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Use for VASP input generation, POTCAR handling, and parsing VASP outputs (vasprun.xml, OUTCAR, OSZICAR, PROCAR, CHGCAR, LOCPOT, EIGENVAL) via pymatgen.io.vasp and input sets.
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Structured brainstorming and ideation facilitation using proven creativity techniques. Use when users want to generate ideas, explore solutions, break through creative blocks, or need facilitated ideation sessions. Triggers include requests like 'help me brainstorm,' 'generate ideas for,' 'creative solutions to,' or 'think of alternatives.'
Use when investigating why something happened and need to distinguish correlation from causation, identify root causes vs symptoms, test competing hypotheses, control for confounding variables, or design experiments to validate causal claims. Invoke when debugging systems, analyzing failures, researching health outcomes, evaluating policy impacts, or when user mentions root cause, causal chain, confounding, spurious correlation, or asks "why did this really happen?"
Use when comparing multiple named alternatives across several criteria, need transparent trade-off analysis, making group decisions requiring alignment, choosing between vendors/tools/strategies, stakeholders need to see decision rationale, balancing competing priorities (cost vs quality vs speed), user mentions "which option should we choose", "compare alternatives", "evaluate vendors", "trade-offs", or when decision needs to be defensible and data-driven.
Use when dealing with complex systems that need simplification, identifying bottlenecks or critical failure points, redesigning architecture or processes for better performance, breaking down problems that feel overwhelming, analyzing dependencies to understand ripple effects, user mentions "this is too complex", "where's the bottleneck", "how do we redesign this", "what are the key components", or when optimization requires understanding how parts interact.
Use when optimizing multi-factor systems with limited experimental budget, screening many variables to find the vital few, discovering interactions between parameters, mapping response surfaces for peak performance, validating robustness to noise factors, or when users mention factorial designs, A/B/n testing, parameter tuning, process optimization, or experimental efficiency.
Use when you have validated symmetry groups and need to design neural network architecture that respects those symmetries. Invoke when user mentions equivariant layers, G-CNN, e3nn, steerable networks, building symmetry into model, or needs architecture recommendations for specific symmetry groups. Provides architecture patterns and implementation guidance.
| name | pymatgen-io-vasp |
| description | Use for VASP input generation, POTCAR handling, and parsing VASP outputs (vasprun.xml, OUTCAR, OSZICAR, PROCAR, CHGCAR, LOCPOT, EIGENVAL) via pymatgen.io.vasp and input sets. |
| metadata | {"short-description":"pymatgen VASP IO"} |
Pymatgen VASP IO supports input generation, standard input sets, and output parsing for VASP calculations.
Ensure pymatgen is installed in your Python environment:
pip install pymatgen
# or
conda install -c conda-forge pymatgen
Example usage pattern:
from pymatgen.io.vasp import Vasprun, Outcar
# your code here
Vasprun, Outcar, Oszicar, Eigenval, ProcarExecutable examples in the scripts/ directory:
2017-04-14-Inputs_and_Analysis_of_VASP_runs.py - VASP input setup and output analysis.Note: POTCAR files are not bundled; confirm pseudopotential paths before use. Note: Do not execute VASP unless explicitly requested.
Detailed reference material (load as needed):
references/vasp-io.md - VASP IO classes and examplesreferences/docs/pymatgen.io.vasp.md - Local API docs