# Read parameter file
config = ConfigParser(defaults={'succession': 'native'})
with open(argv[1]) as fh:
config.readfp(fh)
# Kernel Parameters
# TODO Estimate hyper-parameters
tau = config.getfloat('Prior',
'tau') # A priori uncertainty; standard deviation
ell = config.getfloat('Prior', 'ell') # Characteristic length
mu = config.getfloat('Prior', 'mu') # Constant a priori velocity model
# Read station coordinates
station_file = config.get('Observations', 'station_file')
all_stations = read_station_file(station_file)
# Read pseudo data
data_file = config.get('Observations', 'data')
pseudo_data = np.genfromtxt(data_file, dtype=dt_obs)
# Observations
pairs = ListPairs(pseudo_data, all_stations)
# XXX Appears a little clumsy to me
if config.get('Observations', 'succession') == 'native':
pass
elif config.get('Observations', 'succession') == 'ascending':
pairs.sort(key=lambda p: p.central_angle)
elif config.get('Observations', 'succession') == 'descending':
pairs.sort(key=lambda p: p.central_angle, reverse=True)
elif config.get('Observations', 'succession') == 'random':
__author__ = "Stefan Mauerberger"
__copyright__ = "Copyright (C) 2017 Stefan Mauerberger"
__license__ = "GPLv3"
''' Save a plot of the reference velocity model '''
import numpy as np
from matplotlib import pyplot as plt
from gptt import dt_latlon, ListPairs, read_station_file
from plotting import rcParams, prepare_map, lllat, lllon, urlat, urlon, cmap_mu
from reference import c_act, dt_obs
plt.rcParams.update(rcParams)
# Read station coordinates
all_stations = read_station_file('../dat/stations.dat')
# Read pseudo data
pseudo_data = np.genfromtxt('../dat/pseudo_data.dat', dtype=dt_obs)
# Instantiate
pairs = ListPairs(pseudo_data, all_stations)
# Stations
stations = pairs.stations
# Prepare map
fig = plt.figure()
ax_map = fig.add_subplot(111)
m = prepare_map(ax=ax_map)
# Add axes for the colorbar
bbox = ax_map.get_position()
ax_cbr = fig.add_axes((bbox.x0, bbox.y0 - 0.06, bbox.width, 0.04))