Package schrodinger :: Package application :: Package matsci :: Module mecp_mod :: Class MECPStep
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Class MECPStep

object --+
         |
        MECPStep

Manage an MECP step, which can be an iteration or a line search iteration.

Instance Methods [hide private]
 
__init__(self, iteration, call_number, x_initial, method, perp_factor, para_factor, verbose, logger, bfgs_obj)
Create an instance.
 
logInitialGeometry(self)
Log the initial geometry.
 
logHessianEigVals(self)
Log the Hessian eigenvalues.
 
logStepSize(self)
Log the step size.
 
handleFinalGeometry(self, x_final)
Handle the final geometry.
 
setInTemplates(self)
Set the Jaguar input templates.
numpy.array or None
getUnitNormalToDeltaForces(self, prev_mecp_step=None)
Get the unit vector that is normal to the delta forces vector.
 
setEnergiesAndForces(self, prev_mecp_step=None)
Set the energies and forces for the two states as well as well as the energy and forces to use for the MECP optimization.
 
setEnergiesAndForcesData(self, prev_mecp_step=None)
Set energies and forces data.
 
setJobData(self, jobs, prev_mecp_step=None)
Set job data.
 
logEnergyAndForces(self, header, energy, forces, max_force, rms_force, energy_header='Energy / Hartree', forces_header='Forces / Hartree/Ang.')
Log energy and forces.
str
getFormattedSummaryLine(self, entries)
Return a formatted summary line from the given data entries.
 
logSummaryHeader(self)
Log the summary header.
 
logSummary(self)
Log a summary.
 
logJobData(self)
Log job data.
 
terminate(self, convergence_dict)
Terminate the MECP optimization.

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

Properties [hide private]

Inherited from object: __class__

Method Details [hide private]

__init__(self, iteration, call_number, x_initial, method, perp_factor, para_factor, verbose, logger, bfgs_obj)
(Constructor)

 

Create an instance.

Parameters:
  • iteration (int) - the iteration
  • call_number (int) - the call number
  • x_initial (numpy.array) - the initial geometry vector (N X 1)
  • method (str) - the method to use to determine the MECP
  • perp_factor (float) - prefactor for the energy term whose gradient lies perpendicular to the crossing seam
  • para_factor (float) - prefactor for the energy term whose gradient lies parallel to the crossing seam
  • verbose (bool) - specifies verbose logging
  • logger (logging.Logger) - output logger
  • bfgs_obj (BFGS) - a BFGS object that manages the optimization
Overrides: object.__init__

handleFinalGeometry(self, x_final)

 

Handle the final geometry.

Parameters:
  • x_final (numpy.array) - the final geometry vector (N X 1)

getUnitNormalToDeltaForces(self, prev_mecp_step=None)

 

Get the unit vector that is normal to the delta forces vector.

Parameters:
  • prev_mecp_step (MECPStep or None) - MECPStep from the previous iteration or line search iteration or None if there isn't one
Returns: numpy.array or None
the unit vector perpendicular to the delta forces vector or None if there isn't one

setEnergiesAndForces(self, prev_mecp_step=None)

 

Set the energies and forces for the two states as well as well as the energy and forces to use for the MECP optimization.

Parameters:
  • prev_mecp_step (MECPStep or None) - MECPStep from the previous iteration or line search iteration or None if there isn't one

setEnergiesAndForcesData(self, prev_mecp_step=None)

 

Set energies and forces data.

Parameters:
  • prev_mecp_step (MECPStep or None) - MECPStep from the previous iteration or line search iteration or None if there isn't one

setJobData(self, jobs, prev_mecp_step=None)

 

Set job data.

Parameters:
  • jobs (list) - contains the JaguarJob instances for the two jobs
  • prev_mecp_step (MECPStep or None) - MECPStep from the previous iteration or line search iteration or None if there isn't one

logEnergyAndForces(self, header, energy, forces, max_force, rms_force, energy_header='Energy / Hartree', forces_header='Forces / Hartree/Ang.')

 

Log energy and forces.

Parameters:
  • header (str) - a header
  • energy (float or None) - the energy or None if there isn't one
  • forces (numpy.array) - the forces (natoms X 3)
  • max_force (float) - the magnitude of the largest forces element
  • rms_force (float) - the RMS of forces
  • energy_header (str) - an energy header
  • forces_header (str) - a forces header

getFormattedSummaryLine(self, entries)

 

Return a formatted summary line from the given data entries.

Parameters:
  • entries (list) - the data to format
Returns: str
a formatted summary line

terminate(self, convergence_dict)

 

Terminate the MECP optimization.

Parameters:
  • convergence_dict (dict) - contains various convergence thresholds