Fix test/optimize/test_optimize.py: OptimizeWarning: Unknown solver o… (

#1218) …ptions: maxfun * Use the correct option for setting the maximum number of function evaluations for each scipy optimizer. Closes #970 Note that this changes the default settings for some optimizers for which `maxfun` has so far been ignored. * Reenable tests for scipy `trust-constr` and `dogleg` optimizers, closes #613
ICB-DCM · Nov 29, 2023 · 56fbf78 · 56fbf78
1 parent 00514bc
commit 56fbf78
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Showing 2 changed files with 15 additions and 6 deletions.
diff --git a/pypesto/optimize/optimizer.py b/pypesto/optimize/optimizer.py
@@ -471,10 +471,13 @@ def is_least_squares(self):
 
     def get_default_options(self):
         """Create default options specific for the optimizer."""
+        options = {'disp': False}
         if self.is_least_squares():
-            options = {'max_nfev': 1000, 'disp': False}
-        else:
-            options = {'maxfun': 1000, 'disp': False}
+            options['max_nfev'] = 1000
+        elif self.method.lower() in ('l-bfgs-b', 'tnc'):
+            options['maxfun'] = 1000
+        elif self.method.lower() in ('nelder-mead', 'powell'):
+            options['maxfev'] = 1000
         return options
 
 

diff --git a/test/optimize/test_optimize.py b/test/optimize/test_optimize.py
@@ -54,19 +54,21 @@ def problem(request) -> pypesto.Problem:
             'Powell',
             'CG',
             'BFGS',
+            'dogleg',
             'Newton-CG',
             'L-BFGS-B',
             'TNC',
             'COBYLA',
             'SLSQP',
+            'trust-constr',
             'trust-ncg',
             'trust-exact',
             'trust-krylov',
             'ls_trf',
             'ls_dogbox',
         ]
     ],
-    # disabled: ,'trust-constr', 'ls_lm', 'dogleg'
+    # disabled: 'ls_lm' (ValueError when passing bounds)
     ('ipopt', ''),
     ('dlib', ''),
     ('pyswarm', ''),
@@ -142,7 +144,10 @@ def problem(request) -> pypesto.Problem:
 
 @pytest.fixture(
     params=optimizers,
-    ids=[f"{i}-{o[0]}" for i, o in enumerate(optimizers)],
+    ids=[
+        f"{i}-{o[0]}{'-' + str(o[1]) if isinstance(o[1], str) and o[1] else ''}"
+        for i, o in enumerate(optimizers)
+    ],
 )
 def optimizer(request):
     return request.param
@@ -249,7 +254,8 @@ def get_optimizer(library, solver):
     options = {'maxiter': 100}
 
     if library == 'scipy':
-        options['maxfun'] = options.pop('maxiter')
+        if solver == "TNC" or solver.startswith("ls_"):
+            options['maxfun'] = options.pop('maxiter')
         optimizer = optimize.ScipyOptimizer(method=solver, options=options)
     elif library == 'ipopt':
         optimizer = optimize.IpoptOptimizer()