137 lines
3.8 KiB
Plaintext
137 lines
3.8 KiB
Plaintext
---
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title: QuadraticObjective
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description: API reference for qiskit.optimization.problems.QuadraticObjective
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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.optimization.problems.QuadraticObjective
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---
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# QuadraticObjective
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<Class id="qiskit.optimization.problems.QuadraticObjective" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-aqua/tree/stable/0.9/qiskit/optimization/problems/quadratic_objective.py" signature="QuadraticObjective(quadratic_program, constant=0.0, linear=None, quadratic=None, sense=<ObjSense.MINIMIZE: 1>)" modifiers="class">
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Bases: `qiskit.optimization.problems.quadratic_program_element.QuadraticProgramElement`
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Representation of quadratic objective function of the form: constant + linear \* x + x \* quadratic \* x.
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Constructs a quadratic objective function.
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**Parameters**
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* **quadratic\_program** (`Any`) – The parent quadratic program.
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* **constant** (`float`) – The constant offset of the objective.
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* **linear** (`Union`\[`ndarray`, `spmatrix`, `List`\[`float`], `Dict`\[`Union`\[`int`, `str`], `float`], `None`]) – The coefficients of the linear part of the objective.
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* **quadratic** (`Union`\[`ndarray`, `spmatrix`, `List`\[`List`\[`float`]], `Dict`\[`Tuple`\[`Union`\[`int`, `str`], `Union`\[`int`, `str`]], `float`], `None`]) – The coefficients of the quadratic part of the objective.
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* **sense** (`ObjSense`) – The optimization sense of the objective.
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## Methods
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### evaluate
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<Function id="qiskit.optimization.problems.QuadraticObjective.evaluate" signature="QuadraticObjective.evaluate(x)">
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Evaluate the quadratic objective for given variable values.
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**Parameters**
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**x** (`Union`\[`ndarray`, `List`, `Dict`\[`Union`\[`int`, `str`], `float`]]) – The values of the variables to be evaluated.
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**Return type**
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`float`
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**Returns**
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The value of the quadratic objective given the variable values.
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</Function>
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### evaluate\_gradient
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<Function id="qiskit.optimization.problems.QuadraticObjective.evaluate_gradient" signature="QuadraticObjective.evaluate_gradient(x)">
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Evaluate the gradient of the quadratic objective for given variable values.
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**Parameters**
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**x** (`Union`\[`ndarray`, `List`, `Dict`\[`Union`\[`int`, `str`], `float`]]) – The values of the variables to be evaluated.
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**Return type**
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`ndarray`
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**Returns**
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The value of the gradient of the quadratic objective given the variable values.
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</Function>
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## Attributes
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### constant
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<Attribute id="qiskit.optimization.problems.QuadraticObjective.constant">
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Returns the constant part of the objective function.
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**Return type**
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`float`
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**Returns**
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The constant part of the objective function.
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</Attribute>
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### linear
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<Attribute id="qiskit.optimization.problems.QuadraticObjective.linear">
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Returns the linear part of the objective function.
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**Return type**
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`LinearExpression`
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**Returns**
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The linear part of the objective function.
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</Attribute>
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### quadratic
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<Attribute id="qiskit.optimization.problems.QuadraticObjective.quadratic">
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Returns the quadratic part of the objective function.
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**Return type**
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`QuadraticExpression`
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**Returns**
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The quadratic part of the objective function.
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</Attribute>
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### quadratic\_program
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<Attribute id="qiskit.optimization.problems.QuadraticObjective.quadratic_program">
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Returns the parent QuadraticProgram.
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**Return type**
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`Any`
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**Returns**
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The parent QuadraticProgram.
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</Attribute>
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### sense
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<Attribute id="qiskit.optimization.problems.QuadraticObjective.sense">
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Returns the sense of the objective function.
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**Return type**
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`ObjSense`
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**Returns**
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The sense of the objective function.
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</Attribute>
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</Class>
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