def _check_input(values_dict):
"""Perform checks on inputs.
Specifically:
1. Ensure all components are `TimeSeries` objects.
2. Ensure all components have equal `dt`.
3. Ensure all components have same `nsamples`, if not trim.
Parameters
----------
values_dict : dict
Key is human-readable component name {'ns', 'ew', 'vt'}.
Value is corresponding `TimeSeries` object.
Returns
-------
Tuple
Containing checked components as tuple of the form
`(ns, ew, vt)`.
"""
ns = values_dict["ns"]
try:
ns = TimeSeries.from_timeseries(ns)
except AttributeError as e:
msg = f"'ns' must be a `TimeSeries`, not {type(ns)}."
raise TypeError(msg) from e
values_dict["ns"] = ns
dt = ns.dt
nsamples = ns.nsamples
for key, value in values_dict.items():
if key == "ns":
continue
if isinstance(value, TimeSeries):
values_dict[key] = TimeSeries.from_timeseries(value)
else:
msg = f"`{key}`` must be a `TimeSeries`, not {type(value)}."
raise TypeError(msg)
if value.dt != dt:
msg = "All components must have equal `dt`."
raise ValueError(msg)
if value.nsamples != nsamples:
txt = "".join(
[f"{_k}={_v.nsamples} " for _k, _v in values_dict.items()])
msg = f"Components are different length: {txt}"
raise ValueError(msg)
return (values_dict["ns"], values_dict["ew"], values_dict["vt"])
def from_dict(cls, dictionary):
"""Create `Sensor3c` object from dictionary representation.
Parameters
---------
dictionary : dict
Must contain keys "ns", "ew", and "vt", and may also contain
the optional key "meta". "ns", "ew", and "vt" must be
dictionary representations of `TimeSeries` objects, see
`SigProPy <https://sigpropy.readthedocs.io/en/latest/?badge=latest>`_
documentation for details.
Returns
-------
Sensor3c
Instantiated `Sensor3c` object.
"""
if dictionary.get("meta") is None:
dictionary["meta"] = None
comps = []
for comp in ["ns", "ew", "vt"]:
comps.append(TimeSeries.from_dict(dictionary[comp]))
return cls(*comps, dictionary["meta"])
def reload_file(self):
logging.info("begin - reload_file()")
# Reset state
self.applied_filter = False
self.applied_taper = False
self.fseries = False
# Load File and Update Plot to Reflect This
if self.fname.endswith(".miniseed"):
traces = obspy.read(self.fname)
self.tseries = TimeSeries.from_trace(traces[0])
else:
df = pd.read_csv(self.fname, names=["time", "amp"])
self.tseries = TimeSeries(df.amp.to_numpy(),
df.time[1] - df.time[0])
self.update_tseries_plot()
self.update_fseries_plot()
def from_mseed(cls, fname):
"""Initialize a 3-component sensor (Sensor3c) object from a
.miniseed file.
Parameters
----------
fname : str
Name of miniseed file, full path may be used if desired.
The file should contain three traces with the
appropriate channel names. Refer to the `SEED` Manual
`here <https://www.fdsn.org/seed_manual/SEEDManual_V2.4.pdf>`_.
for specifics.
Returns
-------
Sensor3c
Initialized 3-component sensor object.
"""
traces = obspy.read(fname)
if len(traces) != 3:
msg = f"miniseed file {fname} has {len(traces)} traces, but should have 3."
raise ValueError(msg)
found_ew, found_ns, found_vt = False, False, False
for trace in traces:
if trace.meta.channel.endswith("E") and not found_ew:
ew = TimeSeries.from_trace(trace)
found_ew = True
elif trace.meta.channel.endswith("N") and not found_ns:
ns = TimeSeries.from_trace(trace)
found_ns = True
elif trace.meta.channel.endswith("Z") and not found_vt:
vt = TimeSeries.from_trace(trace)
found_vt = True
else:
msg = f"Missing, duplicate, or incorrectly named components. See documentation."
raise ValueError(msg)
meta = {"File Name": fname}
return cls(ns, ew, vt, meta)
def _combine_horizontal_td(self, method, horizontals, azimuth):
az_rad = math.radians(azimuth)
ns = horizontals["ns"]
ew = horizontals["ew"]
if method in ["azimuth", "single-azimuth"]:
horizontal = ns.amp*math.cos(az_rad) + ew.amp*math.sin(az_rad)
else:
msg = f"method={method} has not been implemented."
raise NotImplementedError(msg)
if isinstance(ns, WindowedTimeSeries):
return WindowedTimeSeries(horizontal, ns.dt)
elif isinstance(ns, TimeSeries):
return TimeSeries(horizontal, ns.dt)
else:
raise NotImplementedError
def _combine_horizontal_td(self, method, azimuth):
"""Combine horizontal components in the time domain.
azimuth : float, optional
Azimuth (clockwise positive) from North (i.e., 0 degrees).
Returns
-------
TimeSeries
Representing the combined horizontal components.
"""
az_rad = math.radians(azimuth)
if method in ["azimuth", "single-azimuth"]:
horizontal = self.ns._amp * \
math.cos(az_rad) + self.ew._amp*math.sin(az_rad)
else:
msg = f"method={method} has not been implemented."
raise NotImplementedError(msg)
return TimeSeries(horizontal, self.ns.dt)
def from_saf(cls, fname):
"""Create `Sensor3c` object from a SAF ASCII file.
Parameters
---------
fname : str
Name of the SESAME ASCII (SAF) file.
Returns
-------
Sensor3c
Instantiated `Sensor3c` object.
"""
meta = {}
meta["File Name"] = fname
# This is the default value if a project name is not provided.
meta["project_name"] = PROJECT_NAME
meta["evt_x"] = EVT_X
meta["evt_y"] = EVT_Y
meta["evt_z"] = EVT_Z
with open(fname) as fsaf:
# Look for some parameters in the header and
# for the line where data start.
for num, line in enumerate(fsaf, 1):
spl = line.split(sep=SAF_SEP)
# Remove all white spaces
spl = [s.replace(" ", "") for s in spl]
if "####----" in line:
# Data should start from here
data_start = num
break
if spl:
# List is not empty
# print(spl)
if spl[0] == "SAMP_FREQ":
# Collect the sampling frequency
# CHECK HERE IF THE SAMPLING FREQUENCY IS OK!
samp_freq = float(spl[1])
elif spl[0] == "PROJECT_NAME":
try:
# Collect the name of the project
project_name = spl[1]
except IndexError:
# No name provided for the project
project_name = "None"
meta["project_name"] = project_name
elif spl[0] == "START_TIME":
# print(spl[1])
YYYY = int(spl[1][:4])
MM = int(spl[1][4:6])
DD = int(spl[1][6:8])
hh = int(spl[1][8:10])
mm = int(spl[1][10:12])
ss = int(spl[1][12:14])
# print(YYYY, MM, DD)
starttime = obspy.UTCDateTime(YYYY, MM, DD, hh, mm, ss)
meta["starttime"] = (spl[1][:4]+"/"+spl[1][4:6]+"/"+spl[1][6:8]+" "
+spl[1][8:10]+":"+spl[1][10:12]+":"+spl[1][12:14])
elif spl[0] == "EVT_X":
meta["evt_x"] = float(spl[1])
elif spl[0] == "EVT_Y":
meta["evt_y"] = float(spl[1])
elif spl[0] == "EVT_Z":
meta["evt_z"] = float(spl[1])
# Read the dataset unsing pandas
data = pd.read_csv(fname, sep=r"\s+", skiprows=data_start, header=None, float_precision="round_trip")
data.rename(columns={0: "vt",1: "ns", 2:"ew"}, inplace=True)
trace_ew = obspy.Trace()
trace_ew.data = data["ew"].to_numpy()
trace_ew.stats.sampling_rate = samp_freq
trace_ew.stats.starttime = starttime
ew = TimeSeries.from_trace(trace_ew)
trace_ns = obspy.Trace()
trace_ns.data = data["ns"].to_numpy()
trace_ns.stats.sampling_rate = samp_freq
trace_ns.stats.starttime = starttime
ns = TimeSeries.from_trace(trace_ns)
trace_vt = obspy.Trace()
trace_vt.data = data["vt"].to_numpy()
trace_vt.stats.sampling_rate = samp_freq
trace_vt.stats.starttime = starttime
vt = TimeSeries.from_trace(trace_vt)
return cls(ns, ew, vt, meta)
def from_mseed(cls, fname=None, fnames_1c=None):
"""Create 3-component sensor (Sensor3c) object from .mseed file.
Parameters
----------
fname : str, optional
Name of miniseed file, full path may be used if desired.
The file should contain three traces with the
appropriate channel names. Refer to the `SEED` Manual
`here <https://www.fdsn.org/seed_manual/SEEDManual_V2.4.pdf>`_.
for specifics, default is `None`.
fnames_1c : dict, optional
Some data acquisition systems supply three separate miniSEED
files rather than a single combined file. To use those types
of files, simply specify the three files in a `dict` of
the form `{'e':'east.mseed', 'n':'north.mseed',
'z':'vertical.mseed'}`, default is `None`.
Returns
-------
Sensor3c
Initialized 3-component sensor object.
Raises
------
ValueError
If both `fname` and `fname_verbose` are `None`.
"""
if fnames_1c is None and fname is None:
msg = "`fnames_1c` and `fname` cannot both be `None`."
raise ValueError(msg)
if fnames_1c is not None:
trace_list = []
for key in ["e", "n", "z"]:
stream = obspy.read(fnames_1c[key], format="MSEED")
if len(stream) > 1:
msg = f"File {fnames_1c[key]} contained {len(stream)}"
msg += "traces, rather than 1 as was expected."
raise IndexError(msg)
trace = stream[0]
if trace.meta.channel[-1] != key.capitalize():
msg = "Component indicated in the header of "
msg += f"{fnames_1c[key]} is {trace.meta.channel[-1]} "
msg += f"which does not match the key {key} specified. "
msg += "Ignore this warning only if you know "
msg += "your digitizer's header is incorrect."
warnings.warn(msg)
trace.meta.channel = trace.meta.channel[:-1] + \
key.capitalize()
trace_list.append(trace)
traces = obspy.Stream(trace_list)
else:
traces = obspy.read(fname, format="MSEED")
if len(traces) != 3:
msg = f"miniseed file {fname} has {len(traces)} traces, but should have 3."
raise ValueError(msg)
found_ew, found_ns, found_vt = False, False, False
for trace in traces:
if trace.meta.channel.endswith("E") and not found_ew:
ew = TimeSeries.from_trace(trace)
found_ew = True
elif trace.meta.channel.endswith("N") and not found_ns:
ns = TimeSeries.from_trace(trace)
found_ns = True
elif trace.meta.channel.endswith("Z") and not found_vt:
vt = TimeSeries.from_trace(trace)
found_vt = True
else:
msg = "Missing, duplicate, or incorrectly named components. See documentation."
raise ValueError(msg)
meta = {"File Name": fname}
return cls(ns, ew, vt, meta)