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-rwxr-xr-xbin/analyze-archive.py60
1 files changed, 47 insertions, 13 deletions
diff --git a/bin/analyze-archive.py b/bin/analyze-archive.py
index 4c442af..5a6b8f0 100755
--- a/bin/analyze-archive.py
+++ b/bin/analyze-archive.py
@@ -101,6 +101,9 @@ Options:
--export-energymodel=<model.json>
Export energy model. Works out of the box for v1 and v2 logfiles. Requires --hwmodel for v0 logfiles.
+
+--no-cache
+ Do not load cached measurement results
"""
import getopt
@@ -142,6 +145,15 @@ def format_quality_measures(result):
def model_quality_table(result_lists, info_list):
+ print(
+ "{:20s} {:15s} {:19s} {:19s} {:19s}".format(
+ "key",
+ "attribute",
+ "static".center(19),
+ "parameterized".center(19),
+ "LUT".center(19),
+ )
+ )
for state_or_tran in result_lists[0]["by_name"].keys():
for key in result_lists[0]["by_name"][state_or_tran].keys():
buf = "{:20s} {:15s}".format(state_or_tran, key)
@@ -152,7 +164,7 @@ def model_quality_table(result_lists, info_list):
result = results["by_name"][state_or_tran][key]
buf += format_quality_measures(result)
else:
- buf += "{:6}----{:9}".format("", "")
+ buf += "{:7}----{:8}".format("", "")
print(buf)
@@ -300,7 +312,7 @@ if __name__ == "__main__":
try:
optspec = (
- "info "
+ "info no-cache "
"plot-unparam= plot-param= plot-traces= show-models= show-quality= "
"ignored-trace-indexes= function-override= "
"export-traces= "
@@ -362,11 +374,18 @@ if __name__ == "__main__":
sys.exit(2)
raw_data = RawData(
- args, with_traces=("export-traces" in opt or "plot-traces" in opt)
+ args,
+ with_traces=("export-traces" in opt or "plot-traces" in opt),
+ skip_cache=("no-cache" in opt),
)
if "info" in opt:
print(" ".join(raw_data.filenames) + ":")
+ if raw_data.ptalog:
+ options = " --".join(
+ map(lambda kv: f"{kv[0]}={str(kv[1])}", raw_data.ptalog["opt"].items())
+ )
+ print(f" Options: --{options}")
if raw_data.version <= 1:
data_source = "MIMOSA"
elif raw_data.version == 2:
@@ -420,7 +439,7 @@ if __name__ == "__main__":
)
sys.exit(2)
- if len(traces) > 20:
+ if len(traces) > 40:
print(f"""Truncating plot to 40 of {len(traces)} traces (random sample)""")
traces = random.sample(traces, 40)
@@ -693,7 +712,7 @@ if __name__ == "__main__":
)
if "overall" in show_quality or "all" in show_quality:
- print("overall static/param/lut MAE assuming equal state distribution:")
+ print("overall state static/param/lut MAE assuming equal state distribution:")
print(
" {:6.1f} / {:6.1f} / {:6.1f} µW".format(
model.assess_states(static_model),
@@ -701,15 +720,30 @@ if __name__ == "__main__":
model.assess_states(lut_model),
)
)
- print("overall static/param/lut MAE assuming 95% STANDBY1:")
- distrib = {"STANDBY1": 0.95, "POWERDOWN": 0.03, "TX": 0.01, "RX": 0.01}
- print(
- " {:6.1f} / {:6.1f} / {:6.1f} µW".format(
- model.assess_states(static_model, distribution=distrib),
- model.assess_states(param_model, distribution=distrib),
- model.assess_states(lut_model, distribution=distrib),
+ distrib = dict()
+ num_states = len(model.states())
+ p95_state = None
+ for state in model.states():
+ distrib[state] = 1.0 / num_states
+
+ if "STANDBY1" in model.states():
+ p95_state = "STANDBY1"
+ elif "SLEEP" in model.states():
+ p95_state = "SLEEP"
+
+ if p95_state is not None:
+ for state in distrib.keys():
+ distrib[state] = 0.05 / (num_states - 1)
+ distrib[p95_state] = 0.95
+
+ print(f"overall state static/param/lut MAE assuming 95% {p95_state}:")
+ print(
+ " {:6.1f} / {:6.1f} / {:6.1f} µW".format(
+ model.assess_states(static_model, distribution=distrib),
+ model.assess_states(param_model, distribution=distrib),
+ model.assess_states(lut_model, distribution=distrib),
+ )
)
- )
if "summary" in show_quality or "all" in show_quality:
model_summary_table(