def boot_stack(ccp_data, bin_loca, depaxis):
stack_data = []
for i in range(ccp_data.shape[0]):
print('{}/{}'.format(i + 1, bin_loca.shape[0]))
boot_stack = {}
bin_mu = np.zeros(depaxis.shape[0])
bin_ci = np.zeros([depaxis.shape[0], 2])
bin_count = np.zeros(depaxis.shape[0])
for j in range(depaxis.shape[0]):
bin_count[j] = ccp_data[i, j].shape[1]
if ccp_data[i, j].shape[1] > 1:
cci = ci(ccp_data[i, j], n_samples=2000)
bin_ci[j, 0] = cci[0]
bin_ci[j, 1] = cci[1]
bin_mu[j] = np.average(ccp_data[i, j])
else:
bin_ci[j, 0] = np.nan
bin_ci[j, 1] = np.nan
bin_mu[j] = np.nan
boot_stack['bin_lat'] = bin_loca[i, 0]
boot_stack['bin_lon'] = bin_loca[i, 1]
boot_stack['mu'] = bin_mu
boot_stack['ci'] = bin_ci
boot_stack['count'] = bin_count
stack_data.append(boot_stack)
return stack_data
def boot_bin_stack(data_bin):
count = data_bin.shape[0]
if count > 1:
cci = ci(data_bin, n_samples=2000)
mu = np.average(data_bin)
else:
cci = np.array([np.nan, np.nan])
mu = np.nan
return mu, cci, count
def search_pierce(rfdep, depaxis, bin_loca, profile_range, bin_radius=75):
bin_radius = km2deg(bin_radius)
data = []
for i in range(bin_loca.shape[0]):
rfbin = {}
print('{}/{}'.format(i + 1, bin_loca.shape[0]))
ccp_mean = np.zeros(depaxis.shape[0])
ccp_count = np.zeros(depaxis.shape[0])
ccp_ci = np.zeros((depaxis.shape[0], 2))
for j, dep in zip(range(depaxis.shape[0]), depaxis):
bin_dep = np.array([])
for sta in rfdep:
fall_idx = np.where(
distaz(sta['Piercelat'][0, 0][:, dep], sta['Piercelon'][
0, 0][:, dep], bin_loca[i, 0], bin_loca[i, 1]).delta <
bin_radius)[0]
bin_dep = np.append(
bin_dep, sta['moveout_correct'][0, 0][fall_idx, dep])
if bin_dep.shape[0] > 1:
bin_ci = ci(bin_dep, n_samples=2000)
bin_mu = np.average(bin_dep)
else:
bin_ci = (np.nan, np.nan)
bin_mu = np.nan
ccp_count[j] = bin_dep.shape[0]
ccp_mean[j] = bin_mu
ccp_ci[j, 0] = bin_ci[0]
ccp_ci[j, 1] = bin_ci[1]
rfbin['bin_lat'] = bin_loca[i, 0]
rfbin['bin_lon'] = bin_loca[i, 1]
rfbin['profile_dis'] = profile_range[i]
rfbin['mu'] = ccp_mean
rfbin['ci'] = ccp_ci
rfbin['count'] = ccp_count
data.append(rfbin)
return data
# pierce_interval = distaz.deg2km(dis_event) * np.abs(distaz.cosd(azi - azi_event))
if np.abs(dis_along - Profile_range[i]
) < bin_radius and dis_proj < seispy.geo.deg2km(
bin_radius):
# print(pierce_interval, azi - azi_event, bin_radius)
# Stack_RF = Stack_RF + RFdepth[0, k]['moveout_correct'][2*Stack_range[j], l]
Stack_RF = np.append(
Stack_RF,
RFdepth[0, k]['moveout_correct'][2 * Stack_range[j],
l])
Event_count = Event_count + 1
if isboot:
if Event_count > 1:
straptimes = int(Event_count * 2)
ci = boot.ci(Stack_RF, n_samples=straptimes, method='pi')
mu = np.average(Stack_RF)
else:
ci = np.zeros(2)
if j == 0:
mu = np.nan
ci = np.array([np.nan, np.nan])
fid.write('%-8.3f %-8.3f %-6.3f %-6.3f %-8.3f %-8.3f %-8.3f %d\n' %
(Profile_lat[i], Profile_lon[i], Profile_range[i],
Stack_range[j], mu, ci[0], ci[1], Event_count))
else:
if Event_count > 0:
mu = np.mean(Stack_RF)
fid.write('%-8.3f %-8.3f %-6.3f %-6.3f %-8.3f %d\n' %
(Profile_lat[i], Profile_lon[i], Profile_range[i],
Stack_range[j], mu, Event_count))
for l in range(RFdepth[0, k]['Piercelat'].shape[1]):
# azi_event = distaz.distaz(Profile_lat[i], Profile_lon[i], RFdepth[0, k]['Piercelat'][l, 0], RFdepth[0, k]['Piercelon'][l, 0]).baz
dis_event = seispy.distaz(
Profile_lat[i], Profile_lon[i],
RFdepth[0, k]['Piercelat'][2 * Stack_range[j], l],
RFdepth[0, k]['Piercelon'][2 * Stack_range[j], l]).delta
# pierce_interval = distaz.deg2km(dis_event) * np.abs(distaz.cosd(azi - azi_event))
if dis_event < seispy.geo.km2deg(bin_radius):
Amp_bin = np.append(
Amp_bin,
RFdepth[0, k]['moveout_correct'][2 * Stack_range[j],
l])
Event_count = Event_count + 1
if Event_count > 1:
straptimes = int(Event_count * 2)
ci = boot.ci(Amp_bin, n_samples=straptimes, method='pi')
mu = np.average(Amp_bin)
else:
mu = 0
ci = np.zeros(2)
# fid.write('%-8.3f %-8.3f %-6.3f %-6.3f %-8.5f %-8.5f %-8.5f %d\n' % (Profile_lat[i], Profile_lon[i], Profile_range[i], Stack_range[j], mu, ci[0], ci[1], Event_count))
mu_arr[j][0] = mu
ci_arr[j] = ci
Event_count_arr[j][0] = Event_count
mu_arr = sm.nonparametric.lowess(mu_arr[:, 0],
Stack_range,
frac=smooth_para)[:, 1]
ci_arr[:, 0] = sm.nonparametric.lowess(ci_arr[:, 0],
Stack_range,
frac=smooth_para)[:, 1]
ci_arr[:, 1] = sm.nonparametric.lowess(ci_arr[:, 1],
pier_lon = RFdepth[0, k]['Piercelon'][2*Stack_range[j], l]
pier_azi = seispy.distaz(lat1, lon1, pier_lat, pier_lon).baz
pier_dis = seispy.distaz(lat1, lon1, pier_lat, pier_lon).degreesToKilometers()
dis_along = pier_dis * seispy.geo.cosd(azi - pier_azi)
# (pro_lat, pro_lon) = seispy.geo.latlon_from(lat1, lon1, azi, seispy.geo.km2deg(dis_along))
# dis_event = seispy.distaz(Profile_lat[i], Profile_lon[i], RFdepth[0, k]['Piercelat'][2*Stack_range[j], l], RFdepth[0, k]['Piercelon'][2*Stack_range[j], l]).degreesToKilometers()
# pierce_interval = distaz.deg2km(dis_event) * np.abs(distaz.cosd(azi - azi_event))
if np.abs(dis_along - Profile_range[i]) < bin_radius:
# print(pierce_interval, azi - azi_event, bin_radius)
# Stack_RF = Stack_RF + RFdepth[0, k]['moveout_correct'][2*Stack_range[j], l]
Stack_RF = np.append(Stack_RF, RFdepth[0, k]['moveout_correct'][2*Stack_range[j], l])
Event_count = Event_count + 1
if isboot:
if Event_count > 1:
straptimes = int(Event_count * 2)
ci = boot.ci(Stack_RF, n_samples=straptimes, method='pi')
mu = np.average(Stack_RF)
else:
ci = np.zeros(2)
if j == 0:
mu = np.nan
ci = np.array([np.nan, np.nan])
fid.write('%-8.3f %-8.3f %-6.3f %-6.3f %-8.3f %-8.3f %-8.3f %d\n' %
(Profile_lat[i], Profile_lon[i], Profile_range[i], Stack_range[j], mu, ci[0], ci[1], Event_count))
else:
if Event_count > 0:
mu = np.mean(Stack_RF)
fid.write('%-8.3f %-8.3f %-6.3f %-6.3f %-8.3f %d\n' %
(Profile_lat[i], Profile_lon[i], Profile_range[i], Stack_range[j], mu, Event_count))
# fid.write('%-8.3f %-8.3f %-6.3f %-6.3f %-8.5f %-8.5f %-8.5f %d\n' % (Profile_lat[i], Profile_lon[i], Profile_range[i], Stack_range[j], mu, ci[0], ci[1], Event_count))
# mu_arr[j][0] = np.nan
# ci_arr[j] = np.array([np.nan, np.nan])
# Event_count_arr[j][0] = 0
# continue
for k in staidx:
for l in range(RFdepth[0, k]['Piercelat'].shape[1]):
# azi_event = distaz.distaz(Profile_lat[i], Profile_lon[i], RFdepth[0, k]['Piercelat'][l, 0], RFdepth[0, k]['Piercelon'][l, 0]).baz
dis_event = seispy.distaz(Profile_lat[i], Profile_lon[i], RFdepth[0, k]['Piercelat'][2*Stack_range[j], l], RFdepth[0, k]['Piercelon'][2*Stack_range[j], l]).delta
# pierce_interval = distaz.deg2km(dis_event) * np.abs(distaz.cosd(azi - azi_event))
if dis_event < seispy.geo.km2deg(bin_radius):
Amp_bin = np.append(Amp_bin, RFdepth[0, k]['moveout_correct'][2*Stack_range[j], l])
Event_count = Event_count + 1
if Event_count > 1:
straptimes = int(Event_count*2)
ci = boot.ci(Amp_bin, n_samples=straptimes, method='pi')
mu = np.average(Amp_bin)
else:
mu = 0
ci = np.zeros(2)
# fid.write('%-8.3f %-8.3f %-6.3f %-6.3f %-8.5f %-8.5f %-8.5f %d\n' % (Profile_lat[i], Profile_lon[i], Profile_range[i], Stack_range[j], mu, ci[0], ci[1], Event_count))
mu_arr[j][0] = mu
ci_arr[j] = ci
Event_count_arr[j][0] = Event_count
mu_arr = sm.nonparametric.lowess(mu_arr[:, 0], Stack_range, frac=smooth_para)[:, 1]
ci_arr[:, 0] = sm.nonparametric.lowess(ci_arr[:, 0], Stack_range, frac=smooth_para)[:, 1]
ci_arr[:, 1] = sm.nonparametric.lowess(ci_arr[:, 1], Stack_range, frac=smooth_para)[:, 1]
Stack_data[i][0] = Profile_lat[i]
Stack_data[i][1] = Profile_lon[i]
Stack_data[i][2] = Profile_range[i]
Stack_data[i][3] = Stack_range
