Allow specifying iter_cb for refine (instead of normal callback)

brian2modelfitting/fitter.py

@@ -4,9 +4,9 @@
 from brian2.parsing.sympytools import sympy_to_str, str_to_sympy
 from brian2.units.fundamentalunits import DIMENSIONLESS, get_dimensions
 from numpy import ones, array, arange, concatenate, mean, argmin, nanmin, reshape, zeros
-from brian2 import (NeuronGroup,  defaultclock, get_device, Network,
+from brian2 import (NeuronGroup, defaultclock, get_device, Network,
                     StateMonitor, SpikeMonitor, second, get_local_namespace,
-                    Quantity)
+                    Quantity, get_logger)
 from brian2.input import TimedArray
 from brian2.equations.equations import Equations
 from brian2.devices import set_device, reset_device, device
@@ -18,6 +18,8 @@
 from .utils import callback_setup, make_dic
 
 
+logger = get_logger(__name__)
+
 def get_param_dic(params, param_names, n_traces, n_samples):
     """Transform parameters into a dictionary of appropiate size"""
     params = array(params)
@@ -634,7 +636,7 @@ def refine(self, params=None, t_start=None, normalization=None,
         if normalization is None:
             normalization = getattr(self.metric, 'normalization', 1.)
 
-        callback = callback_setup(callback, None)
+        callback_func = callback_setup(callback, None)
 
         # Set up Parameter objects
         parameters = lmfit.Parameters()
@@ -705,13 +707,26 @@ def _callback_wrapper(params, iter, resid, *args, **kwds):
             best_idx = argmin(errors)
             best_error = errors[best_idx]
             best_params = tested_parameters[best_idx]
-            return callback(params, errors, best_params, best_error, iter)
+            return callback_func(params, errors, best_params, best_error, iter)
 
         assert 'Dfun' not in kwds
         if calc_gradient:
             kwds.update({'Dfun': _calc_gradient})
+        if 'iter_cb' in kwds:
+            # Use the given callback but raise a warning if callback is not
+            # set to None
+            if callback is not None:
+                logger.warn('The iter_cb keyword has been specified together '
+                            f'with callback={callback!r}. Only the iter_cb '
+                            'callback will be used. Use the standard '
+                            'callback mechanism or set callback=None to '
+                            'remove this warning.',
+                            name_suffix='iter_cb_callback')
+            iter_cb = kwds.pop('iter_cb')
+        else:
+            iter_cb = _callback_wrapper
         result = lmfit.minimize(_calc_error, parameters,
-                                iter_cb=_callback_wrapper,
+                                iter_cb=iter_cb,
                                 **kwds)
 
         if needs_device_reset:

brian2modelfitting/tests/test_modelfitting_tracefitter.py

@@ -294,7 +294,6 @@ def test_fitter_refine_tstart(setup_constant):
                                t_start=50*dt)
 
     # Fit should be close to 20mV
-    print(params['c'])
     assert np.abs(params['c']*volt - 20*mV) < 1*mV