fbtk 0.9.7

High-performance molecular simulation toolkit with Python bindings

FBTK: Forblaze Toolkit

High-performance molecular analysis and building tools powered by Rust. Designed as a "Transparent Accelerator" for Python (ASE/RDKit) workflows with a smart, object-oriented interface.

Features

• 🚀 High Performance: Core logic written in Rust with parallel processing (Rayon).
• 🏗️ Intelligent Builder:
  • Optimized Initial Packing: Grid-based placement with uniform density.
  • Polymer Synthesis: Automatic chain generation with leaving atom support.
  • Tacticity Control: Supports Isotactic, Syndiotactic, and Atactic arrangements via center-of-mass analysis and mirroring.
  • Built-in 3D Generation: 3D coordinate generation from SMILES handled by internal VSEPR + UFF engine.
  • Fast Structural Relaxation: O(N) Cell-list optimization with the FIRE algorithm.
• 🔍 Advanced Analysis:
  • Parallel RDF, MSD, COM (Center of Mass), Angles, Dihedrals.
  • O(N) Neighbor List search.
• 📏 Robust Physics: Correct handling of PBC, Triclinic cells, and Minimum Image Convention (MIC).

Installation

Python Library (Recommended)

pip install fbtk

Requirements: Python 3.8+ (Zero external dependencies).

Standalone CLI (No Python Required)

For non-Python environments, pre-compiled standalone binaries for Linux, Windows, and macOS are available on the GitHub Releases page.

• Download the archive for your platform (e.g., fbtk-cli-v0.9.6-linux-x86_64.tar.gz).
• Requirements: None. These are self-contained binaries.

Key Features

• 🚀 High Performance: Core logic written in Rust with parallel processing (Rayon).
• 🏗️ Intelligent Builder:
  • Optimized Initial Packing: Grid-based placement with uniform density.
  • Polymer Synthesis: Automatic chain generation with terminal capping (hydrogen addition).
  • Tacticity Control: Supports Isotactic, Syndiotactic, and Atactic arrangements.
  • Charge Assignment: Automatic partial charge calculation via Gasteiger method.
  • Built-in 3D Generation: 3D coordinate generation from SMILES handled by internal VSEPR + UFF engine.
  • Fast Structural Relaxation: O(N) Cell-list optimization with the FIRE algorithm.
• 🔍 Advanced Analysis:
  • Parallel RDF, MSD, COM (Center of Mass), Angles, Dihedrals.
• 📏 Robust Physics: Correct handling of PBC, Triclinic cells, and Minimum Image Convention (MIC).
• 📦 Zero Dependency: No RDKit, no NumPy, no SciPy required for the core engine. Perfect for clean deployment.

1. System Building

Build and relax a complex molecular system with just a few lines of code.

import fbtk

# 1. Setup Builder
builder = fbtk.Builder(density=0.8)
builder.add_molecule_smiles("ethanol", count=50, smiles="CCO")

# 2. Build and Relax
system = builder.build()
system.relax(steps=500)

# 3. Export to ASE
atoms = system.to_ase()
atoms.write("system.xyz")

2. RDF Analysis

Fast analysis of large trajectories using smart selection queries.

from ase.io import read
import fbtk

# Load trajectory (ASE list of Atoms)
traj = read('simulation.lammpstrj', index=':')

# Compute RDF using a simple query string
r, g_r = fbtk.compute_rdf(traj, query="O-H", r_max=10.0)

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3. Command Line Interface (CLI)

FBTK provides standalone CLI tools for batch processing.

fbtk-build: Build from Recipe

# Run building and relaxation from a YAML recipe
fbtk-build --recipe recipe.yaml --relax --output system.mol2

Example recipe.yaml:

system:
  density: 0.8
  cell_shape: [20.0, 20.0, 20.0]
components:
  - name: "ethanol"
    role: "molecule"
    input:
      smiles: "CCO"
    count: 50

fbtk-analyze: Analyze Trajectory

# Compute RDF for a LAMMPS trajectory
fbtk-analyze rdf --input traj.lammpstrj --query "type 1 with type 2"

Selection Query Syntax

FBTK supports intuitive strings to select atoms for analysis:

• Element: "O", "H", "element C"
• Pairs (RDF): "O-H", "C - C"
• Index Range: "index 0:100" (start:end)
• Residue: "resname STY"

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Author

Forblaze Project
Website: https://forblaze-works.com/en/