def read_mex_orbits(fname):
"""docstring for read_mex_orbits"""
# 11 2004 JAN 11 02:23:03 1/0021867775.48376 2004 JAN 11 07:24:05 238.65 -11.59 270.18 -2.24 274.35 86.64 0.717 228.71 357.75 222497088.5 12965.68
utc_date = np.dtype([('Year','int'), ('MonthStr','a',3),
('Day','int'),('Time','a',8)])
print('Reading %s ... ' % fname, end=' ')
orbit_list = celsius.OrbitDict()
lines = 0
with open(fname) as f:
f.readline()
f.readline()
for line in f.readlines():
try:
parts = line.lstrip().split(' ')
n = int(parts[0])
tmp = celsius.Orbit(
n,
celsius.utcstr_to_spiceet(parts[4]),
celsius.utcstr_to_spiceet(parts[1]),
name='MEX')
orbit_list[n] = tmp
lines += 1
except Exception as e:
if 'Unable to determine' in parts[4]:
break
else:
raise
for k in orbit_list:
if k > 1:
orbit_list[k].start = orbit_list[k-1].apoapsis
else:
orbit_list[k].start = orbit_list[k].periapsis - 1.0
orbit_list[k].finish = orbit_list[k].apoapsis
print(' Read %d lines' % lines)
return orbit_list
def plot_aspera_els(start, finish=None, verbose=False, ax=None, colorbar=True,
vmin=None, vmax=None, cmap=None, safe=True):
"""docstring for plot_aspera_els"""
if cmap is None:
cmap = plt.cm.Spectral_r
if ax is None:
ax = plt.gca()
plt.sca(ax)
if finish is None:
finish = start + 86400.
if vmin is None:
vmin = 5.
if vmax is None:
vmax = 9.
no_days = (finish - start) / 86400.
if verbose: print('Plotting ASPERA/ELS between %s and %s...' % (celsius.utcstr(start, 'ISOC'), celsius.utcstr(finish, 'ISOC')))
directory = mex.data_directory + 'aspera/els/'
all_files_to_read = []
for et in np.arange(start - 10., finish + 10., 86400.):
dt = celsius.spiceet_to_datetime(et)
f_name = directory + 'MEX_ELS_EFLUX_%4d%02d%02d_*.cef' % (dt.year, dt.month, dt.day)
all_day_files = glob.glob(f_name)
if not all_day_files:
if verbose: print("No files matched %s" % f_name)
else:
all_files_to_read.extend(all_day_files)
success = False
all_extents = []
for f_name in all_files_to_read:
try:
# Find energy bins:
with open(f_name, 'r') as f:
line_no = 0
while line_no < 43:
line_no += 1
line = f.readline()
if 'DATA = ' in line:
energy_bins = np.fromstring(line[7:], sep=',')
energy_bins.sort()
break
else:
raise IOError("No ENERGY_BINS info found in header")
data = np.loadtxt(f_name, skiprows = 43, converters={1:lambda x: celsius.utcstr_to_spiceet(x[:-1])})
if data.shape[1] != (energy_bins.shape[0] + 2):
raise ValueError("Size of ENERGY_BINS and DATA doesn't match")
# Check timing:
dt = np.diff(data[:,1])
spacing = np.median(dt)
# checks = abs(dt - spacing) > (spacing/100.)
# if np.any(checks):
# # raise ValueError("Spacing is not constant: %d differ by more than 1%% of %f:" % (np.sum(checks), spacing))
# print "Spacing is not constant: %d differ by more than 1%% of %f (Maximum = %f):" % (np.sum(checks), spacing, max(abs(dt - spacing)))
#
# if safe and (max(abs(dt - spacing)) > 10.):
# print '-- To big spacing - dumping'
# continue
# Interpolate to constant spacing:
n_records = int((data[-1,1] - data[0,1]) / spacing)
new_data = np.empty((n_records, data.shape[1])) + np.nan
new_data[:,1] = np.linspace(data[0,1], data[-1,1], n_records)
for i in range(3, data.shape[1]):
new_data[:,i] = np.interp(new_data[:,1],data[:,1], data[:,i], left=np.nan, right=np.nan)
data = new_data
extent = (data[0,1], data[-1,1], energy_bins[0], energy_bins[-1])
if (extent[0] > finish) or (extent[1] < start):
if verbose:
print("This block not within plot range - dumping")
continue
all_extents.append(extent)
if verbose:
print('Plotting ASPERA ELS block, Time: %s - %s, Energy: %f - %f' % (
celsius.utcstr(extent[0],'ISOC'), celsius.utcstr(extent[1],'ISOC'),
extent[2], extent[3]))
print('Shape = ', data.shape)
plt.imshow(np.log10(data[:,3:].T), interpolation="nearest", aspect='auto', extent=extent, vmin=vmin, vmax=vmax, cmap=cmap)
success = True
except IOError as e:
if verbose:
print('Error reading %f' % f_name)
print('--', e)
continue
if success and colorbar:
plt.xlim(start, finish)
plt.ylim(max([e[2] for e in all_extents]), min([e[3] for e in all_extents]))
celsius.ylabel('E / eV')
plt.yscale('log')
cmap.set_under('w')
old_ax = plt.gca()
plt.colorbar(cax=celsius.make_colorbar_cax(), cmap=cmap, ticks=[5,6,7,8,9])
plt.ylabel(r'log$_{10}$ D.E.F.')
plt.sca(old_ax)