"""Interactive fitting widget for Jupyter notebooks.""" from .util import _widget_guess_initial_step, _make_finite import warnings import numpy as np from typing import Dict, Any, Callable with warnings.catch_warnings(): # ipywidgets produces deprecation warnings through use of internal APIs :( warnings.simplefilter("ignore") try: import ipywidgets as widgets from ipywidgets.widgets.interaction import show_inline_matplotlib_plots from IPython.display import clear_output from matplotlib import pyplot as plt except ModuleNotFoundError as e: e.msg += ( "\n\nPlease install ipywidgets, IPython, and matplotlib to " "enable interactive" ) raise def make_widget( minuit: Any, plot: Callable[..., None], kwargs: Dict[str, Any], raise_on_exception: bool, ): """Make interactive fitting widget.""" # Implementations makes heavy use of closures, # we frequently use variables which are defined # near the end of the function. original_values = minuit.values[:] original_limits = minuit.limits[:] def plot_with_frame(from_fit, report_success): trans = plt.gca().transAxes try: with warnings.catch_warnings(): minuit.visualize(plot, **kwargs) except Exception: if raise_on_exception: raise import traceback plt.figtext( 0, 0.5, traceback.format_exc(limit=-1), fontdict={"family": "monospace", "size": "x-small"}, va="center", color="r", backgroundcolor="w", wrap=True, ) return fval = minuit.fmin.fval if from_fit else minuit._fcn(minuit.values) plt.text( 0.05, 1.05, f"FCN = {fval:.3f}", transform=trans, fontsize="x-large", ) if from_fit and report_success: plt.text( 0.95, 1.05, f"{'success' if minuit.valid and minuit.accurate else 'FAILURE'}", transform=trans, fontsize="x-large", ha="right", ) def fit(): if algo_choice.value == "Migrad": minuit.migrad() elif algo_choice.value == "Scipy": minuit.scipy() elif algo_choice.value == "Simplex": minuit.simplex() return False else: assert False # pragma: no cover, should never happen return True class OnParameterChange: # Ugly implementation notes: # We want the plot when the user moves the slider widget, but not when # we update the slider value manually from our code. Unfortunately, # the latter also calls OnParameterChange, which leads to superfluous plotting. # I could not find a nice way to prevent that (and I tried many), so as a workaround # we optionally skip a number of calls, when the slider is updated. def __init__(self, skip: int = 0): self.skip = skip def __call__(self, change: Dict[str, Any] = {}): if self.skip > 0: self.skip -= 1 return from_fit = change.get("from_fit", False) report_success = change.get("report_success", False) if not from_fit: for i, x in enumerate(parameters): minuit.values[i] = x.slider.value if any(x.fit.value for x in parameters): saved = minuit.fixed[:] for i, x in enumerate(parameters): minuit.fixed[i] = not x.fit.value from_fit = True report_success = do_fit(None) minuit.fixed = saved # Implementation like in ipywidegts.interaction.interactive_output with out: clear_output(wait=True) plot_with_frame(from_fit, report_success) with warnings.catch_warnings(): warnings.simplefilter("ignore") show_inline_matplotlib_plots() def do_fit(change): report_success = fit() for i, x in enumerate(parameters): x.reset(minuit.values[i]) if change is None: return report_success OnParameterChange()({"from_fit": True, "report_success": report_success}) def on_update_button_clicked(change): for x in parameters: x.slider.continuous_update = not x.slider.continuous_update def on_reset_button_clicked(change): minuit.reset() minuit.values = original_values minuit.limits = original_limits for i, x in enumerate(parameters): x.reset(minuit.values[i], minuit.limits[i]) OnParameterChange()() class Parameter(widgets.HBox): def __init__(self, minuit, par): val = minuit.values[par] vmin, vmax = minuit.limits[par] step = _widget_guess_initial_step(val, vmin, vmax) vmin2 = vmin if np.isfinite(vmin) else val - 100 * step vmax2 = vmax if np.isfinite(vmax) else val + 100 * step tlabel = widgets.Label(par, layout=widgets.Layout(width=f"{longest_par}em")) tmin = widgets.BoundedFloatText( _round(vmin2), min=_make_finite(vmin), max=vmax2, step=1e-1 * (vmax2 - vmin2), layout=widgets.Layout(width="4.1em"), ) tmax = widgets.BoundedFloatText( _round(vmax2), min=vmin2, max=_make_finite(vmax), step=1e-1 * (vmax2 - vmin2), layout=widgets.Layout(width="4.1em"), ) self.slider = widgets.FloatSlider( val, min=vmin2, max=vmax2, step=step, continuous_update=True, readout_format=".3g", layout=widgets.Layout(min_width="50%"), ) self.slider.observe(OnParameterChange(), "value") def on_min_change(change): self.slider.min = change["new"] tmax.min = change["new"] lim = minuit.limits[par] minuit.limits[par] = (self.slider.min, lim[1]) def on_max_change(change): self.slider.max = change["new"] tmin.max = change["new"] lim = minuit.limits[par] minuit.limits[par] = (lim[0], self.slider.max) tmin.observe(on_min_change, "value") tmax.observe(on_max_change, "value") self.fix = widgets.ToggleButton( minuit.fixed[par], description="Fix", tooltip="Fix", layout=widgets.Layout(width="3.1em"), ) self.fit = widgets.ToggleButton( False, description="Fit", tooltip="Fit", layout=widgets.Layout(width="3.5em"), ) def on_fix_toggled(change): minuit.fixed[par] = change["new"] if change["new"]: self.fit.value = False def on_fit_toggled(change): self.slider.disabled = change["new"] if change["new"]: self.fix.value = False OnParameterChange()() self.fix.observe(on_fix_toggled, "value") self.fit.observe(on_fit_toggled, "value") super().__init__([tlabel, tmin, self.slider, tmax, self.fix, self.fit]) def reset(self, value, limits=None): self.slider.unobserve_all("value") self.slider.value = value if limits: self.slider.min, self.slider.max = limits # Installing the observer actually triggers a notification, # we skip it. See notes in OnParameterChange. self.slider.observe(OnParameterChange(1), "value") longest_par = max(len(par) for par in minuit.parameters) parameters = [Parameter(minuit, par) for par in minuit.parameters] button_layout = widgets.Layout(max_width="8em") fit_button = widgets.Button( description="Fit", button_style="primary", layout=button_layout, ) fit_button.on_click(do_fit) update_button = widgets.ToggleButton( True, description="Continuous", layout=button_layout, ) update_button.observe(on_update_button_clicked) reset_button = widgets.Button( description="Reset", button_style="danger", layout=button_layout, ) reset_button.on_click(on_reset_button_clicked) algo_choice = widgets.Dropdown( options=["Migrad", "Scipy", "Simplex"], value="Migrad", layout=button_layout, ) ui = widgets.VBox( [ widgets.HBox([fit_button, update_button, reset_button, algo_choice]), widgets.VBox(parameters), ] ) out = widgets.Output() OnParameterChange()() return widgets.HBox([out, ui]) def _round(x: float) -> float: return float(f"{x:.1g}")