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-rw-r--r--lib/dfatool.py74
1 files changed, 41 insertions, 33 deletions
diff --git a/lib/dfatool.py b/lib/dfatool.py
index 56f0f2d..e0eb0d4 100644
--- a/lib/dfatool.py
+++ b/lib/dfatool.py
@@ -405,6 +405,7 @@ def _preprocess_etlog(measurement):
float(setup["voltage"]),
int(setup["state_duration"]),
measurement["transition_names"],
+ with_traces=measurement["with_traces"],
)
try:
etlog.load_data(measurement["content"])
@@ -1261,6 +1262,7 @@ class RawData:
"setup": self.setup_by_fileno[j],
"repeat_id": repeat_id,
"expected_trace": ptalog["traces"][j],
+ "with_traces": self.with_traces,
"transition_names": list(
map(
lambda x: x["name"],
@@ -2592,7 +2594,13 @@ class EnergyTraceLog:
at the moment.
"""
- def __init__(self, voltage: float, state_duration: int, transition_names: list):
+ def __init__(
+ self,
+ voltage: float,
+ state_duration: int,
+ transition_names: list,
+ with_traces=False,
+ ):
"""
Create a new EnergyTraceLog object.
@@ -2604,6 +2612,7 @@ class EnergyTraceLog:
self.voltage = voltage
self.state_duration = state_duration * 1e-3
self.transition_names = transition_names
+ self.with_traces = with_traces
self.verbose = False
self.errors = list()
@@ -2807,44 +2816,43 @@ class EnergyTraceLog:
),
)
- energy_trace.append(
- {
- "isa": "transition",
- "W_mean": np.mean(
- self.interval_power[
- transition_start_index:transition_done_index
- ]
- ),
- "W_std": np.std(
- self.interval_power[
- transition_start_index:transition_done_index
- ]
- ),
- "s": duration,
- "s_coarse": self.interval_start_timestamp[transition_done_index]
- - self.interval_start_timestamp[transition_start_index],
- }
- )
+ transition_power_W = self.interval_power[
+ transition_start_index:transition_done_index
+ ]
+
+ transition = {
+ "isa": "transition",
+ "W_mean": np.mean(transition_power_W),
+ "W_std": np.std(transition_power_W),
+ "s": duration,
+ "s_coarse": self.interval_start_timestamp[transition_done_index]
+ - self.interval_start_timestamp[transition_start_index],
+ }
+
+ if self.with_traces:
+ transition["uW"] = transition_power_W * 1e6
+
+ energy_trace.append(transition)
if len(energy_trace) > 1:
energy_trace[-1]["W_mean_delta_prev"] = (
energy_trace[-1]["W_mean"] - energy_trace[-2]["W_mean"]
)
- energy_trace.append(
- {
- "isa": "state",
- "W_mean": np.mean(
- self.interval_power[state_start_index:state_done_index]
- ),
- "W_std": np.std(
- self.interval_power[state_start_index:state_done_index]
- ),
- "s": self.state_duration,
- "s_coarse": self.interval_start_timestamp[state_done_index]
- - self.interval_start_timestamp[state_start_index],
- }
- )
+ state_power_W = self.interval_power[state_start_index:state_done_index]
+ state = {
+ "isa": "state",
+ "W_mean": np.mean(state_power_W),
+ "W_std": np.std(state_power_W),
+ "s": self.state_duration,
+ "s_coarse": self.interval_start_timestamp[state_done_index]
+ - self.interval_start_timestamp[state_start_index],
+ }
+
+ if self.with_traces:
+ state["uW"] = state_power_W * 1e6
+
+ energy_trace.append(state)
energy_trace[-2]["W_mean_delta_next"] = (
energy_trace[-2]["W_mean"] - energy_trace[-1]["W_mean"]