pyrolite

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Geochemistry data analysis and visualization for igneous, metamorphic, and sedimentary rocks. Use when Claude needs to: (1) Create ternary diagrams for compositional data, (2) Plot REE spider diagrams with normalization, (3) Build TAS or other classification diagrams, (4) Apply log-ratio transforms to compositional data, (5) Calculate CIPW norms, (6) Generate Harker variation diagrams, (7) Compute element ratios and anomalies.

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Sourcesteadfastasart/geoscience-skills

Added on2026-05-16

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pyrolite - Geochemistry Analysis

Quick Reference

python

import pandas as pd
import matplotlib.pyplot as plt
from pyrolite.geochem.norm import get_reference_composition

df = pd.read_csv('samples.csv')
df.pyrochem   # Geochemistry methods
df.pyrocomp   # Compositional methods

# Normalize and plot REE
chondrite = get_reference_composition('Chondrite_McDonough1995')
ax = df.pyrochem.normalize_to(chondrite, units='ppm').pyroplot.REE(unity_line=True)

Key Modules

Module	Purpose
`pyrolite.plot`	Ternary, spider diagrams
`pyrolite.geochem.norm`	Normalization references
`pyrolite.comp`	CLR, ALR, ILR transforms
`pyrolite.plot.templates`	TAS, Pearce diagrams
`pyrolite.mineral.normative`	CIPW norm

Essential Operations

Ternary Diagram

python

ax = df[['SiO2', 'CaO', 'Na2O']].pyroplot.scatter(c='k', s=50)

TAS Diagram

python

from pyrolite.plot.templates import TAS
df['Na2O_K2O'] = df['Na2O'] + df['K2O']
ax = TAS()
ax.scatter(df['SiO2'], df['Na2O_K2O'], c='red', s=50)

REE Pattern

python

chondrite = get_reference_composition('Chondrite_McDonough1995')
ax = df.pyrochem.normalize_to(chondrite, units='ppm').pyroplot.REE(unity_line=True)

Trace Element Spider

python

pm = get_reference_composition('PM_McDonough1995')
ax = df.pyrochem.normalize_to(pm).pyroplot.spider(unity_line=True)

Compositional Transforms

python

df_closed = df.pyrocomp.renormalise(scale=100)  # Closure
df_clr = df.pyrocomp.CLR()   # Centered log-ratio
df_alr = df.pyrocomp.ALR()   # Additive log-ratio
df_ilr = df.pyrocomp.ILR()   # Isometric log-ratio

Element Ratios and Anomalies

python

df['La_Yb'] = df['La'] / df['Yb']                        # LREE/HREE
df['Eu_Eu*'] = df['Eu'] / (df['Sm'] * df['Gd']) ** 0.5   # Eu anomaly
lambdas = df.pyrochem.lambda_lnREE()                      # REE shape

CIPW Norm

python

from pyrolite.mineral.normative import CIPW_norm
norm = CIPW_norm(df)  # df must have major oxides in wt%

Harker Diagrams

python

fig, axes = plt.subplots(2, 3, figsize=(12, 8))
for ax, elem in zip(axes.flatten(), ['TiO2', 'Al2O3', 'FeO', 'MgO', 'CaO', 'Na2O']):
    ax.scatter(df['SiO2'], df[elem], c='blue', s=50)
    ax.set_xlabel('SiO2 (wt%)'); ax.set_ylabel(f'{elem} (wt%)')

Pearce Discrimination

python

from pyrolite.plot.templates import pearce_templates
ax = pearce_templates.YNb()
ax.scatter(df['Nb'], df['Y'], c='red', s=50)

Common Normalization References

Reference	Code	Use For
Chondrite	`Chondrite_McDonough1995`	REE patterns
Primitive Mantle	`PM_McDonough1995`	Trace elements
N-MORB	`NMORB_SunMcDonough1989`	Ocean basalts
Upper Crust	`UCC_RudnickGao2003`	Crustal rocks

When to Use vs Alternatives

Tool	Best For	Limitations
pyrolite	Python-native geochemistry, pandas integration, compositional transforms	Fewer built-in classification templates than GCDkit
GCDkit	Comprehensive classification diagrams, R ecosystem	R-based, not Python
PetroGraph	Quick GUI-based classification and plotting	Not scriptable, limited customization
Custom matplotlib	Full control over plot appearance	No built-in normalization or templates

Use pyrolite when you need geochemistry analysis integrated with pandas workflows, compositional log-ratio transforms, or REE normalization in Python.

Consider alternatives when you need extensive petrographic classification templates (use GCDkit), a quick GUI for classification (use PetroGraph), or only need simple scatter plots without normalization (use matplotlib directly).

Common Workflows

Geochemical classification and REE pattern analysis

Load sample data into pandas DataFrame
Close compositions with
```
df.pyrocomp.renormalise(scale=100)
```
Plot TAS diagram with
```
TAS()
```
and overlay sample data
Normalize REE to chondrite with
```
df.pyrochem.normalize_to()
```
Plot REE spider diagram with
```
df.pyroplot.REE()
```
Calculate Eu anomaly and La/Yb ratio
Generate Harker variation diagrams for major elements
Export figures for publication

Tips

Close compositions before analysis (ensure sum to 100%)
Use log-ratios (CLR/ALR/ILR) for statistical analysis
Choose appropriate normalization for spider diagrams
Check for Eu anomaly (positive = cumulate, negative = fractionation)

References

Normalization References - Reference compositions and values
Classification Schemes - TAS, Pearce, AFM diagrams

Scripts

scripts/geochemistry_plots.py - Generate common plots

pyrolite

NPX Install

Tags

SKILL.md Content

pyrolite - Geochemistry Analysis

Quick Reference

Key Modules

Essential Operations

Ternary Diagram

TAS Diagram

REE Pattern

Trace Element Spider

Compositional Transforms

Element Ratios and Anomalies

CIPW Norm

Harker Diagrams

Pearce Discrimination

Common Normalization References

When to Use vs Alternatives

Common Workflows

Geochemical classification and REE pattern analysis

Tips

References

Scripts