mtpy

name: mtpy description: | Magnetotelluric data processing and modelling. Read EDI files, analyze MT responses, perform inversions, and visualize resistivity models. Use when Claude needs to: (1) Read/write EDI files, (2) Process MT impedance tensors, (3) Analyze phase tensors and dimensionality, (4) Plot apparent resistivity and phase curves, (5) Create pseudosections, (6) Perform strike analysis, (7) Run 1D inversions, (8) Prepare data for 2D/3D modelling. version: 1.0.0 author: Geoscience Skills license: MIT tags: [Magnetotellurics, MT, EDI, Impedance Tensor, EM, Geophysics] dependencies: [mtpy>=2.0.0, numpy, matplotlib] complements: [simpeg, pyvista] workflow_role: analysis

mtpy - Magnetotelluric Analysis

Quick Reference

from mtpy import MT, MTCollection

# Read single station
mt = MT('station001.edi')

# Access data
Z = mt.Z                         # Complex impedance tensor
freq = mt.frequency              # Frequency array
rho_xy = mt.apparent_resistivity[:, 0, 1]  # Apparent resistivity

# Station info
print(mt.station, mt.latitude, mt.longitude)

# Write EDI
mt.write_edi('output.edi')

Key Classes

Essential Operations

Load and Inspect EDI

from mtpy import MT

mt = MT('station001.edi')
print(f"Station: {mt.station}")
print(f"Location: ({mt.latitude}, {mt.longitude})")
print(f"Frequencies: {len(mt.frequency)} points")
print(f"Period range: {1/mt.frequency.max():.2f} - {1/mt.frequency.min():.0f} s")

Load Multiple Stations

from mtpy import MTCollection

mc = MTCollection()
mc.from_edis('survey_data/*.edi')
print(f"Loaded {len(mc)} stations")

for station in mc:
    print(f"  {station.station}: ({station.latitude:.4f}, {station.longitude:.4f})")

Plot MT Response

from mtpy import MT
from mtpy.imaging import PlotMTResponse

mt = MT('station001.edi')
plot = PlotMTResponse(mt)
plot.plot()  # Apparent resistivity and phase

Phase Tensor Analysis

from mtpy import MT
from mtpy.imaging import PlotPhaseTensor

mt = MT('station001.edi')

# Get phase tensor parameters
phi_min = mt.phase_tensor.phimin
phi_max = mt.phase_tensor.phimax
skew = mt.phase_tensor.skew       # 3D indicator

# Plot
pt = PlotPhaseTensor(mt)
pt.plot()

Rotate Impedance Tensor

from mtpy import MT

mt = MT('station001.edi')
mt_rotated = mt.rotate(30)        # 30 degrees clockwise
mt.rotate_to_strike()             # Auto-rotate to geoelectric strike

Create Pseudosection

from mtpy import MTCollection
from mtpy.imaging import PlotPseudoSection

mc = MTCollection()
mc.from_edis('profile/*.edi')

ps = PlotPseudoSection(mc)
ps.plot(plot_type='apparent_resistivity', mode='te')  # or 'tm', 'det'

Export Data

from mtpy import MT
import pandas as pd

mt = MT('station001.edi')

# Export to CSV
df = pd.DataFrame({
    'frequency': mt.frequency,
    'rho_xy': mt.apparent_resistivity[:, 0, 1],
    'rho_yx': mt.apparent_resistivity[:, 1, 0],
    'phase_xy': mt.phase[:, 0, 1],
    'phase_yx': mt.phase[:, 1, 0]
})
df.to_csv('mt_data.csv', index=False)

# Export for ModEM
mt.write_modem('station001.dat')

Impedance Tensor Components

Phase Tensor Parameters

When to Use vs Alternatives

Use mtpy when you need end-to-end MT analysis in Python: reading EDI files, QC, phase tensor analysis, pseudosections, and preparing data for ModEM or other inversion codes.

Consider alternatives when you need time-series to impedance processing from raw field data (use EMTF), or a fully integrated commercial inversion package with GUI (use WinGLink).

Common Workflows

Load, QC, and analyze MT station data

• Load EDI file(s) with MT() or MTCollection()
• Inspect station metadata (location, frequency range)
• Plot apparent resistivity and phase with PlotMTResponse
• Check phase tensor parameters for dimensionality (skew > 5 = 3D)
• Identify and mask noisy data points using error thresholds
• Rotate impedance tensor to geoelectric strike if needed
• Create pseudosection for profile data
• Export cleaned data for inversion (ModEM format)

Common Issues

References

• EDI Format - EDI file structure and sections
• Plotting Options - Visualization parameters and styles

Scripts

• scripts/mt_analysis.py - MT data analysis and QC