The mseedlib package allows for reading and writing of miniSEED formatted data, which is commonly used for seismological and other geophysical time series data.
The module leverages the C-language libmseed for most of the heavy data format and manipulation work.
The releases should be installed
directly from PyPI with, for example, pip install mseedlib
.
The package does not depend on anything other than the Python standard library.
Working programs for a variety of use cases ca be found in the examples directory of the repository.
Read a file and print details from each record:
from mseedlib import MS3RecordReader,TimeFormat
input_file = 'testdata-3channel-signal.mseed3'
with MS3RecordReader(input_file) as msreader:
for msr in msreader:
# Print values directly
print(f' SourceID: {msr.sourceid}, record length {msr.reclen}')
print(f' Start Time: {msr.starttime_str(timeformat=TimeFormat.ISOMONTHDAY_SPACE_Z)}')
print(f' Samples: {msr.samplecnt}')
# Alternatively, use the library print function
msr.print()
Read a file into a trace list and print the list:
from mseedlib import MSTraceList
input_file = 'testdata-3channel-signal.mseed3'
mstl = MSTraceList(input_file)
# Print the trace list using the library print function
mstl.print(details=1, gaps=True)
# Alternatively, traverse the data structures and print each trace ID and segment
for traceid in mstl.traceids():
print(traceid)
for segment in traceid.segments():
print(' ', segment)
Writing miniSEED requires specifying a "record handler" function that is a callback to consume, and do whatever you want, with generated records.
Simple example of writing multiple channels of data:
import math
from mseedlib import MSTraceList, timestr2nstime
# Generate synthetic sinusoid data, starting at 0, 45, and 90 degrees
data0 = list(map(lambda x: int(math.sin(math.radians(x)) * 500), range(0, 500)))
data1 = list(map(lambda x: int(math.sin(math.radians(x)) * 500), range(45, 500 + 45)))
data2 = list(map(lambda x: int(math.sin(math.radians(x)) * 500), range(90, 500 + 90)))
mstl = MSTraceList()
sample_rate = 40.0
start_time = timestr2nstime("2024-01-01T15:13:55.123456789Z")
format_version = 2
record_length = 512
# Add synthetic data to the trace list
mstl.add_data(sourceid="FDSN:XX_TEST__B_S_0",
data_samples=data0, sample_type='i',
sample_rate=sample_rate, start_time=start_time)
mstl.add_data(sourceid="FDSN:XX_TEST__B_S_0",
data_samples=data1, sample_type='i',
sample_rate=sample_rate, start_time=start_time)
mstl.add_data(sourceid="FDSN:XX_TEST__B_S_0",
data_samples=data2, sample_type='i',
sample_rate=sample_rate, start_time=start_time)
# Record handler called for each generated record
def record_handler(record, handler_data):
handler_data['fh'].write(record)
output_file = 'output.mseed'
with open(output_file, 'wb') as file_handle:
# Generate miniSEED records
mstl.pack(record_handler,
{'fh':file_handle},
flush_data=True)
The package functionality and exposed API are designed to support the most
common use cases of reading and writing miniSEED data using libmseed
.
Extensions of data handling beyond the functionality of the library are
out-of-scope for this package. Furthermore, the naming of functions,
classes, arguments, etc. follows the naming used in the library in order
to reference their fundamentals at the C level if needed; even though this
leaves some names distinctly non-Pythonic.
In a nutshell, the goal of this package is to provide just enough of a Python
layer to libmseed
to handle the most common cases of miniSEED data without
needing to know any of the C-level details.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Copyright (C) 2024 Chad Trabant, EarthScope Data Services