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

Classes

class  Quantity
 Base class for thermodynamical quantity used for fitting. More...
 
class  Quantity_Density
 
class  Quantity_H_vap
 

Functions

def mean_stderr (ts)
 Return mean and standard deviation of a time series ts. More...
 
def energy_derivatives (engine, FF, mvals, h, pgrad, length, AGrad=True)
 Compute the first 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.quantity.energy_derivatives (   engine,
  FF,
  mvals,
  h,
  pgrad,
  length,
  AGrad = True 
)

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

The function calls the finite difference subroutine on the energy_driver subroutine also in this script.

Parameters

engine : Engine Use this Engine (GMX,TINKER,OPENMM etc.) object to get the energy snapshots. FF : FF Force field object. mvals : list Mathematical parameter values. h : float Finite difference step size. length : int Number of snapshots (length of energy trajectory). AGrad : Boolean Switch that turns derivatives on or off; if off, return all zeros.

Returns

G : np.array Derivative of the energy in a FF.np x length array.

Definition at line 52 of file quantity.py.

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◆ mean_stderr()

def src.quantity.mean_stderr (   ts)

Return mean and standard deviation of a time series ts.

Definition at line 19 of file quantity.py.

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Variable Documentation

◆ logger

src.quantity.logger = getLogger(__name__)

Definition at line 14 of file quantity.py.