PyLatticeIO

Read and write lattice QCD data in Python with NumPy.

This project was originally the I/O part of PyQUDA, and I simplified the code to create this repository. This might be helpful to analysis lattice QCD data in Python.

This repository contains Python implementations to read and write different lattice QCD data such as gauge configurations and propagators generated by Chroma software.

Just loading data into NumPy format is useless, and you should use these I/O samples along with your analysis script.

The propagator will be rotated to DeGrand-Rossi basis.

Returned NDArray

Type	shape	dtype	Comment
Gauge	(Nd, Lt, Lz, Ly, Lx, Nc, Nc)	complex128	row-colum order
Propagator	(Lt, Lz, Ly, Lx, Ns, Ns, Nc, Nc)	complex128	sink-source order
Staggered propagator	(Lt, Lz, Ly, Lx, Nc, Nc)	complex128	sink-source order
Fermion	(Lt, Lz, Ly, Lx, Ns, Nc)	complex128
Staggered fermion	(Lt, Lz, Ly, Lx, Nc)	complex128

Supported format

Software	Gauge	Propagator	Other
Chroma	Read	Read
MILC	Read	Read
KYU	Read/Write	Read/Write
IO General			Read

MPI I/O with mpi4py

The repository requires mpi4py to read lattice QCD data in parallel. You could setup the grid by calling setGrid(grid_size). If you do not call this function, each process will read the entire field.

test.mpi.py:

import pylatticeio as io

io.setGrid([1, 1, 2, 2])
gauge = io.readChromaQIOGauge("./data/weak_field.lime")
print(gauge.shape)

And then run the script by

mpiexec -n 4 python test.mpi.py

You should get the shape of gauge to be (Nd, Lt/2, Lz/2, Ly, Lx, Nc, Nc), since the gauge is divided in z and t directions.

The rank of a process varies fastest in the t direction. For example, with grid_size=[1, 1, 2, 2], the grid coordinate and the corresponding rank of a process is

item
rank	0	1	2	3
grid coordinate	0,0,0,0	0,0,0,1	0,0,1,0	0,0,1,1

You can also check this by calling io.getCoordFromRank and io.getRankFromCoord.