qiskit.chemistry.algorithms.pes_samplers.EnergySurface1DSpline¶

class EnergySurface1DSpline[source]¶

A simple cubic spline interpolation for the potential energy surface.

A spline interpolation method for data fitting.

This allows for fitting BOPES sampler results or potential energy surfaces.

__init__()[source]¶

A spline interpolation method for data fitting.

This allows for fitting BOPES sampler results or potential energy surfaces.

Methods

`__init__`()	A spline interpolation method for data fitting.
`eval`(x)	After fitting the data to the fit function, predict the energy at a point x.
`fit`(xdata, ydata[, initial_vals, bounds_list])	Fits surface to data.
`get_equilibrium_geometry`([scaling])	Returns the geometry for the minimal energy (scaled by ‘scaling’) Default units (scaling=1.0) are Angstroms.
`get_minimal_energy`([scaling])	Returns the value of the minimal energy (scaled by ‘scaling’) Default units (scaling=1.0) are J/mol.
`get_trust_region`()	Get the trust region.

eval(x)[source]¶

After fitting the data to the fit function, predict the energy at a point x.

Parameters: x (float) – Value to be evaluated
Return type: float
Returns: Value of surface fit in point x.

fit(xdata, ydata, initial_vals=None, bounds_list=None)[source]¶

Fits surface to data.

Parameters

xdata (List[float]) – x data to be fitted
ydata (List[float]) – y data to be fitted
initial_vals (Optional[List[float]]) – Initial values for fit parameters. None for default. Order of parameters is d_e, alpha, r_0 and m_shift (see fit_function implementation)
bounds_list (Optional[Tuple[List[float], List[float]]]) – Bounds for the fit parameters. None for default. Order of parameters is d_e, alpha, r_0 and m_shift (see fit_function implementation)

Return type

None

get_equilibrium_geometry(scaling=1.0)[source]¶

Returns the geometry for the minimal energy (scaled by ‘scaling’) Default units (scaling=1.0) are Angstroms. Scale by 1E-10 to get meters. :type scaling: float :param scaling: scaling factor

Return type: float
Returns: equilibrium geometry

get_minimal_energy(scaling=1.0)[source]¶

Returns the value of the minimal energy (scaled by ‘scaling’) Default units (scaling=1.0) are J/mol. Scale appropriately for Hartrees. :type scaling: float :param scaling: scaling factor

Return type: float
Returns: minimum energy

get_trust_region()[source]¶

Get the trust region.

Returns the bounds of the region (in space) where the energy surface implementation can be trusted. When doing spline interpolation, for example, that would be the region where data is interpolated (vs. extrapolated) from the arguments of fit().

Return type: Tuple[float, float]
Returns: The trust region between bounds.