Lennard Jones Alpha potential test

In this example, the potential energy between two particles is compared to the analytical value.

import math
import sys
import subprocess
import unittest
import pandas as pd

# Run a feasst simulation with the given parameters
def run_fst(params):
    with open("launch.txt", "w") as myfile: myfile.write("""
Configuration {config_params}
Potential Model LennardJonesAlpha alpha 12
ThermoParams beta 1000000
Log output_file lj.csv max_precision true clear_file true
Run num_trials 1
    syscode = subprocess.call("../../../build/bin/fst < launch.txt > launch.log", shell=True, executable='/bin/bash')
    if syscode > 0: sys.exit(1)

class TestMonteCarloLJRef(unittest.TestCase):
    def test_two_particle(self):
        """Test the LJ potential against analytical calculation of two particles"""
        params = {"displacement": 1.2345}
        with open("two.xyz", "w") as myfile: myfile.write(
-1 8 8 8
0 0 0 0
1 0 0 {displacement}""".format(**params))
        run_fst({"config_params": "particle_type0 /feasst/plugin/models/particle/ljdelta.fstprt xyz_file two.xyz delta_sigma 0.5"})
        df = pd.read_csv('lj.csv')
        self.assertEqual(2, df['num_particles_of_type0'][0])

        # compute the expected analytical LJ energy
        enlj = 4*((params["displacement"]+0.5)**(-24) - (params["displacement"]+0.5)**(-12))

        # Compare the analytical results with the FEASST computed energies.
        self.assertAlmostEqual(enlj, df['LennardJonesAlpha'][0], 12)
        self.assertAlmostEqual(enlj, df['energy'][0], 12)

unittest.main(argv=[''], verbosity=2, exit=False)

test_two_particle (__main__.TestMonteCarloLJRef)
Test the LJ potential against analytical calculation of two particles ... ok

Ran 1 test in 0.008s

<unittest.main.TestProgram at 0x7f9e37043cd0>

Did this tutorial work as expected? Did you find any inconsistencies or have any comments? Please contact us. Any feedback is appreciated!