mirror of
https://github.com/vale981/HOPSFlow-Paper
synced 2025-03-06 10:11:39 -05:00
124 lines
4.3 KiB
Python
124 lines
4.3 KiB
Python
from speed_coupling_scan import *
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taurus_path = "taurus"
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from hiro_models.model_auxiliary import import_results
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import_results(
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other_data_path="./taurus/.data",
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other_results_path="./taurus/results",
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interactive=False,
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models_to_import=models,
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force=True,
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)
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f, a = plt.subplots()
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for model in models:
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Δs = (model.steady_index(observable=model.system_energy()))
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#Δ = (model.steady_index(observable=model.total_power(), fraction=.7))
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# for Δ in Δs[2:]:
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# pu.plot_with_σ(model.t[:model.strobe[1][1]], Δ, ax=a)
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#plt.plot(Δ)
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print(Δs)
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try:
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# pu.plot_with_σ(model.t, model.total_energy_from_power().sum_baths(), ax=a, label=fr"$\delta={model.δ[0]}$, $\tau_I={model.timings_L[0][1] - model.timings_L[0][0]:.3}$")
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# pu.plot_with_σ(model.t, model.total_energy().sum_baths(), ax=a, label=fr"$\delta={model.δ[0]}$, $\tau_I={model.timings_L[0][1] - model.timings_L[0][0]:.3}$")
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pu.plot_with_σ(model.t, model.total_energy_from_power(), ax=a, label=fr"$\delta={model.δ[0]}$, $\tau_I={model.timings_L[0][1] - model.timings_L[0][0]:.3}$")
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pu.plot_with_σ(model.t, model.total_energy(), ax=a, label=fr"$\delta={model.δ[0]}$, $\tau_I={model.timings_L[0][1] - model.timings_L[0][0]:.3}$")
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print(model.system_energy().N)
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print(model.system_power().N)
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print(model.interaction_power().N)
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except:
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pass
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a.legend()
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f, a =ot.plot_3d_heatmap(models, lambda model: -model.power(fraction=.3).value, lambda model: model.δ[0], lambda model: model.timings_L[0][1] - model.timings_L[0][0])
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a.set_xlabel(r"$\delta$")
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a.set_ylabel(r"$\tau_I$")
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a.set_zlabel(r"$P$")
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f, a = plt.subplots()
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for model in models:
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try:
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power = model.power(fraction=.5)
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a.plot(power.Ns, power.values, label=fr"$\delta={model.δ[0]}$, $\tau_I={model.timings_L[0][1] - model.timings_L[0][0]:.3}$")
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except:
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pass
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a.legend()
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from speed_coupling_scan import *
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taurus_path = "taurus"
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from hiro_models.model_auxiliary import import_results
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import_results(
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other_data_path="./taurus/.data",
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other_results_path="./taurus/results",
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interactive=False,
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models_to_import=models,
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# force=True,
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)
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f, a = plt.subplots()
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for model in models:
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Δs = (model.steady_index(observable=model.system_energy()))
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#Δ = (model.steady_index(observable=model.total_power(), fraction=.7))
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# for Δ in Δs[2:]:
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# pu.plot_with_σ(model.t[:model.strobe[1][1]], Δ, ax=a)
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#plt.plot(Δ)
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print(Δs)
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try:
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# pu.plot_with_σ(model.t, model.total_energy_from_power().sum_baths(), ax=a, label=fr"$\delta={model.δ[0]}$, $\tau_I={model.timings_L[0][1] - model.timings_L[0][0]:.3}$")
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# pu.plot_with_σ(model.t, model.total_energy().sum_baths(), ax=a, label=fr"$\delta={model.δ[0]}$, $\tau_I={model.timings_L[0][1] - model.timings_L[0][0]:.3}$")
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pu.plot_with_σ(model.t, model.total_energy_from_power(), ax=a, label=fr"$\delta={model.δ[0]}$, $\tau_I={model.timings_L[0][1] - model.timings_L[0][0]:.3}$")
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pu.plot_with_σ(model.t, model.total_energy(), ax=a, label=fr"$\delta={model.δ[0]}$, $\tau_I={model.timings_L[0][1] - model.timings_L[0][0]:.3}$")
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print(model.system_energy().N)
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print(model.system_power().N)
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print(model.interaction_power().N)
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except:
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pass
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a.legend()
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f = plt.figure()
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a_power = f.add_subplot(121, projection='3d')
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a_efficiency = f.add_subplot(122, projection='3d')
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ot.plot_3d_heatmap(
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models,
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lambda model: -model.power(fraction=0.5).value,
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lambda model: model.δ[0],
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lambda model: model.timings_L[0][1] - model.timings_L[0][0],
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normalize=True,
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ax=a_power,
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)
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a_power.set_xlabel(r"$\delta$")
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a_power.set_ylabel(r"$\tau_I$")
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a_power.set_zlabel(r"$P$ (normalized)")
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ot.plot_3d_heatmap(
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models,
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lambda model: model.efficiency(fraction=0.5).value,
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lambda model: model.δ[0],
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lambda model: model.timings_L[0][1] - model.timings_L[0][0],
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ax=a_efficiency,
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)
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a_efficiency.set_xlabel(r"$\delta$")
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a_efficiency.set_ylabel(r"$\tau_I$")
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a_efficiency.set_zlabel(r"$\eta$")
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fs.export_fig("coupling_speed_scan", fig=f)
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f
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f, a = plt.subplots()
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for model in models:
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try:
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power = model.power(fraction=.5)
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a.plot(power.Ns, power.values, label=fr"$\delta={model.δ[0]}$, $\tau_I={model.timings_L[0][1] - model.timings_L[0][0]:.3}$")
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except:
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pass
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a.legend()
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