General MacroMocelecular I/O, or GEMMI, is a C++ 11 header only library for low level crystalographic .

Because its header only it is certainly the easiest to access and use low level crystalographic C++ library, however GEMMI comes with python binding via Pybind11, making it arguably the easiest low level crystalographic library to access and use in python as well!

What follows is a cookbook of useful Python code that uses GEMMI to accomplish macromolecular crystalographic tasks.

Installation

pip install gemmi

Importing GEMMI

import gemmi

Loading models

structure: gemmmi.Structure = gemmi.read_pdb(pdb_path)  # PDB file
structure: gemmmi.Structure = gemmi.cif.read(cif_path)  # mmCIF file

Loading reflection data

mtz = gemmi.read_mtz_file('../tests/5e5z.mtz')

Loading crystalographic maps

xmap = gemmi.read_ccp4_map(xmap_path)

Write models

structure.write_pdb(path)  # Write to a pdb
structure.make_mmcif_document().write_file(path)  # Write to a mmCIF

Write reflections

mtz.write_to_file(path)

Write crystalographic maps

ccp4 = gemmi.Ccp4Map()
ccp4.grid = xmap
ccp4.update_ccp4_header(2, True)
ccp4.write_ccp4_map(path)

Transforming reflection data to grids

xmap = mtz.transform_f_phi_to_map("FWT", "PHWT", sample_rate=4)

Subsampling grids (single point)

position = gemmi.Position((2, 3, 4))
grid.interpolate_value(position)  

Subsampling grids (orhtogonal grid of points)

arr = numpy.zeros([32, 32, 32], dtype=numpy.float32)
tr = gemmi.Transform()
tr.mat.fromlist([[0.1, 0, 0], [0, 0.1, 0], [0, 0, 0.1]])
tr.vec.fromlist([1, 2, 3])
grid.interpolate_values(arr, tr)