ForceBalance API  1.3
Automated optimization of force fields and empirical potentials
Classes | Functions | Variables
src.thermo Namespace Reference

Classes

class  Point
 
class  Thermo
 A target for fitting general experimental data sets. More...
 

Functions

def energy_derivatives (engine, FF, mvals, h, pgrad, dipole=False)
 Compute the first and second derivatives of a set of snapshot energies with respect to the force field parameters. More...
 

Variables

 logger = getLogger(__name__)
 

Function Documentation

◆ energy_derivatives()

def src.thermo.energy_derivatives (   engine,
  FF,
  mvals,
  h,
  pgrad,
  dipole = False 
)

Compute the first and second derivatives of a set of snapshot energies with respect to the force field parameters.

This basically calls the finite difference subroutine on the energy_driver subroutine also in this script.

In the future we may need to be more sophisticated with controlling the quantities which are differentiated, but for now this is okay..

Parameters
[in]engineEngine object for calculating energies
[in]FFForce field object
[in]mvalsMathematical parameter values
[in]hFinite difference step size
[in]pgradList of active parameters for differentiation
[in]dipoleSwitch for dipole derivatives.
Returns
G First derivative of the energies in a N_param x N_coord array
GDx First derivative of the box dipole moment x-component in a N_param x N_coord array
GDy First derivative of the box dipole moment y-component in a N_param x N_coord array
GDz First derivative of the box dipole moment z-component in a N_param x N_coord array

Definition at line 46 of file thermo.py.

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Variable Documentation

◆ logger

src.thermo.logger = getLogger(__name__)

Definition at line 20 of file thermo.py.