traceE = Trace(az)
if PlotUnit == 'VEL':
#integrate accerelation if plotting velocity
traceN.integrate(method='cumtrapz')
traceE.integrate(method='cumtrapz')
plottheta = theta[thetacount] * 180 / np.pi
thetacount = thetacount + 1
# store stats
stationname = sta + '%04d' % i
channelnameN = cha + '%s' % 'N'
channelnameE = cha + '%s' % 'E'
# for NS components
statsN = Stats()
statsN.sampling_rate = 1.0 / sampling_rate_x
statsN.delta = sampling_rate_x
statsN.starttime = starttime
statsN.npts = len(traceN.data)
statsN.network = net
statsN.station = stationname
statsN.location = ''
statsN.channel = channelnameN
traceN.stats = statsN
traceN.stats.sac = obspy.core.AttribDict()
traceN.stats.sac.back_azimuth = plottheta # use this as azimuth of station
#---applying filters---#
traceN.filter('bandpass', freqmin=freqmin, freqmax=freqmax)
tN = traceN.stats.starttime
traceN.trim(starttime=tN, endtime=tN + trim_end_time)
traceN.taper(0.05, side='right')
def read_TEXCEL_CSV(filename, **kwargs):
"""
Reads a texcel csv file and returns a uquake Stream object.
.. warning::
This function should NOT be called directly, it registers via the
uquake :func:`~uquake.core.stream.read` function, call this
instead.
:param filename: the path to the file
:param kwargs:
:return: ~uquake.core.stream.Stream
"""
with open(filename) as fle:
x = []
y = []
z = []
for k, line in enumerate(fle):
if k == 0:
if 'MICROPHONE' in line:
offset = 9
else:
offset = 8
# header
if k < 2:
continue
val = line.strip().split(',')
# relative time
if k == 3:
rt0 = timedelta(seconds=float(val[0]))
elif k == 6:
station = str(eval(val[offset]))
elif k == 7:
date = val[offset]
elif k == 8:
date_time = date + " " + val[offset]
datetime = parse(date_time)
starttime = datetime + rt0
elif k == 9:
site = val[offset]
elif k == 10:
location = val[offset]
elif k == 17:
sensitivity_x = float(val[offset])
sensitivity_y = float(val[offset + 1])
sensitivity_z = float(val[offset + 2])
elif k == 18:
range_x = float(val[offset])
range_y = float(val[offset + 1])
range_z = float(val[offset + 2])
elif k == 19:
trigger_x = float(val[offset])
trigger_y = float(val[offset + 1])
trigger_z = float(val[offset + 2])
elif k == 20:
si_x = float(val[offset])
si_y = float(val[offset + 1])
si_z = float(val[offset + 2])
elif k == 21:
sr_x = float(val[offset])
sr_y = float(val[offset + 1])
sr_z = float(val[offset + 2])
x.append(float(val[1]))
y.append(float(val[2]))
z.append(float(val[3]))
x = np.array(x)
y = np.array(y)
z = np.array(z)
stats = Stats()
stats.network = site
stats.delta = si_x / 1000.0
stats.npts = len(x)
stats.location = location
stats.station = station
stats.starttime = UTCDateTime(starttime)
stats.channel = 'radial'
tr_x = Trace(data=x / 1000.0, header=stats)
stats.delta = si_y / 1000.0
stats.channel = 'transverse'
tr_y = Trace(data=y / 1000.0, header=stats)
stats.delta = si_z / 1000.0
stats.channel = 'vertical'
tr_z = Trace(data=z / 1000.0, header=stats)
return Stream(traces=[tr_x, tr_y, tr_z])
def parseISF(self, isf_data, header_only=None, convert=None):
"""
Determine starting point of data.
Header has something like 'CURVE #520000', where ascii '5' is the
length of the length field '20000'.
::
'CURVE #520000xxxx...'
^ ^^ ^
| || +---- data_loc: location of first valid byte of data
| |+--------- len_loc: location of first byte of data length field
| +---------- len_len_loc: location of length of length
+----------------- tag_loc: location of start tag
"""
start_tag = 'CURVE #'
tag_loc = int(isf_data.find(start_tag))
len_len_loc = tag_loc + len(start_tag)
len_loc = len_len_loc + 1
len_len = int(isf_data[len_len_loc]) # e.g. 5
data_loc = len_loc + len_len
data_len = int(isf_data[len_loc:len_loc+len_len]) # e.g. 20000
# Extract and parse header
header = isf_data[:tag_loc]
# Reformat the header into a dictionary
header_dict = {}
items = header.replace(':WFMPRE:','').replace(':','').split(';') # list of "key value" pairs
for item in items:
if(item):
key, value = item.split(' ', 1) # maxsplit 1 to ignore subsequent spaces in value
value = value.replace('"', '')
header_dict[key] = value
if(header_only):
return header_dict
# Extract data and convert from string to integer value
data = isf_data[data_loc:]
stats = Stats()
stats.npts = int(header_dict['NR_PT'])
stats.calib = float(header_dict['YMULT'])
byte_order = header_dict['BYT_OR'] # 'MSB' or 'LSB'
if(byte_order == 'MSB'):
byte_order = '>'
else:
byte_order = '<'
points = []
for i in range(0, stats.npts*2, 2):
value = data[i:i+2] # as string
converted = struct.unpack('%sh' % byte_order, value)[0]
points.append(converted)
# Optionally convert points to engineering units
if(convert):
try:
points = np.array(points) * stats.calib # requires numpy
except NameError:
# If numpy not available, use list instead.
p = []
for point in points:
p.append(point * stats.calib)
points = p
stats.time_offset = float(header_dict['XZERO'])
stats.calib_unit = header_dict['YUNIT']
stats.delta = float(header_dict['XINCR'])
stats.amp_offset = float(header_dict['YOFF'])
stats.comments = header_dict['WFID']
stats.channel = header_dict['WFID'][0:3]
return stats, points