Add ability to pass options to SciPy minimizers

src/iminuit/minuit.py

@@ -987,6 +987,7 @@ def scipy(
         hess: Any = None,
         hessp: Any = None,
         constraints: Iterable = None,
+        options: Dict[str, Any] = {},
     ) -> "Minuit":
         """
         Minimize with SciPy algorithms.
@@ -1014,6 +1015,10 @@ def scipy(
             as the original fcn, see hess parameter for details. No parameters may be
             omitted in the signature, even if those parameters are not used in the
             constraint.
+        options : dict, optional
+            A dictionary of solver options to pass to the SciPy minimizer through the
+            `options` parameter of :func:`scipy.optimize.minimize`. See each solver
+            method for the options it accepts.
 
         Notes
         -----
@@ -1027,6 +1032,9 @@ def scipy(
         criterion is evaluated only after the original algorithm already stopped. This
         means that usually SciPy minimizers will use more iterations than Migrad and
         the tolerance :attr:`tol` has no effect on SciPy minimizers.
+
+        You can specify convergence tolerance and other options for the SciPy minimizers
+        through the `options` parameter.
         """
         try:
             from scipy.optimize import (
@@ -1043,6 +1051,9 @@ def scipy(
         if ncall is None:
             ncall = self._migrad_maxcall()
 
+        if type(options) is not dict:
+            raise ValueError("options must be a dictionary")
+
         cfree = ~np.array(self.fixed[:], dtype=bool)
         cpar = np.array(self.values[:])
         no_fixed_parameters = np.all(cfree)
@@ -1224,18 +1235,29 @@ def __call__(self, par, v):
             else:
                 method = "BFGS"
 
+        # copy to avoid mutable problems
+        scipy_options = dict(options)
+
+        # attempt to set default number of function evaluations if not provided
         # various workarounds for API inconsistencies in scipy.optimize.minimize
-        options = {"maxiter": ncall}
+        if "maxiter" not in options:
+            scipy_options["maxiter"] = ncall
         if method in (
             "Nelder-Mead",
             "Powell",
         ):
-            options["maxfev"] = ncall
-            del options["maxiter"]
+            if "maxfev" not in options:
+                scipy_options["maxfev"] = ncall
+
+            if "maxiter" not in options:
+                del scipy_options["maxiter"]
 
         if method in ("L-BFGS-B", "TNC"):
-            options["maxfun"] = ncall
-            del options["maxiter"]
+            if "maxfun" not in options:
+                scipy_options["maxfun"] = ncall
+
+            if "maxiter" not in options:
+                del scipy_options["maxiter"]
 
         if method in ("COBYLA", "SLSQP", "trust-constr") and constraints is None:
             constraints = ()
@@ -1255,7 +1277,7 @@ def __call__(self, par, v):
                 hess=hess,
                 hessp=hessp,
                 constraints=constraints,
-                options=options,
+                options=scipy_options,
             )
         if self.print_level > 0:
             print(r)

tests/test_scipy.py

@@ -231,6 +231,12 @@ def test_bad_constraint():
         m.scipy(constraints=[{}])
 
 
+def test_bad_options():
+    m = Minuit(fcn, a=1, b=2)
+    with pytest.raises(ValueError):
+        m.scipy(options=[])
+
+
 def test_high_print_level(capsys):
     m = Minuit(fcn, a=1, b=2)
     m.scipy()