Skip to main content

QM-Tools-AW

A collection of quantum mechanics and computational chemistry tools for data analysis, visualization, and manipulation.

Installation

pip install qm-tools-aw

Features

General Utilities

  • File I/O operations (JSON, pickle)
  • Molecular geometry manipulation and conversion
  • Handling of various file formats (XYZ, PDB, Psi4 input)
  • Distance calculations and molecular structure analysis
  • Visualization helpers (e.g., PyMOL script generation)

Plot Utilities

  • Violin plots for error analysis with customizable aesthetics
  • Support for statistical visualizations of computational chemistry data

SAPT Analysis

  • Symmetry-Adapted Perturbation Theory (SAPT) term computation for higher-order SAPT mimicking Psi4 but on a pandas DataFrame

Software Access

  • Interface with external chemistry software
  • Tools for working with checkmol for functional group analysis

Usage Examples

Create Violin Plots for Error Analysis

import pandas as pd
import numpy as np
from qm_tools_aw.plot import violin_plot

# Create sample data
df = pd.DataFrame({
    'MP2': np.random.normal(0.5, 5, 1000),
    'HF': np.random.normal(-0.5, 5, 1000),
})

# Create violin plot
violin_plot(
    df,
    {'MP2 Method': 'MP2', 'HF Method': 'HF'},
    output_filename="method_comparison",
    ylim=[-25, 25],
    plt_title="Method Error Comparison"
)

Results: Plotting method_comparison

Process Molecular Geometries

from qm_tools_aw.tools import read_xyz_to_pos_carts, write_cartesians_to_xyz, print_cartesians_pos_carts

# Read XYZ file
pos, carts = read_xyz_to_pos_carts("molecule.xyz")

# Manipulate coordinates
carts[:, 0] += 1.0  # Shift x coordinates

# Write modified structure
write_cartesians_to_xyz(pos, carts, "modified.xyz")
print_cartesians_pos_carts(pos, carts)

Results:


8	0.2978039460	-0.0560602560	0.0099422620
1	-0.0221932240	0.8467757820	-0.0114887140
1	1.2575210620	0.0421214960	0.0052189990

Documentation

For detailed documentation on all functions and classes, refer to the docstrings in the source code.

Dependencies

  • NumPy
  • Pandas
  • Matplotlib
  • QCElemental
  • Other standard Python libraries

License

This project is licensed under the MIT License - see the LICENSE file for details.

Metadata

Release files for qm-tools-aw 1.5.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for qm-tools-aw 1.5.3
File Size Uploaded Provenance Actions
qm_tools_aw-1.5.3.tar.gz 25.9 kB Without provenance Details for qm_tools_aw-1.5.3.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for qm-tools-aw 1.5.3
File Interpreter ABI Platform Actions
qm_tools_aw-1.5.3-py3-none-any.whl Python 3 none any Details for qm_tools_aw-1.5.3-py3-none-any.whl

Total release size: 51.7 kB

Release files / qm_tools_aw-1.5.3.tar.gz

Download URL qm_tools_aw-1.5.3.tar.gz
Size 25.9 kB
Tags Source
SHA-256 checksum
How to use checksums
c7e322f249cd0b18ca09b952137e52f762003cca5437f7683bf023235624e52a
BLAKE2b-256 checksum
How to use checksums
1914db963e91f639f286ea024cdba2391260db8af98d2eb8bd596e9bd34b89d3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.11

Release files / qm_tools_aw-1.5.3-py3-none-any.whl

Download URL qm_tools_aw-1.5.3-py3-none-any.whl
Size 25.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
1d6341d398a5238566c930cbf0dcae218e36eb9c9f7857820842879c89897d17
BLAKE2b-256 checksum
How to use checksums
0f498340d97330d2c15dad91f861d6771f1fdf55519f05b495ccfbb896d4ac29
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.11

Security for qm-tools-aw 1.5.3

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page