125 lines
6.1 KiB
Plaintext
125 lines
6.1 KiB
Plaintext
---
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title: EnergySurfaceBase (v0.26)
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description: API reference for qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase in qiskit v0.26
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in_page_toc_min_heading_level: 1
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python_api_type: class
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python_api_name: qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase
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---
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<span id="qiskit-chemistry-algorithms-pes-samplers-energysurfacebase" />
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# qiskit.chemistry.algorithms.pes\_samplers.EnergySurfaceBase
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<Class id="qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-aqua/tree/stable/0.9/qiskit/chemistry/algorithms/pes_samplers/potentials/potential_base.py" signature="EnergySurfaceBase" modifiers="class">
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Class to hold a potential energy surface
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### \_\_init\_\_
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<Function id="qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.__init__" signature="__init__()">
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Initialize self. See help(type(self)) for accurate signature.
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</Function>
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## Methods
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| -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------- |
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| [`__init__`](#qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.__init__ "qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.__init__")() | Initialize self. |
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| [`eval`](#qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.eval "qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.eval")(x) | After fitting the data to the fit function, predict the energy at a point x. |
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| [`fit`](#qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.fit "qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.fit")(xdata, ydata\[, initial\_vals, bounds\_list]) | Fits surface to data |
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| [`get_equilibrium_geometry`](#qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.get_equilibrium_geometry "qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.get_equilibrium_geometry")(\[scaling]) | Get the equilibrium energy. |
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| [`get_minimal_energy`](#qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.get_minimal_energy "qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.get_minimal_energy")(\[scaling]) | Get the minimal energy. |
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| [`get_trust_region`](#qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.get_trust_region "qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.get_trust_region")() | Get the trust region. |
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### eval
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<Function id="qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.eval" signature="eval(x)" modifiers="abstract">
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After fitting the data to the fit function, predict the energy at a point x.
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**Parameters**
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**x** (`float`) – value to evaluate surface in
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**Return type**
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`float`
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**Returns**
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value of surface in point x
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</Function>
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### fit
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<Function id="qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.fit" signature="fit(xdata, ydata, initial_vals=None, bounds_list=None)" modifiers="abstract">
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Fits surface to data
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**Parameters**
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* **xdata** (`List`\[`float`]) – x data to be fitted
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* **ydata** (`List`\[`float`]) – y data to be fitted
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* **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)
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* **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)
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**Return type**
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`None`
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</Function>
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### get\_equilibrium\_geometry
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<Function id="qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.get_equilibrium_geometry" signature="get_equilibrium_geometry(scaling=1.0)" modifiers="abstract">
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Get the equilibrium energy.
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Returns the geometry for the minimal energy (scaled by ‘scaling’) Default units (scaling=1.0) are Angstroms. Scale by 1E-10 to get meters.
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**Parameters**
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**scaling** (`float`) – scaling factor
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**Return type**
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`float`
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**Returns**
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equilibrium geometry
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</Function>
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### get\_minimal\_energy
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<Function id="qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.get_minimal_energy" signature="get_minimal_energy(scaling=1.0)" modifiers="abstract">
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Get the minimal energy.
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Returns the value of the minimal energy (scaled by ‘scaling’) Default units (scaling=1.0) are J/mol. Scale appropriately for Hartrees.
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**Parameters**
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**scaling** (`float`) – scaling factor
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**Return type**
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`float`
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**Returns**
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minimum energy
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</Function>
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### get\_trust\_region
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<Function id="qiskit.chemistry.algorithms.pes_samplers.EnergySurfaceBase.get_trust_region" signature="get_trust_region()" modifiers="abstract">
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Get the trust region.
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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().
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**Return type**
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`Tuple`\[`float`, `float`]
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**Returns**
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the trust region between bounds
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</Function>
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</Class>
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