GeoSeis

A Python package for exploring seismic waveform datasets and their station metadata. GeoSeis can discover MiniSEED files, summarize waveform records by station and channel, inspect StationXML metadata, and calculate station geometry.

Installation

Install the published package with pip:

python -m pip install geoseis

To work from a source checkout, install the development dependencies too:

poetry install --with dev
poetry run pytest

The dev group contains pytest and Twine. These tools are used to test and publish GeoSeis; they are not required to use the package.

Configure Data Paths

GeoSeis reads paths from GEOSEIS_-prefixed environment variables or a .env file in the current working directory. Environment variables take precedence. Copy the example file and update its values for your machine:

cp .env.example .env

Set the paths in .env:

GEOSEIS_PROJECT_ROOT=/absolute/path/to/your/project
GEOSEIS_RAW_DATA_DIR=/absolute/path/to/your/miniseed/data
GEOSEIS_RAW_DIR=/absolute/path/to/your/raw/metadata

The local .env file is ignored by Git. You can also define these variables in your shell or deployment environment instead. The settings values are pathlib.Path objects.

Quick Start

from geoseis.configs.configs import GeoSeisSettings
from geoseis.io.dataset_inventory import DatasetInventory

settings = GeoSeisSettings()
inventory = DatasetInventory(settings)

waveform_files = inventory.find_all_files()
stations = inventory.build_stations(waveform_files)
channels = inventory.build_channels()
channel_metadata = channels.get_info()

station = stations[("LK", "LKG01")]
channel_summary = station.get_aggregate()
channel_coverage = station.get_coverage()

build_stations() returns a mapping keyed by (network_code, station_code). Each StationData provides summaries for its waveform records. build_channels() reads the configured StationXML files; get_info() returns their channel metadata as a pandas DataFrame.

Development

Run the test suite from the repository root:

poetry run pytest