277 lines
8.2 KiB
Plaintext
277 lines
8.2 KiB
Plaintext
---
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title: QVFitter (v0.31)
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description: API reference for qiskit.ignis.verification.QVFitter in qiskit v0.31
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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.ignis.verification.QVFitter
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---
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# QVFitter
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<Class id="qiskit.ignis.verification.QVFitter" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-ignis/tree/stable/0.6/qiskit/ignis/verification/quantum_volume/fitters.py" signature="QVFitter(backend_result=None, statevector_result=None, qubit_lists=None)" modifiers="class">
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Bases: `object`
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Class for fitters for quantum volume.
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**Parameters**
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* **backend\_result** (*list*) – list of results (qiskit.Result).
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* **statevector\_result** (*list*) – the ideal statevectors of each circuit
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* **qubit\_lists** (*list*) – list of qubit lists (what was passed to the circuit generation)
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## Methods
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<span id="qiskit-ignis-verification-qvfitter-add-data" />
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### add\_data
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<Function id="qiskit.ignis.verification.QVFitter.add_data" signature="QVFitter.add_data(new_backend_result, rerun_fit=True)">
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Add a new result. Re calculate fit
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**Parameters**
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* **new\_backend\_result** (*list*) – list of qv results
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* **rerun\_fit** (*bool*) – re calculate the means and fit the result
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**Raises**
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**QiskitError** – If the ideal distribution isn’t loaded yet
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#### Additional information:
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Assumes that ‘result’ was executed is the output of circuits generated by qv\_circuits,
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</Function>
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<span id="qiskit-ignis-verification-qvfitter-add-statevectors" />
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### add\_statevectors
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<Function id="qiskit.ignis.verification.QVFitter.add_statevectors" signature="QVFitter.add_statevectors(new_statevector_result)">
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Add the ideal results and convert to the heavy outputs.
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Assume the result is from ‘statevector\_simulator’
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**Parameters**
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**new\_statevector\_result** (*list*) – ideal results
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**Raises**
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**QiskitError** – If the result has already been added for the circuit
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</Function>
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<span id="qiskit-ignis-verification-qvfitter-calc-confidence-level" />
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### calc\_confidence\_level
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<Function id="qiskit.ignis.verification.QVFitter.calc_confidence_level" signature="QVFitter.calc_confidence_level(z_value)">
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Calculate confidence level using z value.
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Accumulative probability for standard normal distribution in \[-z, +infinity] is 1/2 (1 + erf(z/sqrt(2))), where z = (X - mu)/sigma = (hmean - 2/3)/sigma
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**Parameters**
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**z\_value** (*float*) – z value in in standard normal distibution.
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**Returns**
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confidence level in decimal (not percentage).
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**Return type**
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float
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</Function>
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<span id="qiskit-ignis-verification-qvfitter-calc-data" />
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### calc\_data
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<Function id="qiskit.ignis.verification.QVFitter.calc_data" signature="QVFitter.calc_data()">
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Make a count dictionary for each unique circuit from all the results.
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Calculate the heavy output probability.
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#### Additional information:
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Assumes that ‘result’ was executed is the output of circuits generated by qv\_circuits,
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</Function>
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<span id="qiskit-ignis-verification-qvfitter-calc-statistics" />
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### calc\_statistics
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<Function id="qiskit.ignis.verification.QVFitter.calc_statistics" signature="QVFitter.calc_statistics()">
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Convert the heavy outputs in the different trials into mean and error for plotting.
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Here we assume the error is due to a binomial distribution. Error (standard deviation) for binomial distribution is sqrt(np(1-p)), where n is the number of trials (self.\_ntrials) and p is the success probability (self.\_ydata\[0]\[depthidx]/self.\_ntrials).
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</Function>
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<span id="qiskit-ignis-verification-qvfitter-calc-z-value" />
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### calc\_z\_value
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<Function id="qiskit.ignis.verification.QVFitter.calc_z_value" signature="QVFitter.calc_z_value(mean, sigma)">
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Calculate z value using mean and sigma.
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**Parameters**
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* **mean** (*float*) – mean
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* **sigma** (*float*) – standard deviation
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**Returns**
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z\_value in standard normal distibution.
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**Return type**
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float
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</Function>
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<span id="qiskit-ignis-verification-qvfitter-plot-hop-accumulative" />
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### plot\_hop\_accumulative
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<Function id="qiskit.ignis.verification.QVFitter.plot_hop_accumulative" signature="QVFitter.plot_hop_accumulative(depth, ax=None, figsize=(7, 5))">
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Plot individual and accumulative heavy output probability (HOP) as a function of number of trials.
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**Parameters**
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* **depth** (*int*) – depth of QV circuits
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* **ax** (*Axes or None*) – plot axis (if passed in).
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* **figsize** (*tuple*) – figure size in inches.
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**Raises**
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**ImportError** – If matplotlib is not installed.
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**Returns**
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A figure of individual and accumulative HOP as a function of number of trials, with 2-sigma confidence interval and 2/3 threshold.
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**Return type**
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matplotlib.Figure
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</Function>
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<span id="qiskit-ignis-verification-qvfitter-plot-qv-data" />
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### plot\_qv\_data
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<Function id="qiskit.ignis.verification.QVFitter.plot_qv_data" signature="QVFitter.plot_qv_data(ax=None, show_plt=True, figsize=(7, 5), set_title=True, title=None)">
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Plot the qv data as a function of depth
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**Parameters**
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* **ax** (*Axes or None*) – plot axis (if passed in).
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* **show\_plt** (*bool*) – display the plot.
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* **figsize** (*tuple*) – Figure size in inches.
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* **set\_title** (*bool*) – set figure title.
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* **title** (*String or None*) – text for setting figure title
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**Raises**
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**ImportError** – If matplotlib is not installed.
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**Returns**
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A figure of Quantum Volume data (heavy output probability) with two-sigma error bar as a function of circuit depth.
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**Return type**
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matplotlib.Figure
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</Function>
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<span id="qiskit-ignis-verification-qvfitter-plot-qv-trial" />
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### plot\_qv\_trial
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<Function id="qiskit.ignis.verification.QVFitter.plot_qv_trial" signature="QVFitter.plot_qv_trial(depth, trial_index, figsize=(7, 5), ax=None)">
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Plot individual trial. :param depth: circuit depth :type depth: int :param trial\_index: trial index :type trial\_index: int :param figsize: Figure size in inches. :type figsize: tuple :param ax: plot axis (if passed in). :type ax: Axes or None
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**Returns**
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A figure for histogram of ideal and experiment probabilities.
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**Return type**
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matplotlib.Figure
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</Function>
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<span id="qiskit-ignis-verification-qvfitter-quantum-volume" />
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### quantum\_volume
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<Function id="qiskit.ignis.verification.QVFitter.quantum_volume" signature="QVFitter.quantum_volume()">
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Return the volume for each depth.
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**Returns**
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List of quantum volumes
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**Return type**
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list
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</Function>
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<span id="qiskit-ignis-verification-qvfitter-qv-success" />
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### qv\_success
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<Function id="qiskit.ignis.verification.QVFitter.qv_success" signature="QVFitter.qv_success()">
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Return whether each depth was successful (> 2/3 with confidence level > 0.977 corresponding to z\_value = 2) and the confidence level.
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**Returns**
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List of list of 2 elements for each depth: - success True/False - confidence level
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**Return type**
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list
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</Function>
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## Attributes
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### depths
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<Attribute id="qiskit.ignis.verification.QVFitter.depths">
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Return depth list.
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</Attribute>
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### heavy\_output\_counts
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<Attribute id="qiskit.ignis.verification.QVFitter.heavy_output_counts">
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Return the number of heavy output counts as measured.
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</Attribute>
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### heavy\_output\_prob\_ideal
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<Attribute id="qiskit.ignis.verification.QVFitter.heavy_output_prob_ideal">
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Return the heavy output probability ideally.
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</Attribute>
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### heavy\_outputs
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<Attribute id="qiskit.ignis.verification.QVFitter.heavy_outputs">
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Return the ideal heavy outputs dictionary.
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</Attribute>
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### qubit\_lists
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<Attribute id="qiskit.ignis.verification.QVFitter.qubit_lists">
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Return depth list.
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</Attribute>
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### results
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<Attribute id="qiskit.ignis.verification.QVFitter.results">
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Return all the results.
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</Attribute>
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### ydata
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<Attribute id="qiskit.ignis.verification.QVFitter.ydata">
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Return the average and std of the output probability.
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</Attribute>
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</Class>
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