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authorDaniel Friesel <derf@finalrewind.org>2018-01-29 15:32:52 +0100
committerDaniel Friesel <derf@finalrewind.org>2018-01-29 15:32:52 +0100
commit4ce047e96b74c58a44b3f80320a8c03f43bc8fea (patch)
tree4184e52b4a394567b8c39c25fc66dd84b473fac4 /lib
parent18afba9273d1fa2cce2ed66f8c5f102e59fa962f (diff)
weed out clipping measurements as early as possible
Diffstat (limited to 'lib')
-rwxr-xr-xlib/dfatool.py18
1 files changed, 13 insertions, 5 deletions
diff --git a/lib/dfatool.py b/lib/dfatool.py
index 60ccefd..3e3a0b5 100755
--- a/lib/dfatool.py
+++ b/lib/dfatool.py
@@ -188,6 +188,18 @@ class RawData:
on_isa = online_trace_part['isa'])
return False
+ # Clipping in UNINITIALIZED (offline_idx == 0) can happen during
+ # calibration and is handled by MIMOSA
+ if offline_idx != 0 and offline_trace_part['clip_rate'] != 0:
+ processed_data['error'] = 'Offline #{off_idx:d} (online {on_name:s} @ {on_idx:d}/{on_sub:d}) was clipping {clip:f}% of the time'.format(
+ off_idx = offline_idx, on_idx = online_run_idx,
+ on_sub = online_trace_part_idx,
+ on_name = online_trace_part['name'],
+ clip = offline_trace_part['clip_rate'] * 100,
+ )
+ return False
+
+
if online_trace_part['isa'] == 'state' and online_trace_part['name'] != 'UNINITIALIZED':
online_prev_transition = traces[online_run_idx]['trace'][online_trace_part_idx-1]
online_next_transition = traces[online_run_idx]['trace'][online_trace_part_idx+1]
@@ -236,7 +248,6 @@ class RawData:
'duration' : [],
'power_std' : [],
'energy' : [],
- 'clipping' : [],
'paramkeys' : [],
'param': [],
}
@@ -256,8 +267,6 @@ class RawData:
offline_trace_part['uW_std'])
online_trace_part['offline_aggregates']['energy'].append(
offline_trace_part['uW_mean'] * (offline_trace_part['us'] - 20))
- online_trace_part['offline_aggregates']['clipping'].append(
- offline_trace_part['clip_rate'])
online_trace_part['offline_aggregates']['paramkeys'].append(paramkeys)
online_trace_part['offline_aggregates']['param'].append(paramvalue)
if online_trace_part['isa'] == 'transition':
@@ -341,7 +350,7 @@ class EnergyModel:
def _aggregate_to_ndarray(self, aggregate):
for elem in aggregate.values():
- for key in ['clipping', 'power', 'power_std', 'energy', 'duration', 'timeout', 'rel_energy_prev', 'rel_energy_next']:
+ for key in ['power', 'power_std', 'energy', 'duration', 'timeout', 'rel_energy_prev', 'rel_energy_next']:
if key in elem:
elem[key] = np.array(elem[key])
@@ -408,7 +417,6 @@ class EnergyModel:
print('[W] Got no data for {} {}'.format(name, key))
except FloatingPointError as fpe:
print('[W] Got no data for {} {}: {}'.format(name, key, fpe))
- print(lut_model)
def lut_median_getter(name, key, param, **kwargs):
return lut_model[(name, tuple(param))][key]