Skip to main content

Petrology tools

Project description

Lydwhitt_tools

A collection of functions and tools I have developed and find useful during my volcanology PhD.

Whilst I have a lot of tools and functions on my computer that I use regularly, I haven't yet put them all in a place to help others. There are a lot of very simple tasks that waste time, which I've created tools to complete, and I will be adding them to this repository over time.

I started collating this in August 2025 — so bear with me whilst I get it going!


Install

pip install lydwhitt-tools


Quickstart

Here’s the simplest way to run the geochemical filter tool: import pandas as pd import lydwhitt_tools as lwt Load your geochemical dataset df = pd.read_csv("my_data.csv") Apply the filter (defaults: total_perc=96, percentiles=(98, 98)) filtered_df = lwt.geochemical_filter(df, phase="Cpx") print(filtered_df.head())


Detailed Usage

The geochemical_filter function filters geochemical datasets using the Mahalanobis distance method in two passes.

Function signature: lwt.geochemical_filter(df, phase, total_perc=None, percentiles=None)

Parameters:

  • phase (str) – e.g., "Cpx", "Plg", "Liq". Must match the suffix used after oxide wt% values in your dataset.
  • total_perc (float, optional) – Minimum total oxide percentage allowed. Defaults to 96.
  • percentiles (int, float, or tuple, optional) – Percentile cutoffs for Pass 1 and Pass 2.
    • Single value applies to both passes (e.g., percentiles=98).
    • Tuple gives different cutoffs for each pass (e.g., percentiles=(95, 99)).

Example: Use different percentiles for each pass filtered_df = lwt.geochemical_filter(df, phase="Plg", total_perc=97, percentiles=(95, 99))


Output

The function returns the filtered DataFrame, including flags for each pass:

  • Mahalanobis – Mahalanobis distance for each row in the given pass.
  • P1_Outlier – Boolean flag indicating if the row was an outlier in Pass 1.
  • P2_Outlier – Boolean flag indicating if the row was an outlier in Pass 2.

Features Coming Soon

This repository will grow to include: -formula recalculations for different phases -simple plotting frameworks -data re-oragnisation tools for popular gothermobarometry packages


License

This project is licensed under the MIT License.

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

lydwhitt_tools-0.1.0.tar.gz (4.7 kB view details)

Uploaded Source

Built Distribution

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

lydwhitt_tools-0.1.0-py3-none-any.whl (5.2 kB view details)

Uploaded Python 3

File details

Details for the file lydwhitt_tools-0.1.0.tar.gz.

File metadata

  • Download URL: lydwhitt_tools-0.1.0.tar.gz
  • Upload date:
  • Size: 4.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.9

File hashes

Hashes for lydwhitt_tools-0.1.0.tar.gz
Algorithm Hash digest
SHA256 d49304e6b189ea74a0a0e32888b0a5e2e434b02c4cb1e5adab161c8ebeaef287
MD5 40ebc091736198c833d4fd321a81d2a9
BLAKE2b-256 e712f7d2b6203b7a7b095beab9780d591136645b2cd7f5e3bb879a5ca429f423

See more details on using hashes here.

File details

Details for the file lydwhitt_tools-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: lydwhitt_tools-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 5.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.9

File hashes

Hashes for lydwhitt_tools-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 95f7ce910bc52709e479eca3cbf765155e772561be4eb3739abc7b5b81e01ac2
MD5 809449e740fe8794d64625c53bbfc62f
BLAKE2b-256 d3db92a7067d15615fa381847fd0a3511191176df38da49cbc86db636fee6361

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