ENH: Add iprint support to COBYLA

Author: nbelakovski

scipy/optimize/_cobyla_py.py

@@ -192,7 +192,7 @@ def fmin_cobyla(func, x0, cons, args=(), consargs=None, rhobeg=1.0,
 @synchronized
 def _minimize_cobyla(fun, x0, args=(), constraints=(),
                      rhobeg=1.0, tol=1e-6, maxiter=1000,
-                     disp=False, catol=np.sqrt(np.finfo(float).eps),
+                     disp=0, catol=np.sqrt(np.finfo(float).eps),
                      ftarget=-np.inf, callback=None, bounds=None,
                      **unknown_options):
     """
@@ -206,9 +206,15 @@ def _minimize_cobyla(fun, x0, args=(), constraints=(),
     tol : float
         Final accuracy in the optimization (not precisely guaranteed).
         This is a lower bound on the size of the trust region.
-    disp : bool
-        Set to True to print convergence messages. If False,
-        `verbosity` is ignored as set to 0.
+    disp : int
+        0: there will be no printing;
+        1: a message will be printed to the screen at the return, showing the
+            best vector of variables found and its objective function value
+        2: in addition to 1, each new value of RHO is printed to the screen,
+            with the best vector of variables so far and its objective function
+            value.
+        3: in addition to 2, each function evaluation with its variables will
+            be printed to the screen.
     maxiter : int
         Maximum number of function evaluations.
     catol : float
@@ -225,7 +231,10 @@ def _minimize_cobyla(fun, x0, args=(), constraints=(),
     _check_unknown_options(unknown_options)
     maxfun = maxiter
     rhoend = tol
-    iprint = int(bool(disp))
+    iprint = disp if disp is not None else 0
+    if iprint != 0 and iprint != 1 and iprint != 2 and iprint != 3:
+        raise ValueError(f'disp argument to minimize must be 0, 1, 2, or 3,\
+                          received {iprint}')
 
     # create the ScalarFunction, cobyla doesn't require derivative function
     def _jac(x, *args):

scipy/optimize/tests/test_cobyla.py

@@ -11,7 +11,7 @@ class TestCobyla:
     def setup_method(self):
         self.x0 = [4.95, 0.66]
         self.solution = [math.sqrt(25 - (2.0/3)**2), 2.0/3]
-        self.opts = {'disp': False, 'rhobeg': 1, 'tol': 1e-5,
+        self.opts = {'disp': 0, 'rhobeg': 1, 'tol': 1e-5,
                      'maxiter': 100}
 
     def fun(self, x):
@@ -24,9 +24,9 @@ def con2(self, x):
         return -self.con1(x)
 
     def test_simple(self):
-        # use disp=True as smoke test for gh-8118
+        # use disp=1 as smoke test for gh-8118
         x = fmin_cobyla(self.fun, self.x0, [self.con1, self.con2], rhobeg=1,
-                        rhoend=1e-5, maxfun=100, disp=True)
+                        rhoend=1e-5, maxfun=100, disp=1)
         assert_allclose(x, self.solution, atol=1e-4)
 
     def test_minimize_simple(self):