listfile = local_path + '/phd/ownCloud/data/Regions/MetalEarth/malartic/j2/mal_amt.lst'
dataset = WSDS.Dataset(listfile=listfile)
dataset.remove_sites(sites='MAL062A')
dataset.sort_sites('south-north')
data = dataset.data
# data = WSDS.Data(datafile='C:/Users/eric/phd/Kilauea/stitched/1_day/Z/Kilauea_may_daily.data')
days = (501, 530)
hour_or_day = 1 # sets the interval in labels, so choose appropriately
n_interp = 300
cax_rho = [0, 4]
# data = WSDS.Data(datafile=datafile)
# rmsites = [site for site in data.site_names if site[0] == 'e' or site[0] == 'd']
# data.remove_sites(rmsites)
# data.sort_sites(order='west-east')
rho = {site.name: utils.compute_rho(site)[0] for site in data.sites.values()}
pha = {site.name: utils.geotools_filter(np.log10(site.periods), utils.compute_phase(site, 'xy')[0], 0.8, 1) for site in data.sites.values()}
# pha = {site.name: utils.compute_phase(site)[0] for site in data.sites.values()}
bost = {site.name: utils.compute_bost1D(site)[0] for site in data.sites.values()}
depths = {site.name: utils.compute_bost1D(site)[1] for site in data.sites.values()}
periods = []
loc = []
rhovals = []
phavals = []
depth_vals = []
bostvals = []
for jj, site in enumerate(data.site_names):
for ii, p in enumerate(data.sites[site].periods):
periods.append(p)
bostvals.append(bost[site][ii])
depth_vals.append(depths[site][ii])
rhovals.append(rho[site][ii])
# datafile = 'C:/Users/eric/Documents/MATLAB/MATLAB/Inversion/Regions/MetalEarth/swayze/swz_cull1/swz_cull1f_Z.dat'
datafile = 'C:/Users/eric/phd/ownCloud/data/Regions/MetalEarth/j2/cull_allSuperior.data'
listfile = 'C:/Users/eric/phd/ownCloud/data/Regions/MetalEarth/j2/culled_allSuperior.lst'
data = WSDS.Data(datafile=datafile, listfile=listfile)
raw = WSDS.RawData(listfile=listfile)
raw.locations = raw.get_locs(mode='latlong')
for ii in range(len(raw.locations)):
lon, lat = utils.project((raw.locations[ii, 1], raw.locations[ii, 0]), zone=16, letter='U')[2:]
raw.locations[ii, 1], raw.locations[ii, 0] = lon, lat
data.locations = raw.locations
save_path = 'C:/Users/eric/phd/ownCloud/Documents/Seminars/Seminar 3/Figures/Pseudosections/culled/'
# rmsites = [site for site in data.site_names if site[0] == 'e' or site[0] == 'd']
# data.remove_sites(rmsites)
# data.sort_sites(order='west-east')
rho = {site.name: utils.compute_rho(site)[0] for site in data.sites.values()}
pha = {site.name: utils.compute_phase(site)[0] for site in data.sites.values()}
rho_lim = [0, 5]
n_interp = 250
period = 14
padding = 50000
# bost = {site.name: utils.compute_bost1D(site)[0] for site in data.sites.values()}
# depths = {site.name: utils.compute_bost1D(site)[1] for site in data.sites.values()}
rho_error_tol = 0.5
phase_error_tol = 10
for idx, period in enumerate(data.periods):
loc_x = []
loc_y = []
rho_vals = []
phase_vals = []
loc_z = []
fig = plt.figure(figsize=(12, 6))
axes.append(plt.subplot2grid((3, 2), (0, 0), rowspan=2))
axes.append(plt.subplot2grid((3, 2), (2, 0), rowspan=1))
axes.append(plt.subplot2grid((3, 2), (0, 1), rowspan=2))
axes.append(plt.subplot2grid((3, 2), (2, 1), rowspan=1))
# site = data.sites[sites[0]]
for ii, name in enumerate(sites):
site = data.sites[name]
rhoxy, rhoxy_err, rhoxy_log10err = utils.compute_rho(site,
calc_comp='rhoxy',
errtype='errors')
rhoyx, rhoyx_err, rhoyx_log10err = utils.compute_rho(site,
calc_comp='rhoyx',
errtype='errors')
phaxy, phaxy_err = utils.compute_phase(site,
calc_comp='phaxy',
wrap=True,
errtype='errors')[:2]
phayx, phayx_err = utils.compute_phase(site,
calc_comp='phayx',
wrap=True,
errtype='errors')[:2]
axes[(ii) * 2].errorbar(np.log10(site.periods),
np.log10(rhoxy),
xerr=None,
yerr=rhoxy_log10err,
marker='o',
linestyle='',
color='b',
markersize=5,
label='XY')
axes[(ii) * 2].errorbar(np.log10(site.periods),