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 |
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