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---
title: DragFitter
description: API reference for qiskit.ignis.characterization.DragFitter
in_page_toc_min_heading_level: 1
python_api_type: class
python_api_name: qiskit.ignis.characterization.DragFitter
---
<span id="qiskit-ignis-characterization-dragfitter" />
# qiskit.ignis.characterization.DragFitter
<Class id="qiskit.ignis.characterization.DragFitter" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-ignis/tree/stable/0.5/qiskit/ignis/characterization/calibrations/fitters.py" signature="DragFitter(backend_result, xdata, qubits, fit_p0, fit_bounds=None)" modifiers="class">
Drag Experiment fitter
See IQFitter \_\_init\_\_
fit\_p0 is \[a, x0, c] where the fit is a\*(x-x0)^2+c
### \_\_init\_\_
<Function id="qiskit.ignis.characterization.DragFitter.__init__" signature="__init__(backend_result, xdata, qubits, fit_p0, fit_bounds=None)">
See IQFitter \_\_init\_\_
fit\_p0 is \[a, x0, c] where the fit is a\*(x-x0)^2+c
</Function>
## Methods
| | |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------- |
| [`__init__`](#qiskit.ignis.characterization.DragFitter.__init__ "qiskit.ignis.characterization.DragFitter.__init__")(backend\_result, xdata, qubits, fit\_p0) | See IQFitter \_\_init\_\_ |
| [`add_data`](#qiskit.ignis.characterization.DragFitter.add_data "qiskit.ignis.characterization.DragFitter.add_data")(results\[, recalc, refit]) | Add new execution results to previous execution results |
| [`drag_amplitude`](#qiskit.ignis.characterization.DragFitter.drag_amplitude "qiskit.ignis.characterization.DragFitter.drag_amplitude")(\[qind]) | Return the drag amplitude from the fit |
| [`fit_data`](#qiskit.ignis.characterization.DragFitter.fit_data "qiskit.ignis.characterization.DragFitter.fit_data")(\[qid, p0, bounds, series]) | Fit the curve. |
| [`guess_params`](#qiskit.ignis.characterization.DragFitter.guess_params "qiskit.ignis.characterization.DragFitter.guess_params")(\[qind]) | Guess parameters for the drag fit |
| [`plot`](#qiskit.ignis.characterization.DragFitter.plot "qiskit.ignis.characterization.DragFitter.plot")(qind\[, series, ax, show\_plot]) | Plot the data and fit |
## Attributes
| | |
| ----------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- |
| [`backend_result`](#qiskit.ignis.characterization.DragFitter.backend_result "qiskit.ignis.characterization.DragFitter.backend_result") | Return the execution results |
| [`description`](#qiskit.ignis.characterization.DragFitter.description "qiskit.ignis.characterization.DragFitter.description") | Return the fitter’s purpose, e.g. |
| [`fit_fun`](#qiskit.ignis.characterization.DragFitter.fit_fun "qiskit.ignis.characterization.DragFitter.fit_fun") | Return the function used in the fit, e.g. |
| [`measured_qubits`](#qiskit.ignis.characterization.DragFitter.measured_qubits "qiskit.ignis.characterization.DragFitter.measured_qubits") | Return the indices of the qubits to be characterized |
| [`params`](#qiskit.ignis.characterization.DragFitter.params "qiskit.ignis.characterization.DragFitter.params") | Return the fit function parameters that were calculated by curve\_fit |
| [`params_err`](#qiskit.ignis.characterization.DragFitter.params_err "qiskit.ignis.characterization.DragFitter.params_err") | Return the error of the fit function parameters |
| [`series`](#qiskit.ignis.characterization.DragFitter.series "qiskit.ignis.characterization.DragFitter.series") | Return the list of series for the data |
| [`xdata`](#qiskit.ignis.characterization.DragFitter.xdata "qiskit.ignis.characterization.DragFitter.xdata") | Return the data points on the x-axis, the independenet parameter which is fit against |
| [`ydata`](#qiskit.ignis.characterization.DragFitter.ydata "qiskit.ignis.characterization.DragFitter.ydata") | Return the data points on the y-axis |
### add\_data
<Function id="qiskit.ignis.characterization.DragFitter.add_data" signature="add_data(results, recalc=True, refit=True)">
Add new execution results to previous execution results
**Parameters**
* **results** (`Union`\[`Result`, `List`\[`Result`]]) – new execution results
* **recalc** (`bool`) – whether tp recalculate the data
* **refit** (`bool`) – whether to refit the data
</Function>
### backend\_result
<Attribute id="qiskit.ignis.characterization.DragFitter.backend_result">
Return the execution results
**Return type**
`Union`\[`Result`, `List`\[`Result`]]
</Attribute>
### description
<Attribute id="qiskit.ignis.characterization.DragFitter.description">
Return the fitter’s purpose, e.g. ‘T1’
**Return type**
`str`
</Attribute>
### drag\_amplitude
<Function id="qiskit.ignis.characterization.DragFitter.drag_amplitude" signature="drag_amplitude(qind=- 1)">
Return the drag amplitude from the fit
**Parameters**
**qind** (*int*) – qubit index
**Returns**
drag amp
**Return type**
float
</Function>
### fit\_data
<Function id="qiskit.ignis.characterization.DragFitter.fit_data" signature="fit_data(qid=- 1, p0=None, bounds=None, series=None)">
Fit the curve.
Compute self.\_params and self.\_params\_err
**Parameters**
* **qid** (`int`) – qubit for fitting. If -1 fit for all the qubits
* **p0** (`Optional`\[`List`\[`float`]]) – initial guess, equivalent to p0 in scipy.optimize
* **bounds** (`Optional`\[`Tuple`\[`List`\[`float`], `List`\[`float`]]]) – bounds, equivalent to bounds in scipy.optimize
* **series** (`Optional`\[`str`]) – series to fit (if None fit all)
</Function>
### fit\_fun
<Attribute id="qiskit.ignis.characterization.DragFitter.fit_fun">
Return the function used in the fit, e.g. BaseFitter.\_exp\_fit\_fun
**Return type**
`Callable`
</Attribute>
### guess\_params
<Function id="qiskit.ignis.characterization.DragFitter.guess_params" signature="guess_params(qind=0)">
Guess parameters for the drag fit
**Parameters**
**qind** (*int*) – qubit index
**Returns**
**guess parameters**
\[a, x0, c] where the fit is $a * (x - x0)^{2+c}$
**Return type**
list
</Function>
### measured\_qubits
<Attribute id="qiskit.ignis.characterization.DragFitter.measured_qubits">
Return the indices of the qubits to be characterized
**Return type**
`List`\[`int`]
</Attribute>
### params
<Attribute id="qiskit.ignis.characterization.DragFitter.params">
Return the fit function parameters that were calculated by curve\_fit
**Return type**
`List`\[`float`]
</Attribute>
### params\_err
<Attribute id="qiskit.ignis.characterization.DragFitter.params_err">
Return the error of the fit function parameters
**Return type**
`List`\[`float`]
</Attribute>
### plot
<Function id="qiskit.ignis.characterization.DragFitter.plot" signature="plot(qind, series='0', ax=None, show_plot=False)">
Plot the data and fit
**Parameters**
* **qind** (*int*) – qubit index
* **series** (*str*) – data series to plot (for rabi data always ‘0’)
* **ax** (*Axes*) – matploblib axes (if none created)
* **show\_plot** (*bool*) – do plot.show
**Returns**
Plot axes
**Return type**
Axes
</Function>
### series
<Attribute id="qiskit.ignis.characterization.DragFitter.series">
Return the list of series for the data
**Return type**
`Optional`\[`List`\[`str`]]
</Attribute>
### xdata
<Attribute id="qiskit.ignis.characterization.DragFitter.xdata">
Return the data points on the x-axis, the independenet parameter which is fit against
**Return type**
`Union`\[`List`\[`float`], `array`]
</Attribute>
### ydata
<Attribute id="qiskit.ignis.characterization.DragFitter.ydata">
Return the data points on the y-axis
The data points are returning in the form of a list of dictionaries:
> * **ydata\[i]\[‘mean’] is a list, where item**
>
> no. j is the probability of success of qubit i for a circuit that lasts xdata\[j].
>
> * **ydata\[i]\[‘std’] is a list, where ydata\[‘std’]\[j] is the**
>
> standard deviation of the success of qubit i.
**Return type**
`List`\[`Dict`]
</Attribute>
</Class>
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