Minuit.interactive outside of Jupyter notebooks (scikit-hep#1056)

Implementation of a PyQt6 widget for `minuit.interactive` (Issue scikit-hep#771 ).
In order to make the plotting work properly, I changed the API for the
`visualize` methods of the build-in cost functions so that they
optionally accept matplotlib `Axes` objects (and for `CostSum`s a
`Figure`). If these arguments don't receive a value, `pyplot` is used.
This should keep the disruption of existing code as minimal as I could
manage.

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Adrian Peter Krone <adrian.krone@ptoton.me>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Louis Varriano <139183994+lvarriano@users.noreply.github.com>
Co-authored-by: Hans Dembinski <HDembinski@users.noreply.github.com>
Co-authored-by: SamuelBorden <sjborden@uw.edu>
Co-authored-by: Hans Dembinski <hans.dembinski@gmail.com>

Author: 7 people

.github/workflows/coverage.yml

@@ -32,6 +32,7 @@ jobs:
     - uses: actions/setup-python@v5
       with:
         python-version: "3.12"
+    - uses: tlambert03/setup-qt-libs@v1
     - uses: astral-sh/setup-uv@v4
     - run: uv pip install --system nox
     - run: nox -s cov

noxfile.py

@@ -67,7 +67,7 @@ def pypy(session: nox.Session) -> None:
 
 
 # Python-3.12 provides coverage info faster
-@nox.session(python="3.12", venv_backend="uv", reuse_venv=True)
+@nox.session(venv_backend="uv", reuse_venv=True)
 def cov(session: nox.Session) -> None:
     """Run covage and place in 'htmlcov' directory."""
     session.install("--only-binary=:all:", "-e.[test,doc]")

pyproject.toml

@@ -44,6 +44,7 @@ test = [
     "ipywidgets",
     # needed by ipywidgets >= 8.0.6
     "ipykernel",
+    "PySide6",
     "joblib",
     "jacobi",
     "matplotlib",
@@ -52,6 +53,8 @@ test = [
     "numba-stats; platform_python_implementation=='CPython'",
     "pytest",
     "pytest-xdist",
+    "pytest-xvfb",
+    "pytest-qt",
     "scipy",
     "tabulate",
     "boost_histogram",
@@ -101,6 +104,7 @@ pydocstyle.convention = "numpy"
 
 [tool.ruff.lint.per-file-ignores]
 "test_*.py" = ["B", "D"]
+"conftest.py" = ["B", "D"]
 "*.ipynb" = ["D"]
 "automatic_differentiation.ipynb" = ["F821"]
 "cython.ipynb" = ["F821"]

src/iminuit/ipywidget.py

@@ -1,9 +1,9 @@
 """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
-import sys
 
 with warnings.catch_warnings():
     # ipywidgets produces deprecation warnings through use of internal APIs :(
@@ -148,7 +148,7 @@ class Parameter(widgets.HBox):
         def __init__(self, minuit, par):
             val = minuit.values[par]
             vmin, vmax = minuit.limits[par]
-            step = _guess_initial_step(val, vmin, vmax)
+            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
 
@@ -277,18 +277,5 @@ def reset(self, value, limits=None):
     return widgets.HBox([out, ui])
 
 
-def _make_finite(x: float) -> float:
-    sign = -1 if x < 0 else 1
-    if abs(x) == np.inf:
-        return sign * sys.float_info.max
-    return x
-
-
-def _guess_initial_step(val: float, vmin: float, vmax: float) -> float:
-    if np.isfinite(vmin) and np.isfinite(vmax):
-        return 1e-2 * (vmax - vmin)
-    return 1e-2
-
-
 def _round(x: float) -> float:
     return float(f"{x:.1g}")

src/iminuit/minuit.py

@@ -2341,10 +2341,14 @@ def interactive(
         **kwargs,
     ):
         """
-        Return fitting widget (requires ipywidgets, IPython, matplotlib).
+        Interactive GUI for fitting.
 
-        A fitting widget is returned which can be displayed and manipulated in a
-        Jupyter notebook to find good starting parameters and to debug the fit.
+        Starts a fitting application (requires PySide6, matplotlib) in which the
+        fit is visualized and the parameters can be manipulated to find good
+        starting parameters and to debug the fit.
+
+        When called in a Jupyter notebook (requires ipywidgets, IPython, matplotlib),
+        a fitting widget is returned instead, which can be displayed.
 
         Parameters
         ----------
@@ -2371,9 +2375,14 @@ def interactive(
         --------
         Minuit.visualize
         """
-        from iminuit.ipywidget import make_widget
-
         plot = self._visualize(plot)
+
+        if mutil.is_jupyter():
+            from iminuit.ipywidget import make_widget
+
+        else:
+            from iminuit.qtwidget import make_widget
+
         return make_widget(self, plot, kwargs, raise_on_exception)
 
     def _free_parameters(self) -> Set[str]: