Skip to main content

A tool to infer node locations and states from tree sequences.

Project description

fastgaia (v0.1.2)

Designed and implemented by Chris Talbot, based on gaia from Grundler et al., pre-print here, GitHub here.

fastgaia is a Python package implementation of gaia that can run up to 30x faster for large tree sequences. fastgaia offers a command-line interface and a comprehensive Python function for inferring the geographic locations of ancestors given a tree sequence. After installing, use fastgaia --help from terminal or fastgaia.infer_locations(...) in your Python console for more details.

Note: In simulation tests on a 20x20 plane, fastgaia infers coordinates of ancestors within 0.16 units of their correct location across all timescales - this is only 0.01 units worse than gaia. fastgaia is particularly accurate for very recent ancestors, inferring locations within 0.001 units of the locations inferred using gaia. However, it should still be noted that fastgaia provides improved efficiency at the expense of accuracy. While inferences for more nodes with more recent samples as descendants will be close in accuracy to inferences from gaia, inferences in the deep past will be increasingly inaccurate compared to gaia without sufficient temporal sampling. Accuracy of discrete state inference remains untested.

Features

  • Continuous Inference: Infers continuous locations of nodes based on provided sample locations or tree sequence individual location data.
  • Discrete Inference: Infers discrete states of nodes using a transition cost matrix.
  • Flexible Output: Outputs results in CSV format for easy analysis.

Installation

You can install fastgaia via pip:

pip install fastgaia

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

fastgaia-0.1.2.tar.gz (10.5 kB view details)

Uploaded Source

Built Distribution

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

fastgaia-0.1.2-py3-none-any.whl (10.2 kB view details)

Uploaded Python 3

File details

Details for the file fastgaia-0.1.2.tar.gz.

File metadata

  • Download URL: fastgaia-0.1.2.tar.gz
  • Upload date:
  • Size: 10.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for fastgaia-0.1.2.tar.gz
Algorithm Hash digest
SHA256 0492f1f4da255761d4a7871b1e0e5182aa234867c5cae58baf17967c850b77c6
MD5 08f3593b79f70b5295dcd4b2be1dfe97
BLAKE2b-256 b7334de30a72d233111b84ad0c77ef176ef46b09af27864d6458cb0b89ef5dfc

See more details on using hashes here.

File details

Details for the file fastgaia-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: fastgaia-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 10.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for fastgaia-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 24ab547d98f270a8fe98e51ef8a0078a1a3588d085f893b70fcba3f055b5b5ee
MD5 208549262916c551e1244ee9d0b39b29
BLAKE2b-256 6b19e6be847f7596d2971ae900d1c18df4db1106e4de967a47477102c2bff52d

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