def main():
# MAIN PROGRAM BODY
# Parse the command line switches
optioncount = len(sys.argv)
SAC = False
outputfile_defined = False
filelist = []
dir=""
extension = '.txt'
if optioncount > 1:
if optioncount == 4:
if sys.argv[3] == '-s':
SAC = True
# print "SAC set to true."
outfile = sys.argv[2]
infile = sys.argv[1]
filelist.append(infile)
elif optioncount == 3:
if "." in sys.argv[1]:
infile = sys.argv[1]
filelist.append(infile)
outputfile_defined = True
outfile = sys.argv[2]
else:
if len(sys.argv[2])==4 and "." in sys.argv[2]: # set a different extension
extension = sys.argv[2]
filelist = os.listdir(sys.argv[1])
dir=sys.argv[1]
elif optioncount == 2:
if "." in sys.argv[1]:
infile = sys.argv[1]
filelist.append(infile)
else:
dir = sys.argv[1]
filelist = os.listdir(sys.argv[1])
for n in range(len(filelist)):
if extension in filelist[n]:
if len(filelist)>1:
infile = dir+"/"+filelist[n]
if string.find(infile,'.') > 0:
outfile = infile[:string.find(infile,'.')]+'.sac'
seedfile = infile[:string.find(infile,'.')]+'.mseed'
else:
outfile = infile +'.sac'
seedfile = infile + '.mseed'
PNE = load(infile)
# PNE[0] is the header where:
# PNE[0][0][1] = The comment descriptor of the data
# PNE[0][1][1] = The station name
# PNE[0][2][1] = Component axis(Z,N, or E)
# PNE[0][4][1] = Start time
# PNE[0][5][1] = Calibration factor
# PNE[0][6][1] = Time correction in seconds
Comment = PNE[0][0][1]
Stname = PNE[0][1][1][:7]
Component = PNE[0][2][1][:3]
St_time = time.strptime(PNE[0][4][1][:-4],"%d_%b_%Y_%H:%M:%S")
Frac_sec = int(PNE[0][4][1][21:])
CF = np.float32(PNE[0][5][1])
TC = PNE[0][6][1] # time correction
Offset = float(PNE[1][0][0])
#
# Delta is calculated from the offset time of last sample
# minus offset of first sample / total number of samples.
Delta = (float(PNE[1][len(PNE[1])-1][0])-Offset)/(len(PNE[1])-1)
# Load Data array
# Samples in file are multiplied by 10,000 to convert from
# measurements of centimeters to microns, then it's divided by
# the Amplification (conversion) factor, known as CF
Data = []
for n in range (len(PNE[1])-1):
Datum = np.float32(np.float32(PNE[1][n][1])*10000.0/CF)
Data.append(Datum)
b = np.arange(len(Data),dtype=np.float32)
for n in range(len(Data)): # Load the array with time-history data
b[n] = Data[n]
t = SACTrace(data = b)
# set the SAC header values
t.scale = 1.0 # Set the scale for use with DIMAS software
t.delta = Delta
t.nzyear = St_time.tm_year
t.nzjday = St_time.tm_yday
t.nzhour = St_time.tm_hour
t.nzmin = St_time.tm_min
t.nzsec = St_time.tm_sec
t.nzmsec = Frac_sec # int((Frac_second)*1000)
t.kstnm = Stname[:7]
t.kcmpnm = Component
t.IDEP = 4 # 4 = units of velocity (in Volts)
# Dependent variable choices:
# (1)unknown,
# (2)displacement(nm),
# (3)velocity(nm/sec),
# (4)velocity(volts),
# (5)nm/sec/sec
t.kinst = "Velocity" # Instrument type
t.knetwk = "LM" # Network designator
t.kuser0 = "Nanometr" # Place the system of units into the user text field 0
# t.WriteSacBinary(outfile)
with open(outfile,'wb') as sacfile:
t.write(sacfile)
print " File successfully written: {0}".format(outfile)
sacfile.close()
st=read(outfile)
st.write(seedfile,format="mseed")
print " File successfully written: {0}".format(seedfile)
print "File written to {}".format(outfile)
else:
print "Useage: PNE2SAC infile.txt (outfile.asc)"
print "Or, PNE2SAC target_directory target_extension(like .txt)"
print "No infile or directory specified."
print len(sys.argv)
def csv2sac(infile, cconstant):
#
Channel = ["", "", "", ""]
units = ['Counts ', 'Counts ', 'Counts ', 'Counts ']
comment = ['Velocity', 'Velocity', 'Velocity', 'Velocity']
(header, stack) = load(infile)
first_sample, medsps = timingvalidate(stack)
if first_sample <> 0:
print "\n\nA timing error exists in the 1st sample of the 1st record in this DAT series.\n"
print "Remove the first DAT file in the folder and try again."
sys.exit()
# print "The first sample shows instantaneous sample rate of {} S/second.".format(medsps)
# datetime = stack[0][13]+","+stack[0][14]
# Frac_second = float(stack[0][17])
datetime = stack[0][15] + "," + stack[0][
16] # New cs4 format the fields are offset by two more columns
Frac_second = float(stack[0][17])
St_time = time.strptime(datetime, "%Y/%m/%d,%H:%M:%S")
stdate = str(St_time.tm_year) + "_" + str(St_time.tm_mon) + "_" + str(
St_time.tm_mday)
stmin = str(St_time.tm_hour) + "_" + str(St_time.tm_min) + "_" + str(
St_time.tm_sec) + "_" + str(int(Frac_second * 1000))
Filetime = stdate + "_" + stmin + "_"
Station = cconstant[0]
Network = cconstant[15]
# File naming convention: YYYY.DDD.HH.MM.SS.SSS.NN.STATION.CHANNEL
seedfil = infile[0:string.rfind(
infile, '\\')] + "/" + Filetime + Network + "_" + Station
sacfil = infile[0:string.rfind(infile, '.')]
for i in range(0, 4):
Channel[i] = cconstant[(2 * i) + 1]
Samplecount = len(stack)
print "Sample count stands at {} samples.".format(Samplecount)
Delta = 1.0 / float(getsps(stack))
# Delta = 1/medsps
print "Delta = {0:.8f}, Sample rate = {1:.8f}".format(Delta, 1 / Delta)
#
# stack[1] = channel 1 time history
# .
#
# stack[4] = channel 4 time history
#
for i in range(0, 4): # Build each channel
b = np.arange(
len(stack),
dtype=np.float32) # Establishes the size of the datastream
for n in range(len(stack)): # Load the array with time-history data
b[n] = np.float32(
stack[n][i +
1]) # Convert the measurement from counts to volts.
t = SACTrace(data=b)
# set the SAC header values
t.scale = 1.0 # Set the scale for each channel for use with DIMAS software
t.delta = Delta
t.nzyear = St_time.tm_year
t.nzjday = St_time.tm_yday
t.nzhour = St_time.tm_hour
t.nzmin = St_time.tm_min
t.nzsec = St_time.tm_sec
t.nzmsec = int((Frac_second) * 1000)
t.kstnm = Station
t.kcmpnm = Channel[i]
t.IDEP = 4 # 4 = units of velocity (in Volts)
# Dependent variable choices: (1)unknown, (2)displacement(nm),
# (3)velocity(nm/sec), (4)velocity(volts),
# (5)nm/sec/sec
t.kinst = comment[i - 1] # Instrument type
t.knetwk = Network # Network designator
t.kuser0 = units[
i - 1] # Place the system of units into the user text field 0
out = sacfil + "_{}.sac".format(Channel[i])
seed = seedfil + "_{}.mseed".format(Channel[i])
if Channel[
i] != "UNK": # We do not write streams in which the channel name is UNK
with open(out, 'wb') as sacfile:
t.write(sacfile)
print " File successfully written: {0}".format(out)
sacfile.close()
st = read(out)
st.write(seed, format="mseed")
print " File successfully written: {0}".format(seed)
# subprocess.call(["del",f],shell=True)
# for i in range(0,1): # Build special channel for timing
b = np.arange(len(stack),
dtype=np.float32) # Establishes the size of the datastream
for n in range(len(stack)): # Load the array with time-history data
b[n] = np.float32(stack[n][13]) # Get the timing value.
t = SACTrace(data=b)
# set the SAC header values
t.scale = 1.0 # Set the scale for each channel. This one is important to declare.
t.delta = Delta
t.nzyear = St_time.tm_year
t.nzjday = St_time.tm_yday
t.nzhour = St_time.tm_hour
t.nzmin = St_time.tm_min
t.nzsec = St_time.tm_sec
t.nzmsec = int((Frac_second) * 1000)
t.kstnm = Station
t.kcmpnm = 'GPS' # This is a GPS timing signal.
t.IDEP = 1 # 4 = units of velocity (in Volts)
# Dependent variable choices: (1)unknown, (2)displacement(nm),
# (3)velocity(nm/sec), (4)velocity(volts),
# (5)nm/sec/sec
t.kinst = 'GPS' # Instrument type
t.knetwk = Network # Network designator
t.kuser0 = 'digital' # Place the system of units into the user text field 0
out = sacfil + "_{}.sac".format('GPS')
with open(out, 'wb') as sacfile:
t.write(sacfile)
# print " File successfully written: {}.sac".format(out)
# print "Published sample rate in sac file = {}".format(t.stats.sampling_rate)
sacfile.close()
def csv2sac(infile,cconstant):
#
Channel = ["","","",""]
units = ['Counts ','Counts ','Counts ','Counts ']
comment = ['Velocity','Velocity','Velocity','Velocity']
(header,stack) = load(infile)
first_sample,medsps = timingvalidate(stack)
if first_sample <> 0:
print "\n\nA timing error exists in the 1st sample of the 1st record in this DAT series.\n"
print "Remove the first DAT file in the folder and try again."
sys.exit()
# print "The first sample shows instantaneous sample rate of {} S/second.".format(medsps)
# datetime = stack[0][13]+","+stack[0][14]
# Frac_second = float(stack[0][17])
datetime = stack[0][15]+","+stack[0][16] # New cs4 format the fields are offset by two more columns
Frac_second = float(stack[0][17])
St_time = time.strptime(datetime,"%Y/%m/%d,%H:%M:%S")
stdate = str(St_time.tm_year)+"_"+str(St_time.tm_mon)+"_"+str(St_time.tm_mday)
stmin = str(St_time.tm_hour)+"_"+str(St_time.tm_min)+"_"+str(St_time.tm_sec)+"_"+str(int(Frac_second*1000))
Filetime = stdate+"_"+stmin+"_"
Station = cconstant[0]
Network = cconstant[15]
# File naming convention: YYYY.DDD.HH.MM.SS.SSS.NN.STATION.CHANNEL
seedfil = infile[0:string.rfind(infile,'\\')]+"/"+Filetime+Network+"_"+Station
sacfil = infile[0:string.rfind(infile,'.')]
for i in range(0,4):
Channel[i]=cconstant[(2*i)+1]
Samplecount = len(stack)
print "Sample count stands at {} samples.".format(Samplecount)
Delta = 1.0/float(getsps(stack))
# Delta = 1/medsps
print "Delta = {0:.8f}, Sample rate = {1:.8f}".format(Delta,1/Delta)
#
# stack[1] = channel 1 time history
# .
#
# stack[4] = channel 4 time history
#
for i in range(0,4): # Build each channel
b = np.arange(len(stack),dtype=np.float32) # Establishes the size of the datastream
for n in range(len(stack)): # Load the array with time-history data
b[n] = np.float32(stack[n][i+1]) # Convert the measurement from counts to volts.
t = SACTrace(data = b)
# set the SAC header values
t.scale=1.0 # Set the scale for each channel for use with DIMAS software
t.delta=Delta
t.nzyear=St_time.tm_year
t.nzjday=St_time.tm_yday
t.nzhour=St_time.tm_hour
t.nzmin=St_time.tm_min
t.nzsec=St_time.tm_sec
t.nzmsec=int((Frac_second)*1000)
t.kstnm=Station
t.kcmpnm=Channel[i]
t.IDEP=4 # 4 = units of velocity (in Volts)
# Dependent variable choices: (1)unknown, (2)displacement(nm),
# (3)velocity(nm/sec), (4)velocity(volts),
# (5)nm/sec/sec
t.kinst=comment[i-1] # Instrument type
t.knetwk=Network # Network designator
t.kuser0=units[i-1] # Place the system of units into the user text field 0
out = sacfil+"_{}.sac".format(Channel[i])
seed = seedfil+"_{}.mseed".format(Channel[i])
if Channel[i] !="UNK": # We do not write streams in which the channel name is UNK
with open(out,'wb') as sacfile:
t.write(sacfile)
print " File successfully written: {0}".format(out)
sacfile.close()
st=read(out)
st.write(seed,format="mseed")
print " File successfully written: {0}".format(seed)
# subprocess.call(["del",f],shell=True)
# for i in range(0,1): # Build special channel for timing
b = np.arange(len(stack),dtype=np.float32) # Establishes the size of the datastream
for n in range(len(stack)): # Load the array with time-history data
b[n] = np.float32(stack[n][13]) # Get the timing value.
t = SACTrace(data = b)
# set the SAC header values
t.scale=1.0 # Set the scale for each channel. This one is important to declare.
t.delta=Delta
t.nzyear=St_time.tm_year
t.nzjday=St_time.tm_yday
t.nzhour=St_time.tm_hour
t.nzmin=St_time.tm_min
t.nzsec= St_time.tm_sec
t.nzmsec= int((Frac_second)*1000)
t.kstnm=Station
t.kcmpnm='GPS' # This is a GPS timing signal.
t.IDEP=1 # 4 = units of velocity (in Volts)
# Dependent variable choices: (1)unknown, (2)displacement(nm),
# (3)velocity(nm/sec), (4)velocity(volts),
# (5)nm/sec/sec
t.kinst='GPS' # Instrument type
t.knetwk=Network # Network designator
t.kuser0='digital' # Place the system of units into the user text field 0
out = sacfil+"_{}.sac".format('GPS')
with open(out,'wb') as sacfile:
t.write(sacfile)
# print " File successfully written: {}.sac".format(out)
# print "Published sample rate in sac file = {}".format(t.stats.sampling_rate)
sacfile.close()
