mirror of
https://github.com/vale981/HOPSFlow-Paper
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26 KiB
26 KiB
Motivated by the striking result from over here we would like to find some approximation of the optimal cycle.
Bayesian optimization allows us to optimize towards the result with as few cycles as possible.
Boilerplate
from bayes_opt import BayesianOptimization
import figsaver as fs
import plot_utils as pu
from hiro_models.one_qubit_model import StocProcTolerances
from hiro_models.otto_cycle import OttoEngine
import hiro_models.model_auxiliary as aux
import numpy as np
import qutip as qt
import utilities as ut
import stocproc
import matplotlib.pyplot as plt
import otto_utilities as ot
import ray
ray.shutdown()
#ray.init(address='auto')
ray.init()
from hops.util.logging_setup import logging_setup
import logging
logging_setup(logging.INFO)
plt.rcParams['figure.figsize'] = (12,4)
def timings(τ_c, τ_i, percent_overlap=0):
τ_cI = τ_c * (1-percent_overlap)
τ_thI = (1 - 2 * τ_cI) / 2
τ_th = (1 - 2 * τ_c) / 2
τ_i_on = (τ_thI - 2*τ_i)
timings_H = (0, τ_c, τ_c + τ_th, 2*τ_c + τ_th)
timings_L_hot = (τ_cI, τ_cI + τ_i, τ_cI + τ_i + τ_i_on, τ_cI + 2 * τ_i + τ_i_on)
timings_L_cold = tuple(time + timings_H[2] for time in timings_L_hot)
return timings_H, (timings_L_cold, timings_L_hot)First Attempt: Only shifting the coupling to the bath
<<boilerplate>>To keep the number of parameters down, we'll shift the bath coupling without changing the coupling length. Later, an asymmetric approach with more parameters may be attempted.
τ_mod, τ_I = 0.15, 0.15
(p_H, p_L) = timings(τ_mod, τ_I, 0)
prototype = OttoEngine(
δ=[0.4, 0.4],
ω_c=[2, 2],
ψ_0=qt.basis([2], [1]),
description=f"Classic Cycle",
k_max=3,
bcf_terms=[4] * 2,
truncation_scheme="simplex",
driving_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
thermal_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
T=[0.5, 4],
therm_methods=["tanhsinh", "tanhsinh"],
Δ=1,
num_cycles=3,
Θ=1.5 / 0.05,
dt=0.01,
timings_H=p_H,
timings_L=p_L,
streaming_mode=True,
shift_to_resonance=(False, True),
L_shift=(0, 0),
)
def make_cycle(shift_c, shift_h):
crazy_model = prototype.copy()
(p_H, p_L) = timings(τ_mod, τ_I, 1)
p_L = [list(timings) for timings in p_L]
p_L[1][2] += τ_I
p_L[1][3] += τ_I
p_L[0][0] -= τ_I
p_L[0][1] -= τ_I
crazy_model.timings_H = p_H
crazy_model.timings_L = tuple(tuple(timing) for timing in p_L)
crazy_model.L_shift = (shift_c + τ_mod, shift_h)
crazy_model.description = "Full Overlap with Shift"
return crazy_modelThis is the best known config so far.
#ot.plot_cycle(make_cycle(τ_mod, τ_mod))
ot.plot_cycle(make_cycle(.4018, .303))| <Figure | size | 1200x400 | with | 1 | Axes> | <AxesSubplot: | xlabel= | $\tau$ | ylabel= | Operator Norm | > |
Now we define our objective function
def objective(shift_c, shift_h, N=500):
print(shift_c, shift_h)
model = make_cycle(shift_c, shift_h)
ot.integrate_online(model, N)
return -1 * model.power(steady_idx=-2).value… and run the optimizer.
# Bounded region of parameter space
from bayes_opt.logger import JSONLogger
from bayes_opt.event import Events
from bayes_opt.util import load_logs
pbounds = {"shift_c": (-0.1, 0.5), "shift_h": (-0.1, 0.5)}
optimizer = BayesianOptimization(
f=objective,
pbounds=pbounds,
random_state=1,
)
# load_logs(optimizer, logs=["./logs.json"]);
# logger = JSONLogger(path="./logs.json")
# optimizer.subscribe(Events.OPTIMIZATION_STEP, logger)
optimizer.probe(
params={"shift_c": 0.15, "shift_h": 0.15},
lazy=True,
)
optimizer.maximize(
init_points=4,
n_iter=100,
) [INFO hops.core.integration 264609] Choosing the nonlinear integrator.
[INFO root 264609] Starting analysis process.
| iter | target | shift_c | shift_h |
-------------------------------------------------
[INFO root 264609] Started analysis process with pid 268966.
[INFO hops.core.hierarchy_data 264609] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results_49165931924fa512ce3e8357ea5e629d22c808f8070c3949c830b5948e16ecf2.fifo
[INFO hops.core.integration 264609] Using 16 integrators.
[INFO hops.core.integration 264609] Some 0 trajectories have to be integrated.
[INFO hops.core.integration 264609] Using 165 hierarchy states.
0it [00:00, ?it/s]
[INFO hops.core.integration 264609] Choosing the nonlinear integrator.
[INFO root 264609] Starting analysis process.
| [0m1 [0m | [0m-0.0 [0m | [0m0.1502 [0m | [0m0.3322 [0m |
[INFO root 264609] Started analysis process with pid 268971.
[INFO hops.core.hierarchy_data 264609] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results_c369b7aefe5503442c698bdb4de83a3f7b1c88ae9cdf1456153e9087c7d9fc2f.fifo
[INFO hops.core.integration 264609] Using 16 integrators.
[INFO hops.core.integration 264609] Some 0 trajectories have to be integrated.
[INFO hops.core.integration 264609] Using 165 hierarchy states.
0it [00:00, ?it/s]
[INFO hops.core.integration 264609] Choosing the nonlinear integrator.
[INFO root 264609] Starting analysis process.
| [0m2 [0m | [0m-0.01777 [0m | [0m-0.09993 [0m | [0m0.0814 [0m |
[INFO root 264609] Started analysis process with pid 268976.
[INFO hops.core.hierarchy_data 264609] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results_f6fa2d1ea82b839e46df4013b731e3476b80119a206ef196c9a10f9d625066e4.fifo
[INFO hops.core.integration 264609] Using 16 integrators.
[INFO hops.core.integration 264609] Some 0 trajectories have to be integrated.
[INFO hops.core.integration 264609] Using 165 hierarchy states.
0it [00:00, ?it/s]
[INFO hops.core.integration 264609] Choosing the nonlinear integrator.
[INFO root 264609] Starting analysis process.
| [0m3 [0m | [0m-0.001374[0m | [0m-0.01195 [0m | [0m-0.0446 [0m |
[INFO root 264609] Started analysis process with pid 268981.
[INFO hops.core.hierarchy_data 264609] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results_1779c2e0c81b26e68f18a2298525a84c531fd36c909e6fddc0e41f3b78a02ee1.fifo
[INFO hops.core.integration 264609] Using 16 integrators.
[INFO hops.core.integration 264609] Some 0 trajectories have to be integrated.
[INFO hops.core.integration 264609] Using 165 hierarchy states.
0it [00:00, ?it/s]
[INFO hops.core.integration 264609] Choosing the nonlinear integrator.
[INFO root 264609] Starting analysis process.
| [0m4 [0m | [0m-0.0 [0m | [0m0.01176 [0m | [0m0.1073 [0m |
[INFO root 264609] Started analysis process with pid 269016.
[INFO hops.core.hierarchy_data 264609] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results_4c924d501d086d896c1552881c628116ad03c2100d680cb6ef5cc81dd4b2a2a6.fifo
[INFO hops.core.integration 264609] Using 16 integrators.
[INFO hops.core.integration 264609] Some 0 trajectories have to be integrated.
[INFO hops.core.integration 264609] Using 165 hierarchy states.
0it [00:00, ?it/s]
[INFO hops.core.integration 264609] Choosing the nonlinear integrator.
[INFO root 264609] Starting analysis process.
| [0m5 [0m | [0m-0.02987 [0m | [0m-0.03473 [0m | [0m0.1213 [0m |
[INFO root 264609] Started analysis process with pid 269051.
[INFO hops.core.hierarchy_data 264609] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results_d8ae65a827650db8ac3da6b4bce3faef161be342650b8238d59244d1ec5f69bb.fifo
[INFO hops.core.integration 264609] Using 16 integrators.
[INFO hops.core.integration 264609] Some 0 trajectories have to be integrated.
[INFO hops.core.integration 264609] Using 165 hierarchy states.
0it [00:00, ?it/s]
[INFO hops.core.integration 264609] Choosing the nonlinear integrator.
[INFO root 264609] Starting analysis process.
| [95m6 [0m | [95m0.02888 [0m | [95m0.398 [0m | [95m0.2961 [0m |
[INFO root 264609] Started analysis process with pid 269086.
[INFO hops.core.hierarchy_data 264609] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results_97c6b5378d143228f25a568548ca12c00f145bef0320218d249394cdf75795d6.fifo
[INFO hops.core.integration 264609] Using 16 integrators.
[INFO hops.core.integration 264609] Some 0 trajectories have to be integrated.
[INFO hops.core.integration 264609] Using 165 hierarchy states.
0it [00:00, ?it/s]
[INFO hops.core.integration 264609] Choosing the nonlinear integrator.
[INFO root 264609] Starting analysis process.
| [0m7 [0m | [0m-0.004074[0m | [0m-0.01042 [0m | [0m0.2773 [0m |
[INFO root 264609] Started analysis process with pid 269121.
[INFO hops.core.hierarchy_data 264609] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results_a5de368bb5ac8323883a97b14f8dc14ef84d021a9134152bd2e73a3bd4760052.fifo
[INFO hops.core.integration 264609] Using 16 integrators.
[INFO hops.core.integration 264609] Some 0 trajectories have to be integrated.
[INFO hops.core.integration 264609] Using 165 hierarchy states.
0it [00:00, ?it/s]
[INFO hops.core.integration 264609] Choosing the nonlinear integrator.
[INFO root 264609] Starting analysis process.
| [0m8 [0m | [0m-0.04096 [0m | [0m-0.04836 [0m | [0m0.3552 [0m |
[INFO root 264609] Started analysis process with pid 269156.
[INFO hops.core.hierarchy_data 264609] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results_c981612944d44cef75b47e1c972bc3e1b979a39b180aeceea5746a3cc49138b9.fifo
[INFO hops.core.integration 264609] Using 16 integrators.
[INFO hops.core.integration 264609] Some 0 trajectories have to be integrated.
[INFO hops.core.integration 264609] Using 165 hierarchy states.
0it [00:00, ?it/s]
[INFO hops.core.integration 264609] Choosing the nonlinear integrator.
[INFO root 264609] Starting analysis process.
| [0m9 [0m | [0m7.841e-06[0m | [0m0.1374 [0m | [0m-0.003125[0m |
[INFO root 264609] Started analysis process with pid 269191.
[INFO hops.core.hierarchy_data 264609] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results_ad69b9cace9b50f1041832e082421a317348dcbb5bfda0a3e6b8efb7717c92e8.fifo
[INFO hops.core.integration 264609] Using 16 integrators.
[INFO hops.core.integration 264609] Some 610 trajectories have to be integrated.
[INFO hops.core.integration 264609] Using 165 hierarchy states.
0% 0/610 [00:00<?, ?it/s][INFO hops.core.signal_delay 264609] caught sig 'SIGINT'
[INFO hops.core.signal_delay 264609] caught sig 'SIGINT'
[INFO hops.core.signal_delay 264609] caught sig 'SIGINT'
0% 0/610 [00:10<?, ?it/s]
[INFO hops.core.signal_delay 264609] caught 3 signal(s)
[INFO hops.core.signal_delay 264609] emit signal 'SIGINT'
[INFO hops.core.signal_delay 264609] caught sig 'SIGINT'
[INFO hops.core.signal_delay 264609] emit signal 'SIGINT'
[INFO hops.core.signal_delay 264609] caught sig 'SIGINT'
[INFO hops.core.signal_delay 264609] emit signal 'SIGINT'
[INFO hops.core.signal_delay 264609] caught sig 'SIGINT'
2023-02-02 09:05:23,690 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,691 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,695 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,696 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,697 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,705 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,729 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,741 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,742 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,742 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,743 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,743 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,743 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,744 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,744 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
2023-02-02 09:05:23,745 ERROR worker.py:94 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
[INFO hops.core.signal_delay 264609] caught 3 signal(s)
[INFO hops.core.signal_delay 264609] emit signal 'SIGINT'
[0;31m---------------------------------------------------------------------------[0m [0;31mKeyboardInterrupt[0m Traceback (most recent call last) Cell [0;32mIn[7], line 16[0m [1;32m 7[0m optimizer [38;5;241m=[39m BayesianOptimization( [1;32m 8[0m f[38;5;241m=[39mobjective, [1;32m 9[0m pbounds[38;5;241m=[39mpbounds, [1;32m 10[0m random_state[38;5;241m=[39m[38;5;241m1[39m, [1;32m 11[0m ) [1;32m 12[0m [38;5;66;03m# load_logs(optimizer, logs=["./logs.json"]);[39;00m [1;32m 13[0m [1;32m 14[0m [38;5;66;03m# logger = JSONLogger(path="./logs.json")[39;00m [1;32m 15[0m [38;5;66;03m# optimizer.subscribe(Events.OPTIMIZATION_STEP, logger)[39;00m [0;32m---> 16[0m [43moptimizer[49m[38;5;241;43m.[39;49m[43mmaximize[49m[43m([49m [1;32m 17[0m [43m [49m[43minit_points[49m[38;5;241;43m=[39;49m[38;5;241;43m4[39;49m[43m,[49m [1;32m 18[0m [43m [49m[43mn_iter[49m[38;5;241;43m=[39;49m[38;5;241;43m8[39;49m[43m,[49m [1;32m 19[0m [43m)[49m File [0;32m/nix/store/vkzza81mzwyk5br1c6cm67g48xycvmvl-python3-3.9.15-env/lib/python3.9/site-packages/bayes_opt/bayesian_optimization.py:311[0m, in [0;36mBayesianOptimization.maximize[0;34m(self, init_points, n_iter, acquisition_function, acq, kappa, kappa_decay, kappa_decay_delay, xi, **gp_params)[0m [1;32m 309[0m x_probe [38;5;241m=[39m [38;5;28mself[39m[38;5;241m.[39msuggest(util) [1;32m 310[0m iteration [38;5;241m+[39m[38;5;241m=[39m [38;5;241m1[39m [0;32m--> 311[0m [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43mprobe[49m[43m([49m[43mx_probe[49m[43m,[49m[43m [49m[43mlazy[49m[38;5;241;43m=[39;49m[38;5;28;43;01mFalse[39;49;00m[43m)[49m [1;32m 313[0m [38;5;28;01mif[39;00m [38;5;28mself[39m[38;5;241m.[39m_bounds_transformer [38;5;129;01mand[39;00m iteration [38;5;241m>[39m [38;5;241m0[39m: [1;32m 314[0m [38;5;66;03m# The bounds transformer should only modify the bounds after[39;00m [1;32m 315[0m [38;5;66;03m# the init_points points (only for the true iterations)[39;00m [1;32m 316[0m [38;5;28mself[39m[38;5;241m.[39mset_bounds( [1;32m 317[0m [38;5;28mself[39m[38;5;241m.[39m_bounds_transformer[38;5;241m.[39mtransform([38;5;28mself[39m[38;5;241m.[39m_space)) File [0;32m/nix/store/vkzza81mzwyk5br1c6cm67g48xycvmvl-python3-3.9.15-env/lib/python3.9/site-packages/bayes_opt/bayesian_optimization.py:208[0m, in [0;36mBayesianOptimization.probe[0;34m(self, params, lazy)[0m [1;32m 206[0m [38;5;28mself[39m[38;5;241m.[39m_queue[38;5;241m.[39madd(params) [1;32m 207[0m [38;5;28;01melse[39;00m: [0;32m--> 208[0m [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43m_space[49m[38;5;241;43m.[39;49m[43mprobe[49m[43m([49m[43mparams[49m[43m)[49m [1;32m 209[0m [38;5;28mself[39m[38;5;241m.[39mdispatch(Events[38;5;241m.[39mOPTIMIZATION_STEP) File [0;32m/nix/store/vkzza81mzwyk5br1c6cm67g48xycvmvl-python3-3.9.15-env/lib/python3.9/site-packages/bayes_opt/target_space.py:236[0m, in [0;36mTargetSpace.probe[0;34m(self, params)[0m [1;32m 234[0m x [38;5;241m=[39m [38;5;28mself[39m[38;5;241m.[39m_as_array(params) [1;32m 235[0m params [38;5;241m=[39m [38;5;28mdict[39m([38;5;28mzip[39m([38;5;28mself[39m[38;5;241m.[39m_keys, x)) [0;32m--> 236[0m target [38;5;241m=[39m [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43mtarget_func[49m[43m([49m[38;5;241;43m*[39;49m[38;5;241;43m*[39;49m[43mparams[49m[43m)[49m [1;32m 238[0m [38;5;28;01mif[39;00m [38;5;28mself[39m[38;5;241m.[39m_constraint [38;5;129;01mis[39;00m [38;5;28;01mNone[39;00m: [1;32m 239[0m [38;5;28mself[39m[38;5;241m.[39mregister(x, target) Cell [0;32mIn[4], line 3[0m, in [0;36mobjective[0;34m(shift_c, shift_h, N)[0m [1;32m 1[0m [38;5;28;01mdef[39;00m [38;5;21mobjective[39m(shift_c, shift_h, N[38;5;241m=[39m[38;5;241m1000[39m): [1;32m 2[0m model [38;5;241m=[39m make_cycle(shift_c, shift_h) [0;32m----> 3[0m [43mot[49m[38;5;241;43m.[39;49m[43mintegrate_online[49m[43m([49m[43mmodel[49m[43m,[49m[43m [49m[43mN[49m[43m)[49m [1;32m 5[0m [38;5;28;01mreturn[39;00m [38;5;241m-[39m[38;5;241m1[39m [38;5;241m*[39m model[38;5;241m.[39mpower(steady_idx[38;5;241m=[39m[38;5;241m-[39m[38;5;241m1[39m)[38;5;241m.[39mvalue File [0;32m~/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/otto_utilities.py:155[0m, in [0;36mintegrate_online[0;34m(model, n, stream_folder, **kwargs)[0m [1;32m 154[0m [38;5;28;01mdef[39;00m [38;5;21mintegrate_online[39m(model, n, stream_folder[38;5;241m=[39m[38;5;28;01mNone[39;00m, [38;5;241m*[39m[38;5;241m*[39mkwargs): [0;32m--> 155[0m [43maux[49m[38;5;241;43m.[39;49m[43mintegrate[49m[43m([49m [1;32m 156[0m [43m [49m[43mmodel[49m[43m,[49m [1;32m 157[0m [43m [49m[43mn[49m[43m,[49m [1;32m 158[0m [43m [49m[43mstream_file[49m[38;5;241;43m=[39;49m[43m([49m[38;5;124;43m"[39;49m[38;5;124;43m"[39;49m[43m [49m[38;5;28;43;01mif[39;49;00m[43m [49m[43mstream_folder[49m[43m [49m[38;5;129;43;01mis[39;49;00m[43m [49m[38;5;28;43;01mNone[39;49;00m[43m [49m[38;5;28;43;01melse[39;49;00m[43m [49m[43mstream_folder[49m[43m)[49m [1;32m 159[0m [43m 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exc_val, exc_tb)[0m [1;32m 84[0m [38;5;28;01mif[39;00m [38;5;28mlen[39m([38;5;28mself[39m[38;5;241m.[39msigh[38;5;241m.[39msigs_caught) [38;5;241m>[39m [38;5;241m0[39m [38;5;129;01mand[39;00m [38;5;28mself[39m[38;5;241m.[39mhandler [38;5;129;01mis[39;00m [38;5;129;01mnot[39;00m [38;5;28;01mNone[39;00m: [1;32m 85[0m [38;5;28mself[39m[38;5;241m.[39mhandler([38;5;28mself[39m[38;5;241m.[39msigh[38;5;241m.[39msigs_caught) [0;32m---> 87[0m [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43m_restore[49m[43m([49m[43m)[49m File [0;32m~/src/hops/hops/core/signal_delay.py:68[0m, in [0;36msig_delay._restore[0;34m(self)[0m [1;32m 66[0m [38;5;28;01mfor[39;00m i, s [38;5;129;01min[39;00m [38;5;28menumerate[39m([38;5;28mself[39m[38;5;241m.[39msigs): [1;32m 67[0m signal[38;5;241m.[39msignal(s, [38;5;28mself[39m[38;5;241m.[39mold_handlers[i]) [0;32m---> 68[0m [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43msigh[49m[38;5;241;43m.[39;49m[43memit[49m[43m([49m[43m)[49m File [0;32m~/src/hops/hops/core/signal_delay.py:42[0m, in [0;36mSigHandler.emit[0;34m(self)[0m [1;32m 40[0m [38;5;28;01mfor[39;00m s [38;5;129;01min[39;00m [38;5;28mself[39m[38;5;241m.[39msigs_caught: [1;32m 41[0m log[38;5;241m.[39minfo([38;5;124m"[39m[38;5;124memit signal [39m[38;5;124m'[39m[38;5;132;01m{}[39;00m[38;5;124m'[39m[38;5;124m"[39m[38;5;241m.[39mformat(SIG_MAP[s])) [0;32m---> 42[0m [43mos[49m[38;5;241;43m.[39;49m[43mkill[49m[43m([49m[43mos[49m[38;5;241;43m.[39;49m[43mgetpid[49m[43m([49m[43m)[49m[43m,[49m[43m [49m[43ms[49m[43m)[49m [0;31mKeyboardInterrupt[0m:
with aux.model_db(data_path=".data") as db:
model = db["05a638feb440fd913b41a5be74fbdd5a6cc358f2b556e61e4005b8539ca15115"]["model_config"]
c=make_cycle(0.401813980810373, 0.302982197157591)
# aux.import_results(
# other_data_path = "taurus/.data",
# results_path = "./results",
# other_results_path = "taurus/results",
# interactive = False,
# models_to_import = [model],
# force = False,
# )
#ot.plot_cycle(c)
#model.L_shift
t, total = ot.val_relative_to_steady(model, model.total_energy_from_power(), steady_idx=-2)
pu.plot_with_σ(t, total)
model.power(steady_idx=-2)EnsembleValue([(10000, 3.3527328716046976e-05, 5.0274219343398344e-05)])
