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inverse.py
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inverse.py
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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import obspy
import datetime
from prelude import *
from scipy.signal import find_peaks, spectrogram
from pathlib import Path
show_process = False
auto_peak_pick = False
seismo_data = pd.read_csv('input/all_sta.txt', sep="|")
seismo_latitudes = seismo_data['Latitude']
seismo_longitudes = seismo_data['Longitude']
elevations = seismo_data['Elevation']
station = seismo_data['Station']
flight_num = [530342801,528485724,528473220,528407493,528293430,527937367,529741194,529776675,529179112,530165646,531605202,531715679,529805251,529948401]
time = [1551066051,1550172833,1550168070,1550165577,1550089044,1549912188,1550773710,1550787637,1550511447,1550974151,1551662362,1551736354,1550803701,1550867033]
sta = [1022,1272,1173,1283,1004,"CCB","F6TP","F4TN","F3TN","F7TV",1010,1021,1006,1109]
day = [25,14,14,14,13,11,21,21,18,24,4,4,22,22]
month = [2,2,2,2,2,2,2,2,2,2,3,3,2,2]
for n in range(0,13):
ht = datetime.utcfromtimestamp(time[n])
mins = ht.minute
secs = ht.second
h = ht.hour
tim = 120
h_u = str(h+1)
if h < 23:
day2 = str(day[n])
if h < 10:
h_u = '0'+str(h+1)
h = '0'+str(h)
else:
h_u = str(h+1)
h = str(h)
else:
h_u = '00'
day2 = str(day[n]+1)
if len(str(day[n])) == 1:
day[n] = '0'+str(day[n])
day2 = day[n]
flight_data = pd.read_csv('/scratch/irseppi/nodal_data/flightradar24/20190'+str(month[n])+str(day[n])+'_positions/20190'+str(month[n])+str(day[n])+'_'+str(flight_num[n])+'.csv', sep=",")
flight_latitudes = flight_data['latitude']
flight_longitudes = flight_data['longitude']
tm = flight_data['snapshot_id']
speed = flight_data['speed']
alt = flight_data['altitude']
head = flight_data['heading']
for line in range(len(tm)):
if str(tm[line]) == str(time[n]):
speed = flight_data['speed'][line]
speed_mps = speed * 0.514444
alt = flight_data['altitude'][line]
alt_m = alt * 0.3048
for y in range(len(station)):
if str(station[y]) == str(sta[n]):
dist = distance(seismo_latitudes[y], seismo_longitudes[y], flight_latitudes[line], flight_longitudes[line])
if isinstance(sta[n], str):
day_of_year = str((ht - datetime(2019, 1, 1)).days + 1)
p = "/aec/wf/2019/0"+day_of_year+"/"+str(sta[n])+".*Z.20190"+day_of_year+"000000+"
tr = obspy.read(p)
tr[0].trim(tr[0].stats.starttime +(int(h) *60 *60) + (mins * 60) + secs - tim, tr[0].stats.starttime +(int(h) *60 *60) + (mins * 60) + secs + tim)
data = tr[0][:]
fs = int(tr[0].stats.sampling_rate)
title = f'{tr[0].stats.network}.{tr[0].stats.station}.{tr[0].stats.location}.{tr[0].stats.channel} − starting {tr[0].stats["starttime"]}'
torg = tr[0].times()
else:
p = "/scratch/naalexeev/NODAL/2019-0"+str(month[n])+"-"+str(day[n])+"T"+str(h)+":00:00.000000Z.2019-0"+str(month[n])+"-"+str(day2)+"T"+str(h_u)+":00:00.000000Z."+str(station[y])+".mseed"
tr = obspy.read(p)
tr[2].trim(tr[2].stats.starttime + (mins * 60) + secs - tim, tr[2].stats.starttime + (mins * 60) + secs + tim)
data = tr[2][:]
fs = int(tr[2].stats.sampling_rate)
title = f'{tr[2].stats.network}.{tr[2].stats.station}.{tr[2].stats.location}.{tr[2].stats.channel} − starting {tr[2].stats["starttime"]}'
torg = tr[2].times()
clat, clon, dist_m, tmid = closest_encounter(flight_latitudes, flight_longitudes,line, tm, seismo_latitudes[y], seismo_longitudes[y])
dist_km = dist_m / 1000
tarrive = tim + (time[n] - calc_time(tmid,dist_m,alt_m))
# Compute spectrogram
frequencies, times, Sxx = spectrogram(data, fs, scaling='density', nperseg=fs, noverlap=fs * .9, detrend = 'constant')
a, b = Sxx.shape
MDF = np.zeros((a,b))
for row in range(len(Sxx)):
m = len(Sxx[row])
p = sorted(Sxx[row])
median = p[int(m/2)]
for col in range(m):
MDF[row][col] = median
spec = 10 * np.log10(Sxx) - (10 * np.log10(MDF))
ty = False
if ty == True:
if isinstance(sta[n], int):
spec = np.zeros((a,b))
for col in range(0,b):
p = sorted(Sxx[:, col])
median = p[int(len(p)/2)]
for row in range(len(Sxx)):
spec[row][col] = 10 * np.log10(Sxx[row][col]) - ((10 * np.log10(MDF[row][col])) + ((10*np.log10(median))))
middle_index = len(times) // 2
middle_column = spec[:, middle_index]
vmin = 0
vmax = np.max(middle_column)
p, _ = find_peaks(middle_column, distance=10)
output1 = '/scratch/irseppi/nodal_data/plane_info/inversepicks/2019-0'+str(month[n])+'-'+str(day[n])+'/'+str(flight_num[n])+'/'+str(sta[n])+'/'+str(time[n])+'_'+str(flight_num[n])+'.csv'
if Path(output1).exists():
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
pick_data = pd.read_csv(output1, header=None)
plt.scatter(pick_data.iloc[:, 0], pick_data.iloc[:, 1], color='black', marker='x')
plt.show()
con = input("Do you want to overwrite your previously stored data with your picks? (y or n)")
while con != 'y' and con != 'n':
print('Invalid input. Please enter y or n.')
con = input("Do you want to overwrite your previously stored data with your picks? (y or n)")
if con == 'y':
r1 = open(output1,'w')
coords = []
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
def onclick(event):
global coords
coords.append((event.xdata, event.ydata))
plt.scatter(event.xdata, event.ydata, color='black', marker='x') # Add this line
plt.draw()
print('Clicked:', event.xdata, event.ydata)
r1.write(str(event.xdata) + ',' + str(event.ydata) + ',\n')
cid = plt.gcf().canvas.mpl_connect('button_press_event', onclick)
plt.show(block=True)
r1.close()
pick_again = input("Do you want to repick you points? (y or n)")
while pick_again == 'y':
r1 = open(output1,'w')
coords = []
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
def onclick(event):
global coords
coords.append((event.xdata, event.ydata))
plt.scatter(event.xdata, event.ydata, color='black', marker='x') # Add this line
plt.draw()
print('Clicked:', event.xdata, event.ydata)
r1.write(str(event.xdata) + ',' + str(event.ydata) + ',\n')
cid = plt.gcf().canvas.mpl_connect('button_press_event', onclick)
plt.show(block=True)
r1.close()
pick_again = input("Do you want to repick you points? (y or n)")
else:
coords = []
with open(output1, 'r') as file:
for line in file:
# Split the line using commas
pick_data = line.split(',')
coords.append((float(pick_data[0]), float(pick_data[1])))
file.close() # Close the file after reading
else:
BASE_DIR = '/scratch/irseppi/nodal_data/plane_info/inversepicks/2019-0'+str(month[n])+'-'+str(day[n])+'/'+str(flight_num[n])+'/'+str(sta[n])+'/'
make_base_dir(BASE_DIR)
r1 = open(output1,'w')
coords = []
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
def onclick(event):
global coords
coords.append((event.xdata, event.ydata))
plt.scatter(event.xdata, event.ydata, color='black', marker='x') # Add this line
plt.draw()
print('Clicked:', event.xdata, event.ydata)
r1.write(str(event.xdata) + ',' + str(event.ydata) + ',\n')
cid = plt.gcf().canvas.mpl_connect('button_press_event', onclick)
plt.show(block=True)
r1.close()
pick_again = input("Do you want to repick you points? (y or n)")
while pick_again == 'y':
r1 = open(output1,'w')
coords = []
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
def onclick(event):
global coords
coords.append((event.xdata, event.ydata))
plt.scatter(event.xdata, event.ydata, color='black', marker='x') # Add this line
plt.draw()
print('Clicked:', event.xdata, event.ydata)
r1.write(str(event.xdata) + ',' + str(event.ydata) + ',\n')
cid = plt.gcf().canvas.mpl_connect('button_press_event', onclick)
plt.show(block=True)
r1.close()
pick_again = input("Do you want to repick you points? (y or n)")
# Convert the list of coordinates to a numpy array
coords_array = np.array(coords)
if n == 0:
tprime0 = 112
f0 = 115
v0 = 68
l = 2135
if n == 1:
f0 = 110
tprime0 = 107
v0 = 100
l = 2700
if n == 2:
f0 = 131
tprime0 = 93
v0 = 139
l = 4650
if n == 3:
f0 = 121
tprime0 = 116
v0 = 142
l = 2450
if n == 4:
f0 = 120
tprime0 = 140
v0 = 64
l = 580
if n == 5:
f0 = 17.5
tprime0 = 123
v0 = 112
l = 1150
if n == 6:
f0 = 36
tprime0 = 133
v0 = 92
l = 2400
if n == 7:
f0 = 26
tprime0 = 122
v0 = 126
l = 3000
if n == 8:
f0 = 87.7
tprime0 = 100
v0 = 67
l = 2300
if n == 9:
f0 = 26
tprime0 = 114
v0 = 144
l = 1900
if n > 9:
f0 = fs/4
tprime0 = tarrive
v0 = speed_mps
l = np.sqrt(dist_m**2 + (alt_m-elevations[y])**2)
c = 343
m0 = [f0, v0, l, tprime0]
m,covm = invert_f(m0, coords_array, num_iterations=8)
f0 = m[0]
v0 = m[1]
l = m[2]
tprime0 = m[3]
ft = calc_ft(times, tprime0, f0, v0, l, c)
if isinstance(sta[n], int):
peaks = []
p, _ = find_peaks(middle_column, distance = 7)
corridor_width = (fs/2) / len(p)
if len(p) == 0:
corridor_width = fs/4
coord_inv = []
if show_process == True:
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
for t_f in range(len(times)):
upper = int(ft[t_f] + corridor_width)
lower = int(ft[t_f] - corridor_width)
if lower < 0:
lower = 0
if upper > len(frequencies):
upper = len(frequencies)
tt = spec[lower:upper, t_f]
max_amplitude_index = np.argmax(tt)
max_amplitude_frequency = frequencies[max_amplitude_index+lower]
peaks.append(max_amplitude_frequency)
coord_inv.append((times[t_f], max_amplitude_frequency))
if show_process == True:
plt.scatter(times[t_f], max_amplitude_frequency, color='black', marker='x')
plt.scatter(times[t_f], upper, color='pink', marker='x')
plt.scatter(times[t_f], lower, color='pink', marker='x')
if show_process == True:
plt.show()
coord_inv_array = np.array(coord_inv)
m,_ = invert_f(m0, coord_inv_array, num_iterations=12)
f0 = m[0]
v0 = m[1]
l = m[2]
tprime0 = m[3]
ft = calc_ft(times, tprime0, f0, v0, l, c)
delf = np.array(ft) - np.array(peaks)
new_coord_inv_array = []
for i in range(len(delf)):
if np.abs(delf[i]) <= 3:
new_coord_inv_array.append(coord_inv_array[i])
coord_inv_array = np.array(new_coord_inv_array)
if show_process == True:
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
plt.scatter(coord_inv_array[:,0], coord_inv_array[:,1], color='black', marker='x')
plt.show()
m,covm = invert_f(m0, coord_inv_array, num_iterations=12, sigma=5)
f0 = m[0]
v0 = m[1]
l = m[2]
tprime0 = m[3]
ft = calc_ft(times, tprime0, f0, v0, l, c)
if show_process == True:
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
plt.plot(times, ft, color='g')
plt.show()
if auto_peak_pick == True:
# Find the closest time value to m[3]
closest_time_index = np.argmin(np.abs(times - m[3]))
# Extract the corresponding column from the spectrogram
col = spec[:, closest_time_index]
peaks, _ = find_peaks(col,prominence=15) #distance = 10)
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
plt.axvline(x=tprime0, c = 'g', ls = '--')
plt.plot(col)
for p in peaks:
plt.scatter(times[closest_time_index], frequencies[p], color='black', marker='x')
plt.scatter(p, col[p], color='black', marker='x')
plt.show()
else:
output2 = '/scratch/irseppi/nodal_data/plane_info/overtonepicks/2019-0'+str(month[n])+'-'+str(day[n])+'/'+str(flight_num[n])+'/'+str(sta[n])+'/'+str(time[n])+'_'+str(flight_num[n])+'.csv'
if Path(output2).exists():
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
plt.axvline(x=tprime0, c = '#377eb8', ls = '--')
pick_data = pd.read_csv(output2, header=None)
plt.scatter(pick_data.iloc[:, 0], pick_data.iloc[:, 1], color='black', marker='x')
plt.show()
con = input("Do you want to overwrite your previously stored overtone picks? (y or n)")
while con != 'y' and con != 'n':
print('Invalid input. Please enter y or n.')
con = input("Do you want to overwrite your previously stored overtone picks? (y or n)")
if con == 'y':
r2 = open(output2,'w')
peaks = []
freqpeak = []
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
plt.axvline(x=tprime0, c = '#377eb8', ls = '--')
def onclick(event):
global coords
peaks.append(event.ydata)
freqpeak.append(event.xdata)
plt.scatter(event.xdata, event.ydata, color='black', marker='x') # Add this line
plt.draw()
print('Clicked:', event.xdata, event.ydata)
r2.write(str(event.xdata) + ',' + str(event.ydata) + ',\n')
cid = plt.gcf().canvas.mpl_connect('button_press_event', onclick)
plt.show(block=True)
r2.close()
pick_again = input("Do you want to repick you points? (y or n)")
while pick_again == 'y':
r2 = open(output2,'w')
peaks = []
freqpeak = []
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
plt.axvline(x=tprime0, c = '#377eb8', ls = '--')
def onclick(event):
global coords
peaks.append(event.ydata)
freqpeak.append(event.xdata)
plt.scatter(event.xdata, event.ydata, color='black', marker='x') # Add this line
plt.draw()
print('Clicked:', event.xdata, event.ydata)
r2.write(str(event.xdata) + ',' + str(event.ydata) + ',\n')
cid = plt.gcf().canvas.mpl_connect('button_press_event', onclick)
plt.show(block=True)
r2.close()
pick_again = input("Do you want to repick you points? (y or n)")
elif con == 'n':
peaks = []
freqpeak = []
with open(output2, 'r') as file:
for line in file:
# Split the line using commas
pick_data = line.split(',')
peaks.append(float(pick_data[1]))
freqpeak.append(float(pick_data[0]))
file.close() # Close the file after reading
else:
BASE_DIR = '/scratch/irseppi/nodal_data/plane_info/overtonepicks/2019-0'+str(month[n])+'-'+str(day[n])+'/'+str(flight_num[n])+'/'+str(sta[n])+'/'
make_base_dir(BASE_DIR)
r2 = open(output2,'w')
peaks = []
freqpeak = []
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
plt.axvline(x=tprime0, c = '#377eb8', ls = '--')
def onclick(event):
global coords
peaks.append(event.ydata)
freqpeak.append(event.xdata)
plt.scatter(event.xdata, event.ydata, color='black', marker='x') # Add this line
plt.draw()
print('Clicked:', event.xdata, event.ydata)
r2.write(str(event.xdata) + ',' + str(event.ydata) + ',\n')
cid = plt.gcf().canvas.mpl_connect('button_press_event', onclick)
plt.show(block=True)
r2.close()
pick_again = input("Do you want to repick you points? (y or n)")
while pick_again == 'y':
r2 = open(output2,'w')
peaks = []
freqpeak = []
plt.figure()
plt.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
plt.axvline(x=tprime0, c = '#377eb8', ls = '--')
def onclick(event):
global coords
peaks.append(event.ydata)
freqpeak.append(event.xdata)
plt.scatter(event.xdata, event.ydata, color='black', marker='x') # Add this line
plt.draw()
print('Clicked:', event.xdata, event.ydata)
r2.write(str(event.xdata) + ',' + str(event.ydata) + ',\n')
cid = plt.gcf().canvas.mpl_connect('button_press_event', onclick)
plt.show(block=True)
r2.close()
pick_again = input("Do you want to repick you points? (y or n)")
closest_index = np.argmin(np.abs(tprime0 - times))
arrive_time = spec[:,closest_index]
for i in range(len(arrive_time)):
if arrive_time[i] < 0:
arrive_time[i] = 0
vmin = np.min(arrive_time)
vmax = np.max(arrive_time)
fig, (ax1, ax2) = plt.subplots(2, 1, sharex=False, figsize=(8,6))
ax1.plot(torg, data, 'k', linewidth=0.5)
ax1.set_title(title)
ax1.margins(x=0)
ax1.set_position([0.125, 0.6, 0.775, 0.3]) # Move ax1 plot upwards
# Plot spectrogram
cax = ax2.pcolormesh(times, frequencies, spec, shading='gouraud', cmap='pink_r', vmin=vmin, vmax=vmax)
ax2.set_xlabel('Time (s)')
f0lab = []
ax2.axvline(x=tprime0, c = '#377eb8', ls = '--', linewidth=0.7,label='Estimated arrival: '+str(np.round(tprime0,2))+' s')
for pp in range(len(peaks)):
tprime = freqpeak[pp]
ft0p = peaks[pp]
f0 = calc_f0(tprime, tprime0, ft0p, v0, l, c)
ft = calc_ft(times, tprime0, f0, v0, l, c)
ax2.plot(times, ft, '#377eb8', ls = (0,(5,20)), linewidth=0.7) #(0,(5,10)),
if np.abs(tprime -tprime0) < 1.5:
ax2.scatter(tprime0, ft0p, color='black', marker='x', s=30)
f0lab.append(int(f0))
what_if = calc_ft(times, tarrive, fs/4, speed_mps, np.sqrt(dist_m**2 + alt_m**2), c)
#ax2.plot(times, what_if, 'red', ls = '--', linewidth=0.4)
f0lab_sorted = sorted(f0lab)
covm = np.sqrt(np.diag(covm))
if len(f0lab_sorted) <= 17:
fss = 'medium'
else:
fss = 'small'
ax2.set_title("Final Model:\nt0'= "+str(np.round(tprime0,2))+' +/- ' + str(np.round(covm[3],2)) + ' sec, v0 = '+str(np.round(v0,2))+' +/- ' + str(np.round(covm[1],2)) +' m/s, l = '+str(np.round(l,2))+' +/- ' + str(np.round(covm[2],2)) +' m, \n' + 'f0 = '+str(f0lab_sorted)+' +/- ' + str(np.round(covm[0],2)) +' Hz', fontsize=fss)
ax2.axvline(x=tarrive, c = '#e41a1c', ls = '--',linewidth=0.5,label='Wave arrvial: '+str(np.round(tarrive,2))+' s')
ax2.legend(loc='upper right',fontsize = 'x-small')
ax2.set_ylabel('Frequency (Hz)')
ax2.margins(x=0)
ax3 = fig.add_axes([0.9, 0.11, 0.015, 0.35])
plt.colorbar(mappable=cax, cax=ax3)
ax3.set_ylabel('Relative Amplitude (dB)')
ax2.margins(x=0)
ax2.set_xlim(0, 240)
ax2.set_ylim(0, int(fs/2))
# Plot overlay
spec2 = 10 * np.log10(MDF)
middle_column2 = spec2[:, middle_index]
vmin2 = np.min(middle_column2)
vmax2 = np.max(middle_column2)
# Create ax4 and plot on the same y-axis as ax2
ax4 = fig.add_axes([0.125, 0.11, 0.07, 0.35], sharey=ax2)
ax4.plot(middle_column2, frequencies, c='#ff7f00')
ax4.set_ylim(0, int(fs/2))
ax4.set_xlim(vmax2*1.1, vmin2)
ax4.tick_params(left=False, right=False, labelleft=False, labelbottom=False, bottom=False)
ax4.grid(axis='y')
BASE_DIR = '/scratch/irseppi/nodal_data/plane_info/5plane_spec/2019-0'+str(month[n])+'-'+str(day[n])+'/'+str(flight_num[n])+'/'+str(sta[n])+'/'
make_base_dir(BASE_DIR)
fig.savefig('/scratch/irseppi/nodal_data/plane_info/5plane_spec/2019-0'+str(month[n])+'-'+str(day[n])+'/'+str(flight_num[n])+'/'+str(sta[n])+'/'+str(time[n])+'_'+str(flight_num[n])+'.png')
plt.close()
fig = plt.figure(figsize=(10,6))
plt.grid()
plt.plot(frequencies, arrive_time, c='#377eb8')
if auto_peak_pick == True:
peaks, _ = find_peaks(arrive_time, prominence=15)#0, distance = 10, height = 5, width=1) #for later change parameters for jets and permenant stations
np.diff(peaks)
plt.plot(peaks, arrive_time[peaks], c='k', marker="x", s=50)
for g in range(len(peaks)):
plt.text(peaks[g], arrive_time[peaks[g]], peaks[g], fontsize=15)
else:
for pp in range(len(peaks)):
if np.abs(freqpeak[pp] -tprime0) < 1.5:
upper = int(peaks[pp] + 3)
lower = int(peaks[pp] - 3)
tt = spec[lower:upper, closest_index]
ampp = np.max(tt)
freqp = np.argmax(tt)+lower
plt.scatter(freqp, ampp, color='black', marker='x', s=100)
if isinstance(sta[n], int):
plt.text(freqp - 5, ampp + 0.8, freqp, fontsize=17, fontweight='bold')
else:
plt.text(freqp - 1, ampp + 0.8, freqp, fontsize=17, fontweight='bold')
plt.xlim(0, int(fs/2))
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
plt.ylim(0,vmax*1.1)
plt.xlabel('Frequency (Hz)', fontsize=17)
plt.ylabel('Relative Amplitude at t = {:.2f} s (dB)'.format(tprime0), fontsize=17)
make_base_dir('/scratch/irseppi/nodal_data/plane_info/5spec/20190'+str(month[n])+str(day[n])+'/'+str(flight_num[n])+'/'+str(sta[n])+'/')
fig.savefig('/scratch/irseppi/nodal_data/plane_info/5spec/20190'+str(month[n])+str(day[n])+'/'+str(flight_num[n])+'/'+str(sta[n])+'/'+str(sta[n])+'_' + str(time[n]) + '.png')
plt.close()