lydwhitt-tools 1.1.1

Petrology tools

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!

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Install

pip install lydwhitt-tools

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Available tools

gechemical_filter(df, phase, total_perc=None, percentiles=None): This function is used to filter geochemical datasets using the Mahalanobis distance method in two passes. Please note the fuction filters out rows with totals <96 (default) prior to performing the mahalnobis test passes but re-adds them after processing so they can be plotted. dataframes will need filtering for this and both test results after function is used.

KDE(df, 'column') : This function creates a plottable KDE line for a column of values in a dataframe using the imporved sheather jones method to establish bandwidth. This methodology uses an integrated r script rather thna the usual python computing as this is more preferable in geochemical studies.

MD(x, y, z) : This function finds the value of the first peak found using the KDE function based on a minimum height threshold (may need adjusting per dataset).

iqr_one_peak(df, 'data', z) : This function finds the MD peak as with the previous function but also gives you the Q1 and Q3 range of each dataset.

recalc(df, phase, anhydrous=True, mol_values=True) : This function calculates the apfu or cation fraction of major elment data for Plg, Cpx, Ol and Liq (WR/Glass/MI) data. anhydrous needs to be specified for Liq data and if you dont want the mol fractions in the final dataframe just add the mol_values=true.

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))

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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.

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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

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License

This project is licensed under the MIT License.