Merge pull request #237 from do-mpc/develop

v4.3.3

do_mpc/controller.py

@@ -616,11 +616,18 @@ def set_objective(self, mterm=None, lterm=None):
         if not isinstance(lterm, (casadi.DM, casadi.SX, casadi.MX)):
             raise Exception('lterm must be of type casadi.DM, casadi.SX or casadi.MX. You have: {}.'.format(type(lterm)))
 
-        self.mterm = mterm
+        if mterm is None:
+            self.mterm = DM(0)
+        else:
+            self.mterm = mterm
         # TODO: This function should be evaluated with scaled variables.
         self.mterm_fun = Function('mterm', [_x, _tvp, _p], [mterm])
 
-        self.lterm = lterm
+        if lterm is None:
+            self.lterm = DM(0)
+        else:
+            self.lterm = lterm
+
         self.lterm_fun = Function('lterm', [_x, _u, _z, _tvp, _p], [lterm])
 
         # Check if lterm and mterm use invalid variables as inputs.
@@ -1144,7 +1151,7 @@ def _prepare_nlp(self):
         self.ub_opt_x = opt_x(np.inf)
 
         # Initialize objective function and constraints
-        obj = 0
+        obj = DM(0)
         cons = []
         cons_lb = []
         cons_ub = []

do_mpc/estimator.py

@@ -821,7 +821,7 @@ def set_default_objective(self, P_x, P_v=None, P_p=None, P_w=None):
 
 
         # Calculate stage cost:
-        stage_cost = 0
+        stage_cost = DM(0)
 
         if P_v is None:
             assert n_v == 0, 'Must pass weighting factor P_v, since you have measurement noise on some measurements (configured in model).'
@@ -1220,7 +1220,7 @@ def _prepare_nlp(self):
         self.ub_opt_x = opt_x(np.inf)
 
         # Initialize objective function and constraints
-        obj = 0
+        obj = DM(0)
         cons = []
         cons_lb = []
         cons_ub = []

do_mpc/sampling/datahandler.py

@@ -10,6 +10,7 @@
 from do_mpc.tools import load_pickle, save_pickle
 import types
 import logging
+from inspect import signature
 
 
 
@@ -149,7 +150,11 @@ def _post_process_single(self,sample,result):
         if self.flags['set_post_processing']:
             for key in self.post_processing:
                 if result is not None:
-                    result_processed[key] = self.post_processing[key](result)
+                    # post_processing function is either just a function of the result or of the sample and the result.
+                    if self.post_processing[key]['n_args'] == 1:
+                        result_processed[key] = self.post_processing[key]['function'](result)
+                    elif self.post_processing[key]['n_args'] == 2:
+                        result_processed[key] = self.post_processing[key]['function'](sample, result)
                 else:
                     result_processed[key] = None
         # Result without post processing
@@ -283,6 +288,15 @@ def set_post_processing(self, name, post_processing_function):
         The post processing function is applied to all loaded samples, e.g. with :py:meth:`__getitem__` or :py:meth:`filter`.
         Users can set an arbitrary amount of post processing functions by repeatedly calling this method.
 
+        The ``post_processing_function`` can have two possible signatures:
+
+        1. ``post_processing_function(case_definition, sample_result)``
+
+        2. ``post_processing_function(sample_result)``
+
+        Where ``case_definition`` is a ``dict`` of all variables introduced in the :py:class:`do_mpc.sampling.samplingplanner.SamplingPlanner`
+        and ``sample_results`` is the result obtained from the function introduced with :py:class:`do_mpc.sampling.sampler.Sampler.set_sample_function`.
+
         .. note::
 
             Setting a post processing function with an already existing name will overwrite the previously set post processing function.
@@ -334,5 +348,9 @@ def sample_function(alpha, beta):
         assert isinstance(name, str), 'name must be str, you have {}'.format(type(name))
         assert isinstance(post_processing_function, (types.FunctionType, types.BuiltinFunctionType)), 'post_processing_function must be either Function or BuiltinFunction_or_Method, you have {}'.format(type(post_processing_function))
 
-        self.post_processing.update({name: post_processing_function})
+        # Check signature of function for number of arguments.
+        sig = signature(post_processing_function)
+        n_args = len(sig.parameters.keys())
+
+        self.post_processing.update({name: {'function': post_processing_function, 'n_args': n_args}})
         self.flags['set_post_processing'] = True

documentation/source/example_gallery/data_generator.ipynb

@@ -735,7 +735,7 @@
    "id": "individual-official",
    "metadata": {},
    "source": [
-    "# Sampling closed-loop trajectories\n",
+    "## Sampling closed-loop trajectories\n",
     "\n",
     "A more reasonable use-case in the scope of **do-mpc** is to sample closed-loop trajectories of a dynamical system with a (MPC) controller. \n",
     "\n",

documentation/source/example_gallery/industrial_poly.ipynb

@@ -416,7 +416,6 @@
     "mpc.bounds['lower','_x','accum_monom'] = 0.0\n",
     "\n",
     "# upper bound states\n",
-    "mpc.bounds['upper','_x','T_R'] = 363.15 + temp_range\n",
     "mpc.bounds['upper','_x','T_S'] = 400.0\n",
     "mpc.bounds['upper','_x','Tout_M'] = 400.0\n",
     "mpc.bounds['upper','_x','T_EK'] = 400.0\n",
@@ -425,6 +424,22 @@
     "mpc.bounds['upper','_x','T_adiab'] = 382.15"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The upper bound of the reactor temperature is set via a soft-constraint:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mpc.set_nl_cons('T_R_UB', _x['T_R'], ub=363.15+temp_range, soft_constraint=True, penalty_term_cons=1e4)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -867,7 +882,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -881,7 +896,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.8.5"
   },
   "toc": {
    "base_numbering": 1,

documentation/source/getting_started.ipynb

@@ -1394,8 +1394,8 @@
    "outputs": [],
    "source": [
     "# Change the color for the three states:\n",
-    "for line_i in mpc_graphics.pred_lines['_x', 'phi_1']: line_i.set_color('#1f77b4') # orange\n",
-    "for line_i in mpc_graphics.pred_lines['_x', 'phi_2']: line_i.set_color('#ff7f0e') # blue\n",
+    "for line_i in mpc_graphics.pred_lines['_x', 'phi_1']: line_i.set_color('#1f77b4') # blue\n",
+    "for line_i in mpc_graphics.pred_lines['_x', 'phi_2']: line_i.set_color('#ff7f0e') # orange\n",
     "for line_i in mpc_graphics.pred_lines['_x', 'phi_3']: line_i.set_color('#2ca02c') # green\n",
     "# Change the color for the two inputs:    \n",
     "for line_i in mpc_graphics.pred_lines['_u', 'phi_m_1_set']: line_i.set_color('#1f77b4')\n",
@@ -1869,9 +1869,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "py36",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "py36"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1883,7 +1883,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.8.5"
   },
   "toc": {
    "base_numbering": 1,

examples/industrial_poly/template_mpc.py

@@ -71,7 +71,6 @@ def template_mpc(model):
     mpc.bounds['lower','_x','Tout_AWT'] = 288.0
     mpc.bounds['lower','_x','accum_monom'] = 0.0
 
-    mpc.bounds['upper','_x','T_R'] = 363.15 + temp_range
     mpc.bounds['upper','_x','T_S'] = 400.0
     mpc.bounds['upper','_x','Tout_M'] = 400.0
     mpc.bounds['upper','_x','T_EK'] = 400.0
@@ -95,6 +94,13 @@ def template_mpc(model):
 
     mpc.scaling['_u','m_dot_f'] = 100
 
+    # Check if robust multi-stage is active
+    if mpc.n_robust == 0:
+        # Sot-constraint for the reactor upper bound temperature
+        mpc.set_nl_cons('T_R_UB', _x['T_R'], ub=363.15+temp_range, soft_constraint=True, penalty_term_cons=1e4)
+    else:
+        mpc.bounds['upper','_x','T_R'] = 363.15+temp_range
+
 
     delH_R_var = np.array([950.0, 950.0 * 1.30, 950.0 * 0.70])
     k_0_var = np.array([7.0*1.00, 7.0*1.30, 7.0*0.70])