Rename of get_gates to compute_propagators

Author: nwittler

c3/optimizers/c1.py

@@ -134,7 +134,7 @@ def goal_run(self, current_params: tf.Tensor) -> tf.float64:
         if self.update_model:
             self.pmap.model.update_model()
         dims = self.pmap.model.dims
-        propagators = self.exp.get_gates()
+        propagators = self.exp.compute_propagators()
         try:
             goal = self.fid_func(propagators, self.index, dims, self.evaluation + 1)
         except TypeError:

c3/optimizers/c3.py

@@ -190,7 +190,7 @@ def _one_par_sim_vals(
         # We find the unique gates used in the sequence and compute
         # only those.
         self.exp.opt_gates = list(set(itertools.chain.from_iterable(sequences)))
-        self.exp.get_gates()
+        self.exp.compute_propagators()
         pops = self.exp.evaluate(sequences)
         sim_vals, pops = self.exp.process(
             labels=self.state_labels[target], populations=pops

c3/optimizers/optimizer.py

@@ -133,7 +133,7 @@ def log_best_unitary(self) -> None:
         Save the best unitary in the log.
         """
         with open(self.logdir + "best_point_" + self.logname, "w") as best_point:
-            U_dict = self.exp.unitaries
+            U_dict = self.exp.propagators
             for gate, U in U_dict.items():
                 best_point.write("\n")
                 best_point.write(f"Re {gate}: \n")

c3/optimizers/sensitivity.py

@@ -232,7 +232,7 @@ def goal_run(self, current_params):
                 # We find the unique gates used in the sequence and compute
                 # only them.
                 self.exp.opt_gates = list(set(itertools.chain.from_iterable(sequences)))
-                self.exp.get_gates()
+                self.exp.compute_propagators()
                 pops = self.exp.evaluate(sequences)
                 sim_vals = self.exp.process(
                     labels=self.state_labels[target], populations=pops

c3/qiskit/c3_backend.py

@@ -264,8 +264,8 @@ def run_experiment(self, experiment: QasmQobjExperiment) -> Dict[str, Any]:
                 pop_t = np.append(pop_t, pops, axis=1)
 
         elif self._simulation_type == "physics":
-            exp.get_gates()
-            dUs = exp.dUs
+            exp.compute_propagators()
+            dUs = exp.partial_propagators
             # TODO Implement extracting n_qubits and n_levels from device
             # create initial state for qubits and levels
             psi_init = get_init_ground_state(