| Name | pymseed JSON |
| Version |
0.0.1
JSON |
| download |
| home_page | None |
| Summary | A Python package for reading and writing miniSEED formatted data |
| upload_time | 2025-08-05 21:37:07 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | None |
| keywords |
seismology
miniseed
mseed
data
waveform
seismic
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# pymseed - a Python package to read and write miniSEED formatted data
The pymseed package allows for reading and writing of miniSEED
time series data. Both [miniSEED version 2](https://fdsn.org/pdf/SEEDManual_V2.4.pdf)
(defined in the SEED standard) and [miniSEED version 3](https://docs.fdsn.org/projects/miniseed3)
are supported.
The package is based on the C-language [libmseed](https://earthscope.github.io/libmseed)
for most of the data format and manipulation work.
## Installation
The [releases](https://pypi.org/project/pymseed/) should be installed
directly from PyPI with, for example, `pip install pymseed`.
The package is built using [CFFI](https://cffi.readthedocs.io/) and supports
multiple Python implementations including CPython and PyPy for broad usability.
If using numpy features use optional dependency "numpy" or install it independently
e.g. `pip install pymseed[numpy]`.
For package develop use optional dependency "dev" for needed dependencies
e.g. `pip install pymseed[dev]`.
## Example usage
Working programs for a variety of use cases ca be found in the
[examples](https://github.com/EarthScope/pymseed/tree/main/examples) directory of the repository.
Read a file and print details from each record:
```Python
from pymseed 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:
```Python
from pymseed import MS3TraceList
input_file = 'testdata-3channel-signal.mseed3'
mstl = MS3TraceList(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:
```Python
import math
from pymseed import MS3TraceList, 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 = MS3TraceList()
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_1",
data_samples=data0, sample_type='i',
sample_rate=sample_rate, start_time=start_time)
mstl.add_data(sourceid="FDSN:XX_TEST__B_S_2",
data_samples=data1, sample_type='i',
sample_rate=sample_rate, start_time=start_time)
mstl.add_data(sourceid="FDSN:XX_TEST__B_S_3",
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},
format_version=format_version,
record_length=record_length,
flush_data=True)
```
## Package design rationale
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. often 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.
## License
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](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) 2025 EarthScope Data Services
Raw data
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"description": "# pymseed - a Python package to read and write miniSEED formatted data\n\nThe pymseed package allows for reading and writing of miniSEED\ntime series data. Both [miniSEED version 2](https://fdsn.org/pdf/SEEDManual_V2.4.pdf)\n(defined in the SEED standard) and [miniSEED version 3](https://docs.fdsn.org/projects/miniseed3)\nare supported.\n\nThe package is based on the C-language [libmseed](https://earthscope.github.io/libmseed)\nfor most of the data format and manipulation work.\n\n## Installation\n\nThe [releases](https://pypi.org/project/pymseed/) should be installed\ndirectly from PyPI with, for example, `pip install pymseed`.\n\nThe package is built using [CFFI](https://cffi.readthedocs.io/) and supports\nmultiple Python implementations including CPython and PyPy for broad usability.\n\nIf using numpy features use optional dependency \"numpy\" or install it independently\ne.g. `pip install pymseed[numpy]`.\n\nFor package develop use optional dependency \"dev\" for needed dependencies\ne.g. `pip install pymseed[dev]`.\n\n## Example usage\n\nWorking programs for a variety of use cases ca be found in the\n[examples](https://github.com/EarthScope/pymseed/tree/main/examples) directory of the repository.\n\nRead a file and print details from each record:\n```Python\nfrom pymseed import MS3RecordReader,TimeFormat\n\ninput_file = 'testdata-3channel-signal.mseed3'\n\nwith MS3RecordReader(input_file) as msreader:\n for msr in msreader:\n # Print values directly\n print(f' SourceID: {msr.sourceid}, record length {msr.reclen}')\n print(f' Start Time: {msr.starttime_str(timeformat=TimeFormat.ISOMONTHDAY_SPACE_Z)}')\n print(f' Samples: {msr.samplecnt}')\n\n # Alternatively, use the library print function\n msr.print()\n```\n\nRead a file into a trace list and print the list:\n```Python\nfrom pymseed import MS3TraceList\n\ninput_file = 'testdata-3channel-signal.mseed3'\n\nmstl = MS3TraceList(input_file)\n\n# Print the trace list using the library print function\nmstl.print(details=1, gaps=True)\n\n# Alternatively, traverse the data structures and print each trace ID and segment\nfor traceid in mstl.traceids():\n print(traceid)\n\n for segment in traceid.segments():\n print(' ', segment)\n```\n\nWriting miniSEED requires specifying a \"record handler\" function that is\na callback to consume, and do whatever you want, with generated records.\n\nSimple example of writing multiple channels of data:\n```Python\nimport math\nfrom pymseed import MS3TraceList, timestr2nstime\n\n# Generate synthetic sinusoid data, starting at 0, 45, and 90 degrees\ndata0 = list(map(lambda x: int(math.sin(math.radians(x)) * 500), range(0, 500)))\ndata1 = list(map(lambda x: int(math.sin(math.radians(x)) * 500), range(45, 500 + 45)))\ndata2 = list(map(lambda x: int(math.sin(math.radians(x)) * 500), range(90, 500 + 90)))\n\nmstl = MS3TraceList()\n\nsample_rate = 40.0\nstart_time = timestr2nstime(\"2024-01-01T15:13:55.123456789Z\")\nformat_version = 2\nrecord_length = 512\n\n# Add synthetic data to the trace list\nmstl.add_data(sourceid=\"FDSN:XX_TEST__B_S_1\",\n data_samples=data0, sample_type='i',\n sample_rate=sample_rate, start_time=start_time)\n\nmstl.add_data(sourceid=\"FDSN:XX_TEST__B_S_2\",\n data_samples=data1, sample_type='i',\n sample_rate=sample_rate, start_time=start_time)\n\nmstl.add_data(sourceid=\"FDSN:XX_TEST__B_S_3\",\n data_samples=data2, sample_type='i',\n sample_rate=sample_rate, start_time=start_time)\n\n# Record handler called for each generated record\ndef record_handler(record, handler_data):\n handler_data['fh'].write(record)\n\noutput_file = 'output.mseed'\n\nwith open(output_file, 'wb') as file_handle:\n # Generate miniSEED records\n mstl.pack(record_handler,\n {'fh':file_handle},\n format_version=format_version,\n record_length=record_length,\n flush_data=True)\n```\n\n## Package design rationale\n\nThe package functionality and exposed API are designed to support the most\ncommon use cases of reading and writing miniSEED data using `libmseed`.\nExtensions of data handling beyond the functionality of the library are\nout-of-scope for this package. Furthermore, the naming of functions, classes,\narguments, etc. often follows the naming used in the library in order to\nreference their fundamentals at the C level if needed; even though this leaves\nsome names distinctly non-Pythonic.\n\nIn a nutshell, the goal of this package is to provide just enough of a Python\nlayer to `libmseed` to handle the most common cases of miniSEED data without\nneeding to know any of the C-level details.\n\n## License\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n[http://www.apache.org/licenses/LICENSE-2.0](http://www.apache.org/licenses/LICENSE-2.0)\n\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License.\n\nCopyright (C) 2025 EarthScope Data Services\n",
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