fix: Fixing a crash for the Master algorithm with the 'block_initiali…

CHANGELOG

@@ -1,5 +1,6 @@
 --- CHANGELOG ---
 --- PyFMI-FUTURE ---
+    * Fixed a crash with the `Master` algorithm option `block_initialization`.
 
 --- PyFMI-2.20.0 ---
     * Fixed so FMU `reset` resets to log_level that it was loaded with.

src/pyfmi/master.pyx

@@ -875,6 +875,9 @@ cdef class Master:
         return xd
 
     cpdef np.ndarray get_specific_connection_outputs_discrete(self, model, np.ndarray mask, np.ndarray yout):
+        if len(mask) == 0:
+            # quick return; nothing to get; prevents index array in array slicing
+            return
         cdef int j = 0
         ytmp = model.get(np.array(self.models_dict[model]["local_output_discrete"])[mask])
         for i, flag in enumerate(mask):
@@ -883,6 +886,9 @@ cdef class Master:
                 j = j + 1
 
     cpdef np.ndarray get_specific_connection_outputs(self, model, np.ndarray mask, np.ndarray yout):
+        if len(mask) == 0:
+            # quick return; nothing to get; prevents index array in array slicing
+            return
         cdef int j = 0
         cdef np.ndarray ytmp = (<FMI2.FMUModelCS2>model).get_real(self.models_dict[model]["local_output_vref_array"][mask])
         for i, flag in enumerate(mask):
@@ -1015,6 +1021,9 @@ cdef class Master:
             model.set(self.models_dict[model]["local_input_discrete"], u[i:inext])
 
     cpdef set_specific_connection_inputs(self, model, np.ndarray mask, np.ndarray u):
+        if len(mask) == 0:
+            # quick return; nothing to set; prevents index array in array slicing
+            return
         cdef int i = self.models_dict[model]["global_index_inputs"]
         cdef int inext = i + self.models_dict[model]["local_input_len"]
         cdef np.ndarray usliced = u[i:inext]
@@ -1023,6 +1032,9 @@ cdef class Master:
         (<FMI2.FMUModelCS2>model).set_real(self.models_dict[model]["local_input_vref_array"][mask], usliced[mask])
 
     cpdef set_specific_connection_inputs_discrete(self, model, np.ndarray mask, np.ndarray u):
+        if len(mask) == 0:
+            # quick return; nothing to set; prevents index array in array slicing
+            return
         cdef int i = self.models_dict[model]["global_index_inputs_discrete"]
         cdef int inext = i + self.models_dict[model]["local_input_discrete_len"]
         cdef np.ndarray usliced = u[i:inext]

tests/test_fmi_master.py

@@ -449,6 +449,24 @@ def test_external_inputs(self, input_traj):
         np.testing.assert_array_equal(res[0]["Float64_discrete_output"], [0, 0, 0, 0, 0, 0])
         np.testing.assert_array_equal(res[1]["Float64_discrete_output"], [0, 2, 4, 6, 8, 10])
 
+    def test_block_initialization(self):
+        """Basic smoke-test for the 'block_initialization' option."""
+        fmu1 = FMUModelCS2(os.path.join(FMI2_REF_FMU_PATH, "Feedthrough.fmu"))
+        fmu2 = FMUModelCS2(os.path.join(FMI2_REF_FMU_PATH, "Feedthrough.fmu"))
+        fmu3 = FMUModelCS2(os.path.join(FMI2_REF_FMU_PATH, "Feedthrough.fmu"))
+
+        models = [fmu1, fmu2, fmu3]
+        # some inputs/outputs are intentionally left unconnected
+        connections = [
+            (fmu1, "Float64_continuous_output", fmu2, "Float64_continuous_input"), 
+            (fmu2, "Float64_discrete_output", fmu3, "Float64_discrete_input"),
+        ]
+        master = Master(models, connections)
+
+        opts = master.simulate_options()
+        opts["block_initialization"] = True
+        master.simulate(0, 1, options=opts)
+
 class Test_Master_Result_Downsampling:
     """Tests related to the 'result_downsampling' option of the Master algorithm."""
     @classmethod