Fix generate-dfa-benchmark leaving out benchmark parts when splitting runs

6 files changed, 39 insertions, 15 deletions

diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 6299918..35a4a99 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -17,7 +17,7 @@ run_tests:
   - wget -qO test-data/20170116_145420_sharpLS013B4DN.tar https://lib.finalrewind.org/energy-models/20170116_145420_sharpLS013B4DN.tar
   - wget -qO test-data/20170116_151348_sharpLS013B4DN.tar https://lib.finalrewind.org/energy-models/20170116_151348_sharpLS013B4DN.tar
   - wget -qO test-data/20170220_164723_RF24_int_A.tar https://lib.finalrewind.org/energy-models/20170220_164723_RF24_int_A.tar
-  - wget -qO test-data/20190726_150423_nRF24_no-rx.json https://lib.finalrewind.org/energy-models/20190726_150423_nRF24_no-rx.json
+  - wget -qO test-data/test-data/20190815_111745_nRF24_no-rx.json https://lib.finalrewind.org/energy-models/test-data/20190815_111745_nRF24_no-rx.json
   - PYTHONPATH=lib pytest-3 --cov=lib
   - python3-coverage html
   artifacts:
diff --git a/bin/analyze-timing.py b/bin/analyze-timing.py
index 7e8174d..465932b 100755
--- a/bin/analyze-timing.py
+++ b/bin/analyze-timing.py
@@ -63,7 +63,7 @@ Options:
 --export-energymodel=<model.json>
     Export energy model. Requires --hwmodel.
 
---filter-param=<parameter name>=<parameter value>
+--filter-param=<parameter name>=<parameter value>[,<parameter name>=<parameter value>...]
     Only consider measurements where <parameter name> is <parameter value>
     All other measurements (including those where it is None, that is, has
     not been set yet) are discarded. Note that this may remove entire
@@ -192,7 +192,9 @@ if __name__ == '__main__':
             opts['corrcoef'] = False
 
         if 'filter-param' in opts:
-            opts['filter-param'] = opts['filter-param'].split('=')
+            opts['filter-param'] = list(map(lambda x: x.split('='), opts['filter-param'].split(',')))
+        else:
+            opts['filter-param'] = list()
 
     except getopt.GetoptError as err:
         print(err)
@@ -203,9 +205,9 @@ if __name__ == '__main__':
     preprocessed_data = raw_data.get_preprocessed_data()
     by_name, parameters, arg_count = pta_trace_to_aggregate(preprocessed_data, ignored_trace_indexes)
 
-    if 'filter-param' in opts:
-        param_index = parameters.index(opts['filter-param'][0])
-        param_value = soft_cast_int(opts['filter-param'][1])
+    for param_name_and_value in opts['filter-param']:
+        param_index = parameters.index(param_name_and_value[0])
+        param_value = soft_cast_int(param_name_and_value[1])
         names_to_remove = set()
         for name in by_name.keys():
             indices_to_keep = list(map(lambda x: x[param_index] == param_value, by_name[name]['param']))
diff --git a/bin/generate-dfa-benchmark.py b/bin/generate-dfa-benchmark.py
index 4fb8df4..9919d68 100755
--- a/bin/generate-dfa-benchmark.py
+++ b/bin/generate-dfa-benchmark.py
@@ -136,9 +136,10 @@ def run_benchmark(application_file: str, pta: PTA, runs: list, arch: str, app: s
     if needs_split:
         print('[MAKE] benchmark code is too large, splitting up')
         mid = len(runs) // 2
-        results = run_benchmark(application_file, pta, runs[:mid], arch, app, run_args, harness, sleep, repeat, run_offset = run_offset, runs_total = runs_total)
+        # Previously prepared trace data is useless
         harness.reset()
-        results.extend(run_benchmark(application_file, pta, runs[mid:], arch, app, run_args, harness, sleep, repeat, run_offset = run_offset + mid, runs_total = runs_total))
+        results = run_benchmark(application_file, pta, runs[:mid], arch, app, run_args, harness.copy(), sleep, repeat, run_offset = run_offset, runs_total = runs_total)
+        results.extend(run_benchmark(application_file, pta, runs[mid:], arch, app, run_args, harness.copy(), sleep, repeat, run_offset = run_offset + mid, runs_total = runs_total))
         return results
 
     runner.flash(arch, app, run_args)
@@ -242,7 +243,7 @@ if __name__ == '__main__':
         json_out = {
             'opt' : opt,
             'pta' : pta.to_json(),
-            'traces' : harness.traces,
+            'traces' : list(map(lambda x: x[1].traces, results)),
             'raw_output' : list(map(lambda x: x[2], results)),
         }
         with open(time.strftime('ptalog-%Y%m%d-%H%M%S.json'), 'w') as f:
diff --git a/lib/dfatool.py b/lib/dfatool.py
index e318e81..528eabc 100755
--- a/lib/dfatool.py
+++ b/lib/dfatool.py
@@ -537,7 +537,7 @@ class TimingData:
         for filename in self.filenames:
             with open(filename, 'r') as f:
                 log_data = json.load(f)
-                self.traces_by_fileno.append(log_data['traces'])
+                self.traces_by_fileno.extend(log_data['traces'])
         self._concatenate_analyzed_traces()
 
     def get_preprocessed_data(self, verbose = True):
diff --git a/lib/harness.py b/lib/harness.py
index 020bc72..af74977 100644
--- a/lib/harness.py
+++ b/lib/harness.py
@@ -11,15 +11,30 @@ import re
 # generated otherwise and it should also work with AnalyticModel (which does
 # not have states)
 class TransitionHarness:
+    """Foo."""
     def __init__(self, gpio_pin = None, pta = None, log_return_values = False):
+        """
+        Create a new TransitionHarness
+
+        :param gpio_pin: multipass GPIO Pin used for transition synchronization, e.g. `GPIO::p1_0`. Optional.
+            The GPIO output is high iff a transition is executing
+        :param pta: PTA object
+        :param log_return_values: Log return values of transition function calls?
+        """
         self.gpio_pin = gpio_pin
         self.pta = pta
         self.log_return_values = log_return_values
         self.reset()
 
+    def copy(self):
+        new_object = __class__(gpio_pin = self.gpio_pin, pta = self.pta, log_return_values = self.log_return_values)
+        new_object.traces = self.traces.copy()
+        new_object.trace_id = self.trace_id
+        return new_object
+
     def reset(self):
         self.traces = []
-        self.trace_id = 1
+        self.trace_id = 0
         self.synced = False
 
     def global_code(self):
@@ -102,12 +117,18 @@ class TransitionHarness:
                 pass
 
 class OnboardTimerHarness(TransitionHarness):
+    """Bar."""
     def __init__(self, counter_limits, **kwargs):
         super().__init__(**kwargs)
-        self.trace_id = 0
         self.trace_length = 0
         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, pta = self.pta, log_return_values = self.log_return_values)
+        new_harness.traces = self.traces.copy()
+        new_harness.trace_id = self.trace_id
+        return new_harness
+
     def global_code(self):
         ret = '#include "driver/counter.h"\n'
         ret += '#define PTALOG_TIMING\n'
diff --git a/test/test_timingharness.py b/test/test_timingharness.py
index ac19a29..6479f0a 100755
--- a/test/test_timingharness.py
+++ b/test/test_timingharness.py
@@ -5,7 +5,7 @@ import unittest
 
 class TestModels(unittest.TestCase):
     def test_model_singlefile_rf24(self):
-        raw_data = TimingData(['test-data/20190726_150423_nRF24_no-rx.json'])
+        raw_data = TimingData(['test-data/20190815_111745_nRF24_no-rx.json'])
         preprocessed_data = raw_data.get_preprocessed_data(verbose = False)
         by_name, parameters, arg_count = pta_trace_to_aggregate(preprocessed_data)
         model = AnalyticModel(by_name, parameters, arg_count, verbose = False)
@@ -14,7 +14,7 @@ class TestModels(unittest.TestCase):
         self.assertAlmostEqual(static_model('setPALevel', 'duration'), 146, places=0)
         self.assertAlmostEqual(static_model('setRetries', 'duration'), 73, places=0)
         self.assertAlmostEqual(static_model('setup', 'duration'), 6533, places=0)
-        self.assertAlmostEqual(static_model('write', 'duration'), 12400, places=0)
+        self.assertAlmostEqual(static_model('write', 'duration'), 12634, places=0)
 
         for transition in 'setPALevel setRetries setup write'.split(' '):
             self.assertAlmostEqual(model.stats.param_dependence_ratio(transition, 'duration', 'channel'), 0, places=2)
@@ -25,7 +25,7 @@ class TestModels(unittest.TestCase):
         self.assertEqual(param_info('setup', 'duration'), None)
         self.assertEqual(param_info('write', 'duration')['function']._model_str, '0 + regression_arg(0) + regression_arg(1) * parameter(max_retry_count) + regression_arg(2) * parameter(retry_delay) + regression_arg(3) * parameter(max_retry_count) * parameter(retry_delay)')
 
-        self.assertAlmostEqual(param_info('write', 'duration')['function']._regression_args[0], 1016, places=0)
+        self.assertAlmostEqual(param_info('write', 'duration')['function']._regression_args[0], 1163, places=0)
         self.assertAlmostEqual(param_info('write', 'duration')['function']._regression_args[1], 464, places=0)
         self.assertAlmostEqual(param_info('write', 'duration')['function']._regression_args[2], 1, places=0)
         self.assertAlmostEqual(param_info('write', 'duration')['function']._regression_args[3], 1, places=0)