reciprocalspaceship

reciprocalspaceship provides a pandas-style interface for analysis and manipulation of X-ray crystallography reflection data to support crystallographic computations such as space-group, unit-cell, and symmetry-based operations.

Key Features:

• Tabular Representation of Reflection Data: Extends pandas to represent and manipulate reflection data from diffraction experiments in a tabular DataFrame-like format.
• Built-in Methods for Crystallographic Operations: Implements methods for space group, unit cell, and symmetry-based operations on reflection data.
• Facilitation of Exploratory Data Analysis: Provides tools for exploratory analysis of reflection datasets, including those from unconventional diffraction experiments.
• Integration with Scientific Computing Libraries: Integrates with scientific computing and machine learning libraries to enable downstream analyses.
• Support for Method Development and Prototyping: Enables rapid prototyping and development of novel crystallographic methods and custom analyses.

Scientific Applications:

• X-ray Crystallography Data Analysis: Processing and analysis of reflection data from X-ray crystallography to support interpretation of diffraction experiments.
• Macromolecular Structure Determination: Analyses that contribute to elucidating the atomic structures of macromolecules.
• Analysis of Unconventional Diffraction Experiments: Advanced analysis of nonstandard or specialized diffraction datasets that require custom methods.
• Method Development for Crystallography: Prototyping and testing of new crystallographic algorithms and analytical workflows.

Methodology:

Implements a pandas-style tabular representation of reflection data, provides computational methods for space-group, unit-cell, and symmetry-based operations, and exposes integration points for scientific computing and machine learning libraries to support prototyping.