def process_energy_ts(energy, area, policy):
mi = MEASUREMENT_INTERVAL_SUBSAMPLE if policy.subsample else MEASUREMENT_INTERVAL
debug_figure_energy(energy, area)
if area.mode == 'find':
em = ExperimentModel(
Repeat(
Situation('high', min=1.4, d_min=.1),
Situation('before', max=1.5, d_min=.1),
Situation('insert', min=1.4, max=5, d_min=.01, d_max=2.0),
Situation('between', max=1.2, d_min=2.0, d_max=10.0),
Situation('find', min=1.1, max=5, d_max=2.0),
Situation('after_find', max=7.0, d_min=0.1, d_max=10.0),
),
t0=policy.tmin,
delta_t=mi,
tmax=policy.tmax,
)
else:
em = ExperimentModel(
Repeat(
Situation('high', min=1.4, d_min=.1),
Situation('before', max=1.5, d_min=.1),
Situation('insert', min=1.4, max=5, d_min=.01, d_max=2.0),
Situation('between', max=1.2, d_min=2.0, d_max=20.0),
),
t0=policy.tmin,
delta_t=mi,
tmax=policy.tmax,
)
tsums = []
esums = []
ots = []
baseline = 0
for m in em.match(energy):
#print("xxx {}".format(m.situation.name))
if m.situation.name in ('before', 'between', 'after_find'):
baseline = m.v_average
elif m.situation.name == 'insert' and area.mode == 'insert':
ots.append(m.t0)
tsums.append(m.d)
esums.append(m.v_sum * mi - baseline * m.d)
elif m.situation.name == 'find' and area.mode == 'find':
#print("find t0={} d={} v_sum={} baseline={}".format(m.t0, m.d, m.v_sum, baseline))
ots.append(m.t0)
tsums.append(m.d / FINDS_AT_ONCE)
esums.append((m.v_sum * mi - baseline * m.d) / FINDS_AT_ONCE)
return [tsums], [esums], [ots]
def process_energy_ts(energy, area, policy):
mi = MEASUREMENT_INTERVAL_SUBSAMPLE if policy.subsample else MEASUREMENT_INTERVAL
debug_figure_energy(energy, area)
if area.mode == 'find':
em = ExperimentModel(
Repeat(
Situation('high', min=1.4, d_min=.1),
Situation('before', max=1.5, d_min=.1),
Situation('insert', min=1.4, max=5, d_min=.01, d_max=2.0),
Situation('between', max=1.2, d_min=2.0, d_max=10.0),
Situation('find', min=1.1, max=5, d_max=2.0),
Situation('after_find', max=7.0, d_min=0.1, d_max=10.0),
),
t0 = policy.tmin, delta_t = mi,
tmax = policy.tmax,
)
else:
em = ExperimentModel(
Repeat(
Situation('high', min=1.4, d_min=.1),
Situation('before', max=1.5, d_min=.1),
Situation('insert', min=1.4, max=5, d_min=.01, d_max=2.0),
Situation('between', max=1.2, d_min=2.0, d_max=20.0),
),
t0 = policy.tmin, delta_t = mi,
tmax = policy.tmax,
)
tsums = []
esums = []
ots = []
baseline = 0
for m in em.match(energy):
#print("xxx {}".format(m.situation.name))
if m.situation.name in ('before', 'between', 'after_find'):
baseline = m.v_average
elif m.situation.name == 'insert' and area.mode == 'insert':
ots.append(m.t0)
tsums.append(m.d)
esums.append(m.v_sum * mi - baseline * m.d)
elif m.situation.name == 'find' and area.mode == 'find':
#print("find t0={} d={} v_sum={} baseline={}".format(m.t0, m.d, m.v_sum, baseline))
ots.append(m.t0)
tsums.append(m.d / FINDS_AT_ONCE)
esums.append((m.v_sum * mi - baseline * m.d) / FINDS_AT_ONCE)
return [tsums], [esums], [ots]
def process_energy_ts_erase(energy, area, policy):
mi = MEASUREMENT_INTERVAL_SUBSAMPLE if policy.subsample else MEASUREMENT_INTERVAL
# fixd-width moving average for smoothness,
# also serves as a band stop filter for timer ticks
energy = np_moving_average(energy, int(0.0136 / mi))
debug_figure_energy(energy, area)
em = ExperimentModel(
Situation('start', max = 1.2),
t0 = policy.tmin,
tmax = policy.tmax,
delta_t = mi,
)
baseline = 0
for m in em.match(energy):
baseline = m.v_average
print("baseline=", baseline)
em = ExperimentModel(
Situation('start', max = baseline + .2),
Repeat(
Situation('prep', min=baseline + .05, d_min=0.01, d_max=0.1),
Situation('between', max=baseline + .1, d_min=0.05, d_max=0.2),
Situation('exp', min=baseline + .05, d_min=0.01, d_max=0.1),
Situation('after', max=baseline + .1, d_min=0.4, d_max=0.6),
),
t0 = policy.tmin, delta_t = mi,
tmax = policy.tmax,
)
tsums = []
esums = []
ots = []
for m in em.match(energy):
#print('-- {} {}-{} -> {} - {}'.format(m.situation.name, m.t0, m.t0+m.d, m.v_sum, baseline))
if m.situation.name == 'exp':
ots.append(m.t0)
tsums.append(m.d)
esums.append(m.v_sum * mi - baseline * m.d)
elif m.situation.name in ('idle', 'start', 'between', 'after'):
#print("---- setting baseline: ", m.situation.name, m.v_average)
baseline = m.v_average
print('/process_energy_ts_erase')
return [tsums], [esums], [ots]
def process_energy_teenylime(energy, area, policy):
mi = MEASUREMENT_INTERVAL_SUBSAMPLE if policy.subsample else MEASUREMENT_INTERVAL
debug_figure_energy(energy, area)
em = ExperimentModel(
Situation('power-on', d_max=.02),
Situation('start', max=.25, d_max=.05),
t0 = policy.tmin, delta_t = mi,
tmax = policy.tmax,
)
baseline = 0
for m in em.match(energy):
baseline = m.v_average
print("baseline=", baseline)
b = baseline
em = ExperimentModel(
Situation('power-on', d_max=.02),
Situation('start', max=0.25, d_max=.05),
Repeat(
Situation('between', max = b + .1),
Situation('exp', min = b + .05),
),
t0 = policy.tmin, delta_t = mi,
tmax = policy.tmax,
)
tsums = []
esums = []
ots = []
for m in em.match(energy):
print("---- found: {} {}...{}".format(m.situation.name, m.t0, m.t0 + m.d))
if m.situation.name == 'exp':
print('-- {} {}-{} -> {} - {}'.format(m.situation.name, m.t0, m.t0+m.d, m.v_sum * mi, m.d*baseline))
ots.append(m.t0)
tsums.append(m.d)
esums.append(m.v_sum * mi - baseline * m.d)
elif m.situation.name == 'between':
print("---- correcting baseline: ", m.situation.name, m.v_average)
baseline = m.v_average
return [tsums], [esums], [ots]
def process_energy_ts_erase(energy, area, policy):
mi = MEASUREMENT_INTERVAL_SUBSAMPLE if policy.subsample else MEASUREMENT_INTERVAL
# fixd-width moving average for smoothness,
# also serves as a band stop filter for timer ticks
energy = np_moving_average(energy, int(0.0136 / mi))
debug_figure_energy(energy, area)
em = ExperimentModel(
Situation('start', max=1.2),
t0=policy.tmin,
tmax=policy.tmax,
delta_t=mi,
)
baseline = 0
for m in em.match(energy):
baseline = m.v_average
print("baseline=", baseline)
em = ExperimentModel(
Situation('start', max=baseline + .2),
Repeat(
Situation('prep', min=baseline + .05, d_min=0.01, d_max=0.1),
Situation('between', max=baseline + .1, d_min=0.05, d_max=0.2),
Situation('exp', min=baseline + .05, d_min=0.01, d_max=0.1),
Situation('after', max=baseline + .1, d_min=0.4, d_max=0.6),
),
t0=policy.tmin,
delta_t=mi,
tmax=policy.tmax,
)
tsums = []
esums = []
ots = []
for m in em.match(energy):
#print('-- {} {}-{} -> {} - {}'.format(m.situation.name, m.t0, m.t0+m.d, m.v_sum, baseline))
if m.situation.name == 'exp':
ots.append(m.t0)
tsums.append(m.d)
esums.append(m.v_sum * mi - baseline * m.d)
elif m.situation.name in ('idle', 'start', 'between', 'after'):
#print("---- setting baseline: ", m.situation.name, m.v_average)
baseline = m.v_average
print('/process_energy_ts_erase')
return [tsums], [esums], [ots]
def process_energy_teenylime(energy, area, policy):
mi = MEASUREMENT_INTERVAL_SUBSAMPLE if policy.subsample else MEASUREMENT_INTERVAL
debug_figure_energy(energy, area)
em = ExperimentModel(
Situation('power-on', d_max=.02),
Situation('start', max=.25, d_max=.05),
t0=policy.tmin,
delta_t=mi,
tmax=policy.tmax,
)
baseline = 0
for m in em.match(energy):
baseline = m.v_average
print("baseline=", baseline)
b = baseline
em = ExperimentModel(
Situation('power-on', d_max=.02),
Situation('start', max=0.25, d_max=.05),
Repeat(
Situation('between', max=b + .1),
Situation('exp', min=b + .05),
),
t0=policy.tmin,
delta_t=mi,
tmax=policy.tmax,
)
tsums = []
esums = []
ots = []
for m in em.match(energy):
print("---- found: {} {}...{}".format(m.situation.name, m.t0,
m.t0 + m.d))
if m.situation.name == 'exp':
print('-- {} {}-{} -> {} - {}'.format(m.situation.name, m.t0,
m.t0 + m.d, m.v_sum * mi,
m.d * baseline))
ots.append(m.t0)
tsums.append(m.d)
esums.append(m.v_sum * mi - baseline * m.d)
elif m.situation.name == 'between':
print("---- correcting baseline: ", m.situation.name, m.v_average)
baseline = m.v_average
return [tsums], [esums], [ots]