t)
self.mso_rho = np.sqrt(self.mso_pos[1,:]**2. + self.mso_pos[2,:]**2.)
if self.debug: print('...done.')
def plot_frequency_altitude(self, f=2.0, ax=None, median_filter=False,
vmin=None, vmax=None, altitude_range=(-99.9, 399.9), colorbar=False, return_image=False, annotate=True):
if vmin is None:
vmin = self.vmin
if vmax is None:
vmax = self.vmax
if ax is None:
ax = plt.gca()
plt.sca(ax)
plt.cla()
freq_extent = (self.extent[0], self.extent[1],
altitude_range[1], altitude_range[0])
i = self.ionogram_list[0]
inx = 1.0E6* (i.frequencies.shape[0] * f) / (i.frequencies[-1] - i.frequencies[0])
img = self.tser_arr_all[:,int(inx),:]
new_altitudes = np.arange(altitude_range[0], altitude_range[1], 14.)
new_img = np.zeros((new_altitudes.shape[0], img.shape[1])) + np.nan
for i in self.ionogram_list:
e = int( round((i.time - self.extent[0]) / ais_code.ais_spacing_seconds ))
pos = mex.iau_r_lat_lon_position(float(i.time))
altitudes = pos[0] - ais_code.speed_of_light_kms * ais_code.ais_delays * 0.5 - mex.mars_mean_radius_km
s = np.argsort(altitudes)
new_img[:, e] = np.interp(new_altitudes, altitudes[s], img[s,e], left=np.nan, right=np.nan)
plt.imshow(new_img, vmin=vmin, vmax=vmax,
interpolation='Nearest', extent=freq_extent, origin='upper', aspect='auto')
plt.xlim(freq_extent[0], freq_extent[1])
plt.ylim(*altitude_range)
ax.set_xlim(self.extent[0], self.extent[1])
ax.xaxis.set_major_locator(celsius.SpiceetLocator())
celsius.ylabel(r'Alt./km')
if annotate:
plt.annotate('f = %.1f MHz' % f, (0.02, 0.9),
xycoords='axes fraction', color='cyan', verticalalignment='top', fontsize='small')
if colorbar:
old_ax = plt.gca()
plt.colorbar(cax = celsius.make_colorbar_cax(), ticks=self.cbar_ticks).set_label(r"$Log_{10} V^2 m^{-2} Hz^{-1}$")
plt.sca(old_ax)
if return_image:
return new_img, freq_extent, new_altitudes
orb = mex.orbits[10470]
et = np.linspace(orb.periapsis-3600., orb.periapsis+3600., 1000.)
# Duru 06a
if comparison == 'Duru':
et = np.linspace(
celsius.spiceet("2005-224T04:45:00"), celsius.spiceet("2005-224T05:15:00"), 100)
# Fraenz 10a
if comparison == 'Fraenz':
orb = mex.orbits[5009]
et = np.linspace(-7 * 60., 7 * 60., 100) + orb.periapsis
pos = mex.iau_r_lat_lon_position(et)
# pos[0,:] += mex.mars_mean_radius_km
# pos = np.empty_like(p)
# pos[2,:] = -np.rad2deg(p[1,:])
# pos[1,:] = np.rad2deg(p[2,:])
# pos[0,:] = p[0,:]
if comparison == 'Duru':
pos[0,:] = np.zeros_like(pos[0,:]) + mex.mars_mean_radius_km + 150.
field = a(pos)
print(field)
plt.subplot(311)
plt.plot(et, pos[0,:] - mex.mars_mean_radius_km)
# plt.plot(et, p[0,:] - mex.mars_mean_radius_km)
