API Reference

This page provides documentation for all public-facing objects, methods, and functions in reciprocalspaceship. Since this library was designed to provide a “crystallographically-aware” pandas.DataFrame, many methods are inherited directly from or are compatible with the Pandas API.

Warning

Functions available through the rs.utils namespace are considered private, and may change between releases. These functions underlie the symmetry/spacegroup-related operations that are supported in reciprocalspaceship, and user-facing methods that use the rs.utils functions are available as methods of rs.DataSet.

Reflection Data

Python objects for representing reflection data – tabular data with values (columns) that are indexed by Miller HKL indices. These two objects can be thought of as crystallographically-aware versions of pandas.DataFrame and pandas.Series, respectively.

`DataSet`	Representation of a crystallographic dataset.
`DataSeries`	One-dimensional ndarray with axis labels, representing a slice of a DataSet.

Input/Output

Supported crystallographic file formats for data I/O. Although they are not listed below, write functions for reflection file formats are available as methods of rs.DataSet objects.

`read_mtz`	Populate the dataset object with data from an MTZ reflection file.
`read_cif`	Populate the dataset object with reflection data from a CIF/ENT file.
`read_csv`	Read a comma-separated values (csv) file into a DataSet.
`read_pickle`	Load pickled reciprocalspaceship object from file.
`read_precognition`	Initialize attributes and populate the DataSet object with data from a precognition hkl or ii file of reflections.
`read_crystfel`	Initialize attributes and populate the DataSet object with data from a CrystFEL stream with indexed reflections.
`write_ccp4_map`	Write CCP4 map file from NumPy array of real-space density.

Algorithms

Algorithms for processing reflection data stored in rs.DataSet objects.

`merge`	Merge dataset using inverse-variance weights.
`scale_merged_intensities`	Scales merged intensities using Bayesian statistics in order to estimate structure factor amplitudes.
`compute_intensity_from_structurefactor`	Compute intensities (I) and uncertainty estimates (SigI) from structure factor amplitudes (F) and their uncertainties (SigF) using error propagation

Summary Statistics

Summary statistics that can be computed from rs.DataSet objects.

compute_completeness

Compute completeness of DataSet by resolution bin.

Helpful Functions

Functions intended to help users work with the library. These functions are available from the top-level rs namespace.

`concat`	Concatenate `rs` objects along a particular axis.
`summarize_mtz_dtypes`	Returns a table summarizing the MTZ Dtypes that can be used in a DataSet or DataSeries.

Commandline Tools

Commandline tools to support common use cases.

`rs.mtzdump`	Summarize the contents of an MTZ file
`rs.cifdump`	Summarize the contents of a CIF file