198 lines
11 KiB
Plaintext
198 lines
11 KiB
Plaintext
---
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title: RecursiveMinimumEigenOptimizationResult (v0.26)
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description: API reference for qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult 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.optimization.algorithms.RecursiveMinimumEigenOptimizationResult
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---
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<span id="qiskit-optimization-algorithms-recursiveminimumeigenoptimizationresult" />
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# qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult
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<Class id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-aqua/tree/stable/0.9/qiskit/optimization/algorithms/recursive_minimum_eigen_optimizer.py" signature="RecursiveMinimumEigenOptimizationResult(x, fval, variables, status, replacements, history)" modifiers="class">
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Recursive Eigen Optimizer Result.
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Constructs an instance of the result class.
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**Parameters**
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* **x** (`Union`\[`List`\[`float`], `ndarray`]) – the optimal value found in the optimization.
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* **fval** (`float`) – the optimal function value.
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* **variables** (`List`\[`Variable`]) – the list of variables of the optimization problem.
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* **status** (`OptimizationResultStatus`) – the termination status of the optimization algorithm.
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* **replacements** (`Dict`\[`str`, `Tuple`\[`str`, `int`]]) – a dictionary of substituted variables. Key is a variable being substituted, value is a tuple of substituting variable and a weight, either 1 or -1.
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* **history** (`Tuple`\[`List`\[`MinimumEigenOptimizationResult`], `OptimizationResult`]) – a tuple containing intermediate results. The first element is a list of `MinimumEigenOptimizerResult` obtained by invoking [`MinimumEigenOptimizer`](qiskit.optimization.algorithms.MinimumEigenOptimizer "qiskit.optimization.algorithms.MinimumEigenOptimizer") iteratively, the second element is an instance of `OptimizationResult` obtained at the last step via min\_num\_vars\_optimizer.
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### \_\_init\_\_
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<Function id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.__init__" signature="__init__(x, fval, variables, status, replacements, history)">
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Constructs an instance of the result class.
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**Parameters**
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* **x** (`Union`\[`List`\[`float`], `ndarray`]) – the optimal value found in the optimization.
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* **fval** (`float`) – the optimal function value.
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* **variables** (`List`\[`Variable`]) – the list of variables of the optimization problem.
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* **status** (`OptimizationResultStatus`) – the termination status of the optimization algorithm.
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* **replacements** (`Dict`\[`str`, `Tuple`\[`str`, `int`]]) – a dictionary of substituted variables. Key is a variable being substituted, value is a tuple of substituting variable and a weight, either 1 or -1.
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* **history** (`Tuple`\[`List`\[`MinimumEigenOptimizationResult`], `OptimizationResult`]) – a tuple containing intermediate results. The first element is a list of `MinimumEigenOptimizerResult` obtained by invoking [`MinimumEigenOptimizer`](qiskit.optimization.algorithms.MinimumEigenOptimizer "qiskit.optimization.algorithms.MinimumEigenOptimizer") iteratively, the second element is an instance of `OptimizationResult` obtained at the last step via min\_num\_vars\_optimizer.
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</Function>
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## Methods
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| --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------- |
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| [`__init__`](#qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.__init__ "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.__init__")(x, fval, variables, status, …) | Constructs an instance of the result class. |
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## Attributes
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| -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------- |
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| [`fval`](#qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.fval "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.fval") | Returns the optimal function value. |
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| [`history`](#qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.history "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.history") | Returns intermediate results. |
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| [`raw_results`](#qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.raw_results "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.raw_results") | Return the original results object from the optimization algorithm. |
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| [`replacements`](#qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.replacements "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.replacements") | Returns a dictionary of substituted variables. |
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| [`samples`](#qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.samples "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.samples") | Returns the list of solution samples |
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| [`status`](#qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.status "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.status") | Returns the termination status of the optimization algorithm. |
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| [`variable_names`](#qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.variable_names "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.variable_names") | Returns the list of variable names of the optimization problem. |
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| [`variables`](#qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.variables "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.variables") | Returns the list of variables of the optimization problem. |
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| [`variables_dict`](#qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.variables_dict "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.variables_dict") | Returns the optimal value as a dictionary of the variable name and corresponding value. |
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| [`x`](#qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.x "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.x") | Returns the optimal value found in the optimization or None in case of FAILURE. |
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### fval
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<Attribute id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.fval">
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Returns the optimal function value.
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**Return type**
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`float`
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**Returns**
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The function value corresponding to the optimal value found in the optimization.
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</Attribute>
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### history
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<Attribute id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.history">
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Returns intermediate results. The first element is a list of `MinimumEigenOptimizerResult` obtained by invoking [`MinimumEigenOptimizer`](qiskit.optimization.algorithms.MinimumEigenOptimizer "qiskit.optimization.algorithms.MinimumEigenOptimizer") iteratively, the second element is an instance of `OptimizationResult` obtained at the last step via min\_num\_vars\_optimizer.
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**Return type**
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`Tuple`\[`List`\[`MinimumEigenOptimizationResult`], `OptimizationResult`]
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</Attribute>
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### raw\_results
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<Attribute id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.raw_results">
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Return the original results object from the optimization algorithm.
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Currently a dump for any leftovers.
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**Return type**
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`Any`
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**Returns**
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Additional result information of the optimization algorithm.
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</Attribute>
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### replacements
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<Attribute id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.replacements">
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Returns a dictionary of substituted variables. Key is a variable being substituted, value is a tuple of substituting variable and a weight, either 1 or -1.
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**Return type**
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`Dict`\[`str`, `Tuple`\[`str`, `int`]]
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</Attribute>
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### samples
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<Attribute id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.samples">
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Returns the list of solution samples
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**Return type**
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`List`\[`SolutionSample`]
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**Returns**
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The list of solution samples.
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</Attribute>
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### status
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<Attribute id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.status">
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Returns the termination status of the optimization algorithm.
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**Return type**
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`OptimizationResultStatus`
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**Returns**
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The termination status of the algorithm.
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</Attribute>
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### variable\_names
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<Attribute id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.variable_names">
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Returns the list of variable names of the optimization problem.
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**Return type**
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`List`\[`str`]
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**Returns**
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The list of variable names of the optimization problem.
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</Attribute>
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### variables
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<Attribute id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.variables">
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Returns the list of variables of the optimization problem.
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**Return type**
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`List`\[`Variable`]
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**Returns**
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The list of variables.
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</Attribute>
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### variables\_dict
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<Attribute id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.variables_dict">
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Returns the optimal value as a dictionary of the variable name and corresponding value.
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**Return type**
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`Dict`\[`str`, `float`]
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**Returns**
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The optimal value as a dictionary of the variable name and corresponding value.
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</Attribute>
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### x
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<Attribute id="qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult.x">
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Returns the optimal value found in the optimization or None in case of FAILURE.
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**Return type**
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`Optional`\[`ndarray`]
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**Returns**
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The optimal value found in the optimization.
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</Attribute>
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</Class>
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