VGD Reader

A Python library for reading Thermo Scientific VGD (VG Data) binary files commonly used in X-ray Photoelectron Spectroscopy (XPS).

Features

• Parse single-spectrum and multi-spectrum VGD files
• Extract binding energy, kinetic energy, and intensity data
• Access acquisition parameters (pass energy, dwell time, source energy, etc.)
• Export to Excel format with metadata
• Convert to pandas DataFrame
• No wxPython or GUI dependencies - pure data processing

Installation

pip install vgd-reader

With optional dependencies for Excel export and pandas support:

pip install vgd-reader[all]

Quick Start

Basic Usage

from vgd_reader import read_vgd

# Read a VGD file
data = read_vgd("O1s_Scan.vgd")

# Access data arrays
print(data.binding_energy)      # BE values (numpy array)
print(data.intensity)           # Raw intensity counts
print(data.corrected_intensity) # Normalized intensity

# Access metadata
print(data.core_level)          # e.g., "O1s"
print(data.acquisition.pass_energy)
print(data.acquisition.source_energy)

Working with Multi-Spectrum Files

from vgd_reader import read_vgd

vgd = read_vgd("multi_spectrum.vgd")
print(f"Found {vgd.num_spectra} spectra")

for spectrum in vgd.spectra:
    print(f"{spectrum.core_level} - Index {spectrum.spectrum_index}")
    print(f"  BE range: {spectrum.be_start:.2f} to {spectrum.be_end:.2f} eV")
    print(f"  Pass energy: {spectrum.pass_energy} eV")

Export to Excel

from vgd_reader import read_vgd

data = read_vgd("sample.vgd")
data.to_excel("output.xlsx", include_metadata=True)

Convert to pandas DataFrame

from vgd_reader import read_vgd

data = read_vgd("sample.vgd")
df = data.to_dataframe()
print(df.head())

Low-Level API

For more control, use the low-level parsing functions:

from vgd_reader import parse_vgd_file, calculate_spectrum_data

# Parse raw data
parsed = parse_vgd_file("sample.vgd")
print(parsed['source_energy'])
print(parsed['pass_energy'])
print(parsed['metadata'])

# Calculate spectrum data for a specific index
calc = calculate_spectrum_data(parsed, spectrum_index=0)
be_values = calc['be_values']
intensities = calc['intensities']

API Reference

read_vgd(filepath)

Main entry point. Returns a VGDFile object.

VGDFile

• filepath: Path to the VGD file
• spectra: List of VGDSpectrum objects
• num_spectra: Number of spectra in file
• core_level: Primary core level name from filename
• binding_energy: BE array (first spectrum)
• intensity: Raw intensity array (first spectrum)
• corrected_intensity: Corrected intensity array (first spectrum)
• metadata: VGDMetadata object
• acquisition: VGDAcquisitionParams object
• to_dataframe(): Convert to pandas DataFrame
• to_excel(path): Export to Excel file

VGDSpectrum

• binding_energy: numpy array of BE values
• kinetic_energy: numpy array of KE values
• intensity: numpy array of raw counts
• corrected_intensity: numpy array of normalized data
• core_level: Core level name (e.g., "O1s")
• spectrum_index: Index in multi-spectrum files
• be_start, be_end, be_step: Energy range info
• source_energy, pass_energy: Acquisition parameters
• sample_id, title, author: Metadata
• to_dict(): Convert to dictionary

extract_core_level_name(filename)

Extract clean core level name from filename:

• "O1s_Scan.VGD" → "O1s"
• "Sr3d Scan.VGD" → "Sr3d"

File Format

VGD files use Microsoft OLE2 Compound File format (similar to older .doc files). The library extracts:

• VGData: Raw intensity values (64-bit floats)
• VGDataAxes: Spectrum dimensions for multi-spectrum files
• VGSpaceAxes: Kinetic energy start and step values
• Property Stream: Acquisition parameters (source energy, pass energy, dwell time, etc.)

Binding energy is calculated from kinetic energy using:

BE = Source_Energy - KE

Requirements

• Python ≥ 3.8
• numpy ≥ 1.20.0
• olefile ≥ 0.46
• openpyxl ≥ 3.0.0 (optional, for Excel export)
• pandas ≥ 1.3.0 (optional, for DataFrame conversion)

License

MIT License

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Related Projects

• KherveFitting - Open-source XPS data analysis software
• LMFITXPS - XPS peak fitting with lmfit
• LG4X - Line shape functions for XPS

Acknowledgments

This library was developed as part of the KherveFitting project for XPS data analysis.