Steadfastasart Geoscience Skills Mtpy

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

Converted and distributed by TomeVault — claim your Tome and manage your conversions.