WHAM2DRunner implementation

example.py

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+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="lower", cmap='jet')
+        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([
+    (-3.1, 3.1, 0.1),
+    (-3.1, 3.1, 0.1),
+])
+runner.cvs_init = (1, -1.4)
+runner.E_min = 10
+runner.E_max = 200
+runner.E_incr = 10
+runner.max_iterations = 25
+
+runner.run()