def plot_peak_altitude(self, ax=None, true_color='k',
apparent_color='grey'):
if ax is None:
ax = plt.gca()
plt.sca(ax)
for d in self.digitization_list:
if d.is_invertible():
if d.altitude.size == 0:
try:
d.invert(substitute_fp=ais_code.ne_to_fp(4.))
except BaseException as e:
print(e)
continue
if apparent_color:
plt.plot(d.time, d.altitude[-1], marker='.',
ms=self.marker_size, color=apparent_color)
alt = mex.iau_pgr_alt_lat_lon_position(float(d.time))[0]
plt.plot(d.time,
alt - d.traced_delay[-1] * ais_code.speed_of_light_kms / 2.,
marker='.', color=true_color,
ms=self.marker_size)
celsius.ylabel(r'$h_{max} / km$')
plt.ylim(0o1, 249)
def plot_peak_density(self, fmt='k.', labels=True, ax=None, **kwargs):
if ax is None:
ax = plt.gca()
plt.sca(ax)
for d in self.digitization_list:
if d.is_invertible():
if d.altitude.size == 0:
try:
d.invert(substitute_fp=ais_code.ne_to_fp(4.))
except BaseException as e:
print(e)
continue
plt.plot(d.time, d.density[-1], fmt, **kwargs)
if labels:
celsius.ylabel(r'$n_{e,max} / cm^{-3}$')
ax.set_yscale('log')
plt.ylim(1E4, 5E5)
def plot_profiles_delta(self, ax=None):
if ax is None:
ax = plt.gca()
plt.sca(ax)
ax.set_axis_bgcolor("gray")
n_profiles = int((self.extent[1] - self.extent[0]) / ais_code.ais_spacing_seconds) + 1
ranges = np.arange(80., 300., 1.)
times = np.arange(self.extent[0], self.extent[1], ais_code.ais_spacing_seconds)
img = np.zeros((len(times), len(ranges))) + np.nan
for i, d in enumerate(self.digitization_list):
if d.is_invertible():
d.invert(substitute_fp=ais_code.ne_to_fp(4.))
if d.altitude.size:
# as it comes from invert, local values are first, peaks are last
ii = round((float(d.time) - times[0]) / ais_code.ais_spacing_seconds)
img[ii,:] = np.interp(ranges, d.altitude[::-1],
np.log10(d.density[::-1]),
right=np.nan, left=np.nan)[::-1]
# This gives departures from the curve defined by the extrapolation to the first reflection point
# h = -1. * (d.altitude[0] - d.altitude[1]) / (np.log(d.density[0]/d.density[1]))
# img[ii, :] = np.log10(10.**img[ii,:] - d.density[1] * np.exp(-1. * (ranges - d.altitude[1]) / h))
# This gives departures from the Morgan et al model
sza = np.interp(d.time, self.t, self.sza)
# if sza < 90.:
# chap = mars.ChapmanLayer()
# # inx, = np.where(np.isfinite(img[ii,:]))
# # chap.fit(ranges[inx], 10**img[ii,inx[::-1]], sza)
# try:
# chap.fit(d.altitude[::-1], d.density[::-1], np.deg2rad(sza))
# model_densities = chap(ranges, np.deg2rad(sza))
# print chap
# print 'peak:', d.altitude[-1], d.density[-1], sza
# except ValueError, e:
# print e
# continue
model_densities = self.ionosphere_model(ranges, np.deg2rad(sza))
# img[ii, :] = np.log10(10.**img[ii,:] - model_densities)
img[ii, :] = 10.**img[ii,:] - model_densities[::-1]
# if True:
# ax = plt.gca()
# plt.figure()
# plt.plot(np.log10(d.density), d.altitude,'k-')
# if sza < 90.:
# plt.plot(np.log10(model_densities), ranges,'r-')
# # plt.plot(np.log10(chap(ranges)), ranges, 'r', ls='dotted')
# # plt.plot(np.log10(self.ionosphere_model(ranges, np.deg2rad(sza))), ranges, 'b-')
# # plt.plot(np.log10(self.ionosphere_model(ranges)), ranges, 'b', ls='dotted')
# plt.xlim(2,6)
# plt.sca(ax)
extent = (self.extent[0], self.extent[1], np.nanmin(ranges), np.nanmax(ranges))
plt.imshow(img.T, interpolation='Nearest', extent=extent,
origin='upper',aspect='auto', cmap=matplotlib.cm.RdBu_r, vmin=-1E5,vmax=1E5)
celsius.ylabel("alt. / km")
old_ax = plt.gca()
plt.colorbar(cax = celsius.make_colorbar_cax(), ticks=[-1E5,0,1E5],format='%.1G')
plt.ylabel(r"log $\Delta n_e$ / cm$^{-3}$")
plt.sca(old_ax)
