Skip to main content

TimeSeries Extensions for SGN Framework

Project description

SGN-TS

SGN-TS extends the SGN streaming pipeline framework with time-series data types: precise offset-based timing, uniformly sampled buffers, frame alignment across multiple channels, and a library of signal processing elements.

Installation

pip install sgn-ts

For PyTorch-accelerated operations (resampling, array backends):

pip install sgn-ts[torch]

Quick Example

Generate a sine wave, amplify it, and collect the output:

from sgn import Pipeline
from sgnts.sources import FakeSeriesSource
from sgnts.transforms import Amplify
from sgnts.sinks import TSFrameCollectSink

src = FakeSeriesSource(
    name="src",
    source_pad_names=["out"],
    signal_type="sin",
    rate=2048,
    duration=2,
)
amp = Amplify(name="amp", factor=3.0)
snk = TSFrameCollectSink(name="snk")

Pipeline().connect(src, amp).connect(amp, snk).run()

for frame in snk.data["out"]:
    print(frame.offset, len(frame.buffers))

Documentation

Full documentation is available at docs.ligo.org/greg/sgn-ts.

Related Libraries

  • sgn: Base streaming pipeline framework
  • sgn-ligo: LIGO-specific utilities for SGN

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sgn_ts-0.9.0.tar.gz (227.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sgn_ts-0.9.0-py3-none-any.whl (97.7 kB view details)

Uploaded Python 3

File details

Details for the file sgn_ts-0.9.0.tar.gz.

File metadata

  • Download URL: sgn_ts-0.9.0.tar.gz
  • Upload date:
  • Size: 227.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.11

File hashes

Hashes for sgn_ts-0.9.0.tar.gz
Algorithm Hash digest
SHA256 3d4bbee6b7da64b39422081b911f021aa62df5df75571fdb2dd77cf6035deacd
MD5 42c5de93e449eeb6af00ea82dead82a4
BLAKE2b-256 2306cfe3295d53b219d3dfa2f9f002561a48d17b9b4a45f75d71d00af6cafa78

See more details on using hashes here.

File details

Details for the file sgn_ts-0.9.0-py3-none-any.whl.

File metadata

  • Download URL: sgn_ts-0.9.0-py3-none-any.whl
  • Upload date:
  • Size: 97.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.11

File hashes

Hashes for sgn_ts-0.9.0-py3-none-any.whl
Algorithm Hash digest
SHA256 59b0bf3c62a9fcac3871672c0a1e5d6969848aa208fb0d5425ec9d6ac61f4660
MD5 3bf02464930ba5e0ecab0d5acdc61db4
BLAKE2b-256 d7da99be4a712bafb0b32a85af82d5a48e5b9a8c33fb1864c5aa49369a8db02d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page