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PyNLLocRunner.py
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PyNLLocRunner.py
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#!/usr/bin/python
import os, sys
from numpy import array, arange, arccos, pi, sqrt, linalg ,arctan2
from numpy import zeros, append, genfromtxt, savetxt, loadtxt, degrees
from numpy.linalg import eigh
from matplotlib import ticker
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
from glob import glob
"""
Script for running NLLOC package.
ChangeLogs:
16-Aug-2017 > Initial.
"""
#___________________ USEFULL FUNC
def init_plotting():
plt.rcParams['figure.figsize'] = (16, 9)
plt.rcParams['figure.dpi'] = 75
plt.rcParams['font.size'] = 13
plt.rcParams['font.family'] = 'Times New Roman'
plt.rcParams['axes.labelsize'] = plt.rcParams['font.size']
plt.rcParams['axes.titlesize'] = 1.5*plt.rcParams['font.size']
plt.rcParams['legend.fontsize'] = plt.rcParams['font.size']
plt.rcParams['xtick.labelsize'] = plt.rcParams['font.size']
plt.rcParams['ytick.labelsize'] = plt.rcParams['font.size']
plt.rcParams['xtick.major.size'] = 3
plt.rcParams['xtick.minor.size'] = 3
plt.rcParams['xtick.major.width'] = 1
plt.rcParams['xtick.minor.width'] = 1
plt.rcParams['ytick.major.size'] = 3
plt.rcParams['ytick.minor.size'] = 3
plt.rcParams['ytick.major.width'] = 1
plt.rcParams['ytick.minor.width'] = 1
plt.rcParams['legend.frameon'] = True
plt.rcParams['legend.shadow'] = True
plt.rcParams['legend.loc'] = 'lower left'
plt.rcParams['legend.numpoints'] = 1
plt.rcParams['legend.scatterpoints'] = 1
plt.rcParams['axes.linewidth'] = 1
plt.rcParams['savefig.dpi'] = 200
plt.rcParams['xtick.minor.visible'] = 'False'
plt.rcParams['ytick.minor.visible'] = 'False'
plt.gca().xaxis.set_ticks_position('bottom')
plt.gca().yaxis.set_ticks_position('left')
plt.locator_params(nticks=4)
def k2d(kilometer, radius=6371):
return kilometer / (2.0 * radius * pi / 360.0)
def d2k(degrees, radius=6371):
return degrees * (2.0 * radius * pi / 360.0)
#___________________ MAIN CLASS
class main():
#_________ SET INITIAL PARAMETERS
def __init__(self):
self.nlloc_par = os.path.join('par','nlloc.dat')
self.loc_par = os.path.join('par','loc.dat')
self.run_eng = raw_input('\n\n+++ Which module to run:\n\n1- NLLoc [default]\n2- NLDiffLoc\n\n')
if not self.run_eng.strip() or self.run_eng=='1': self.run_eng = 'NLLOC'
elif self.run_eng=='2': self.run_eng = 'NLDIFFLOC'
else:
print '\n+++ Wrong choice!\n'
sys.exit(0)
self.read_nlloc_par()
self.read_loc_par()
self.p_res_max = self.loc_dic['P_RES_MAX']
self.s_res_max = self.loc_dic['S_RES_MAX']
self.max_dist = self.loc_dic['MAX_DIST']
self.dep_max = self.loc_dic['DEP_MAX']
self.Herr_max = self.loc_dic['HERR_MAX']
self.Zerr_max = self.loc_dic['ZERR_MAX']
self.rms_max = self.loc_dic['RMS_MAX']
self.minds_max = self.loc_dic['MINDS_MAX']
self.dep_hist_bw = self.loc_dic['DEP_HIST_BW']
self.her_hist_bw = self.loc_dic['HER_HIST_BW']
self.zer_hist_bw = self.loc_dic['ZER_HIST_BW']
self.rms_hist_bw = self.loc_dic['RMS_HIST_BW']
#_________ READ NLLOC PARAMETERS FILE
def read_nlloc_par(self):
tmp = loadtxt(self.nlloc_par, comments='#', delimiter='=', dtype=str)
self.nlloc_dic = {}
for i in tmp:
self.nlloc_dic[i[0].strip()] = i[1].strip()
#_________ READ LOCATION PARAMETERS FILE (USED FOR PLOTTING)
def read_loc_par(self):
tmp = loadtxt(self.loc_par, comments='#', delimiter='=', dtype=str)
self.loc_dic = {}
for i in tmp:
self.loc_dic[i[0].strip()] = float(i[1].strip())
self.lat_min = self.loc_dic['LAT_MIN']
self.lat_max = self.loc_dic['LAT_MAX']
self.lon_min = self.loc_dic['LON_MIN']
self.lon_max = self.loc_dic['LON_MAX']
self.dep_max = self.loc_dic['DEP_MAX']
self.nlloc_dic['LOC_ENGINE'] = self.run_eng
def prepare_nldiffloc_files(self):
if self.nlloc_dic['LOC_ENGINE']=='NLDIFFLOC':
cmd = 'Loc2ddct loc/%s.*.*.grid0.loc nlloc %.1f %.1f %.1f'%(self.nlloc_dic['LOCFILES_OUTPUT'],
float(self.nlloc_dic['DLOC_MAX_EVNT_DIS']),
float(self.nlloc_dic['DLOC_MIN_ARR_WT']),
float(self.nlloc_dic['DLOC_MAX_STA_DIS']))
os.system(cmd)
os.rename('nlloc.hyp', os.path.join('inp','nlloc.hyp'))
os.rename('nlloc.ct', os.path.join('inp','nlloc.ct'))
#_________ CALCULATE EIGENVALUE/EIGENVECTORS
def eigsorted(self, cov):
vals, vecs = eigh(cov)
order = vals.argsort()[::-1]
return vals[order], vecs[:,order]
#_________ WRITE NLLOC CONTROL FILE
def write_nlloc_cf(self, P_flag=True, S_flag=False, sta_cor=False):
self.read_nlloc_par()
self.read_loc_par()
if P_flag: self.prepare_nldiffloc_files()
self.nlloc_cf = open('nlloc.cf', 'w')
self.nlloc_cf.write('#__________________START GENERIC CONTROL STATEMENTS\n\n')
self.nlloc_cf.write('CONTROL 1 54321\n')
self.nlloc_cf.write('TRANS LAMBERT WGS-84 %s %s %s %s 0.0\n\n'%(self.nlloc_dic['TRANS_LAT'],
self.nlloc_dic['TRANS_LON'],
self.nlloc_dic['TRANS_LAT_MIN'],
self.nlloc_dic['TRANS_LAT_MAX']))
self.nlloc_cf.write('#__________________END\n')
self.nlloc_cf.write('#__________________START VEL2GRID STATEMENTS\n\n')
self.nlloc_cf.write('VGOUT ./model/layer\n')
self.nlloc_cf.write('VGTYPE P\n')
self.nlloc_cf.write('VGTYPE S\n')
self.nlloc_cf.write('VGGRID 2 %s %s %s %s %s %s SLOW_LEN\n'%(self.nlloc_dic['VGGRID_NUM_G_N_XY'],
self.nlloc_dic['VGGRID_NUM_G_N_Z'],
self.nlloc_dic['VGGRID_GRID_X'],
self.nlloc_dic['VGGRID_GRID_Y'],
self.nlloc_dic['VGGRID_GRID_Z'],
self.nlloc_dic['VGGRID_G_S_XYZ']))
self.nlloc_cf.write('INCLUDE %s\n\n'%(self.nlloc_dic['VGGRID_VEL_INP']))
self.nlloc_cf.write('#__________________END\n')
self.nlloc_cf.write('#__________________START GRID2TIME STATEMENTS\n\n')
if P_flag:
self.nlloc_cf.write('GTFILES ./model/layer ./time/layer P\n')
if S_flag:
self.nlloc_cf.write('GTFILES ./model/layer ./time/layer S\n')
self.nlloc_cf.write('GTMODE GRID2D ANGLES_YES\n')
self.nlloc_cf.write('INCLUDE %s\n'%(self.nlloc_dic['VGGRID_STA_INP']))
self.nlloc_cf.write('GT_PLFD 1.0e-3 0\n\n')
self.nlloc_cf.write('#__________________END\n')
self.nlloc_cf.write('#__________________START NLDIFFLOC STATEMENTS\n\n')
self.nlloc_cf.write('DLOC_HYPFILE inp/nlloc.hyp NLLOC_SUM -1 -1\n')
self.nlloc_cf.write('DLOC_SEARCH MET %d %d %d %.3f %.1f %.1f %.2f\n\n'%(float(self.nlloc_dic['DLOC_NumSamples']),
float(self.nlloc_dic['DLOC_BeginSave']),
float(self.nlloc_dic['DLOC_NumSkip']),
float(self.nlloc_dic['DLOC_Step']),
float(self.nlloc_dic['DLOC_Velocity']),
float(self.nlloc_dic['DLOC_InitialTemp']),
float(self.nlloc_dic['DLOC_MaxStep'])))
self.nlloc_cf.write('#__________________END\n')
self.nlloc_cf.write('#__________________START NLDIFFLOC STATEMENTS\n\n')
self.nlloc_cf.write('LOCSIG %s \n'%(self.nlloc_dic['LOCSIG']))
self.nlloc_cf.write('LOCCOM %s \n'%(self.nlloc_dic['LOCCOM']))
if self.nlloc_dic['LOC_ENGINE']=='NLLOC':
self.nlloc_cf.write('LOCFILES %s %s time/layer loc/%s\n'%(self.nlloc_dic['LOCFILES_OBS'],
self.nlloc_dic['LOCFILES_TYP'],
self.nlloc_dic['LOCFILES_OUTPUT']))
elif self.nlloc_dic['LOC_ENGINE']=='NLDIFFLOC':
self.nlloc_cf.write('LOCFILES inp/nlloc.ct HYPODD_ time/layer loc/%s\n'%(self.nlloc_dic['LOCFILES_OUTPUT']))
if not os.path.exists(os.path.join('inp','nlloc.ct')):
print '\n+++ Not "inp/nlloc.ct" file was found!\n'
sys.exit(0)
output = ['SAVE_NLLOC_ALL','SAVE_NLLOC_SUM','SAVE_HYPO71_SUM']
output.append(' '.join(output))
self.nlloc_cf.write('LOCHYPOUT %s\n'%(output[int(self.nlloc_dic['LOCHYPOUT'])-1]))
self.nlloc_cf.write('LOCSEARCH OCT %s %s %s \n'%(self.nlloc_dic['LOCSEARCH_MIN_XYZ'],
self.nlloc_dic['LOCSEARCH_NODE'],
self.nlloc_dic['LOCSEARCH_STP']))
self.nlloc_cf.write('LOCGRID %s %s %s %s %s PROB_DENSITY SAVE\n'%(self.nlloc_dic['LOCGRID_GNUM_XYZ'],
self.nlloc_dic['LOCGRID_GRID_X'],
self.nlloc_dic['LOCGRID_GRID_Y'],
self.nlloc_dic['LOCGRID_GRID_Z'],
self.nlloc_dic['LOCGRID_G_S_XYZ']))
if self.nlloc_dic['LOC_ENGINE']=='NLLOC':
self.nlloc_cf.write('LOCMETH EDT_OT_WT %s %s %s %s %s %s %s %s\n'%(self.nlloc_dic['LOCMETH_MAX_ST_D'],
self.nlloc_dic['LOCMETH_MIN_NM_PH'],
self.nlloc_dic['LOCMETH_MAX_NM_PH'],
self.nlloc_dic['LOCMETH_MIN_NM_S'],
self.nlloc_dic['LOCMETH_VP_VS'],
self.nlloc_dic['LOCMETH_MAX_G'],
self.nlloc_dic['LOCMETH_MIN_ST_D'],
self.nlloc_dic['LOCMETH_DUP']))
elif self.nlloc_dic['LOC_ENGINE']=='NLDIFFLOC':
self.nlloc_cf.write('LOCMETH L1_NORM 9999.0 3 -1 -1 1.8 6 -1.0 0\n')
self.nlloc_cf.write('LOCGAU %s\n'%(self.nlloc_dic['LOCGAU']))
self.nlloc_cf.write('LLOCGAU2 %s\n'%(self.nlloc_dic['LOCGAU2']))
self.nlloc_cf.write('LOCPHASEID P %s\n'%(self.nlloc_dic['LOCPHASEID_P']))
self.nlloc_cf.write('LOCPHASEID S %s\n'%(self.nlloc_dic['LOCPHASEID_S']))
self.nlloc_cf.write('LOCQUAL2ERR 0.1 0.5 1.0 2.0 99999.9\n')
self.nlloc_cf.write('LOCPHSTAT %s %s %s %s %s %s %s %s\n'%(self.nlloc_dic['LOCPHSTAT_RMS_Max'],
self.nlloc_dic['LOCPHSTAT_NR_Min'],
self.nlloc_dic['LOCPHSTAT_Gap_Max'],
self.nlloc_dic['LOCPHSTAT_P_RMax'],
self.nlloc_dic['LOCPHSTAT_S_RMax'],
self.nlloc_dic['LOCPHSTAT_EL3_Max'],
self.nlloc_dic['LOCPHSTAT_D_Min'],
self.nlloc_dic['LOCPHSTAT_D_Max']))
self.nlloc_cf.write('LOCANGLES ANGLES_YES 5\n')
self.nlloc_cf.write('LOCMAG ML_HB 1.0 1.110 0.00189\n')
if sta_cor:
self.nlloc_cf.write('INCLUDE loc/last.stat_totcorr\n')
self.nlloc_cf.write('\n#__________________END')
self.nlloc_cf.close()
#_________ CHECK REQUIRED DIRECTORIES BEFORE RUNNING NLLOC
def check_dir(self):
if self.run_eng=='NLLOC':
dirs = ['loc','model','time']
ans = raw_input('\n+++ Remove old location results [y] or not [n]:\n\n')
for _ in dirs:
if not os.path.exists(_):
os.mkdir(_)
elif ans.lower() == 'y':
for d in dirs:
for f in glob(os.path.join(d,'*')):
os.remove(f)
else:
for d in ['model','time']:
for f in glob(os.path.join(d,'*')):
os.remove(f)
if not os.path.exists('figs'):
os.mkdir('figs')
#_________ RUN NLLOC/NLDIFFLOC
def run_nlloc(self, sta_cor=False):
self.sta_cor = sta_cor
if not os.path.exists('inp/model.dat') or not os.path.exists('inp/station.dat'):
print '\n+++ Required files "model.dat" or "station.dat" not found!\n\n'
sys.exit(0)
self.write_nlloc_cf(P_flag=True, S_flag=False)
os.system('Vel2Grid nlloc.cf > /dev/null')
os.system('Grid2Time nlloc.cf > /dev/null')
self.write_nlloc_cf(P_flag=False, S_flag=True)
os.system('Grid2Time nlloc.cf > /dev/null')
if self.nlloc_dic['LOC_ENGINE']=='NLDIFFLOC':
print '\n+++ Running NLDiffLoc ...\n'
self.write_nlloc_cf(P_flag=True, S_flag=False, sta_cor=self.sta_cor)
os.system('NLDiffLoc nlloc.cf')
elif sta_cor:
print '\n+++ Running NLLoc [station correction = Yes] ...\n'
self.write_nlloc_cf(P_flag=True, S_flag=False, sta_cor=self.sta_cor)
os.system('NLLoc nlloc.cf > /dev/null')
else:
print '\n+++ Running NLLoc [station correction = No] ...\n'
os.system('NLLoc nlloc.cf > /dev/null')
#_________ EXTRACT NLLOC HYPO
def extract_nlloc_hyp(self, root_name):
root_name = self.nlloc_dic['LOCFILES_OUTPUT']
loc_files = glob(os.path.join('loc','%s.*.*.grid0.loc.hyp'%root_name))
out_evt = open('%s_event.dat'%root_name, 'w')
out_pha = open('%s_phase.dat'%root_name, 'w')
with open(out_evt.name, 'a') as f, open(out_pha.name, 'a') as g:
hdr_f = '# LON LAT DEP RMS GAP ERH ERZ CXX CXY CXZ CYY CYZ CZZ USD_ST USD_PH MIN_DS MAX_DS AVG_DS'
hdr_g = '# STA PHA TT-CAL RES WGT DIST AZ'
f.write('%s\n'%hdr_f)
g.write('%s\n'%hdr_g)
for loc_file in loc_files:
evt_res = zeros(0)
with open(loc_file) as inp:
for line in inp:
l = line.split()
pha_res = zeros(0)
if 'GEOGRAPHIC' in l:
evt_res = append(evt_res, array([float(l[11]), float(l[9]), float(l[13])]))
if 'QUALITY' in l:
evt_res = append(evt_res, array([float(l[8]), float(l[12])]))
if 'STATISTICS' in l:
evt_res = append(evt_res, array([sqrt(float(l[8])+float(l[14])), sqrt(float(l[18]))]))
evt_res = append(evt_res, array([float(l[8]), float(l[10]), float(l[12]),
float(l[14]), float(l[16]), float(l[18])]))
if 'QML_OriginQuality' in l:
evt_res = append(evt_res, array([float(l[8]), float(l[4]), float(l[20]),
float(l[22]), float(l[24])]))
if '>' in l and 'PHASE' not in l:
if 'P' in l[-23].strip().upper(): pha = 'P'
elif 'S' in l[-23].strip().upper(): pha = 'S'
else: pha = '?'
pha_res = '%7s %7s %10.4f %7.4f %7.4f %7.4f %7.2f\n'%(l[0], pha, float(l[-12]), float(l[-11]), float(l[-10]), float(l[-6]), float(l[-5]))
g.write(pha_res)
savetxt(f, evt_res, newline=' ', fmt='%8.3f')
f.write('\n')
#_________ PLOT STATISTICS USING NLLOC [& HYPOCENTER] RESULTS
def plot_statis(self, root_name):
init_plotting()
root_name = self.nlloc_dic['LOCFILES_OUTPUT']
evt_data = genfromtxt('%s_event.dat'%root_name)
pha_data = genfromtxt('%s_phase.dat'%root_name, dtype=str)
#__________PLOT P-RESIDUALS VS WEIGHTS
ax = plt.subplot(3,3,1)
ax.set_xlabel('P residual [sec]')
ax.set_ylabel('P weight')
ax.grid()
c1 = pha_data[:,1]=='P'
c2 = array(pha_data[:,5], dtype=float)<=self.max_dist
x = array(pha_data[(c1)&(c2)][:,3], dtype=float)
y = array(pha_data[(c1)&(c2)][:,4], dtype=float)
z = array(pha_data[(c1)&(c2)][:,5], dtype=float)
ax.set_xlim(-self.p_res_max, self.p_res_max)
sc = ax.scatter(x, y, c=z, lw=0.1)
cb = plt.colorbar(sc)
tick_locator = ticker.MaxNLocator(nbins=6)
cb.locator = tick_locator
cb.update_ticks()
cb.set_label('Distance [km]')
ax.locator_params(axis = 'x', nbins=5)
ax.locator_params(axis = 'y', nbins=5)
#__________PLOT S-RESIDUALS VS WEIGHTS
ax = plt.subplot(3,3,2)
ax.set_xlabel('S residual [sec]')
ax.set_ylabel('S weight')
ax.grid()
c1 = pha_data[:,1]=='S'
c2 = array(pha_data[:,5], dtype=float)<=self.max_dist
x = array(pha_data[(c1)&(c2)][:,3], dtype=float)
y = array(pha_data[(c1)&(c2)][:,4], dtype=float)
z = array(pha_data[(c1)&(c2)][:,5], dtype=float)
ax.set_xlim(-self.s_res_max, self.s_res_max)
sc = ax.scatter(x, y, c=z, lw=0.1)
cb = plt.colorbar(sc)
cb.set_label('Distance [km]')
tick_locator = ticker.MaxNLocator(nbins=6)
cb.locator = tick_locator
cb.update_ticks()
ax.locator_params(axis = 'x', nbins=5)
ax.locator_params(axis = 'y', nbins=5)
#__________PLOT P,S RESIDUALS VS DISTANCE
ax = plt.subplot(3,3,3)
ax.set_xlabel('Distance [km]')
ax.set_ylabel('Residual [sec]')
ax.grid()
x = array(pha_data[pha_data[:,1]=='P'][:,5], dtype=float)
y = array(pha_data[pha_data[:,1]=='P'][:,3], dtype=float)
sc = ax.scatter(x, y, c='r', lw=0.1, alpha=.6, label='P')
x = array(pha_data[pha_data[:,1]=='S'][:,5], dtype=float)
y = array(pha_data[pha_data[:,1]=='S'][:,3], dtype=float)
ax.set_xlim(0, self.max_dist)
ax.set_ylim(-self.s_res_max, self.s_res_max)
sc = ax.scatter(x, y, c='b', lw=0.1, alpha=.6, label='S')
ax.legend(loc=1)
ax.locator_params(axis = 'x', nbins=5)
ax.locator_params(axis = 'y', nbins=5)
#__________PLOT DEPTH HISTOGRAM
ax = plt.subplot(3,3,4)
h = -evt_data[:,2]
w = self.dep_hist_bw
b = arange(min(h), max(h) + w, w)
ax.hist(h,b,color='grey',orientation='horizontal')
ax.set_xlabel('# of event')
ax.set_ylabel('Depth [km]')
ax.set_ylim(-self.dep_max, 0)
ax.grid(True)
ax.locator_params(axis = 'x', nbins=5)
ax.locator_params(axis = 'y', nbins=5)
#__________PLOT H-ERROR HISTOGRAM
ax = plt.subplot(3,3,5)
h = evt_data[:,5]
w = self.her_hist_bw
b = arange(min(h), max(h) + w, w)
ax.hist(h,bins=b,color='grey')
ax.set_xlabel('Horizontal Error [km]')
ax.set_ylabel('# of event')
ax.set_xlim(0, self.Herr_max)
ax.grid(True)
ax.locator_params(axis = 'x', nbins=5)
ax.locator_params(axis = 'y', nbins=5)
#__________PLOT Z-ERROR HISTOGRAM
ax = plt.subplot(3,3,6,sharex=ax,sharey=ax)
h = evt_data[:,6]
w = self.zer_hist_bw
b = arange(min(h), max(h) + w, w)
ax.hist(h,bins=b,color='grey')
ax.set_xlabel('Depth Error [km]')
ax.set_ylabel('# of event')
ax.set_xlim(0, self.Zerr_max)
ax.grid(True)
ax.locator_params(axis = 'x', nbins=5)
ax.locator_params(axis = 'y', nbins=5)
#__________PLOT RMS HISTOGRAM
ax = plt.subplot(3,3,7)
h = evt_data[:,3]
w = self.rms_hist_bw
b = arange(min(h), max(h) + w, w)
ax.hist(h,bins=b,color='grey')
ax.set_xlim(0, self.rms_max)
ax.set_xlabel('RMS [sec]')
ax.set_ylabel('# of event')
ax.grid(True)
ax.locator_params(axis = 'x', nbins=5)
ax.locator_params(axis = 'y', nbins=5)
#__________PLOT MINIMUM DISTANCE VS DEPTH
ax = plt.subplot(3,3,8)
x = evt_data[:,2]
y = evt_data[:,15]
z = evt_data[:,4]
sc = ax.scatter(x, y, c=z, lw=0.1, alpha=.6, label='P')
cb = plt.colorbar(sc)
cb.set_label('Azimuthal Gap [deg]')
tick_locator = ticker.MaxNLocator(nbins=6)
cb.locator = tick_locator
cb.update_ticks()
ax.set_xlabel('Depth [km]')
ax.set_ylabel('Minimum Distance [km]')
ax.set_xlim(0, self.dep_max)
ax.set_ylim(0, self.minds_max)
ax.grid(True)
ax.locator_params(axis = 'x', nbins=5)
ax.locator_params(axis = 'y', nbins=5)
#__________PLOT H-ERROR VS GAP
ax = plt.subplot(3,3,9)
x = evt_data[:,4]
y = evt_data[:,5]
z = evt_data[:,13]
sc = ax.scatter(x, y, c=z, lw=0.1, alpha=.6)
cb = plt.colorbar(sc)
cb.set_label('# of used station [deg]')
tick_locator = ticker.MaxNLocator(nbins=6)
cb.locator = tick_locator
cb.update_ticks()
ax.set_xlabel('Azimuthal Gap [deg]')
ax.set_ylabel('Horizontal Error [km]')
ax.set_xlim(0, 360)
ax.set_ylim(0, max(ax.get_ylim()))
ax.grid(True)
ax.locator_params(axis = 'x', nbins=5)
ax.locator_params(axis = 'y', nbins=5)
plt.tight_layout()
plt.savefig(os.path.join('figs', '%s_stat.png'%root_name))
#__________PLOT MAP EVENTS WITH ERROR ELLIPSE
init_plotting()
ax = plt.subplot(1,1,1)
ax.set_title('$Events:$ $Herr_{max} \leq %dkm$ $and$ $Zerr_{max} \leq %dkm$'%(self.Herr_max, self.Zerr_max))
ax.grid(True)
c1 = evt_data[:,5]<=self.Herr_max
c2 = evt_data[:,6]<=self.Zerr_max
cxx = evt_data[(c1)&(c2)][:,7]
cxy = evt_data[(c1)&(c2)][:,8]
cyy = evt_data[(c1)&(c2)][:,10]
lon = evt_data[(c1)&(c2)][:,0]
lat = evt_data[(c1)&(c2)][:,1]
for x, y, xx, xy, xy, yy in zip(lon, lat, cxx, cxy, cxy, cyy):
cov = array([[xx, xy], [xy, yy]])
vals, vecs = self.eigsorted(cov)
theta = degrees(arctan2(*vecs[:,0][::-1]))
nstd = 1
w, h = 2 * nstd * sqrt(vals)
ell = Ellipse(xy=(x, y), width=k2d(w), height=k2d(h),
angle=theta, color='black', alpha=.5)
ell.set_facecolor('none')
ax.add_artist(ell)
plt.scatter(x, y, color='r', marker='*', zorder=100)
plt.tight_layout()
plt.savefig(os.path.join('figs','%s_map.png'%root_name))
#___________________START
start = main()
start.check_dir()
start.run_nlloc(sta_cor=False)
start.run_nlloc(sta_cor=True)
start.extract_nlloc_hyp(root_name=start.nlloc_dic['LOCFILES_OUTPUT'])
start.plot_statis(root_name=start.nlloc_dic['LOCFILES_OUTPUT'])
for f in glob(start.nlloc_dic['LOCFILES_OUTPUT']+'*'): os.rename(f,os.path.join('figs', f))
print '\n+++ Finito!\n'