gpumdkit-visualization

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Use when plotting molecular dynamics simulation results, NEP training data, or transport properties. Supports 31+ plot types including training loss, parity plots, MSD, SDC, RDF, thermodynamic properties, Arrhenius plots, phonon DOS, thermal conductivity, and descriptor visualization. Use when user asks about: plotting, visualization, training results, MSD plot, RDF plot, thermal conductivity, Arrhenius plot, or NEP training visualization.

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GPUMDkit Visualization

Quick Reference

gpumdkit.sh -plt <type>              # Display plot interactively
gpumdkit.sh -plt <type> save         # Save plot as PNG
gpumdkit.sh -plt <type> -h           # Get help for specific plot

Plot Categories

NEP Training & Evaluation (13 plot types)

Command	Input Files	Description
`train`	`loss.out`, `*_train.out`	Training loss curves and parity plots
`prediction` / `test`	`*_test.out`	Test set parity plots
`train_test`	`_train.out`, `_test.out`	Combined train/test parity plots
`parity_density`	`*_train.out`	Density-based parity plots for large datasets
`train_density`	`loss.out`, `*_train.out`	Training with density visualization
`force_errors`	`force_train.out`	Force error analysis
`restart`	`nep.restart`	NEP restart file visualization
`charge`	`charge_train.out`	Charge distribution (qNEP)
`born_charge` / `bec`	`bec_train.out`, `bec_test.out`	Born effective charges
`dimer`	NEP model	Dimer interaction curves
`des`	`descriptors.npy`	Descriptor PCA/UMAP visualization
`lr`	`loss.out` (gnep)	Learning rate decay

# Training results
gpumdkit.sh -plt train
gpumdkit.sh -plt prediction
gpumdkit.sh -plt force_errors

# Descriptor visualization (requires prior calculation)
gpumdkit.sh -calc des train.xyz descriptors.npy nep.txt Li
gpumdkit.sh -plt des pca
gpumdkit.sh -plt des umap

# Dimer plot
gpumdkit.sh -plt dimer Li Li nep.txt

Transport Properties (10 plot types)

Command	Input Files	Description
`msd`	`msd.out`	Mean square displacement
`msd_conv`	`msd_step*.out`	MSD convergence check
`msd_all`	`msd.out` (all_groups)	MSD per species
`sdc`	`msd.out`	Self-diffusion coefficient
`msd_sdc`	`msd.out`	MSD and SDC combined
`sigma` / `arrhenius_sigma`	`*K/` directories	Arrhenius ionic conductivity
`D` / `arrhenius_d`	`*K/` directories	Arrhenius diffusivity
`sigma_xyz`	`*K/` directories	Directional Arrhenius conductivity
`D_xyz`	`*K/` directories	Directional Arrhenius diffusivity
`doas`	`doas.out`	Density of atomistic states

# MSD and diffusion
gpumdkit.sh -plt msd
gpumdkit.sh -plt sdc
gpumdkit.sh -plt msd_sdc

# MSD for all species (requires all_groups in run.in)
gpumdkit.sh -plt msd_all Li P S

# Arrhenius plots (requires temperature-organized directories)
# Directory structure: 300K/, 350K/, 400K/, ... each containing msd.out
gpumdkit.sh -plt arrhenius_sigma
gpumdkit.sh -plt arrhenius_d

# DOAS visualization (requires prior calculation)
gpumdkit.sh -plt doas doas.out Li

Structural Analysis (9 plot types)

Command	Input Files	Description
`thermo`	`thermo.out`	Thermodynamic properties
`thermo2`	`thermo.out`	Alternative thermo style
`thermo3`	`thermo.out`	Third thermo style
`rdf`	`rdf.out`	Radial distribution function
`rdf_pmf`	`rdf.out`	RDF + potential of mean force
`vac`	`sdc.out`	Velocity autocorrelation
`cohesive`	`cohesive.out`	Cohesive energy curve
`net_force`	extxyz file	Net force distribution
`plane-grid`	`model.xyz`, `displacements.dat`	Displacement grid visualization

# Thermodynamic properties
gpumdkit.sh -plt thermo

# RDF analysis
gpumdkit.sh -plt rdf
gpumdkit.sh -plt rdf 2              # Specific column
gpumdkit.sh -plt rdf_pmf 300        # With PMF at 300K

# Plane-grid displacement
gpumdkit.sh -plt plane-grid -i model.xyz -d displacements.dat -e Pb Sr

Heat Transport (4 plot types)

Command	Input Files	Description
`emd`	EMD outputs	EMD thermal conductivity
`nemd`	NEMD outputs	NEMD thermal transport
`hnemd`	HNEMD outputs	HNEMD thermal transport
`viscosity`	`viscosity.out`	Viscosity components

# EMD thermal conductivity
gpumdkit.sh -plt emd x

# NEMD thermal transport
# Parameters: real_length scale_eff_size cutoff_freq
gpumdkit.sh -plt nemd <real_length> <scale_eff_size> <cutoff_freq> save

# HNEMD thermal transport
gpumdkit.sh -plt hnemd <scale_eff_size> <cutoff_freq> save

# Viscosity
gpumdkit.sh -plt viscosity save

Phonons (1 plot type)

Command	Input Files	Description
`pdos`	`model.xyz`, `run.in`, `dos.out`, `mvac.out`	Phonon DOS and heat capacity

gpumdkit.sh -plt pdos save

Common Workflows

NEP Training Validation

# 1. Plot training loss
gpumdkit.sh -plt train
# 2. Check test predictions
gpumdkit.sh -plt prediction
# 3. Analyze force errors
gpumdkit.sh -plt force_errors
# 4. Visualize descriptors
gpumdkit.sh -plt des pca

Diffusion Analysis

# 1. Plot MSD
gpumdkit.sh -plt msd
# 2. Plot self-diffusion coefficient
gpumdkit.sh -plt sdc
# 3. Combined MSD-SDC plot
gpumdkit.sh -plt msd_sdc
# 4. Arrhenius analysis (multi-temperature)
gpumdkit.sh -plt arrhenius_d

Thermal Transport

# 1. Plot thermodynamic properties
gpumdkit.sh -plt thermo
# 2. Plot thermal conductivity
gpumdkit.sh -plt emd x
# 3. Or NEMD/HNEMD
gpumdkit.sh -plt nemd 10 1 60 save

Output Files

Plot Type	PNG Filename (with `save`)
`train`	`train.png`
`prediction`	`prediction.png`
`train_test`	`train_test.png`
`force_errors`	`force_errors.png`
`des`	`descriptors.png`
`msd`	`msd.png`
`sdc`	`sdc.png`
`msd_sdc`	`MSD_SDC.png`
`thermo`	`thermo.png`
`rdf`	`rdf.png`
`arrhenius_sigma`	`Arrhenius_sigma.png`
`arrhenius_d`	`Arrhenius_D.png`
`emd`	`emd.png`
`nemd`	`nemd.png`
`hnemd`	`hnemd.png`
`viscosity`	`viscosity.png`
`cohesive`	`Cohesive.png`

Dependencies

All plotting scripts require:

matplotlib
numpy

Detailed Documentation

See plot_scripts.md for comprehensive guide.