def main():
# Read acceleration data. If you want velocity units='vel',
# Cdisplacement units='disp'
data_dir = '/Users/tnye/PROJECTS/Duration/data/ci3144585/ground_motion'
files = [
'1994.c.017m30su.n0a', '1994.c.017m30su.n0b', '1994.c.017m30su.n0c'
]
files = [os.path.join(data_dir, f) for f in files]
stream = Stream()
# Data for the trace we are working with
# There are 3 traces (0, 1, 2), and i denotes trace we are working with
for i in range(len(files)):
cmp = processing.read_data(files[i], units='acc')[0]
stream.append(cmp)
durations = [(0.05, 0.75), (0.2, 0.8), (0.05, .95)]
# Plots each boundary on the Norm Arias Intensity graph
f, axes = plt.subplots(len(durations), 1, sharex=True, figsize=(6.5, 7.5))
for i, trace in enumerate(stream):
# Convert acceleration to m/s/s
acc = np.multiply(0.01, trace.data)
channel = trace.stats['channel']
dt = trace.stats.delta
Ia, NIa = arias_intensity.get_arias_intensity(acc, dt, 0)
print("Arias Intensity (%s): %f" % (channel, np.amax(Ia)))
if i == 2:
xlab = True
else:
xlab = False
arias_intensity.plot_durations(NIa, dt, durations, axes[i], xlab)
axes[i].set_title(channel)
plt.savefig('/Users/tnye/PROJECTS/Duration/figures/Afshari_Fig_1_tnye.png',
dpi=300)
def get_RotComp_Arias(station, dt, starttime):
"""
Calculates the rotational independent components of Ia and CAV: geometric
mean, arithmetic mean, and max of two horizontal components.
Args:
station (stream): Stream of 3 traces of acceleration data for a station.
dt (flaot): Time in between each sample taken (s).
starttime (float): Time in s, after start of record, to start
integrating. Usually P-wave arrival time or 0 for full record.
Returns:
Ia_geom (float): Geometric mean of station's Arias intensity.
Ia_arith (float): Arithmetic mean of station's Arias intensity.
Ia_max (flaot): Max Arias intensity of the two horizontal components.
"""
# Calculate Arias intensity.
for i in range(len(station)):
trace = station[i]
Ia, NIa = arias_intensity.get_arias_intensity(
np.multiply(trace.data, 0.01), trace.stats.delta, starttime)
trace.stats.Ia = np.amax(Ia)
# Calculate geometric mean.
Ia_geom = (math.sqrt(station[0].stats['Ia'] * station[2].stats['Ia']))
# Calculate arithmetic mean.
Ia_arith = ((station[0].stats['Ia'] + station[2].stats['Ia']) / 2)
# Calculate max horizontal component.
for i in range(len(station)):
if station[0].stats.Ia > station[2].stats.Ia:
Ia_max = station[0].stats.Ia
else:
Ia_max = station[2].stats.Ia
return (Ia_geom, Ia_arith, Ia_max)
event_id, date, mag, source_lat, source_lon, depth = calc_eq_data.get_earthquake_data(
'usp000fg9t', stations)
# Add distance and P_wave arrival times to stats.
calc_eq_data.get_dist_and_parrivals(stations, station_stats, source_lat,
source_lon, depth)
# Calc Arias intensity and add to stats.
dt = 0.01
for sta in stations:
for i in range(len(sta)):
trace = sta[i]
starttime = trace.stats.P_arriv
acc = np.multiply(0.01, trace.data)
Ia, NIa, = arias_intensity.get_arias_intensity(acc, 0.01, 0)
newIa, newNIa = arias_intensity.get_arias_intensity(acc, 0.01, starttime)
trace.stats.Ia = Ia
trace.stats.NIa = NIa
trace.stats.maxIa = np.amax(Ia)
trace.stats.PIa = newIa
trace.stats.PNIa = newNIa
trace.stats.maxPIa = np.amax(newIa)
time1 = arias_intensity.get_time_from_percent(NIa, 0.05, dt)
time2 = arias_intensity.get_time_from_percent(NIa, 0.95, dt)
trace.stats.arias5 = time1
trace.stats.arias95 = time2
# Gather all NS components into one stream and sort by dsit
"""
Created on Wed Jun 27 16:36:52 2018
@author: tnye
"""
# Third party imports
import numpy as np
from amptools.io.dmg.core import read_dmg
# Local imports
import arias_intensity
stream1 = read_dmg('/Users/tnye/PROJECTS/Duration/data/events/loma_prieta/GILROY1.V2')
stream2 = read_dmg('/Users/tnye/PROJECTS/Duration/data/events/loma_prieta/GILROY2.V2')
print("Arias Gilroy 1")
for trace in stream1:
acc = np.multiply(0.01, trace.data)
channel = trace.stats.channel
Ia, NIa = arias_intensity.get_arias_intensity(acc, trace.stats['delta'], 0)
print(channel, np.amax(Ia))
print("Arias Gilroy 2")
for trace in stream2:
acc = np.multiply(0.01, trace.data)
channel = trace.stats.channel
Ia, NIa = arias_intensity.get_arias_intensity(acc, trace.stats['delta'], 0)
print(channel, np.amax(Ia))
timelist = timevals.reshape(1, -1)
times = []
for x in timelist:
for y in x:
times.append(y)
hcomp = Stream()
for sta in stations:
newtrace = sta.select(channel='NS')
hcomp += newtrace
ratios = []
dist = []
for i in range(len(hcomp)):
trace = hcomp[i]
dt = trace.stats.delta
acc = np.multiply(0.01, trace.data)
Ia, NIa, = arias_intensity.get_arias_intensity(acc, dt, 0)
newIa, newNIa = arias_intensity.get_arias_intensity(acc, dt, times[i])
trace.stats.Ia = np.amax(Ia)
trace.stats.pIa = np.amax(newIa)
ratio = (trace.stats.pIa / trace.stats.Ia)
trace.stats.ratio = ratio
ratios.append(ratio)
dist.append(trace.stats.distkm)
fig = plt.figure(figsize=(5, 4))
ax = fig.add_subplot(111)
plt.ylim(0, 1.02)
plt.scatter(dist, ratios, s=20, c='k')
plt.ylabel('Arias w P-arriv : Arias')
plt.xlabel('Dist km')
plt.title('usp000a1b0')
plt.savefig('/Users/tnye/PROJECTS/Duration/figures/small_quake_arias.png',