def main(trajsPerEpoch, clusters, lagtimes, nruns):
runFolder = os.getcwd()
print("Running from " + runFolder)
for tau, k in itertools.product(lagtimes, clusters):
destFolder = "%dlag/%dcl" % (tau, k)
if not os.path.exists(destFolder):
os.makedirs(destFolder)
os.chdir(destFolder)
folders_MSM = glob.glob("MSM_*")
if isfinished(folders_MSM):
print("Skipping run with lagtime %d, clusters %d" % (tau, k))
os.chdir(runFolder)
continue
else:
for folder in folders_MSM:
shutil.rmtree(folder)
prepareMSMFolders.main(trajsPath=runFolder)
os.chdir("MSM_0")
print("***************")
print("Estimating dG value in folder" + os.getcwd())
parameters = estimateDG.Parameters(ntrajs=None, length=None, lagtime=tau,
nclusters=k, nruns=nruns, skipFirstSteps=0,
useAllTrajInFirstRun=True,
computeDetailedBalance=True,
trajWildcard="traj_*",
folderWithTraj="rawData",
lagtimes=[1, 10, 25, 50, 100, 250, 400, 500, 600, 1000],
clusterCountsThreshold=0)
try:
estimateDG.estimateDG(parameters, cleanupClusterCentersAtStart=True)
except Exception as err:
if "distribution contains entries smaller" in str(err):
print("Caught exception in step with lag %d and k %d, moving to next iteration" % (tau, k))
with open("error.txt", "w") as fe:
fe.write("Caught exception in step with lag %d and k %d, moving to next iteration\n" % (tau, k))
else:
raise_(*sys.exc_info())
os.chdir(runFolder)
def main(trajsPerEpoch,
lagtime,
nclusters,
clusteringStride=1,
nruns=10,
lagtimes=[1, 10, 25, 50, 100, 250, 400, 500, 600, 1000]):
allFolders = np.array(glob.glob("MSM_*"))
epochs = [int(folder[4:]) for folder in allFolders]
args = np.argsort(epochs)
sortedFolders = allFolders[args]
origDir = os.getcwd()
resultsFile = os.path.join(origDir, "results.txt")
with open(resultsFile, "a") as f:
f.write("#Epoch DG StdDG Db StdDb\n")
f.write("#=======================\n")
resultsEpoch = []
initialEpoch = 0
for i, folder in enumerate(sortedFolders[initialEpoch:]):
epoch = i + initialEpoch
print(epoch, folder)
os.chdir(folder)
parameters = estimateDG.Parameters(ntrajs=trajsPerEpoch * (epoch + 1),
length=None,
lagtime=lagtime,
lagtimes=lagtimes,
nclusters=nclusters,
nruns=nruns,
useAllTrajInFirstRun=True,
computeDetailedBalance=True,
trajWildcard="traj_*",
folderWithTraj="rawData",
clusterCountsThreshold=0,
clusteringStride=clusteringStride)
try:
dG, stdDg, db, stdDb = estimateDG.estimateDG(
parameters, cleanupClusterCentersAtStart=True)
print(
"FINAL RESULTS EPOCH %d: dG: %f +- %f, asymmetric fluxes: %f +- %f"
% (epoch, dG, stdDg, db, stdDb))
resultsEpoch.append([dG, stdDg, db, stdDb])
with open(resultsFile, "a") as f:
f.write("%d %.3f %.3f %.3f %.3f\n" %
(epoch, dG, stdDg, db, stdDb))
except Exception as err:
resultsEpoch.append(["Estimation in this epoch crashed"])
if "distribution contains entries smaller" in str(err):
print(
"Caught exception in folder %s with lag %d and k %d, moving to next iteration"
% (folder, lagtime, nclusters))
with open("error.txt", "w") as fe:
fe.write(
"Caught exception in folder %s with lag %d and k %d, moving to next iteration\n"
% (folder, lagtime, nclusters))
else:
raise_(*sys.exc_info())
os.chdir("..")
print("Results")
print("epoch, DG, stdDg, DB, stdDb")
print("=====")
for i, results in enumerate(resultsEpoch):
print(i, results)