qiskit-documentation/docs/api/qiskit/0.31/qiskit.ignis.characterization.DragFitter.mdx

---
title: DragFitter (v0.31)
description: API reference for qiskit.ignis.characterization.DragFitter in qiskit v0.31
in_page_toc_min_heading_level: 1
python_api_type: class
python_api_name: qiskit.ignis.characterization.DragFitter
---

# DragFitter

<Class id="qiskit.ignis.characterization.DragFitter" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-ignis/tree/stable/0.6/qiskit/ignis/characterization/calibrations/fitters.py" signature="DragFitter(backend_result, xdata, qubits, fit_p0, fit_bounds=None)" modifiers="class">
  Bases: `qiskit.ignis.characterization.fitters.IQFitter`

  Drag Experiment fitter

  See IQFitter \_\_init\_\_

  fit\_p0 is \[a, x0, c] where the fit is a\*(x-x0)^2+c

  ## Methods

  <span id="qiskit-ignis-characterization-dragfitter-add-data" />

  ### add\_data

  <Function id="qiskit.ignis.characterization.DragFitter.add_data" signature="DragFitter.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>

  <span id="qiskit-ignis-characterization-dragfitter-drag-amplitude" />

  ### drag\_amplitude

  <Function id="qiskit.ignis.characterization.DragFitter.drag_amplitude" signature="DragFitter.drag_amplitude(qind=- 1)">
    Return the drag amplitude from the fit

    **Parameters**

    **qind** (*int*) – qubit index

    **Returns**

    drag amp

    **Return type**

    float
  </Function>

  <span id="qiskit-ignis-characterization-dragfitter-fit-data" />

  ### fit\_data

  <Function id="qiskit.ignis.characterization.DragFitter.fit_data" signature="DragFitter.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>

  <span id="qiskit-ignis-characterization-dragfitter-guess-params" />

  ### guess\_params

  <Function id="qiskit.ignis.characterization.DragFitter.guess_params" signature="DragFitter.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>

  <span id="qiskit-ignis-characterization-dragfitter-plot" />

  ### plot

  <Function id="qiskit.ignis.characterization.DragFitter.plot" signature="DragFitter.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>

  ## Attributes

  ### 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>

  ### 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>

  ### 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>

  ### 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>