60 lines
1.8 KiB
Python
60 lines
1.8 KiB
Python
from adaptive_umbrella import WHAM2DRunner
|
|
|
|
from copy import deepcopy
|
|
import os
|
|
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
|
|
|
|
class MyUmbrellaRunner(WHAM2DRunner):
|
|
def after_run_hook(self):
|
|
filename = "pmf_{}.pdf".format(self.num_iterations)
|
|
print("Writing new pmf to {}".format(filename))
|
|
pmf_to_plot = deepcopy(self.pmf.T)
|
|
pmf_to_plot[pmf_to_plot < 0] = None
|
|
plt.figure()
|
|
plt.imshow(pmf_to_plot, origin="bottom", cmap='jet')
|
|
ticks = [(x,x) for x in [-3, -2, -1, 0, 1, 2, 3]]
|
|
tick_positions = [ self._get_index_for_lambdas(x)[0] for x in ticks ]
|
|
tick_labels = [ str(x[0]) for x in ticks ]
|
|
|
|
plt.xticks(tick_positions, tick_labels)
|
|
plt.yticks(tick_positions, tick_labels)
|
|
|
|
|
|
cb = plt.colorbar(pad=0.1)
|
|
cb.set_label("kJ/mol")
|
|
plt.savefig(filename)
|
|
os.system("cp {} {}".format(filename, "pmf_current.pdf"))
|
|
|
|
|
|
def simulate_frames(self, lambdas, frames):
|
|
print("{} new simulations:".format(len(lambdas)))
|
|
counter = 0
|
|
|
|
threads = []
|
|
for f in lambdas:
|
|
counter += 1
|
|
if os.path.exists("sim/sim_{}_{}/COLVAR".format(*f)):
|
|
print("{}) Skipping lambdas={}/{}: COLVAR exists".format(counter, *f))
|
|
continue
|
|
|
|
print("{}) Simulate lambda1={}, lambda2={}".format(counter, *f))
|
|
command = "bash sim.sh {} {} 2>&1 > run.log".format(*f)
|
|
# print("Running {}".format(command))
|
|
os.system(command)
|
|
|
|
runner = MyUmbrellaRunner()
|
|
runner.WHAM_EXEC = "/opt/wham/wham-2d/wham-2d"
|
|
runner.cvs = np.array([
|
|
(-3, 3, 0.2),
|
|
(-3, 3, 0.2),
|
|
])
|
|
runner.cvs_init = (1.4, -1.4)
|
|
runner.E_min = 10
|
|
runner.E_max = 100
|
|
runner.E_incr = 10
|
|
runner.max_iterations = 100
|
|
|
|
runner.run()
|