Curve fitting widgets

Overview

The widgets.fit module provides interactive curve fitting widgets allowing:

• to fit data manually (by moving sliders)

• or automatically (with standard optimization algorithms provided by scipy).

The guifit() function is a factory function that returns a dialog box allowing to fit data with a given function.

Example

Here is an example of use of the guifit() function:

import numpy as np

from plotpy.widgets.fit import FitParam, guifit


def test_fit():
    """Test the curve fitting tool"""
    x = np.linspace(-10, 10, 1000)
    y = np.cos(1.5 * x) + np.random.rand(x.shape[0]) * 0.2

    def fit(x, params):
        a, b = params
        return np.cos(b * x) + a

    a = FitParam("Offset", 0.7, -1.0, 1.0)
    b = FitParam("Frequency", 1.2, 0.3, 3.0, logscale=True)
    params = [a, b]
    values = guifit(x, y, fit, params, xlabel="Time (s)", ylabel="Power (a.u.)")

    print(values)
    print([param.value for param in params])


if __name__ == "__main__":
    test_fit()

Reference

plotpy.widgets.fit.guifit(x: ndarray, y: ndarray, fitfunc: Callable, fitparams: list[FitParam] | None = None, fitargs: tuple | None = None, fitkwargs: dict | None = None, wintitle: str | None = None, title: str | None = None, xlabel: str | None = None, ylabel: str | None = None, param_cols: int = 1, auto_fit: bool = True, winsize: tuple[int, int] | None = None, winpos: tuple[int, int] | None = None) → list[float] | None

GUI-based curve fitting tool

Parameters:

• x – x data

• y – y data

• fitfunc – fit function

• fitparams – fit parameters. Defaults to None.

• fitargs – fit args. Defaults to None.

• fitkwargs – fit kwargs. Defaults to None.

• wintitle – window title. Defaults to None.

• title – plot title. Defaults to None.

• xlabel – x label. Defaults to None.

• ylabel – y label. Defaults to None.

• param_cols – number of columns for fit parameters. Defaults to 1.

• auto_fit – auto fit. Defaults to True.

• winsize (tuple[int, int] | None) – window size. Defaults to None.

• winpos (tuple[int, int] | None) – window position. Defaults to None.

Returns:

Fit parameter values or None if the user cancels the dialog

class plotpy.widgets.fit.FitDialog(title: str | None = None, icon: str = 'plotpy.svg', edit: bool = True, toolbar: bool = False, auto_tools: bool = True, options: PlotOptions | dict[str, Any] | None = None, parent: QWidget | None = None, panels: list[PanelWidget] | None = None, param_cols: int = 1, legend_anchor: str = 'TR', auto_fit: bool = False)

Fit dialog box

Parameters:

• title – window title. Defaults to None.

• icon – window icon. Defaults to “plotpy.svg”.

• edit – enable/disable edit menu. Defaults to True.

• toolbar – enable/disable toolbar. Defaults to False.

• auto_tools – enable/disable auto tools. Defaults to True.

• options – plot options. Defaults to None.

• parent – parent widget. Defaults to None.

• panels – list of panel widgets. Defaults to None.

• param_cols – number of columns for parameter table. Defaults to 1.

• legend_anchor – legend anchor. Defaults to “TR”.

• auto_fit – enable/disable auto fit. Defaults to False.

set_data(x: ndarray, y: ndarray, fitfunc: Callable = None, fitparams: list[FitParam] | None = None, fitargs: tuple | None = None, fitkwargs: dict | None = None) → None

Set fit data

Parameters:

• x – x data

• y – y data

• fitfunc – fit function. Defaults to None.

• fitparams – fit parameters. Defaults to None.

• fitargs – fit args. Defaults to None.

• fitkwargs – fit kwargs. Defaults to None.

get_values() → list[float]

Returns fit parameter values

Returns:

Fit parameter values

autofit() → None

Autofit

class plotpy.widgets.fit.FitParam(name: str, value: float, min: float, max: float, logscale: bool = False, steps: int = 5000, format: str = '%.3f', size_offset: int = 0, unit: str = '')

Fit parameters

Parameters:

• name – name of the parameter

• value – value of the parameter

• min – minimum value of the parameter

• max – maximum value of the parameter

• logscale – if True, the parameter is fitted in logscale. Default is False.

• steps – number of steps for the slider. Default is 5000.

• format – format of the parameter. Default is “%.3f”.

• size_offset – size offset of the parameter. Default is 0.

• unit – unit of the parameter. Default is “”.

copy() → FitParam

Return a copy of this fitparam

Returns:

Copy of this fitparam

create_widgets(parent: QWidget, refresh_callback: Callable) → None

Create widgets

Parameters:

• parent – parent widget

• refresh_callback – callback function to refresh the plot

add_widgets(widgets: list[QWidget]) → None

Add widgets

Parameters:

widgets – list of widgets to add

get_widgets() → list[QWidget]

Get widgets

Returns:

List of widgets

set_scale(state: int) → None

Set scale

Parameters:

state – state

set_text(fmt: str = None) → None

Set text

Parameters:

fmt – format (default: None)

line_editing_finished()

Line editing finished

slider_value_changed(int_value: int) → None

Slider value changed

Parameters:

int_value – integer value

update_slider_value()

Update slider value

edit_param(parent: QWidget) → None

Edit param

Parameters:

parent – parent widget

update(refresh: bool = True) → None

Update

Parameters:

refresh – refresh (default: True)

class plotpy.widgets.fit.AutoFitParam(title: str | None = None, comment: str | None = None, icon: str = '', readonly: bool = False)

Automatic fit parameters