def refine_transition_state(self, nebindex=None):
print("refining ts")
if nebindex is None:
#figure out which image to start from
if self.oglview != "neb":
print("choose which NEB image to start from")
return
# raise Exception("choose which NEB image to start from")
nebindex = self.oglwgt.get_slider_index()
self.highlight_frame(-1)
coords = self.nebrunner.path[nebindex].copy()
self.ui.wgt_neb.highlight_point(nebindex)
self.app.processEvents()
tsdata = []
tscoordslist = []
self.local_connect = self.nebrunner.local_connect
#setup the callback function for findTransitionState
def findTS_callback(coords=None, energy=None, rms=None, eigenval=None, **kwargs):
tscoordslist.append(coords.copy())
tsdata.append((energy, rms, eigenval))
tsSearchParams = self.local_connect.tsSearchParams.copy()
tsSearchParams["event"] = findTS_callback
#setup the callback function for the pushoff
pdata = []
pcoordslist = []
def pushoff_callback(coords=None, energy=None, rms=None, **kwargs):
pcoordslist.append(coords)
pdata.append((energy, rms))
pushoff_params = self.local_connect.pushoff_params.copy()
quencher = self.system.get_minimizer(events=[pushoff_callback])
pushoff_params["quench"] = quencher
success, tsret, min1ret, min2ret = _refineTS(self.system.get_potential(), coords,
tsSearchParams=tsSearchParams, pushoff_params=pushoff_params)
#process the results of the transition state search
self.ts_coordspath = np.array(tscoordslist)
self.ts_labels = ["TS path: energy=%g, rms=%g, eigenval=%g"% vals for vals in tsdata]
# print "tscoords shape", self.ts_coords.shape, len(coordslist)
self.show_TS_path()
if success:
#process the results from the pushoff and quenches
ret1 = min1ret[4]
ret2 = min2ret[4]
#the paths from falling off both sides are in pcoordslist. try to split them up
i = ret1.nsteps
pushoff_coordspath1 = [tsret.coords.copy()] + pcoordslist[:i]
pushoff_coordspath2 = [tsret.coords.copy()] + pcoordslist[i:]
data1 = [(tsret.energy, tsret.rms)] + pdata[:i]
data2 = [(tsret.energy, tsret.rms)] + pdata[i:]
pushoff_labels1 = ["Pushoff left: energy=%g, rms=%g"% vals for vals in data1]
pushoff_labels2 = ["Pushoff right: energy=%g, rms=%g"% vals for vals in data2]
#combine them together with one in reversed order.
self.pushoff_coordspath = list(reversed(pushoff_coordspath1)) + pushoff_coordspath2
self.pushoff_labels = list(reversed(pushoff_labels1)) + pushoff_labels2
self.pushoff_coordspath = np.array(self.pushoff_coordspath)
#make a
tsitem = _TSListItem(nebindex, self.ts_coordspath, self.ts_labels, self.pushoff_coordspath, self.pushoff_labels)
self.ts_list.addItem(tsitem)
def refine_transition_state(self, nebindex=None):
print "refining ts"
if nebindex is None:
#figure out which image to start from
if self.oglview != "neb":
print "choose which NEB image to start from"
return
# raise Exception("choose which NEB image to start from")
nebindex = self.oglwgt.get_slider_index()
self.highlight_frame(-1)
coords = self.nebrunner.path[nebindex].copy()
self.ui.wgt_neb.highlight_point(nebindex)
self.app.processEvents()
tsdata = []
tscoordslist = []
self.local_connect = self.nebrunner.local_connect
#setup the callback function for findTransitionState
def findTS_callback(coords=None, energy=None, rms=None, eigenval=None, **kwargs):
tscoordslist.append(coords.copy())
tsdata.append((energy, rms, eigenval))
tsSearchParams = self.local_connect.tsSearchParams.copy()
tsSearchParams["event"] = findTS_callback
#setup the callback function for the pushoff
pdata = []
pcoordslist = []
def pushoff_callback(coords=None, energy=None, rms=None, **kwargs):
pcoordslist.append(coords)
pdata.append((energy, rms))
pushoff_params = self.local_connect.pushoff_params.copy()
quencher = self.system.get_minimizer(events=[pushoff_callback])
pushoff_params["quench"] = quencher
success, tsret, min1ret, min2ret = _refineTS(self.system.get_potential(), coords,
tsSearchParams=tsSearchParams, pushoff_params=pushoff_params)
#process the results of the transition state search
self.ts_coordspath = np.array(tscoordslist)
self.ts_labels = ["TS path: energy=%g, rms=%g, eigenval=%g"% vals for vals in tsdata]
# print "tscoords shape", self.ts_coords.shape, len(coordslist)
self.show_TS_path()
if success:
#process the results from the pushoff and quenches
ret1 = min1ret[4]
ret2 = min2ret[4]
#the paths from falling off both sides are in pcoordslist. try to split them up
i = ret1.nsteps
pushoff_coordspath1 = [tsret.coords.copy()] + pcoordslist[:i]
pushoff_coordspath2 = [tsret.coords.copy()] + pcoordslist[i:]
data1 = [(tsret.energy, tsret.rms)] + pdata[:i]
data2 = [(tsret.energy, tsret.rms)] + pdata[i:]
pushoff_labels1 = ["Pushoff left: energy=%g, rms=%g"% vals for vals in data1]
pushoff_labels2 = ["Pushoff right: energy=%g, rms=%g"% vals for vals in data2]
#combine them together with one in reversed order.
self.pushoff_coordspath = list(reversed(pushoff_coordspath1)) + pushoff_coordspath2
self.pushoff_labels = list(reversed(pushoff_labels1)) + pushoff_labels2
self.pushoff_coordspath = np.array(self.pushoff_coordspath)
#make a
tsitem = _TSListItem(nebindex, self.ts_coordspath, self.ts_labels, self.pushoff_coordspath, self.pushoff_labels)
self.ts_list.addItem(tsitem)
def _refineTSWrapper(inputs):
"""
a stupid wrapper to allow _refineTS to be used with Pool.map which only supports one argument
"""
return _refineTS(inputs[0], inputs[1], **inputs[2])
