use black(1) for uniform code formatting

1 files changed, 338 insertions, 151 deletions

diff --git a/lib/harness.py b/lib/harness.py
index 54518e3..3b279c0 100644
--- a/lib/harness.py
+++ b/lib/harness.py
@@ -24,7 +24,16 @@ class TransitionHarness:
           primitive values (-> set by the return value of the current run, not necessarily constan)
         * `args`: function arguments, if isa == 'transition'
     """
-    def __init__(self, gpio_pin = None, gpio_mode = 'around', pta = None, log_return_values = False, repeat = 0, post_transition_delay_us = 0):
+
+    def __init__(
+        self,
+        gpio_pin=None,
+        gpio_mode="around",
+        pta=None,
+        log_return_values=False,
+        repeat=0,
+        post_transition_delay_us=0,
+    ):
         """
         Create a new TransitionHarness
 
@@ -47,7 +56,14 @@ class TransitionHarness:
         self.reset()
 
     def copy(self):
-        new_object = __class__(gpio_pin = self.gpio_pin, gpio_mode = self.gpio_mode, pta = self.pta, log_return_values = self.log_return_values, repeat = self.repeat, post_transition_delay_us = self.post_transition_delay_us)
+        new_object = __class__(
+            gpio_pin=self.gpio_pin,
+            gpio_mode=self.gpio_mode,
+            pta=self.pta,
+            log_return_values=self.log_return_values,
+            repeat=self.repeat,
+            post_transition_delay_us=self.post_transition_delay_us,
+        )
         new_object.traces = self.traces.copy()
         new_object.trace_id = self.trace_id
         return new_object
@@ -62,12 +78,16 @@ class TransitionHarness:
         of the current benchmark iteration. Resets `done` and `synced`,
         """
         for trace in self.traces:
-            for state_or_transition in trace['trace']:
-                if 'return_values' in state_or_transition:
-                    state_or_transition['return_values'] = state_or_transition['return_values'][:undo_from]
-                for param_name in state_or_transition['parameter'].keys():
-                    if type(state_or_transition['parameter'][param_name]) is list:
-                        state_or_transition['parameter'][param_name] = state_or_transition['parameter'][param_name][:undo_from]
+            for state_or_transition in trace["trace"]:
+                if "return_values" in state_or_transition:
+                    state_or_transition["return_values"] = state_or_transition[
+                        "return_values"
+                    ][:undo_from]
+                for param_name in state_or_transition["parameter"].keys():
+                    if type(state_or_transition["parameter"][param_name]) is list:
+                        state_or_transition["parameter"][
+                            param_name
+                        ] = state_or_transition["parameter"][param_name][:undo_from]
 
     def reset(self):
         """
@@ -95,33 +115,32 @@ class TransitionHarness:
 
     def global_code(self):
         """Return global (pre-`main()`) C++ code needed for tracing."""
-        ret = ''
+        ret = ""
         if self.gpio_pin != None:
-            ret += '#define PTALOG_GPIO {}\n'.format(self.gpio_pin)
-            if self.gpio_mode == 'before':
-                ret += '#define PTALOG_GPIO_BEFORE\n'
-            elif self.gpio_mode == 'bar':
-                ret += '#define PTALOG_GPIO_BAR\n'
+            ret += "#define PTALOG_GPIO {}\n".format(self.gpio_pin)
+            if self.gpio_mode == "before":
+                ret += "#define PTALOG_GPIO_BEFORE\n"
+            elif self.gpio_mode == "bar":
+                ret += "#define PTALOG_GPIO_BAR\n"
         if self.log_return_values:
-            ret += '#define PTALOG_WITH_RETURNVALUES\n'
-            ret += 'uint16_t transition_return_value;\n'
+            ret += "#define PTALOG_WITH_RETURNVALUES\n"
+            ret += "uint16_t transition_return_value;\n"
         ret += '#include "object/ptalog.h"\n'
         if self.gpio_pin != None:
-            ret += 'PTALog ptalog({});\n'.format(self.gpio_pin)
+            ret += "PTALog ptalog({});\n".format(self.gpio_pin)
         else:
-            ret += 'PTALog ptalog;\n'
+            ret += "PTALog ptalog;\n"
         return ret
 
-    def start_benchmark(self, benchmark_id = 0):
+    def start_benchmark(self, benchmark_id=0):
         """Return C++ code to signal benchmark start to harness."""
-        return 'ptalog.startBenchmark({:d});\n'.format(benchmark_id)
+        return "ptalog.startBenchmark({:d});\n".format(benchmark_id)
 
     def start_trace(self):
         """Prepare a new trace/run in the internal `.traces` structure."""
-        self.traces.append({
-            'id' : self.trace_id,
-            'trace' : list(),
-        })
+        self.traces.append(
+            {"id": self.trace_id, "trace": list(),}
+        )
         self.trace_id += 1
 
     def append_state(self, state_name, param):
@@ -131,13 +150,11 @@ class TransitionHarness:
         :param state_name: state name
         :param param: parameter dict
         """
-        self.traces[-1]['trace'].append({
-            'name': state_name,
-            'isa': 'state',
-            'parameter': param,
-        })
+        self.traces[-1]["trace"].append(
+            {"name": state_name, "isa": "state", "parameter": param,}
+        )
 
-    def append_transition(self, transition_name, param, args = []):
+    def append_transition(self, transition_name, param, args=[]):
         """
         Append a transition to the current run in the internal `.traces` structure.
 
@@ -145,122 +162,188 @@ class TransitionHarness:
         :param param: parameter dict
         :param args: function arguments (optional)
         """
-        self.traces[-1]['trace'].append({
-            'name': transition_name,
-            'isa': 'transition',
-            'parameter': param,
-            'args' : args,
-        })
+        self.traces[-1]["trace"].append(
+            {
+                "name": transition_name,
+                "isa": "transition",
+                "parameter": param,
+                "args": args,
+            }
+        )
 
     def start_run(self):
         """Return C++ code used to start a new run/trace."""
-        return 'ptalog.reset();\n'
+        return "ptalog.reset();\n"
 
     def _pass_transition_call(self, transition_id):
-        if self.gpio_mode == 'bar':
-            barcode_bits = Code128('T{}'.format(transition_id), charset='B').modules
+        if self.gpio_mode == "bar":
+            barcode_bits = Code128("T{}".format(transition_id), charset="B").modules
             if len(barcode_bits) % 8 != 0:
                 barcode_bits.extend([1] * (8 - (len(barcode_bits) % 8)))
-            barcode_bytes = [255 - int("".join(map(str, reversed(barcode_bits[i:i+8]))), 2) for i in range(0, len(barcode_bits), 8)]
-            inline_array = "".join(map(lambda s: '\\x{:02x}'.format(s), barcode_bytes))
-            return 'ptalog.startTransition("{}", {});\n'.format(inline_array, len(barcode_bytes))
+            barcode_bytes = [
+                255 - int("".join(map(str, reversed(barcode_bits[i : i + 8]))), 2)
+                for i in range(0, len(barcode_bits), 8)
+            ]
+            inline_array = "".join(map(lambda s: "\\x{:02x}".format(s), barcode_bytes))
+            return 'ptalog.startTransition("{}", {});\n'.format(
+                inline_array, len(barcode_bytes)
+            )
         else:
-            return 'ptalog.startTransition();\n'
+            return "ptalog.startTransition();\n"
 
-    def pass_transition(self, transition_id, transition_code, transition: object = None):
+    def pass_transition(
+        self, transition_id, transition_code, transition: object = None
+    ):
         """
         Return C++ code used to pass a transition, including the corresponding function call.
 
         Tracks which transition has been executed and optionally its return value. May also inject a delay, if
         `post_transition_delay_us` is set.
         """
-        ret = 'ptalog.passTransition({:d});\n'.format(transition_id)
+        ret = "ptalog.passTransition({:d});\n".format(transition_id)
         ret += self._pass_transition_call(transition_id)
-        if self.log_return_values and transition and len(transition.return_value_handlers):
-            ret += 'transition_return_value = {}\n'.format(transition_code)
-            ret += 'ptalog.logReturn(transition_return_value);\n'
+        if (
+            self.log_return_values
+            and transition
+            and len(transition.return_value_handlers)
+        ):
+            ret += "transition_return_value = {}\n".format(transition_code)
+            ret += "ptalog.logReturn(transition_return_value);\n"
         else:
-            ret += '{}\n'.format(transition_code)
+            ret += "{}\n".format(transition_code)
         if self.post_transition_delay_us:
-            ret += 'arch.delay_us({});\n'.format(self.post_transition_delay_us)
-        ret += 'ptalog.stopTransition();\n'
+            ret += "arch.delay_us({});\n".format(self.post_transition_delay_us)
+        ret += "ptalog.stopTransition();\n"
         return ret
 
-    def stop_run(self, num_traces = 0):
-        return 'ptalog.dump({:d});\n'.format(num_traces)
+    def stop_run(self, num_traces=0):
+        return "ptalog.dump({:d});\n".format(num_traces)
 
     def stop_benchmark(self):
-        return 'ptalog.stopBenchmark();\n'
+        return "ptalog.stopBenchmark();\n"
 
-    def _append_nondeterministic_parameter_value(self, log_data_target, parameter_name, parameter_value):
-        if log_data_target['parameter'][parameter_name] is None:
-            log_data_target['parameter'][parameter_name] = list()
-        log_data_target['parameter'][parameter_name].append(parameter_value)
+    def _append_nondeterministic_parameter_value(
+        self, log_data_target, parameter_name, parameter_value
+    ):
+        if log_data_target["parameter"][parameter_name] is None:
+            log_data_target["parameter"][parameter_name] = list()
+        log_data_target["parameter"][parameter_name].append(parameter_value)
 
     def parser_cb(self, line):
-        #print('[HARNESS] got line {}'.format(line))
-        if re.match(r'\[PTA\] benchmark stop', line):
+        # print('[HARNESS] got line {}'.format(line))
+        if re.match(r"\[PTA\] benchmark stop", line):
             self.repetitions += 1
             self.synced = False
             if self.repeat > 0 and self.repetitions == self.repeat:
                 self.done = True
-                print('[HARNESS] done')
+                print("[HARNESS] done")
                 return
-        if re.match(r'\[PTA\] benchmark start, id=(\S+)', line):
+        if re.match(r"\[PTA\] benchmark start, id=(\S+)", line):
             self.synced = True
-            print('[HARNESS] synced, {}/{}'.format(self.repetitions + 1, self.repeat))
+            print("[HARNESS] synced, {}/{}".format(self.repetitions + 1, self.repeat))
         if self.synced:
-            res = re.match(r'\[PTA\] trace=(\S+) count=(\S+)', line)
+            res = re.match(r"\[PTA\] trace=(\S+) count=(\S+)", line)
             if res:
                 self.trace_id = int(res.group(1))
                 self.trace_length = int(res.group(2))
                 self.current_transition_in_trace = 0
             if self.log_return_values:
-                res = re.match(r'\[PTA\] transition=(\S+) return=(\S+)', line)
+                res = re.match(r"\[PTA\] transition=(\S+) return=(\S+)", line)
             else:
-                res = re.match(r'\[PTA\] transition=(\S+)', line)
+                res = re.match(r"\[PTA\] transition=(\S+)", line)
             if res:
                 transition_id = int(res.group(1))
                 # self.traces contains transitions and states, UART output only contains transitions -> use index * 2
                 try:
-                    log_data_target = self.traces[self.trace_id]['trace'][self.current_transition_in_trace * 2]
+                    log_data_target = self.traces[self.trace_id]["trace"][
+                        self.current_transition_in_trace * 2
+                    ]
                 except IndexError:
                     transition_name = None
                     if self.pta:
                         transition_name = self.pta.transitions[transition_id].name
-                    print('[HARNESS] benchmark id={:d} trace={:d}: transition #{:d} (ID {:d}, name {}) is out of bounds'.format(0, self.trace_id, self.current_transition_in_trace, transition_id, transition_name))
-                    print('          Offending line: {}'.format(line))
+                    print(
+                        "[HARNESS] benchmark id={:d} trace={:d}: transition #{:d} (ID {:d}, name {}) is out of bounds".format(
+                            0,
+                            self.trace_id,
+                            self.current_transition_in_trace,
+                            transition_id,
+                            transition_name,
+                        )
+                    )
+                    print("          Offending line: {}".format(line))
                     return
-                if log_data_target['isa'] != 'transition':
+                if log_data_target["isa"] != "transition":
                     self.abort = True
-                    raise RuntimeError('Log mismatch: Expected transition, got {:s}'.format(log_data_target['isa']))
+                    raise RuntimeError(
+                        "Log mismatch: Expected transition, got {:s}".format(
+                            log_data_target["isa"]
+                        )
+                    )
                 if self.pta:
                     transition = self.pta.transitions[transition_id]
-                    if transition.name != log_data_target['name']:
+                    if transition.name != log_data_target["name"]:
                         self.abort = True
-                        raise RuntimeError('Log mismatch: Expected transition {:s}, got transition {:s} -- may have been caused by preceding malformed UART output'.format(log_data_target['name'], transition.name))
+                        raise RuntimeError(
+                            "Log mismatch: Expected transition {:s}, got transition {:s} -- may have been caused by preceding malformed UART output".format(
+                                log_data_target["name"], transition.name
+                            )
+                        )
                     if self.log_return_values and len(transition.return_value_handlers):
                         for handler in transition.return_value_handlers:
-                            if 'parameter' in handler:
+                            if "parameter" in handler:
                                 parameter_value = return_value = int(res.group(2))
 
-                                if 'return_values' not in log_data_target:
-                                    log_data_target['return_values'] = list()
-                                log_data_target['return_values'].append(return_value)
-
-                                if 'formula' in handler:
-                                    parameter_value = handler['formula'].eval(return_value)
-
-                                self._append_nondeterministic_parameter_value(log_data_target, handler['parameter'], parameter_value)
-                                for following_log_data_target in self.traces[self.trace_id]['trace'][(self.current_transition_in_trace * 2 + 1) :]:
-                                    self._append_nondeterministic_parameter_value(following_log_data_target, handler['parameter'], parameter_value)
-                                if 'apply_from' in handler and any(map(lambda x: x['name'] == handler['apply_from'], self.traces[self.trace_id]['trace'][: (self.current_transition_in_trace * 2 + 1)])):
-                                    for preceding_log_data_target in reversed(self.traces[self.trace_id]['trace'][: (self.current_transition_in_trace * 2)]):
-                                        self._append_nondeterministic_parameter_value(preceding_log_data_target, handler['parameter'], parameter_value)
-                                        if preceding_log_data_target['name'] == handler['apply_from']:
+                                if "return_values" not in log_data_target:
+                                    log_data_target["return_values"] = list()
+                                log_data_target["return_values"].append(return_value)
+
+                                if "formula" in handler:
+                                    parameter_value = handler["formula"].eval(
+                                        return_value
+                                    )
+
+                                self._append_nondeterministic_parameter_value(
+                                    log_data_target,
+                                    handler["parameter"],
+                                    parameter_value,
+                                )
+                                for following_log_data_target in self.traces[
+                                    self.trace_id
+                                ]["trace"][
+                                    (self.current_transition_in_trace * 2 + 1) :
+                                ]:
+                                    self._append_nondeterministic_parameter_value(
+                                        following_log_data_target,
+                                        handler["parameter"],
+                                        parameter_value,
+                                    )
+                                if "apply_from" in handler and any(
+                                    map(
+                                        lambda x: x["name"] == handler["apply_from"],
+                                        self.traces[self.trace_id]["trace"][
+                                            : (self.current_transition_in_trace * 2 + 1)
+                                        ],
+                                    )
+                                ):
+                                    for preceding_log_data_target in reversed(
+                                        self.traces[self.trace_id]["trace"][
+                                            : (self.current_transition_in_trace * 2)
+                                        ]
+                                    ):
+                                        self._append_nondeterministic_parameter_value(
+                                            preceding_log_data_target,
+                                            handler["parameter"],
+                                            parameter_value,
+                                        )
+                                        if (
+                                            preceding_log_data_target["name"]
+                                            == handler["apply_from"]
+                                        ):
                                             break
                 self.current_transition_in_trace += 1
 
+
 class OnboardTimerHarness(TransitionHarness):
     """TODO
 
@@ -271,13 +354,25 @@ class OnboardTimerHarness(TransitionHarness):
         benchmark iteration.
         I.e. `.traces[*]['trace'][*]['offline_aggregates']['duration'] = [..., ...]`
     """
+
     def __init__(self, counter_limits, **kwargs):
         super().__init__(**kwargs)
         self.trace_length = 0
-        self.one_cycle_in_us, self.one_overflow_in_us, self.counter_max_overflow = counter_limits
+        (
+            self.one_cycle_in_us,
+            self.one_overflow_in_us,
+            self.counter_max_overflow,
+        ) = counter_limits
 
     def copy(self):
-        new_harness = __class__((self.one_cycle_in_us, self.one_overflow_in_us, self.counter_max_overflow), gpio_pin = self.gpio_pin, gpio_mode = self.gpio_mode, pta = self.pta, log_return_values = self.log_return_values, repeat = self.repeat)
+        new_harness = __class__(
+            (self.one_cycle_in_us, self.one_overflow_in_us, self.counter_max_overflow),
+            gpio_pin=self.gpio_pin,
+            gpio_mode=self.gpio_mode,
+            pta=self.pta,
+            log_return_values=self.log_return_values,
+            repeat=self.repeat,
+        )
         new_harness.traces = self.traces.copy()
         new_harness.trace_id = self.trace_id
         return new_harness
@@ -293,123 +388,215 @@ class OnboardTimerHarness(TransitionHarness):
         """
         super().undo(undo_from)
         for trace in self.traces:
-            for state_or_transition in trace['trace']:
-                if 'offline_aggregates' in state_or_transition:
-                    state_or_transition['offline_aggregates']['duration'] = state_or_transition['offline_aggregates']['duration'][:undo_from]
+            for state_or_transition in trace["trace"]:
+                if "offline_aggregates" in state_or_transition:
+                    state_or_transition["offline_aggregates"][
+                        "duration"
+                    ] = state_or_transition["offline_aggregates"]["duration"][
+                        :undo_from
+                    ]
 
     def global_code(self):
         ret = '#include "driver/counter.h"\n'
-        ret += '#define PTALOG_TIMING\n'
+        ret += "#define PTALOG_TIMING\n"
         ret += super().global_code()
         return ret
 
-    def start_benchmark(self, benchmark_id = 0):
-        ret = 'counter.start();\n'
-        ret += 'counter.stop();\n'
-        ret += 'ptalog.passNop(counter);\n'
+    def start_benchmark(self, benchmark_id=0):
+        ret = "counter.start();\n"
+        ret += "counter.stop();\n"
+        ret += "ptalog.passNop(counter);\n"
         ret += super().start_benchmark(benchmark_id)
         return ret
 
-    def pass_transition(self, transition_id, transition_code, transition: object = None):
-        ret = 'ptalog.passTransition({:d});\n'.format(transition_id)
+    def pass_transition(
+        self, transition_id, transition_code, transition: object = None
+    ):
+        ret = "ptalog.passTransition({:d});\n".format(transition_id)
         ret += self._pass_transition_call(transition_id)
-        ret += 'counter.start();\n'
-        if self.log_return_values and transition and len(transition.return_value_handlers):
-            ret += 'transition_return_value = {}\n'.format(transition_code)
+        ret += "counter.start();\n"
+        if (
+            self.log_return_values
+            and transition
+            and len(transition.return_value_handlers)
+        ):
+            ret += "transition_return_value = {}\n".format(transition_code)
         else:
-            ret += '{}\n'.format(transition_code)
-        ret += 'counter.stop();\n'
-        if self.log_return_values and transition and len(transition.return_value_handlers):
-            ret += 'ptalog.logReturn(transition_return_value);\n'
-        ret += 'ptalog.stopTransition(counter);\n'
+            ret += "{}\n".format(transition_code)
+        ret += "counter.stop();\n"
+        if (
+            self.log_return_values
+            and transition
+            and len(transition.return_value_handlers)
+        ):
+            ret += "ptalog.logReturn(transition_return_value);\n"
+        ret += "ptalog.stopTransition(counter);\n"
         return ret
 
-    def _append_nondeterministic_parameter_value(self, log_data_target, parameter_name, parameter_value):
-        if log_data_target['parameter'][parameter_name] is None:
-            log_data_target['parameter'][parameter_name] = list()
-        log_data_target['parameter'][parameter_name].append(parameter_value)
+    def _append_nondeterministic_parameter_value(
+        self, log_data_target, parameter_name, parameter_value
+    ):
+        if log_data_target["parameter"][parameter_name] is None:
+            log_data_target["parameter"][parameter_name] = list()
+        log_data_target["parameter"][parameter_name].append(parameter_value)
 
     def parser_cb(self, line):
         # print('[HARNESS] got line {}'.format(line))
-        res = re.match(r'\[PTA\] nop=(\S+)/(\S+)', line)
+        res = re.match(r"\[PTA\] nop=(\S+)/(\S+)", line)
         if res:
             self.nop_cycles = int(res.group(1))
             if int(res.group(2)):
-                raise RuntimeError('Counter overflow ({:d}/{:d}) during NOP test, wtf?!'.format(res.group(1), res.group(2)))
-        if re.match(r'\[PTA\] benchmark stop', line):
+                raise RuntimeError(
+                    "Counter overflow ({:d}/{:d}) during NOP test, wtf?!".format(
+                        res.group(1), res.group(2)
+                    )
+                )
+        if re.match(r"\[PTA\] benchmark stop", line):
             self.repetitions += 1
             self.synced = False
             if self.repeat > 0 and self.repetitions == self.repeat:
                 self.done = True
-                print('[HARNESS] done')
+                print("[HARNESS] done")
                 return
         # May be repeated, e.g. if the device is reset shortly after start by
         # EnergyTrace.
-        if re.match(r'\[PTA\] benchmark start, id=(\S+)', line):
+        if re.match(r"\[PTA\] benchmark start, id=(\S+)", line):
             self.synced = True
-            print('[HARNESS] synced, {}/{}'.format(self.repetitions + 1, self.repeat))
+            print("[HARNESS] synced, {}/{}".format(self.repetitions + 1, self.repeat))
         if self.synced:
-            res = re.match(r'\[PTA\] trace=(\S+) count=(\S+)', line)
+            res = re.match(r"\[PTA\] trace=(\S+) count=(\S+)", line)
             if res:
                 self.trace_id = int(res.group(1))
                 self.trace_length = int(res.group(2))
                 self.current_transition_in_trace = 0
             if self.log_return_values:
-                res = re.match(r'\[PTA\] transition=(\S+) cycles=(\S+)/(\S+) return=(\S+)', line)
+                res = re.match(
+                    r"\[PTA\] transition=(\S+) cycles=(\S+)/(\S+) return=(\S+)", line
+                )
             else:
-                res = re.match(r'\[PTA\] transition=(\S+) cycles=(\S+)/(\S+)', line)
+                res = re.match(r"\[PTA\] transition=(\S+) cycles=(\S+)/(\S+)", line)
             if res:
                 transition_id = int(res.group(1))
                 cycles = int(res.group(2))
                 overflow = int(res.group(3))
                 if overflow >= self.counter_max_overflow:
                     self.abort = True
-                    raise RuntimeError('Counter overflow ({:d}/{:d}) in benchmark id={:d} trace={:d}: transition #{:d} (ID {:d})'.format(cycles, overflow, 0, self.trace_id, self.current_transition_in_trace, transition_id))
-                duration_us = cycles * self.one_cycle_in_us + overflow * self.one_overflow_in_us - self.nop_cycles * self.one_cycle_in_us
+                    raise RuntimeError(
+                        "Counter overflow ({:d}/{:d}) in benchmark id={:d} trace={:d}: transition #{:d} (ID {:d})".format(
+                            cycles,
+                            overflow,
+                            0,
+                            self.trace_id,
+                            self.current_transition_in_trace,
+                            transition_id,
+                        )
+                    )
+                duration_us = (
+                    cycles * self.one_cycle_in_us
+                    + overflow * self.one_overflow_in_us
+                    - self.nop_cycles * self.one_cycle_in_us
+                )
                 if duration_us < 0:
                     duration_us = 0
                 # self.traces contains transitions and states, UART output only contains transitions -> use index * 2
                 try:
-                    log_data_target = self.traces[self.trace_id]['trace'][self.current_transition_in_trace * 2]
+                    log_data_target = self.traces[self.trace_id]["trace"][
+                        self.current_transition_in_trace * 2
+                    ]
                 except IndexError:
                     transition_name = None
                     if self.pta:
                         transition_name = self.pta.transitions[transition_id].name
-                    print('[HARNESS] benchmark id={:d} trace={:d}: transition #{:d} (ID {:d}, name {}) is out of bounds'.format(0, self.trace_id, self.current_transition_in_trace, transition_id, transition_name))
-                    print('          Offending line: {}'.format(line))
+                    print(
+                        "[HARNESS] benchmark id={:d} trace={:d}: transition #{:d} (ID {:d}, name {}) is out of bounds".format(
+                            0,
+                            self.trace_id,
+                            self.current_transition_in_trace,
+                            transition_id,
+                            transition_name,
+                        )
+                    )
+                    print("          Offending line: {}".format(line))
                     return
-                if log_data_target['isa'] != 'transition':
+                if log_data_target["isa"] != "transition":
                     self.abort = True
-                    raise RuntimeError('Log mismatch in benchmark id={:d} trace={:d}: transition #{:d} (ID {:d}): Expected transition, got {:s}'.format(0,
-                        self.trace_id, self.current_transition_in_trace, transition_id, log_data_target['isa']))
+                    raise RuntimeError(
+                        "Log mismatch in benchmark id={:d} trace={:d}: transition #{:d} (ID {:d}): Expected transition, got {:s}".format(
+                            0,
+                            self.trace_id,
+                            self.current_transition_in_trace,
+                            transition_id,
+                            log_data_target["isa"],
+                        )
+                    )
                 if self.pta:
                     transition = self.pta.transitions[transition_id]
-                    if transition.name != log_data_target['name']:
+                    if transition.name != log_data_target["name"]:
                         self.abort = True
-                        raise RuntimeError('Log mismatch in benchmark id={:d} trace={:d}: transition #{:d} (ID {:d}): Expected transition {:s}, got transition {:s} -- may have been caused by preceding maformed UART output'.format(0, self.trace_id, self.current_transition_in_trace, transition_id, log_data_target['name'], transition.name, line))
+                        raise RuntimeError(
+                            "Log mismatch in benchmark id={:d} trace={:d}: transition #{:d} (ID {:d}): Expected transition {:s}, got transition {:s} -- may have been caused by preceding maformed UART output".format(
+                                0,
+                                self.trace_id,
+                                self.current_transition_in_trace,
+                                transition_id,
+                                log_data_target["name"],
+                                transition.name,
+                                line,
+                            )
+                        )
                     if self.log_return_values and len(transition.return_value_handlers):
                         for handler in transition.return_value_handlers:
-                            if 'parameter' in handler:
+                            if "parameter" in handler:
                                 parameter_value = return_value = int(res.group(4))
 
-                                if 'return_values' not in log_data_target:
-                                    log_data_target['return_values'] = list()
-                                log_data_target['return_values'].append(return_value)
-
-                                if 'formula' in handler:
-                                    parameter_value = handler['formula'].eval(return_value)
-
-                                self._append_nondeterministic_parameter_value(log_data_target, handler['parameter'], parameter_value)
-                                for following_log_data_target in self.traces[self.trace_id]['trace'][(self.current_transition_in_trace * 2 + 1) :]:
-                                    self._append_nondeterministic_parameter_value(following_log_data_target, handler['parameter'], parameter_value)
-                                if 'apply_from' in handler and any(map(lambda x: x['name'] == handler['apply_from'], self.traces[self.trace_id]['trace'][: (self.current_transition_in_trace * 2 + 1)])):
-                                    for preceding_log_data_target in reversed(self.traces[self.trace_id]['trace'][: (self.current_transition_in_trace * 2)]):
-                                        self._append_nondeterministic_parameter_value(preceding_log_data_target, handler['parameter'], parameter_value)
-                                        if preceding_log_data_target['name'] == handler['apply_from']:
+                                if "return_values" not in log_data_target:
+                                    log_data_target["return_values"] = list()
+                                log_data_target["return_values"].append(return_value)
+
+                                if "formula" in handler:
+                                    parameter_value = handler["formula"].eval(
+                                        return_value
+                                    )
+
+                                self._append_nondeterministic_parameter_value(
+                                    log_data_target,
+                                    handler["parameter"],
+                                    parameter_value,
+                                )
+                                for following_log_data_target in self.traces[
+                                    self.trace_id
+                                ]["trace"][
+                                    (self.current_transition_in_trace * 2 + 1) :
+                                ]:
+                                    self._append_nondeterministic_parameter_value(
+                                        following_log_data_target,
+                                        handler["parameter"],
+                                        parameter_value,
+                                    )
+                                if "apply_from" in handler and any(
+                                    map(
+                                        lambda x: x["name"] == handler["apply_from"],
+                                        self.traces[self.trace_id]["trace"][
+                                            : (self.current_transition_in_trace * 2 + 1)
+                                        ],
+                                    )
+                                ):
+                                    for preceding_log_data_target in reversed(
+                                        self.traces[self.trace_id]["trace"][
+                                            : (self.current_transition_in_trace * 2)
+                                        ]
+                                    ):
+                                        self._append_nondeterministic_parameter_value(
+                                            preceding_log_data_target,
+                                            handler["parameter"],
+                                            parameter_value,
+                                        )
+                                        if (
+                                            preceding_log_data_target["name"]
+                                            == handler["apply_from"]
+                                        ):
                                             break
-                if 'offline_aggregates' not in log_data_target:
-                    log_data_target['offline_aggregates'] = {
-                        'duration' : list()
-                    }
-                log_data_target['offline_aggregates']['duration'].append(duration_us)
+                if "offline_aggregates" not in log_data_target:
+                    log_data_target["offline_aggregates"] = {"duration": list()}
+                log_data_target["offline_aggregates"]["duration"].append(duration_us)
                 self.current_transition_in_trace += 1