Module earthquakepy.tsReaders
Expand source code
import re
import numpy as np
from earthquakepy import timeseries
def read_peer_nga_file(filepath):
"""
Reads PEER NGA record file and generates a timeseries object.
Parameters
----------
filepath (string): PEER NGA file path
Returns
-------
TimeSeries object
"""
with open(filepath, "r") as f:
lines = f.readlines()
nlines = len(lines)
for n in range(nlines):
line = lines[n]
if n == 0:
pass
elif n == 1:
eq, eqDate, station, component = line.strip("\n").split(",")
elif n == 2:
yunit = line
elif n == 3:
npts = int(re.match(r".*= *([0-9]*),.*", line)[1])
dt = float(re.match(r".*= *(0?\.[0-9]*) SEC", line)[1])
time = dt * npts
y = np.zeros(int(npts))
else:
elms = line.strip("\n").split()
nelms = len(elms)
i = (n - 4) * nelms
j = i + nelms
y[i:j] = [float(e) for e in elms]
ts = timeseries.TimeSeries(dt, y)
ts.set_tunit("s")
ts.set_yunit(yunit)
ts.set_eqname(eq)
ts.set_eqdate(eqDate)
ts.set_station(station)
ts.set_component(component)
ts.set_npts(npts)
ts.set_dt(dt)
ts.set_time(time)
ts.set_filepath(filepath)
return ts
def read_raw_file(filename, **kwargs):
"""
Reads a raw file readable by numpy.genfromtxt(). The first column is assumed as time and second column as ordinates. Accepts all arguments supported by genfromtxt().
Parameters
----------
filename: (str) filename of the file containing raw data
Returns
-------
Timeseries object
"""
data = np.genfromtxt(filename, **kwargs)
ts = timeseries.TimeSeries(data[:, 0], data[:, 1])
return ts
Functions
def read_peer_nga_file(filepath)
-
Reads PEER NGA record file and generates a timeseries object.
Parameters
filepath (string): PEER NGA file path
Returns
TimeSeries object
Expand source code
def read_peer_nga_file(filepath): """ Reads PEER NGA record file and generates a timeseries object. Parameters ---------- filepath (string): PEER NGA file path Returns ------- TimeSeries object """ with open(filepath, "r") as f: lines = f.readlines() nlines = len(lines) for n in range(nlines): line = lines[n] if n == 0: pass elif n == 1: eq, eqDate, station, component = line.strip("\n").split(",") elif n == 2: yunit = line elif n == 3: npts = int(re.match(r".*= *([0-9]*),.*", line)[1]) dt = float(re.match(r".*= *(0?\.[0-9]*) SEC", line)[1]) time = dt * npts y = np.zeros(int(npts)) else: elms = line.strip("\n").split() nelms = len(elms) i = (n - 4) * nelms j = i + nelms y[i:j] = [float(e) for e in elms] ts = timeseries.TimeSeries(dt, y) ts.set_tunit("s") ts.set_yunit(yunit) ts.set_eqname(eq) ts.set_eqdate(eqDate) ts.set_station(station) ts.set_component(component) ts.set_npts(npts) ts.set_dt(dt) ts.set_time(time) ts.set_filepath(filepath) return ts
def read_raw_file(filename, **kwargs)
-
Reads a raw file readable by numpy.genfromtxt(). The first column is assumed as time and second column as ordinates. Accepts all arguments supported by genfromtxt().
Parameters
filename
:(str) filename
ofthe file containing raw data
Returns
Timeseries object
Expand source code
def read_raw_file(filename, **kwargs): """ Reads a raw file readable by numpy.genfromtxt(). The first column is assumed as time and second column as ordinates. Accepts all arguments supported by genfromtxt(). Parameters ---------- filename: (str) filename of the file containing raw data Returns ------- Timeseries object """ data = np.genfromtxt(filename, **kwargs) ts = timeseries.TimeSeries(data[:, 0], data[:, 1]) return ts