Official Resources
- PyPI: https://pypi.org/project/bandplot/
- Documentation: Included in package
- License: Open source
Overview
bandplot is a Python package for electron band structure, DOS, and phonon band structure/DOS plotting from VASPKIT or phonopy results. It provides automated plotting with two main commands: bandplot for electronic band structures and phononplot for phonon dispersions.
Scientific domain: Band structure and phonon plotting from VASPKIT/phonopy
Target user community: Researchers using VASPKIT or phonopy who need automated publication-quality plots
Theoretical Methods
- Band structure plotting from VASPKIT output
- DOS plotting from VASPKIT output
- Phonon band structure from phonopy
- Phonon DOS from phonopy
- matplotlib-based visualization
Capabilities (CRITICAL)
- Electronic band structure plotting
- Electronic DOS plotting
- Phonon band structure plotting
- Phonon DOS plotting
- VASPKIT output parsing
- phonopy output parsing
- PyPI installable
Sources: PyPI, GitHub
Key Strengths
VASPKIT Integration:
- Direct VASPKIT output parsing
- Standard VASPKIT workflow
- No manual data extraction
- Consistent with VASPKIT conventions
Dual Electronic/Phonon:
- Electronic band + DOS
- Phonon band + DOS
- Same tool for both
- Consistent style
PyPI Installable:
- pip install bandplot
- No manual setup
- Standard Python package
- Easy to use
Inputs & Outputs
-
Input formats:
- VASPKIT band data
- VASPKIT DOS data
- phonopy band data
- phonopy DOS data
-
Output data types:
- Band structure plots
- DOS plots
- Phonon band plots
- Phonon DOS plots
Interfaces & Ecosystem
- VASPKIT: Primary data source
- phonopy: Phonon data source
- Matplotlib: Visualization
- Python: Core language
Performance Characteristics
- Speed: Fast (plotting)
- Accuracy: DFT-level
- System size: Any
- Memory: Low
Computational Cost
- Plotting: Seconds
- DFT pre-requisite: Hours (separate)
- Typical: Very efficient
Limitations & Known Constraints
- VASPKIT dependent: Requires VASPKIT-processed data
- Plotting only: No analysis features
- Limited customization: Standard plots
- Small community: Niche tool
Comparison with Other Codes
- vs sumo: bandplot is VASPKIT-specific, sumo is general VASP
- vs plot4dft: bandplot is VASPKIT+phonopy, plot4dft is raw VASP/QE
- vs VASPKIT plotting: bandplot extends VASPKIT plotting capabilities
- Unique strength: PyPI-installable band+DOS+phonon plotting from VASPKIT/phonopy output
Application Areas
Publication Figures:
- Band structure plots
- DOS plots
- Phonon dispersion plots
- Combined figures
VASPKIT Workflow:
- Post-VASPKIT plotting
- Standardized output
- Consistent formatting
- Quick publication figures
Best Practices
VASPKIT Setup:
- Use VASPKIT to generate band/DOS data first
- Follow VASPKIT conventions
- Use appropriate k-path
- Check data quality before plotting
Plotting:
- Use default settings for quick plots
- Customize for publication
- Validate against known systems
- Export in vector format
Community and Support
- PyPI package
- Open source
- Limited documentation
- Niche community
Verification & Sources
Primary sources:
- PyPI: https://pypi.org/project/bandplot/
Confidence: VERIFIED
Verification status: ✅ VERIFIED
- Source code: ACCESSIBLE (PyPI)
- Documentation: Included in package
- Specialized strength: PyPI-installable band+DOS+phonon plotting from VASPKIT/phonopy output