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-rw-r--r--bin/Proof_Of_Concept_PELT.py69
1 files changed, 58 insertions, 11 deletions
diff --git a/bin/Proof_Of_Concept_PELT.py b/bin/Proof_Of_Concept_PELT.py
index 40c405d..4819f64 100644
--- a/bin/Proof_Of_Concept_PELT.py
+++ b/bin/Proof_Of_Concept_PELT.py
@@ -221,7 +221,7 @@ def calculate_penalty_value(signal, model="l1", jump=5, min_dist=2, range_min=0,
else:
# range_min == range_max. has the same effect as pen_override
knee = (range_min, None)
- print_info(str(knee[0]) + " has been selected as kneepoint.")
+ print_info(str(knee[0]) + " has been selected as penalty.")
if knee[0] is not None:
return knee
@@ -375,11 +375,15 @@ def print_error(str_to_prt):
print("[ERROR]" + str_prt, file=sys.stderr)
-def norm_signal(signal):
+def norm_signal(signal, scaler=50):
# TODO: maybe refine normalisation of signal
+ max_val = max(signal)
normed_signal = np.zeros(shape=len(signal))
for i, signal_i in enumerate(signal):
- normed_signal[i] = signal_i / 1000
+ normed_signal[i] = signal_i / max_val
+ normed_signal[i] = normed_signal[i] * scaler
+ # plt.plot(normed_signal)
+ # plt.show()
return normed_signal
@@ -559,6 +563,7 @@ if __name__ == '__main__':
by_name_file = None
param_names_file = None
from_cache = False
+ not_accurate = False
if opt_cache_loc is not None:
flag = False
by_name_loc = os.path.join(opt_cache_loc, "by_name.txt")
@@ -701,6 +706,10 @@ if __name__ == '__main__':
print_info("Discarding measurement No. " + str(num_measurement)
+ " because it did not recognize the number of "
"raw_states correctly.")
+ # l_signal = measurements_by_config['offline'][num_measurement]['uW']
+ # l_bkpts = [s[1] for s in raw_states]
+ # fig, ax = rpt.display(np.array(l_signal), l_bkpts)
+ # plt.show()
# for i, x in enumerate(states_duration_list):
# states_duration_list[i] = x / num_used_measurements
# for i, x in enumerate(states_consumption_list):
@@ -718,7 +727,7 @@ if __name__ == '__main__':
+ " Others did not recognize number of states correctly.")
num_used_measurements = i
# TODO: DEBUG Kram
- sys.exit(0)
+ #sys.exit(0)
else:
print_info("Used all available measurements.")
@@ -730,7 +739,25 @@ if __name__ == '__main__':
# break
# combine all state durations and consumptions to parametrized model
-
+ if len(state_durations_by_config) == 0:
+ print("No refinement necessary for this state. The macromodel is usable.")
+ sys.exit()
+ if len(state_durations_by_config) / len(configurations) > 1 / 2 \
+ and len(state_durations_by_config) != len(configurations):
+ print_warning(
+ "Some measurements(>50%) need to be refined, however that is not true for"
+ " all measurements. This hints a correlation between the structure of"
+ " the underlying automaton and parameters. Only the ones which need to"
+ " be refined will be refined. THE RESULT WILL NOT ACCURATELY DEPICT "
+ " THE REAL WORLD.")
+ not_accurate = True
+ if len(state_durations_by_config) / len(configurations) < 1 / 2:
+ print_warning(
+ "Some measurements(<50%) need to be refined, however that is not true for"
+ " all measurements. This hints a correlation between the structure of"
+ " the underlying automaton and parameters. Or a poor quality of measurements."
+ " No Refinement will be done.")
+ sys.exit(-1)
# this is only necessary because at this state only linear automatons can be modeled.
num_states_array = [int()] * len(state_consumptions_by_config)
for i, (_, states_consumption_list) in enumerate(state_consumptions_by_config):
@@ -748,7 +775,9 @@ if __name__ == '__main__':
"Config No." + str(num_config) + " not usable yet due to different "
+ "number of states. This hints a correlation between parameters and "
+ "the structure of the resulting automaton. This will be possibly"
- + " supported in a future version of this tool.")
+ + " supported in a future version of this tool. HOWEVER AT THE MOMENT"
+ " THIS WILL LEAD TO INACCURATE RESULTS!")
+ not_accurate = True
usable_configs = usable_configs - 1
else:
param_list.extend(configurations[num_config]['offline_aggregates']['param'])
@@ -759,18 +788,28 @@ if __name__ == '__main__':
else:
print_info("Using only " + str(usable_configs) + " Configs.")
by_name = {}
+ usable_configs_2 = len(state_consumptions_by_config)
for i in range(num_raw_states):
consumptions_for_state = []
durations_for_state = []
for j, (_, states_consumption_list) in enumerate(state_consumptions_by_config):
- consumptions_for_state.extend(states_consumption_list[i])
- durations_for_state.extend(state_durations_by_config[j][1][i])
+ if len(states_consumption_list) == num_raw_states:
+ consumptions_for_state.extend(states_consumption_list[i])
+ durations_for_state.extend(state_durations_by_config[j][1][i])
+ else:
+ not_accurate = True
+ usable_configs_2 = usable_configs_2 - 1
+ if usable_configs_2 != usable_configs:
+ print_error("an zwei unterschiedlichen Stellen wurden unterschiedlich viele "
+ "Messungen rausgeworfen. Bei Janis beschweren.")
state_name = "state_" + str(i)
state_dict = {
"param": param_list,
"power": consumptions_for_state,
"duration": durations_for_state,
- "attributes": ["power", "duration"]
+ "attributes": ["power", "duration"],
+ # Da kein richtiger Automat generiert wird, gibt es auch keine Transitionen
+ "isa": "state"
}
by_name[state_name] = state_dict
by_param = by_name_to_by_param(by_name)
@@ -943,7 +982,9 @@ if __name__ == '__main__':
"param": param_list,
"power": consumptions_for_state,
"duration": durations_for_state,
- "attributes": ["power", "duration"]
+ "attributes": ["power", "duration"],
+ # Da kein richtiger Automat generiert wird, gibt es auch keine Transitionen
+ "isa": "state"
}
new_by_name[state_name] = new_state_dict
new_by_param = by_name_to_by_param(new_by_name)
@@ -993,7 +1034,13 @@ if __name__ == '__main__':
model_function = model_function.replace(replace_string, str(arg))
print("Duration-Function for state " + state_name + ": "
+ model_function)
- model = PTAModel(by_name, param_names, dict())
+ model = PTAModel(new_by_name, param_names, dict())
+ model_json = model.to_json()
+ print(model_json)
+ if not_accurate:
+ print_warning(
+ "THIS RESULT IS NOT ACCURATE. SEE WARNINGLOG TO GET A BETTER UNDERSTANDING"
+ " WHY.")
# TODO: removed clustering (temporarily), since it provided too much dificultys