semvec/pypi-packages huggingface dataset:
qeijo 0.1
Lightweight library to easily launch ab initio calculations with Quantum Espresso.

First of all, *qeijo* is not an acronym. Okay, we have the Q and E for Quantum Espresso, for sure, but that's it. 
The point was just to use a funny name for the package. 

*qeijo* is an incorrect way - on purpose, of course - of spelling "queijo", which is simply the Portuguese word 
for "cheese".

This package contains a lightweight library that allows the user to launch electronic structure calculations with 
Quantum Espresso and then collect the results, all done in a Pythonic way. Just to be clear, I don't 
claim that this package can compete in terms of features with much larger frameworks for atomistic 
simulations, like ASE. All you can expect from *qeijo* is that it is light and easy to use.

In version 0.1, there is only one module, *pw*, which must be used to build an input to the pw.x program, 
launch a total energy calculation and get from it important quantities, like the total energy of the 
system, the relaxed atomic coordinates, magnetization, etc. In future releases, I plan to add interfaces 
to other programs from the Quantum Espresso package, as well as work a bit more on user documentation.

### Basic Usage Example

---

    # Launching a calculation with pw.x of H2 molecule, reading the input from an existing input file
    from qeijo import pw

    cmd="mpirun -np 2 pw.x"
    h2_calc=pw.calc()
    h2_calc.read_input("h2.inp")
    inpstr=h2_calc.build_input()
    h2_out=h2_calc.run(command_line=cmd,input_string=inpstr,saveout=True,
                       outfile="h2.out",savecoords=True,coordfile="h2.xyz")

    # Print the total energy in eV
    print("Total energy: %f" % h2_out.energy[-1])

    # Print the relaxed coordinates of the the two H atoms
    print("H1: %f %f %f" % (h2_out.x[0],h2_out.y[0],h2_out.z[0]))
    print("H2: %f %f %f" % (h2_out.x[1],h2_out.y[1],h2_out.z[1]))
harisonmg-automl 0.0.1
Experimenting with Python AutoML libraries and frameworks
Requires Python: >=3.6

# automl
Experimenting with Python AutoML libraries and frameworks

[![Tests](https://github.com/harisonmg/automl/actions/workflows/ci.yml/badge.svg)](https://github.com/harisonmg/automl/actions/workflows/ci.yml)
[![Coverage Status](https://coveralls.io/repos/github/harisonmg/automl/badge.svg?branch=main)](https://coveralls.io/github/harisonmg/automl?branch=main)
sparg 1.0.1
A package to estimate dispersal rates and locate genetic ancestors from tree sequences
Requires Python: >=3.7

```
   sparg    s parg    sparg    s parg   sparg 
  spa  rg   sp   ar  sp   ar   spa     sp   ar
  spa       gs   pa  gs   pa   rg      gs   pa
    rgsp    rgspar   rg   sp   sp      rg   sp
      arg   gs       ar   gs   ar       argspa
  sp  arg   pa       pa   rg   gs           rg
   sparg    rg        spar g  parg      sparg
```

Estimating dispersal rates and locating genetic ancestors with genome-wide genealogies

This is the software. For the paper, see https://github.com/mmosmond/sparg-ms.

## Installation

Using python3 you can install from PyPi from the command line

```
pip install sparg
```

See tutorial/tutorial.ipynb for a demo on how to use.

## Acknowledgements
Some code for importance sampling adapted from https://github.com/35ajstern/palm.
Logo inspired by concrete poetry of bpNichol.