kawin.FreeEnergyHessian
kawin.hessian(chemical_potentials, composition_set)
Returns the hessian of the objective function for a single phase
Parameters
----------
chemical_potentials : 1-D ndarray
composition_set : pycalphad.core.composition_set.CompositionSet
Returns
-------
Matrix of floats for each second derivative
Derivatives along each axis will be in order of:
site fractions, phase amount, lagrangian multipliers, chemical potential
kawin.totalddx(chemical_potentials, composition_set, refElement)
Total derivative of site fractions, phase amount, lagrangian multipliers
and chemical potential with respect to system composition
d/dx = partial d/dxA - partial d/dxR where R is reference
Parameters
----------
chemical_potentials : 1-D ndarray
composition_set : pycalphad.core.composition_set.CompositionSet
refElement : str
Reference element
Returns
-------
Array of floats for each derivative
Derivatives will be in order of:
site fractions, phase amount, lagrangian multipliers, chemical potential
kawin.partialddx(chemical_potentials, composition_set)
Partial derivative of site fractions, phase amount, lagrangian multipliers
and chemical potential with respect to system composition
Parameters
----------
chemical_potentials : 1-D ndarray
composition_set : pycalphad.core.composition_set.CompositionSet
Returns
-------
Array of floats for each derivative
Derivatives will be in order of:
site fractions, phase amount, lagrangian multipliers, chemical potential
kawin.dMudX(chemical_potentials, composition_set, refElement)
Total derivative of chemical potential with respect to system composition
dmuA/dxB = (partial dmuA/dxB - partial dmuA/dxR) - (partial dmuR/dxB - partial dmuR/dxR)
where R is reference
This more or less represents the curvature of the free energy surface with reference element R
Parameters
----------
chemical_potentials : 1-D ndarray
composition_set : pycalphad.core.composition_set.CompositionSet
refElement : str
Reference element
Returns
-------
Array of floats for each derivative, (n-1 x n-1) matrix
Derivatives will be in alphabetical order of elements
kawin.partialdMudX(chemical_potentials, composition_set)
Partial derivative of chemical potential with respect to system composition
Parameters
----------
composition_set : pycalphad.core.composition_set.CompositionSet
Returns
-------
Array of floats for each derivative, (n x n) matrix
Derivatives will be in alphabetical order of elements