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https://github.com/vale981/master-thesis
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try antoher route: high temperature but very weak coupling
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5 changed files with 533 additions and 400 deletions
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@ -31,10 +31,10 @@ def anti_zeno_engine(
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cycle_scale=1,
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switch_cycles=3,
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detune=0,
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δ=[2] * 2,
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δ=[10] * 2,
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T_h=5,
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therm_initial_state=False,
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s=1,
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s=[1, 1],
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dt=0.1,
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T_c=0,
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ε_init=0,
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@ -79,6 +79,21 @@ def anti_zeno_engine(
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τ_c + τ_off,
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)
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ts = [
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np.concatenate(
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[
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ut.linspace_with_strobe(
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max((τ_c + τ_off) * i - Δ_switch, 0),
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(τ_c + τ_off) * (i) + τ_c + Δ_switch,
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int((τ_c + 2 * Δ_switch) / dt),
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Δ,
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),
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np.linspace((τ_c + τ_off) * (i) + τ_c, (τ_c + τ_off) * (i + 1), 10),
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]
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)
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for i in range(n)
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]
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initializing_period = 0
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if ε_init > 0:
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initializing_period = (
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@ -135,11 +150,27 @@ def anti_zeno_engine(
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[0, initializing_period, initializing_period + τ_off, np.inf],
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)
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ts = [times + initializing_period + τ_off for times in ts]
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ts.insert(
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0,
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np.concatenate(
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[
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ut.linspace_with_strobe(
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0,
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initializing_period + Δ_switch,
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int((initializing_period + Δ_switch) / dt),
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Δ,
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),
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np.linspace(initializing_period, initializing_period + τ_off, 10),
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]
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),
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)
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model = QubitModelMutliBath(
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δ=δ,
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ω_c=[ω_c, ω_c],
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ω_s=[ω_0 - Δ - ω_c + detune, ω_0 + Δ - ω_c + detune],
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t=ut.linspace_with_strobe(0, t_max, int(t_max / dt), Δ),
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t=np.unique(np.concatenate(ts)),
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ψ_0=(
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np.sqrt(1 / (np.exp(ω_0 / T_h) + 1)) * qt.basis([2], [0])
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+ np.sqrt(1 / (np.exp(-ω_0 / T_h) + 1)) * qt.basis([2], [1])
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@ -183,25 +214,24 @@ def anti_zeno_engine(
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(τ_mod, τ_c, τ_bath, cycles, model.ω_s, ω_0, τ_s, τ_off, n, Δ_switch, τ_init),
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) = anti_zeno_engine(
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Δ=11,
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ε=.05,#.1,
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ω_c=1,
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ε=.5,#.1,
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ω_c=2,
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ε_couple=0.7,
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n=8,
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n=0 ,
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detune=.5,
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ω_0=20,
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T_c=1e3,
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T_h=1e4,
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δ=[3.2, 1],
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δ=[3.2*.01, 1*.01],
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γ=.2,
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switch_cycles=1,
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therm_initial_state=False,
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s=[1] * 2,
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ε_init=0.1,
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terms=6,
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therm_initial_state=True,
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ε_init=.1,
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terms=4,
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dt=0.01,
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sp_tol=1e-2,
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)
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model.k_max = 4
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model.k_max = 3
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# model, params = anti_zeno_engine(ε=1/2, ε_couple=1e-4, n=1, detune=.5, δ=[.1,.1])
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fs.tex_value(
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@ -258,12 +288,13 @@ vs = np.linspace(0.1, 10, 100)
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plt.plot(vs, chi(vs, ω_0))
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plt.plot(vs, G_h(vs))
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aux.integrate(model, 10)
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aux.integrate(model, 100)
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#_, ax = fs.plot_energy_overview(model, markersize=1, ensemble_args=dict(gc_sleep=0.05))
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fig, ax = plt.subplots()
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with aux.get_data(model) as data:
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fs.plot_with_σ(model.t, model.total_power(data), ax=ax)
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fs.plot_with_σ(model.t, model.total_energy_from_power(data), ax=ax)
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#ax.legend()
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@ -308,7 +339,7 @@ ts_end = model.t[ind_end]
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# #plt.plot(model.t, model.L[0].operator_norm(model.t))
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with aux.get_data(model) as data:
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tot_e = (model.total_energy_from_power(data)) #model.total_energy(data).value
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tot_power = (model.total_power(data)) #model.total_energy(data).value
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fig, ax = plt.subplots()
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fig.set_size_inches(fs.get_figsize("poster", 0.49))
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@ -320,18 +351,17 @@ for t in ts_end:
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plt.axvline(t, linestyle="dotted", color="lightblue", linewidth=1)
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fs.plot_with_σ(
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model.t[ind_begin[0] ::10], tot_e.slice(ind_begin[0], None, 10), ax=ax, linewidth=0.5
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model.t[ind_begin[0] ::10], tot_power.slice(ind_begin[0], None, 10), ax=ax, linewidth=0.5
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)
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ax.plot(
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model.t[ind_begin[0] ::10],
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ut.smoothen(model.t[ind_begin[0] :], tot_e.value[ind_begin[0] :], frac=0.1)[::10],
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ut.smoothen(model.t[ind_begin[0] :], tot_power.value[ind_begin[0] :], frac=0.1)[::10],
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)
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powers = []
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for begin, end in zip(ind_begin, ind_end):
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powers.append(
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(tot_e.slice(end, end+1) - tot_e.slice(begin, begin+1))
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* (1 / (model.t[ind_end[0]] - model.t[ind_begin[0]]))
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(tot_power.slice(begin, end)).mean
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)
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power = sum(powers) * (1/(len(powers)))
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@ -342,8 +372,8 @@ ax.set_xlabel(r"$\tau$")
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#fs.export_fig("anti_zeno_with_cool")
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fs.tex_value(
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(power.value[0]),
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err=power.σ[0],
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(power.value),
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err=power.σ,
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prefix="P=",
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save="power_with_cool",
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)
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@ -26,7 +26,7 @@ Init ray and silence stocproc.
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#+end_src
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#+RESULTS:
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: RayContext(dashboard_url='', python_version='3.9.13', ray_version='1.13.0', ray_commit='e4ce38d001dbbe09cd21c497fedd03d692b2be3e', address_info={'node_ip_address': '141.30.17.225', 'raylet_ip_address': '141.30.17.225', 'redis_address': None, 'object_store_address': '/tmp/ray/session_2022-07-07_19-11-40_930040_398742/sockets/plasma_store.8', 'raylet_socket_name': '/tmp/ray/session_2022-07-07_19-11-40_930040_398742/sockets/raylet.3', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-07-07_19-11-40_930040_398742', 'metrics_export_port': 42078, 'gcs_address': '141.30.17.16:6379', 'address': '141.30.17.16:6379', 'node_id': 'f0ec7ea2877bae7b0c671e3bc3532313b0601cd2ed54100a4bdbf452'})
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: RayContext(dashboard_url='', python_version='3.9.13', ray_version='1.13.0', ray_commit='e4ce38d001dbbe09cd21c497fedd03d692b2be3e', address_info={'node_ip_address': '141.30.17.225', 'raylet_ip_address': '141.30.17.225', 'redis_address': None, 'object_store_address': '/tmp/ray/session_2022-07-07_19-11-40_930040_398742/sockets/plasma_store.11', 'raylet_socket_name': '/tmp/ray/session_2022-07-07_19-11-40_930040_398742/sockets/raylet.6', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-07-07_19-11-40_930040_398742', 'metrics_export_port': 49187, 'gcs_address': '141.30.17.16:6379', 'address': '141.30.17.16:6379', 'node_id': '05751e0798000d84f4d4e4a94be6dc3b05fdf36ca9db3fb65b1b6de5'})
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#+begin_src jupyter-python :results none
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from hops.util.logging_setup import logging_setup
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@ -47,10 +47,10 @@ Init ray and silence stocproc.
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cycle_scale=1,
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switch_cycles=3,
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detune=0,
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δ=[2] * 2,
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δ=[10] * 2,
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T_h=5,
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therm_initial_state=False,
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s=1,
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s=[1, 1],
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dt=0.1,
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T_c=0,
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ε_init=0,
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@ -95,6 +95,21 @@ Init ray and silence stocproc.
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τ_c + τ_off,
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)
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ts = [
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np.concatenate(
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[
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ut.linspace_with_strobe(
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max((τ_c + τ_off) * i - Δ_switch, 0),
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(τ_c + τ_off) * (i) + τ_c + Δ_switch,
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int((τ_c + 2 * Δ_switch) / dt),
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Δ,
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),
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np.linspace((τ_c + τ_off) * (i) + τ_c, (τ_c + τ_off) * (i + 1), 10),
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]
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)
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for i in range(n)
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]
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initializing_period = 0
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if ε_init > 0:
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initializing_period = (
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@ -151,11 +166,27 @@ Init ray and silence stocproc.
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[0, initializing_period, initializing_period + τ_off, np.inf],
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)
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ts = [times + initializing_period + τ_off for times in ts]
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ts.insert(
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0,
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np.concatenate(
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[
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ut.linspace_with_strobe(
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0,
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initializing_period + Δ_switch,
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int((initializing_period + Δ_switch) / dt),
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Δ,
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),
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np.linspace(initializing_period, initializing_period + τ_off, 10),
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]
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),
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)
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model = QubitModelMutliBath(
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δ=δ,
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ω_c=[ω_c, ω_c],
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ω_s=[ω_0 - Δ - ω_c + detune, ω_0 + Δ - ω_c + detune],
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t=ut.linspace_with_strobe(0, t_max, int(t_max / dt), Δ),
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t=np.unique(np.concatenate(ts)),
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ψ_0=(
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np.sqrt(1 / (np.exp(ω_0 / T_h) + 1)) * qt.basis([2], [0])
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+ np.sqrt(1 / (np.exp(-ω_0 / T_h) + 1)) * qt.basis([2], [1])
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@ -202,25 +233,24 @@ Init ray and silence stocproc.
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(τ_mod, τ_c, τ_bath, cycles, model.ω_s, ω_0, τ_s, τ_off, n, Δ_switch, τ_init),
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) = anti_zeno_engine(
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Δ=11,
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ε=.05,#.1,
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ω_c=1,
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ε=.5,#.1,
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ω_c=2,
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ε_couple=0.7,
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n=8,
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n=0 ,
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detune=.5,
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ω_0=20,
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T_c=1e3,
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T_h=1e4,
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δ=[3.2, 1],
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δ=[3.2*.01, 1*.01],
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γ=.2,
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switch_cycles=1,
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therm_initial_state=False,
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s=[1] * 2,
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ε_init=0.1,
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terms=6,
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therm_initial_state=True,
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ε_init=.1,
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terms=4,
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dt=0.01,
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sp_tol=1e-2,
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)
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model.k_max = 4
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model.k_max = 3
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# model, params = anti_zeno_engine(ε=1/2, ε_couple=1e-4, n=1, detune=.5, δ=[.1,.1])
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fs.tex_value(
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@ -257,7 +287,7 @@ Init ray and silence stocproc.
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#+end_src
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#+RESULTS:
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| \(α(0)=1.6\) | \(ω_0=20\) | \(γ=0.5\) | \(Δ=11\) | \(T_c=1000\) | \(T_h=10000\) |
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| \(α(0)=0.0\) | \(ω_0=20\) | \(γ=0.5\) | \(Δ=11\) | \(T_c=1000\) | \(T_h=10000\) |
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Let's test the assumptions of the paper.
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@ -266,7 +296,7 @@ Let's test the assumptions of the paper.
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#+end_src
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#+RESULTS:
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: 9
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: 5
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** BCFs and Modulations
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#+begin_src jupyter-python :tangle nil
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@ -274,7 +304,7 @@ Let's test the assumptions of the paper.
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return model.bcf(1)(t) + 2 * (model.thermal_correlations(1)(t).real)
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plt.clf()
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plt.gcf().set_size_inches(fs.get_figsize("poster", 0.49))
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plt.plot(model.t, np.abs(thermal_bcf(model.t))/np.abs(thermal_bcf(0)), alpha=.5, zorder=5, label="BCF (cold bath)")
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#plt.plot(model.t, np.abs(thermal_bcf(model.t))/np.abs(thermal_bcf(0)), alpha=.5, zorder=5, label="BCF (cold bath)")
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#plt.plot(model.t, abs(model.bcf(0)(model.t)) / abs(model.bcf(0)(model.t)).max(), linewidth=1)
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plt.plot(model.t, model.L[0].operator_norm(model.t), linewidth=1, label=r"$||L||$")
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plt.plot(model.t, (model.H.operator_norm(model.t) - ω_0/2)/ω_0, linewidth=.5, label=r"$||H_{\mathrm{S}}||$")
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@ -286,47 +316,8 @@ Let's test the assumptions of the paper.
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#+RESULTS:
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:RESULTS:
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# [goto error]
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#+begin_example
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[0;31m---------------------------------------------------------------------------[0m
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[0;31mKeyboardInterrupt[0m Traceback (most recent call last)
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Input [0;32mIn [24][0m, in [0;36m<cell line: 5>[0;34m()[0m
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[1;32m 3[0m plt[38;5;241m.[39mclf()
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[1;32m 4[0m plt[38;5;241m.[39mgcf()[38;5;241m.[39mset_size_inches(fs[38;5;241m.[39mget_figsize([38;5;124m"[39m[38;5;124mposter[39m[38;5;124m"[39m, [38;5;241m0.49[39m))
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[0;32m----> 5[0m plt[38;5;241m.[39mplot(model[38;5;241m.[39mt, np[38;5;241m.[39mabs([43mthermal_bcf[49m[43m([49m[43mmodel[49m[38;5;241;43m.[39;49m[43mt[49m[43m)[49m)[38;5;241m/[39mnp[38;5;241m.[39mabs(thermal_bcf([38;5;241m0[39m)), alpha[38;5;241m=[39m[38;5;241m.5[39m, zorder[38;5;241m=[39m[38;5;241m5[39m, label[38;5;241m=[39m[38;5;124m"[39m[38;5;124mBCF (cold bath)[39m[38;5;124m"[39m)
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[1;32m 6[0m [38;5;66;03m#plt.plot(model.t, abs(model.bcf(0)(model.t)) / abs(model.bcf(0)(model.t)).max(), linewidth=1)[39;00m
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[1;32m 7[0m plt[38;5;241m.[39mplot(model[38;5;241m.[39mt, model[38;5;241m.[39mL[[38;5;241m0[39m][38;5;241m.[39moperator_norm(model[38;5;241m.[39mt), linewidth[38;5;241m=[39m[38;5;241m1[39m, label[38;5;241m=[39m[38;5;124mr[39m[38;5;124m"[39m[38;5;124m$||L||$[39m[38;5;124m"[39m)
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Input [0;32mIn [24][0m, in [0;36mthermal_bcf[0;34m(t)[0m
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[1;32m 1[0m [38;5;28;01mdef[39;00m [38;5;21mthermal_bcf[39m(t):
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[0;32m----> 2[0m [38;5;28;01mreturn[39;00m model[38;5;241m.[39mbcf([38;5;241m1[39m)(t) [38;5;241m+[39m [38;5;241m2[39m [38;5;241m*[39m ([43mmodel[49m[38;5;241;43m.[39;49m[43mthermal_correlations[49m[43m([49m[38;5;241;43m1[39;49m[43m)[49m[43m([49m[43mt[49m[43m)[49m[38;5;241m.[39mreal)
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File [0;32m~/src/hops/hops/util/bcf.py:368[0m, in [0;36mOhmic_StochasticPotentialCorrelations.__call__[0;34m(self, tau)[0m
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[1;32m 366[0m tau_flat [38;5;241m=[39m tau[38;5;241m.[39mflat
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[1;32m 367[0m [38;5;28;01mfor[39;00m i, ti [38;5;129;01min[39;00m [38;5;28menumerate[39m(tau_flat):
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[0;32m--> 368[0m res_flat[i] [38;5;241m=[39m [38;5;28mself[39m[38;5;241m.[39m_c [38;5;241m*[39m [43mzeta_func[49m[43m([49m[43m [49m[38;5;66;43;03m# type: ignore[39;49;00m
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[1;32m 369[0m [43m [49m[38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43ms_p1[49m[43m,[49m
|
||||
[1;32m 370[0m [43m [49m[43m([49m[38;5;241;43m1[39;49m[43m [49m[38;5;241;43m+[39;49m[43m [49m[38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43m_beta_w_c[49m[43m [49m[38;5;241;43m+[39;49m[43m [49m[38;5;241;43m1[39;49m[43mj[49m[43m [49m[38;5;241;43m*[39;49m[43m [49m[38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43mw_c[49m[43m [49m[38;5;241;43m*[39;49m[43m [49m[43mti[49m[43m)[49m[43m [49m[38;5;241;43m/[39;49m[43m [49m[38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43m_beta_w_c[49m[43m,[49m
|
||||
[1;32m 371[0m [43m [49m[38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43m_expshift[49m[43m,[49m
|
||||
[1;32m 372[0m [43m [49m[43m)[49m
|
||||
[1;32m 373[0m [38;5;28;01mreturn[39;00m res [38;5;241m*[39m shift_fac
|
||||
[1;32m 374[0m [38;5;28;01melse[39;00m:
|
||||
|
||||
File [0;32m~/src/hops/hops/util/bcf.py:18[0m, in [0;36mzeta_func[0;34m(s, a, shift)[0m
|
||||
[1;32m 16[0m [38;5;129m@lru_cache[39m(maxsize[38;5;241m=[39m[38;5;241m10000[39m)
|
||||
[1;32m 17[0m [38;5;28;01mdef[39;00m [38;5;21mzeta_func[39m(s, a, shift[38;5;241m=[39m[38;5;241m1[39m):
|
||||
[0;32m---> 18[0m [38;5;28;01mreturn[39;00m [43mlerch_phi[49m[43m([49m[43mshift[49m[43m,[49m[43m [49m[43ms[49m[43m,[49m[43m [49m[43ma[49m[43m)[49m
|
||||
|
||||
File [0;32m~/src/hops/hops/util/zeta_function.py:35[0m, in [0;36m_arb_lerch_phi[0;34m(z, s, a)[0m
|
||||
[1;32m 32[0m args [38;5;241m=[39m [_complex_double[38;5;241m.[39mfrom_complex([38;5;28mcomplex[39m(arg)) [38;5;28;01mfor[39;00m arg [38;5;129;01min[39;00m (z, s, a)]
|
||||
[1;32m 33[0m cy [38;5;241m=[39m _complex_double()
|
||||
[0;32m---> 35[0m [38;5;28;01mif[39;00m [43m_arb_c_lerch_phi[49m[43m([49m[43mctypes[49m[38;5;241;43m.[39;49m[43mbyref[49m[43m([49m[43mcy[49m[43m)[49m[43m,[49m[43m [49m[38;5;241;43m*[39;49m[43margs[49m[43m,[49m[43m [49m[38;5;241;43m0[39;49m[43m)[49m:
|
||||
[1;32m 36[0m [38;5;28;01mraise[39;00m [38;5;167;01mValueError[39;00m([38;5;124mf[39m[38;5;124m"[39m[38;5;124munable to evaluate function accurately at [39m[38;5;132;01m{[39;00mz,s,a[38;5;132;01m}[39;00m[38;5;124m"[39m)
|
||||
[1;32m 38[0m [38;5;28;01mreturn[39;00m [38;5;28mcomplex[39m(cy)
|
||||
|
||||
[0;31mKeyboardInterrupt[0m:
|
||||
#+end_example
|
||||
: <Figure size 467.245x288.773 with 0 Axes>
|
||||
: <matplotlib.legend.Legend at 0x7f8cad7d3c70>
|
||||
[[file:./.ob-jupyter/52319af8927d7fbb9f93dd71384478ec06ef6faf.svg]]
|
||||
:END:
|
||||
|
||||
#+begin_src jupyter-python :tangle nil
|
||||
|
|
@ -378,8 +369,8 @@ Let's test the assumptions of the paper.
|
|||
|
||||
#+RESULTS:
|
||||
:RESULTS:
|
||||
[[file:./.ob-jupyter/883fc0e7a11b2b217146d85efa2efa97c0241e6f.svg]]
|
||||
[[file:./.ob-jupyter/dde9d6a8f8078acc424ec172395bcf5662433dc9.svg]]
|
||||
[[file:./.ob-jupyter/0e7e96064672b6bc919ca89d52825c59e9543cfb.svg]]
|
||||
[[file:./.ob-jupyter/00d9a4ef93705497b6722f5e6ab91c0542aea18e.svg]]
|
||||
:END:
|
||||
|
||||
#+begin_src jupyter-python
|
||||
|
|
@ -391,8 +382,8 @@ Let's test the assumptions of the paper.
|
|||
#+RESULTS:
|
||||
:RESULTS:
|
||||
| <Figure | size | 432x288 | with | 1 | Axes> | <AxesSubplot:> |
|
||||
[[file:./.ob-jupyter/533ffeef663f158f1eb3ebccbf211ec3a6ff45b2.svg]]
|
||||
[[file:./.ob-jupyter/b9dca795dc334e8536ef2fdc9e04e574651ae7f7.svg]]
|
||||
[[file:./.ob-jupyter/fb29a999f1e1de740de4032f57ab31d19c605398.svg]]
|
||||
[[file:./.ob-jupyter/6bf5c5d63ea0269db05193940e43ce7493b3258d.svg]]
|
||||
:END:
|
||||
|
||||
#+begin_src jupyter-python
|
||||
|
|
@ -407,7 +398,7 @@ Let's test the assumptions of the paper.
|
|||
#+RESULTS:
|
||||
:RESULTS:
|
||||
| <Figure | size | 432x288 | with | 1 | Axes> | <AxesSubplot:> |
|
||||
[[file:./.ob-jupyter/e12e1e2c5d3423239792faa5cf30cded921e5f45.svg]]
|
||||
[[file:./.ob-jupyter/97998d422bd247943fb1c04d060ee2c05aa65a3b.svg]]
|
||||
:END:
|
||||
|
||||
|
||||
|
|
@ -433,45 +424,99 @@ Let's test the assumptions of the paper.
|
|||
|
||||
** Integration
|
||||
#+begin_src jupyter-python
|
||||
aux.integrate(model, 10)
|
||||
#+end_src
|
||||
aux.integrate(model, 100)
|
||||
#+End_src
|
||||
|
||||
#+RESULTS:
|
||||
:RESULTS:
|
||||
#+begin_example
|
||||
[INFO hops.core.integration 92605] Choosing the nonlinear integrator.
|
||||
[INFO hops.core.integration 92605] Using 9 integrators.
|
||||
[INFO hops.core.integration 92605] Some 10 trajectories have to be integrated.
|
||||
[INFO hops.core.integration 92605] Using 1820 hierarchy states.
|
||||
0% 0/10 [00:00<?, ?it/s][2m[36m(integration_task pid=578795, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=578794, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=578791, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=578796, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=578792, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=578793, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=578797, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=578798, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[INFO hops.core.signal_delay 92605] caught sig 'SIGINT'
|
||||
[INFO hops.core.signal_delay 92605] caught sig 'SIGINT'
|
||||
10% 1/10 [06:48<1:01:14, 408.33s/it]
|
||||
2022-07-19 16:25:10,818 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 92605] caught 2 signal(s)
|
||||
[INFO hops.core.signal_delay 92605] emit signal 'SIGINT'
|
||||
2022-07-19 16:25:10,847 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.
|
||||
2022-07-19 16:25:11,007 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.
|
||||
2022-07-19 16:25:11,013 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.
|
||||
2022-07-19 16:25:11,030 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.
|
||||
2022-07-19 16:25:11,082 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.
|
||||
2022-07-19 16:25:11,095 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.
|
||||
2022-07-19 16:25:11,121 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.
|
||||
2022-07-19 16:25:11,149 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.integration 241007] Choosing the nonlinear integrator.
|
||||
[INFO hops.core.integration 241007] Using 21 integrators.
|
||||
[INFO hops.core.integration 241007] Some 90 trajectories have to be integrated.
|
||||
[INFO hops.core.integration 241007] Using 165 hierarchy states.
|
||||
0% 0/90 [00:00<?, ?it/s][2m[36m(integration_task pid=21822, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=21823, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=21825, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=21820, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=21821, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=21824, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=591114, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=591119, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=591116, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=591120, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(integration_task pid=591121, ip=141.30.17.16)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[33m(raylet)[0m [2022-07-20 09:31:08,789 C 92539 92539] (raylet) node_manager.cc:170: This node has beem marked as dead.
|
||||
[2m[33m(raylet)[0m *** StackTrace Information ***
|
||||
[2m[33m(raylet)[0m ray::SpdLogMessage::Flush()
|
||||
[2m[33m(raylet)[0m ray::RayLog::~RayLog()
|
||||
[2m[33m(raylet)[0m std::_Function_handler<>::_M_invoke()
|
||||
[2m[33m(raylet)[0m std::_Function_handler<>::_M_invoke()
|
||||
[2m[33m(raylet)[0m std::_Function_handler<>::_M_invoke()
|
||||
[2m[33m(raylet)[0m ray::rpc::ClientCallImpl<>::OnReplyReceived()
|
||||
[2m[33m(raylet)[0m std::_Function_handler<>::_M_invoke()
|
||||
[2m[33m(raylet)[0m EventTracker::RecordExecution()
|
||||
[2m[33m(raylet)[0m std::_Function_handler<>::_M_invoke()
|
||||
[2m[33m(raylet)[0m boost::asio::detail::completion_handler<>::do_complete()
|
||||
[2m[33m(raylet)[0m boost::asio::detail::scheduler::do_run_one()
|
||||
[2m[33m(raylet)[0m boost::asio::detail::scheduler::run()
|
||||
[2m[33m(raylet)[0m boost::asio::io_context::run()
|
||||
[2m[33m(raylet)[0m main
|
||||
[2m[33m(raylet)[0m __libc_start_call_main
|
||||
[2m[33m(raylet)[0m
|
||||
[2m[33m(raylet)[0m [2022-07-13 10:41:27,801 C 578762 578762] (raylet) node_manager.cc:170: This node has beem marked as dead.
|
||||
[2m[33m(raylet)[0m *** StackTrace Information ***
|
||||
[2m[33m(raylet)[0m ray::SpdLogMessage::Flush()
|
||||
[2m[33m(raylet)[0m ray::RayLog::~RayLog()
|
||||
[2m[33m(raylet)[0m std::_Function_handler<>::_M_invoke()
|
||||
[2m[33m(raylet)[0m std::_Function_handler<>::_M_invoke()
|
||||
[2m[33m(raylet)[0m std::_Function_handler<>::_M_invoke()
|
||||
[2m[33m(raylet)[0m ray::rpc::ClientCallImpl<>::OnReplyReceived()
|
||||
[2m[33m(raylet)[0m std::_Function_handler<>::_M_invoke()
|
||||
[2m[33m(raylet)[0m EventTracker::RecordExecution()
|
||||
[2m[33m(raylet)[0m std::_Function_handler<>::_M_invoke()
|
||||
[2m[33m(raylet)[0m boost::asio::detail::completion_handler<>::do_complete()
|
||||
[2m[33m(raylet)[0m boost::asio::detail::scheduler::do_run_one()
|
||||
[2m[33m(raylet)[0m boost::asio::detail::scheduler::run()
|
||||
[2m[33m(raylet)[0m boost::asio::io_context::run()
|
||||
[2m[33m(raylet)[0m main
|
||||
[2m[33m(raylet)[0m __libc_start_call_main
|
||||
[2m[33m(raylet)[0m
|
||||
[2m[33m(raylet)[0m [2022-07-20 10:41:29,167 E 122306 122344] (raylet) agent_manager.cc:107: The raylet exited immediately because the Ray agent failed. The raylet fate shares with the agent. This can happen because the Ray agent was unexpectedly killed or failed. See `dashboard_agent.log` for the root cause.
|
||||
20% 18/90 [01:56<07:45, 6.47s/it][INFO hops.core.signal_delay 241007] caught sig 'SIGINT'
|
||||
21% 19/90 [01:59<07:26, 6.29s/it]
|
||||
2022-07-20 15:03:10,268 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.
|
||||
2022-07-20 15:03:10,271 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.
|
||||
2022-07-20 15:03:10,273 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.
|
||||
2022-07-20 15:03:10,277 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.
|
||||
2022-07-20 15:03:10,278 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.
|
||||
2022-07-20 15:03:10,281 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.
|
||||
2022-07-20 15:03:10,285 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 241007] caught 1 signal(s)
|
||||
2022-07-20 15:03:10,286 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 241007] emit signal 'SIGINT'
|
||||
2022-07-20 15:03:10,288 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.
|
||||
2022-07-20 15:03:10,289 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.
|
||||
2022-07-20 15:03:10,291 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.
|
||||
2022-07-20 15:03:10,292 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.
|
||||
2022-07-20 15:03:10,293 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.
|
||||
2022-07-20 15:03:10,343 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.
|
||||
2022-07-20 15:03:10,365 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.
|
||||
2022-07-20 15:03:10,412 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.
|
||||
2022-07-20 15:03:10,435 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.
|
||||
2022-07-20 15:03:10,468 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.
|
||||
2022-07-20 15:03:10,475 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.
|
||||
2022-07-20 15:03:10,513 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.
|
||||
2022-07-20 15:03:10,521 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.
|
||||
2022-07-20 15:03:10,539 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.
|
||||
2022-07-20 15:03:10,577 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.
|
||||
2022-07-20 15:03:10,583 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.
|
||||
#+end_example
|
||||
# [goto error]
|
||||
#+begin_example
|
||||
[0;31m---------------------------------------------------------------------------[0m
|
||||
[0;31mKeyboardInterrupt[0m Traceback (most recent call last)
|
||||
Input [0;32mIn [10][0m, in [0;36m<cell line: 1>[0;34m()[0m
|
||||
[0;32m----> 1[0m [43maux[49m[38;5;241;43m.[39;49m[43mintegrate[49m[43m([49m[43mmodel[49m[43m,[49m[43m [49m[38;5;241;43m10[39;49m[43m)[49m
|
||||
Input [0;32mIn [18][0m, in [0;36m<cell line: 1>[0;34m()[0m
|
||||
[0;32m----> 1[0m [43maux[49m[38;5;241;43m.[39;49m[43mintegrate[49m[43m([49m[43mmodel[49m[43m,[49m[43m [49m[38;5;241;43m100[39;49m[43m)[49m
|
||||
|
||||
File [0;32m~/src/two_qubit_model/hiro_models/model_auxiliary.py:108[0m, in [0;36mintegrate[0;34m(model, n, data_path, clear_pd)[0m
|
||||
[1;32m 98[0m [38;5;66;03m# with model_db(data_path) as db:[39;00m
|
||||
|
|
@ -520,18 +565,35 @@ Let's test the assumptions of the paper.
|
|||
:END:
|
||||
|
||||
|
||||
#+begin_src jupyter-python
|
||||
#+Begin_src jupyter-python
|
||||
#_, ax = fs.plot_energy_overview(model, markersize=1, ensemble_args=dict(gc_sleep=0.05))
|
||||
|
||||
fig, ax = plt.subplots()
|
||||
with aux.get_data(model) as data:
|
||||
fs.plot_with_σ(model.t, model.total_power(data), ax=ax)
|
||||
fs.plot_with_σ(model.t, model.total_energy_from_power(data), ax=ax)
|
||||
|
||||
#ax.legend()
|
||||
#+end_src
|
||||
|
||||
#+RESULTS:
|
||||
[[file:./.ob-jupyter/2c9eb35e738a2d2f38342499314d16e9df3b49f9.svg]]
|
||||
:RESULTS:
|
||||
#+begin_example
|
||||
Loading: 90% 9/10 [00:00<00:00, 138.66it/s]
|
||||
[2m[36m(_ensemble_remote_function pid=22270, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(_ensemble_remote_function pid=22267, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(_ensemble_remote_function pid=22265, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(_ensemble_remote_function pid=22268, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(_ensemble_remote_function pid=22264, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(_ensemble_remote_function pid=22266, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(_ensemble_remote_function pid=22271, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[2m[36m(_ensemble_remote_function pid=22269, ip=141.30.17.8)[0m WARNING:root:Using mpmath for the zeta (lerch phi) function. Install a recent version of ``arb`` for more performance.
|
||||
[INFO root 241007] Writing cache to: results/interaction_power_67cca8aef6bb8d5c44cd03d2e435820ea5a6ad6df4c336139cd691b49fb51540_interaction_energy_task_29_None_1132783dc3e4b63333ab34011167d84b9c35e6e83409bc4c77ac7f48df69c157.npy
|
||||
Loading: 80% 4/5 [00:00<00:00, 171.20it/s]
|
||||
[INFO root 241007] Writing cache to: results/f8ad5eb5a8a6d9fb98ca17682691e53506757d7244d54c67c53f9f3314c68a05_67cca8aef6bb8d5c44cd03d2e435820ea5a6ad6df4c336139cd691b49fb51540_op_exp_task_29_None_8eaaa0856f1a481703397da647054bbc3035c456b4fe49fb302a4fb76fa7c865.npy
|
||||
#+end_example
|
||||
[[file:./.ob-jupyter/b3e65afd3656a3af59f525458b4df39d5222d518.svg]]
|
||||
:END:
|
||||
|
||||
- **too fast decoupling kills it**
|
||||
- no anti-zeno effects without detuning?
|
||||
|
|
@ -557,7 +619,7 @@ Let's test the assumptions of the paper.
|
|||
#+end_src
|
||||
|
||||
#+RESULTS:
|
||||
[[file:./.ob-jupyter/5edda2f8ea9ded1d8b676b5d786955e13cc4e74c.svg]]
|
||||
[[file:./.ob-jupyter/be0e2c3ba2a64e4022395469cd31f4dc5d5e37f2.svg]]
|
||||
|
||||
- no steady state ... but we have to average...
|
||||
|
||||
|
|
@ -569,8 +631,8 @@ Let's test the assumptions of the paper.
|
|||
|
||||
#+RESULTS:
|
||||
:RESULTS:
|
||||
| <matplotlib.lines.Line2D | at | 0x7fedc6bda3a0> |
|
||||
[[file:./.ob-jupyter/f6b3798eb5c85d096cb217d7503c921359257c76.svg]]
|
||||
| <matplotlib.lines.Line2D | at | 0x7fd544382d90> |
|
||||
[[file:./.ob-jupyter/8c2b46e2adbdadab36d7fdf6bc2d97f63c2217b3.svg]]
|
||||
:END:
|
||||
|
||||
** TODO Power and Efficiency
|
||||
|
|
@ -606,34 +668,10 @@ We need the time points where we sample the total energy.
|
|||
# #plt.plot(model.t, model.L[0].operator_norm(model.t))
|
||||
|
||||
with aux.get_data(model) as data:
|
||||
tot_e = (model.total_energy_from_power(data)) #model.total_energy(data).value
|
||||
tot_power = (model.total_power(data)) #model.total_energy(data).value
|
||||
#+end_src
|
||||
|
||||
#+RESULTS:
|
||||
:RESULTS:
|
||||
# [goto error]
|
||||
#+begin_example
|
||||
[0;31m---------------------------------------------------------------------------[0m
|
||||
[0;31mRuntimeError[0m Traceback (most recent call last)
|
||||
Input [0;32mIn [170][0m, in [0;36m<cell line: 10>[0;34m()[0m
|
||||
[1;32m 6[0m ts_end [38;5;241m=[39m model[38;5;241m.[39mt[ind_end]
|
||||
[1;32m 8[0m [38;5;66;03m# #plt.plot(model.t, model.L[0].operator_norm(model.t))[39;00m
|
||||
[0;32m---> 10[0m [38;5;28;01mwith[39;00m [43maux[49m[38;5;241;43m.[39;49m[43mget_data[49m[43m([49m[43mmodel[49m[43m)[49m [38;5;28;01mas[39;00m data:
|
||||
[1;32m 11[0m tot_e [38;5;241m=[39m (model[38;5;241m.[39mtotal_energy_from_power(data))
|
||||
|
||||
File [0;32m~/src/two_qubit_model/hiro_models/model_auxiliary.py:146[0m, in [0;36mget_data[0;34m(model, data_path, read_only, **kwargs)[0m
|
||||
[1;32m 135[0m [38;5;28;01mreturn[39;00m HIData(
|
||||
[1;32m 136[0m path,
|
||||
[1;32m 137[0m hi_key[38;5;241m=[39mmodel[38;5;241m.[39mhops_config,
|
||||
[0;32m (...)[0m
|
||||
[1;32m 142[0m [38;5;241m*[39m[38;5;241m*[39mkwargs,
|
||||
[1;32m 143[0m )
|
||||
[1;32m 145[0m [38;5;28;01melse[39;00m:
|
||||
[0;32m--> 146[0m [38;5;28;01mraise[39;00m [38;5;167;01mRuntimeError[39;00m([38;5;124mf[39m[38;5;124m"[39m[38;5;124mNo data found for model with hash [39m[38;5;124m'[39m[38;5;132;01m{[39;00mhexhash[38;5;132;01m}[39;00m[38;5;124m'[39m[38;5;124m.[39m[38;5;124m"[39m)
|
||||
|
||||
[0;31mRuntimeError[0m: No data found for model with hash '59011e9f7180d914d68f21cdd8930f5b6c73a161eb03df9d4210b159b9d38ebe'.
|
||||
#+end_example
|
||||
:END:
|
||||
|
||||
|
||||
#+begin_src jupyter-python
|
||||
|
|
@ -647,18 +685,17 @@ We need the time points where we sample the total energy.
|
|||
plt.axvline(t, linestyle="dotted", color="lightblue", linewidth=1)
|
||||
|
||||
fs.plot_with_σ(
|
||||
model.t[ind_begin[0] ::10], tot_e.slice(ind_begin[0], None, 10), ax=ax, linewidth=0.5
|
||||
model.t[ind_begin[0] ::10], tot_power.slice(ind_begin[0], None, 10), ax=ax, linewidth=0.5
|
||||
)
|
||||
ax.plot(
|
||||
model.t[ind_begin[0] ::10],
|
||||
ut.smoothen(model.t[ind_begin[0] :], tot_e.value[ind_begin[0] :], frac=0.1)[::10],
|
||||
ut.smoothen(model.t[ind_begin[0] :], tot_power.value[ind_begin[0] :], frac=0.1)[::10],
|
||||
)
|
||||
|
||||
powers = []
|
||||
for begin, end in zip(ind_begin, ind_end):
|
||||
powers.append(
|
||||
(tot_e.slice(end, end+1) - tot_e.slice(begin, begin+1))
|
||||
,* (1 / (model.t[ind_end[0]] - model.t[ind_begin[0]]))
|
||||
(tot_power.slice(begin, end)).mean
|
||||
)
|
||||
|
||||
power = sum(powers) * (1/(len(powers)))
|
||||
|
|
@ -669,8 +706,8 @@ We need the time points where we sample the total energy.
|
|||
|
||||
#fs.export_fig("anti_zeno_with_cool")
|
||||
fs.tex_value(
|
||||
(power.value[0]),
|
||||
err=power.σ[0],
|
||||
(power.value),
|
||||
err=power.σ,
|
||||
prefix="P=",
|
||||
save="power_with_cool",
|
||||
)
|
||||
|
|
@ -678,8 +715,8 @@ We need the time points where we sample the total energy.
|
|||
|
||||
#+RESULTS:
|
||||
:RESULTS:
|
||||
: \(P=-0.050\pm 0.012\)
|
||||
[[file:./.ob-jupyter/09324320b4eae0a79669ed696f40eaec8adfb93a.svg]]
|
||||
: \(P=-0.12\pm 0.05\)
|
||||
[[file:./.ob-jupyter/ee342b28ea9884126abbf873ede39644af783db9.svg]]
|
||||
:END:
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -2,11 +2,11 @@
|
|||
"nodes": {
|
||||
"flake-utils": {
|
||||
"locked": {
|
||||
"lastModified": 1656065134,
|
||||
"narHash": "sha256-oc6E6ByIw3oJaIyc67maaFcnjYOz1mMcOtHxbEf9NwQ=",
|
||||
"lastModified": 1656928814,
|
||||
"narHash": "sha256-RIFfgBuKz6Hp89yRr7+NR5tzIAbn52h8vT6vXkYjZoM=",
|
||||
"owner": "numtide",
|
||||
"repo": "flake-utils",
|
||||
"rev": "bee6a7250dd1b01844a2de7e02e4df7d8a0a206c",
|
||||
"rev": "7e2a3b3dfd9af950a856d66b0a7d01e3c18aa249",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
|
|
@ -17,11 +17,11 @@
|
|||
},
|
||||
"flake-utils_2": {
|
||||
"locked": {
|
||||
"lastModified": 1656065134,
|
||||
"narHash": "sha256-oc6E6ByIw3oJaIyc67maaFcnjYOz1mMcOtHxbEf9NwQ=",
|
||||
"lastModified": 1656928814,
|
||||
"narHash": "sha256-RIFfgBuKz6Hp89yRr7+NR5tzIAbn52h8vT6vXkYjZoM=",
|
||||
"owner": "numtide",
|
||||
"repo": "flake-utils",
|
||||
"rev": "bee6a7250dd1b01844a2de7e02e4df7d8a0a206c",
|
||||
"rev": "7e2a3b3dfd9af950a856d66b0a7d01e3c18aa249",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
|
|
@ -32,11 +32,11 @@
|
|||
},
|
||||
"nixpkgs": {
|
||||
"locked": {
|
||||
"lastModified": 1656239181,
|
||||
"narHash": "sha256-wW1xRFBn376yGloXZ4QzBE4hjipMawpV18Lshd9QSPw=",
|
||||
"lastModified": 1658161305,
|
||||
"narHash": "sha256-X/nhnMCa1Wx4YapsspyAs6QYz6T/85FofrI6NpdPDHg=",
|
||||
"owner": "NixOS",
|
||||
"repo": "nixpkgs",
|
||||
"rev": "f2537a505d45c31fe5d9c27ea9829b6f4c4e6ac5",
|
||||
"rev": "e4d49de45a3b5dbcb881656b4e3986e666141ea9",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
|
|
@ -47,26 +47,11 @@
|
|||
},
|
||||
"nixpkgs_2": {
|
||||
"locked": {
|
||||
"lastModified": 1656239181,
|
||||
"narHash": "sha256-wW1xRFBn376yGloXZ4QzBE4hjipMawpV18Lshd9QSPw=",
|
||||
"lastModified": 1658311025,
|
||||
"narHash": "sha256-GqagY5YmaZB3YaO41kKcQhe5RcpS83wnsW8iCu5Znqo=",
|
||||
"owner": "NixOS",
|
||||
"repo": "nixpkgs",
|
||||
"rev": "f2537a505d45c31fe5d9c27ea9829b6f4c4e6ac5",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
"id": "nixpkgs",
|
||||
"ref": "nixos-unstable",
|
||||
"type": "indirect"
|
||||
}
|
||||
},
|
||||
"nixpkgs_3": {
|
||||
"locked": {
|
||||
"lastModified": 1656492412,
|
||||
"narHash": "sha256-CdTRqPFyE/t/nRfnfN3fxm+OOKjeJdaDbXm7E7k+Fxc=",
|
||||
"owner": "NixOS",
|
||||
"repo": "nixpkgs",
|
||||
"rev": "72f17cca89ec773e5845f5fa1bffcf0b7a4e2094",
|
||||
"rev": "cd8d1784506a7c7eb0796772b73437e0b82fad57",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
|
|
@ -78,14 +63,14 @@
|
|||
"poetry2nix": {
|
||||
"inputs": {
|
||||
"flake-utils": "flake-utils_2",
|
||||
"nixpkgs": "nixpkgs_3"
|
||||
"nixpkgs": "nixpkgs_2"
|
||||
},
|
||||
"locked": {
|
||||
"lastModified": 1656405165,
|
||||
"narHash": "sha256-p2c9QAnKsiUu0a3iHAkpHkO9jAkMWCbG1HCU7/TrYc0=",
|
||||
"lastModified": 1657626303,
|
||||
"narHash": "sha256-O/JJ0hSBCmlx0oP8QGAlRrWn0BvlC5cj7/EZ0CCWHTU=",
|
||||
"owner": "nix-community",
|
||||
"repo": "poetry2nix",
|
||||
"rev": "abc47c71a4920e654e7b2e4261e3e6399bbe2be6",
|
||||
"rev": "920ba682377d5c0d87945c5eb6141ab8447ca509",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
|
|
@ -103,15 +88,17 @@
|
|||
"utils": {
|
||||
"inputs": {
|
||||
"flake-utils": "flake-utils",
|
||||
"nixpkgs": "nixpkgs_2",
|
||||
"nixpkgs": [
|
||||
"nixpkgs"
|
||||
],
|
||||
"poetry2nix": "poetry2nix"
|
||||
},
|
||||
"locked": {
|
||||
"lastModified": 1656499586,
|
||||
"narHash": "sha256-tx99W8VI8xxsnPRK0zZs5V2xFo5/hfhxhrTxCQi/mQ8=",
|
||||
"lastModified": 1658314126,
|
||||
"narHash": "sha256-rEoZSb8bBafEd6m3xu/yQtSFlP8GZxKN15YqMZkeMaQ=",
|
||||
"owner": "vale981",
|
||||
"repo": "hiro-flake-utils",
|
||||
"rev": "3c96df6681a2475d131a5f30e7cb02c223b7c567",
|
||||
"rev": "316cd25ffd9d7afd331cbbc1429f62f30567e288",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
|
|
|
|||
|
|
@ -4,39 +4,15 @@
|
|||
inputs = {
|
||||
nixpkgs.url = "nixpkgs/nixos-unstable";
|
||||
utils.url = "github:vale981/hiro-flake-utils";
|
||||
utils.inputs.nixpkgs.follows = "nixpkgs";
|
||||
};
|
||||
|
||||
outputs = { self, utils, nixpkgs, ... }:
|
||||
(utils.lib.poetry2nixWrapper nixpkgs {
|
||||
name = "10_antizeno_engine";
|
||||
extraOverlay = (self: super: {
|
||||
flint = super.flint.overrideAttrs (old: rec {
|
||||
pname = "flint";
|
||||
version = "39ac8817a18710effd96dff38770f4d1c80ad608";
|
||||
doCheck = false;
|
||||
src = super.pkgs.fetchFromGitHub {
|
||||
owner = "wbhart";
|
||||
repo = "flint2";
|
||||
rev = version;
|
||||
sha256 = "sha256-UIdKUT2oSNth6AHHRPZOTLR7gHnxgmxKWdOR4klPPLw=";
|
||||
};
|
||||
});
|
||||
|
||||
arb = super.arb.overrideAttrs (old: rec {
|
||||
pname = "arb-git";
|
||||
version = "4e879e5602a59c14780085900236c9fa141f993d";
|
||||
doCheck = false;
|
||||
src = super.pkgs.fetchFromGitHub {
|
||||
owner = "fredrik-johansson";
|
||||
repo = "arb";
|
||||
rev = version;
|
||||
sha256 = "sha256-JoBZZk824+O5kVctdUv0qzlX9l3X2RWr5/NPedx50oQ=";
|
||||
};
|
||||
});
|
||||
});
|
||||
shellPackages = (pkgs:
|
||||
(with pkgs;
|
||||
[ pyright python39Packages.jupyter sshfs arb]));
|
||||
[ pyright python39Packages.jupyter sshfs]));
|
||||
|
||||
python = pkgs: pkgs.python39Full;
|
||||
shellOverride = (pkgs: oldAttrs: {
|
||||
|
|
|
|||
481
python/energy_flow_proper/10_antizeno_engine/poetry.lock
generated
481
python/energy_flow_proper/10_antizeno_engine/poetry.lock
generated
|
|
@ -198,7 +198,7 @@ python-versions = ">=3.6"
|
|||
|
||||
[[package]]
|
||||
name = "cffi"
|
||||
version = "1.15.1"
|
||||
version = "1.15.0"
|
||||
description = "Foreign Function Interface for Python calling C code."
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -209,11 +209,11 @@ pycparser = "*"
|
|||
|
||||
[[package]]
|
||||
name = "charset-normalizer"
|
||||
version = "2.1.0"
|
||||
version = "2.0.12"
|
||||
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6.0"
|
||||
python-versions = ">=3.5.0"
|
||||
|
||||
[package.extras]
|
||||
unicode_backport = ["unicodedata2"]
|
||||
|
|
@ -280,7 +280,7 @@ python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
|
|||
|
||||
[[package]]
|
||||
name = "debugpy"
|
||||
version = "1.6.2"
|
||||
version = "1.6.0"
|
||||
description = "An implementation of the Debug Adapter Protocol for Python"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -304,7 +304,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
|||
|
||||
[[package]]
|
||||
name = "distlib"
|
||||
version = "0.3.5"
|
||||
version = "0.3.4"
|
||||
description = "Distribution utilities"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -328,7 +328,7 @@ python-versions = "*"
|
|||
|
||||
[[package]]
|
||||
name = "fastjsonschema"
|
||||
version = "2.16.1"
|
||||
version = "2.15.3"
|
||||
description = "Fastest Python implementation of JSON schema"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -370,7 +370,7 @@ testing = ["covdefaults (>=1.2.0)", "coverage (>=4)", "pytest (>=4)", "pytest-co
|
|||
|
||||
[[package]]
|
||||
name = "fonttools"
|
||||
version = "4.34.4"
|
||||
version = "4.33.3"
|
||||
description = "Tools to manipulate font files"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -452,7 +452,7 @@ qutip = "^4.6.3"
|
|||
type = "git"
|
||||
url = "git@github.com:vale981/two_qubit_model.git"
|
||||
reference = "main"
|
||||
resolved_reference = "dd86c5fae18a28f4e7b16294f2fb3f9641aeed58"
|
||||
resolved_reference = "b15aa6d77d9c2c5b772e4130365a22e06e53e343"
|
||||
|
||||
[[package]]
|
||||
name = "hops"
|
||||
|
|
@ -486,11 +486,11 @@ plotting = ["matplotlib (>=3.5.0,<4.0.0)"]
|
|||
type = "git"
|
||||
url = "git@gitlab.hrz.tu-chemnitz.de:s8896854--tu-dresden.de/hops.git"
|
||||
reference = "time_dep_coupling"
|
||||
resolved_reference = "c9a143db7a0c3edadabe87f25f1c9303a9530f71"
|
||||
resolved_reference = "b2856eed49cd72e65b6d7ef6ec385e664f759725"
|
||||
|
||||
[[package]]
|
||||
name = "hopsflow"
|
||||
version = "1.4.0"
|
||||
version = "1.3.0"
|
||||
description = "Calculating open system bath energy changes with HOPS and analytically."
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -512,7 +512,7 @@ tqdm = "^4.62.3"
|
|||
type = "git"
|
||||
url = "https://github.com/vale981/hopsflow"
|
||||
reference = "main"
|
||||
resolved_reference = "3d34c8aff7a1234af96b61a7e9a05575107c9ce5"
|
||||
resolved_reference = "b7940c1d805b4d9f3a64e9d0fce44398032d6cd7"
|
||||
|
||||
[[package]]
|
||||
name = "humanfriendly"
|
||||
|
|
@ -535,7 +535,7 @@ python-versions = ">=3.5"
|
|||
|
||||
[[package]]
|
||||
name = "ipykernel"
|
||||
version = "6.15.1"
|
||||
version = "6.15.0"
|
||||
description = "IPython Kernel for Jupyter"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -650,7 +650,7 @@ i18n = ["Babel (>=2.7)"]
|
|||
|
||||
[[package]]
|
||||
name = "jsonschema"
|
||||
version = "4.7.2"
|
||||
version = "4.6.1"
|
||||
description = "An implementation of JSON Schema validation for Python"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -721,7 +721,7 @@ test = ["pexpect"]
|
|||
|
||||
[[package]]
|
||||
name = "jupyter-core"
|
||||
version = "4.11.1"
|
||||
version = "4.10.0"
|
||||
description = "Jupyter core package. A base package on which Jupyter projects rely."
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -752,7 +752,7 @@ python-versions = ">=3.6"
|
|||
|
||||
[[package]]
|
||||
name = "kiwisolver"
|
||||
version = "1.4.4"
|
||||
version = "1.4.3"
|
||||
description = "A fast implementation of the Cassowary constraint solver"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -954,7 +954,7 @@ test = ["pytest", "coverage", "requests", "testpath", "nbval", "selenium", "pyte
|
|||
|
||||
[[package]]
|
||||
name = "numpy"
|
||||
version = "1.23.1"
|
||||
version = "1.23.0"
|
||||
description = "NumPy is the fundamental package for array computing with Python."
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -1071,14 +1071,14 @@ python-versions = "*"
|
|||
|
||||
[[package]]
|
||||
name = "pillow"
|
||||
version = "9.2.0"
|
||||
version = "9.1.1"
|
||||
description = "Python Imaging Library (Fork)"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-issues (>=3.0.1)", "sphinx-removed-in", "sphinxext-opengraph"]
|
||||
docs = ["olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-issues (>=3.0.1)", "sphinx-removed-in", "sphinx-rtd-theme (>=1.0)", "sphinxext-opengraph"]
|
||||
tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -1247,7 +1247,7 @@ python-versions = "*"
|
|||
|
||||
[[package]]
|
||||
name = "pywinpty"
|
||||
version = "2.0.6"
|
||||
version = "2.0.5"
|
||||
description = "Pseudo terminal support for Windows from Python."
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -1365,7 +1365,7 @@ tune = ["pandas", "tabulate", "tensorboardX (>=1.9)", "requests"]
|
|||
|
||||
[[package]]
|
||||
name = "requests"
|
||||
version = "2.28.1"
|
||||
version = "2.28.0"
|
||||
description = "Python HTTP for Humans."
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -1373,13 +1373,13 @@ python-versions = ">=3.7, <4"
|
|||
|
||||
[package.dependencies]
|
||||
certifi = ">=2017.4.17"
|
||||
charset-normalizer = ">=2,<3"
|
||||
charset-normalizer = ">=2.0.0,<2.1.0"
|
||||
idna = ">=2.5,<4"
|
||||
urllib3 = ">=1.21.1,<1.27"
|
||||
|
||||
[package.extras]
|
||||
socks = ["PySocks (>=1.5.6,!=1.5.7)"]
|
||||
use_chardet_on_py3 = ["chardet (>=3.0.2,<6)"]
|
||||
use_chardet_on_py3 = ["chardet (>=3.0.2,<5)"]
|
||||
|
||||
[[package]]
|
||||
name = "scipy"
|
||||
|
|
@ -1407,7 +1407,7 @@ win32 = ["pywin32"]
|
|||
|
||||
[[package]]
|
||||
name = "setuptools-scm"
|
||||
version = "7.0.5"
|
||||
version = "7.0.2"
|
||||
description = "the blessed package to manage your versions by scm tags"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -1501,7 +1501,7 @@ scipy = "^1.7.3"
|
|||
type = "git"
|
||||
url = "https://github.com/vale981/stocproc"
|
||||
reference = "master"
|
||||
resolved_reference = "3a9bd00a454239411b4f110f1884ccac068894a4"
|
||||
resolved_reference = "0035c0185a1dbc717d30ac22485020d59c865094"
|
||||
|
||||
[[package]]
|
||||
name = "tabulate"
|
||||
|
|
@ -1555,11 +1555,11 @@ python-versions = ">=3.6"
|
|||
|
||||
[[package]]
|
||||
name = "tornado"
|
||||
version = "6.2"
|
||||
version = "6.1"
|
||||
description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">= 3.7"
|
||||
python-versions = ">= 3.5"
|
||||
|
||||
[[package]]
|
||||
name = "tqdm"
|
||||
|
|
@ -1591,7 +1591,7 @@ test = ["pytest", "pre-commit"]
|
|||
|
||||
[[package]]
|
||||
name = "typer"
|
||||
version = "0.4.2"
|
||||
version = "0.4.1"
|
||||
description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -1602,13 +1602,13 @@ click = ">=7.1.1,<9.0.0"
|
|||
|
||||
[package.extras]
|
||||
all = ["colorama (>=0.4.3,<0.5.0)", "shellingham (>=1.3.0,<2.0.0)"]
|
||||
dev = ["autoflake (>=1.3.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "pre-commit (>=2.17.0,<3.0.0)"]
|
||||
dev = ["autoflake (>=1.3.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)"]
|
||||
doc = ["mkdocs (>=1.1.2,<2.0.0)", "mkdocs-material (>=8.1.4,<9.0.0)", "mdx-include (>=1.4.1,<2.0.0)"]
|
||||
test = ["shellingham (>=1.3.0,<2.0.0)", "pytest (>=4.4.0,<5.4.0)", "pytest-cov (>=2.10.0,<3.0.0)", "coverage (>=5.2,<6.0)", "pytest-xdist (>=1.32.0,<2.0.0)", "pytest-sugar (>=0.9.4,<0.10.0)", "mypy (==0.910)", "black (>=22.3.0,<23.0.0)", "isort (>=5.0.6,<6.0.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.3.0"
|
||||
version = "4.2.0"
|
||||
description = "Backported and Experimental Type Hints for Python 3.7+"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -1633,11 +1633,11 @@ tests = ["nose", "numpy"]
|
|||
|
||||
[[package]]
|
||||
name = "urllib3"
|
||||
version = "1.26.10"
|
||||
version = "1.26.9"
|
||||
description = "HTTP library with thread-safe connection pooling, file post, and more."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, <4"
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, <4"
|
||||
|
||||
[package.extras]
|
||||
brotli = ["brotlicffi (>=0.8.0)", "brotli (>=1.0.9)", "brotlipy (>=0.6.0)"]
|
||||
|
|
@ -1768,74 +1768,60 @@ certifi = [
|
|||
{file = "certifi-2022.6.15.tar.gz", hash = "sha256:84c85a9078b11105f04f3036a9482ae10e4621616db313fe045dd24743a0820d"},
|
||||
]
|
||||
cffi = [
|
||||
{file = "cffi-1.15.1-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:a66d3508133af6e8548451b25058d5812812ec3798c886bf38ed24a98216fab2"},
|
||||
{file = "cffi-1.15.1-cp27-cp27m-manylinux1_i686.whl", hash = "sha256:470c103ae716238bbe698d67ad020e1db9d9dba34fa5a899b5e21577e6d52ed2"},
|
||||
{file = "cffi-1.15.1-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:9ad5db27f9cabae298d151c85cf2bad1d359a1b9c686a275df03385758e2f914"},
|
||||
{file = "cffi-1.15.1-cp27-cp27m-win32.whl", hash = "sha256:b3bbeb01c2b273cca1e1e0c5df57f12dce9a4dd331b4fa1635b8bec26350bde3"},
|
||||
{file = "cffi-1.15.1-cp27-cp27m-win_amd64.whl", hash = "sha256:e00b098126fd45523dd056d2efba6c5a63b71ffe9f2bbe1a4fe1716e1d0c331e"},
|
||||
{file = "cffi-1.15.1-cp27-cp27mu-manylinux1_i686.whl", hash = "sha256:d61f4695e6c866a23a21acab0509af1cdfd2c013cf256bbf5b6b5e2695827162"},
|
||||
{file = "cffi-1.15.1-cp27-cp27mu-manylinux1_x86_64.whl", hash = "sha256:ed9cb427ba5504c1dc15ede7d516b84757c3e3d7868ccc85121d9310d27eed0b"},
|
||||
{file = "cffi-1.15.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:39d39875251ca8f612b6f33e6b1195af86d1b3e60086068be9cc053aa4376e21"},
|
||||
{file = "cffi-1.15.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:285d29981935eb726a4399badae8f0ffdff4f5050eaa6d0cfc3f64b857b77185"},
|
||||
{file = "cffi-1.15.1-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3eb6971dcff08619f8d91607cfc726518b6fa2a9eba42856be181c6d0d9515fd"},
|
||||
{file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:21157295583fe8943475029ed5abdcf71eb3911894724e360acff1d61c1d54bc"},
|
||||
{file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5635bd9cb9731e6d4a1132a498dd34f764034a8ce60cef4f5319c0541159392f"},
|
||||
{file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2012c72d854c2d03e45d06ae57f40d78e5770d252f195b93f581acf3ba44496e"},
|
||||
{file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dd86c085fae2efd48ac91dd7ccffcfc0571387fe1193d33b6394db7ef31fe2a4"},
|
||||
{file = "cffi-1.15.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:fa6693661a4c91757f4412306191b6dc88c1703f780c8234035eac011922bc01"},
|
||||
{file = "cffi-1.15.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:59c0b02d0a6c384d453fece7566d1c7e6b7bae4fc5874ef2ef46d56776d61c9e"},
|
||||
{file = "cffi-1.15.1-cp310-cp310-win32.whl", hash = "sha256:cba9d6b9a7d64d4bd46167096fc9d2f835e25d7e4c121fb2ddfc6528fb0413b2"},
|
||||
{file = "cffi-1.15.1-cp310-cp310-win_amd64.whl", hash = "sha256:ce4bcc037df4fc5e3d184794f27bdaab018943698f4ca31630bc7f84a7b69c6d"},
|
||||
{file = "cffi-1.15.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:3d08afd128ddaa624a48cf2b859afef385b720bb4b43df214f85616922e6a5ac"},
|
||||
{file = "cffi-1.15.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3799aecf2e17cf585d977b780ce79ff0dc9b78d799fc694221ce814c2c19db83"},
|
||||
{file = "cffi-1.15.1-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a591fe9e525846e4d154205572a029f653ada1a78b93697f3b5a8f1f2bc055b9"},
|
||||
{file = "cffi-1.15.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3548db281cd7d2561c9ad9984681c95f7b0e38881201e157833a2342c30d5e8c"},
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||||
{file = "cffi-1.15.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:91fc98adde3d7881af9b59ed0294046f3806221863722ba7d8d120c575314325"},
|
||||
{file = "cffi-1.15.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:94411f22c3985acaec6f83c6df553f2dbe17b698cc7f8ae751ff2237d96b9e3c"},
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||||
{file = "cffi-1.15.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:03425bdae262c76aad70202debd780501fabeaca237cdfddc008987c0e0f59ef"},
|
||||
{file = "cffi-1.15.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:cc4d65aeeaa04136a12677d3dd0b1c0c94dc43abac5860ab33cceb42b801c1e8"},
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||||
{file = "cffi-1.15.1-cp311-cp311-win32.whl", hash = "sha256:a0f100c8912c114ff53e1202d0078b425bee3649ae34d7b070e9697f93c5d52d"},
|
||||
{file = "cffi-1.15.1-cp311-cp311-win_amd64.whl", hash = "sha256:04ed324bda3cda42b9b695d51bb7d54b680b9719cfab04227cdd1e04e5de3104"},
|
||||
{file = "cffi-1.15.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:50a74364d85fd319352182ef59c5c790484a336f6db772c1a9231f1c3ed0cbd7"},
|
||||
{file = "cffi-1.15.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e263d77ee3dd201c3a142934a086a4450861778baaeeb45db4591ef65550b0a6"},
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{file = "click-8.0.4-py3-none-any.whl", hash = "sha256:6a7a62563bbfabfda3a38f3023a1db4a35978c0abd76f6c9605ecd6554d6d9b1"},
|
||||
|
|
@ -1899,7 +1885,26 @@ cython = [
|
|||
{file = "Cython-0.29.30-py2.py3-none-any.whl", hash = "sha256:acb72e0b42079862cf2f894964b41f261e941e75677e902c5f4304b3eb00af33"},
|
||||
{file = "Cython-0.29.30.tar.gz", hash = "sha256:2235b62da8fe6fa8b99422c8e583f2fb95e143867d337b5c75e4b9a1a865f9e3"},
|
||||
]
|
||||
debugpy = []
|
||||
debugpy = [
|
||||
{file = "debugpy-1.6.0-cp310-cp310-macosx_10_15_x86_64.whl", hash = "sha256:eb1946efac0c0c3d411cea0b5ac772fbde744109fd9520fb0c5a51979faf05ad"},
|
||||
{file = "debugpy-1.6.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:e3513399177dd37af4c1332df52da5da1d0c387e5927dc4c0709e26ee7302e8f"},
|
||||
{file = "debugpy-1.6.0-cp310-cp310-win32.whl", hash = "sha256:5c492235d6b68f879df3bdbdb01f25c15be15682665517c2c7d0420e5658d71f"},
|
||||
{file = "debugpy-1.6.0-cp310-cp310-win_amd64.whl", hash = "sha256:40de9ba137d355538432209d05e0f5fe5d0498dce761c39119ad4b950b51db31"},
|
||||
{file = "debugpy-1.6.0-cp37-cp37m-macosx_10_15_x86_64.whl", hash = "sha256:0d383b91efee57dbb923ba20801130cf60450a0eda60bce25bccd937de8e323a"},
|
||||
{file = "debugpy-1.6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:1ff853e60e77e1c16f85a31adb8360bb2d98ca588d7ed645b7f0985b240bdb5e"},
|
||||
{file = "debugpy-1.6.0-cp37-cp37m-win32.whl", hash = "sha256:8e972c717d95f56b6a3a7a29a5ede1ee8f2c3802f6f0e678203b0778eb322bf1"},
|
||||
{file = "debugpy-1.6.0-cp37-cp37m-win_amd64.whl", hash = "sha256:a8aaeb53e87225141fda7b9081bd87155c1debc13e2f5a532d341112d1983b65"},
|
||||
{file = "debugpy-1.6.0-cp38-cp38-macosx_10_15_x86_64.whl", hash = "sha256:132defb585b518955358321d0f42f6aa815aa15b432be27db654807707c70b2f"},
|
||||
{file = "debugpy-1.6.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:8ee75844242b4537beb5899f3e60a578454d1f136b99e8d57ac424573797b94a"},
|
||||
{file = "debugpy-1.6.0-cp38-cp38-win32.whl", hash = "sha256:a65a2499761d47df3e9ea9567109be6e73d412e00ac3ffcf74839f3ddfcdf028"},
|
||||
{file = "debugpy-1.6.0-cp38-cp38-win_amd64.whl", hash = "sha256:bd980d533d0ddfc451e03a3bb32acb2900049fec39afc3425b944ebf0889be62"},
|
||||
{file = "debugpy-1.6.0-cp39-cp39-macosx_10_15_x86_64.whl", hash = "sha256:245c7789a012f86210847ec7ee9f38c30a30d4c2223c3e111829a76c9006a5d0"},
|
||||
{file = "debugpy-1.6.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:0e3aa2368883e83e7b689ddff3cafb595f7b711f6a065886b46a96a7fef874e7"},
|
||||
{file = "debugpy-1.6.0-cp39-cp39-win32.whl", hash = "sha256:72bcfa97f3afa0064afc77ab811f48ad4a06ac330f290b675082c24437730366"},
|
||||
{file = "debugpy-1.6.0-cp39-cp39-win_amd64.whl", hash = "sha256:30abefefd2ff5a5481162d613cb70e60e2fa80a5eb4c994717c0f008ed25d2e1"},
|
||||
{file = "debugpy-1.6.0-py2.py3-none-any.whl", hash = "sha256:4de7777842da7e08652f2776c552070bbdd758557fdec73a15d7be0e4aab95ce"},
|
||||
{file = "debugpy-1.6.0.zip", hash = "sha256:7b79c40852991f7b6c3ea65845ed0f5f6b731c37f4f9ad9c61e2ab4bd48a9275"},
|
||||
]
|
||||
decorator = [
|
||||
{file = "decorator-5.1.1-py3-none-any.whl", hash = "sha256:b8c3f85900b9dc423225913c5aace94729fe1fa9763b38939a95226f02d37186"},
|
||||
{file = "decorator-5.1.1.tar.gz", hash = "sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330"},
|
||||
|
|
@ -1908,7 +1913,10 @@ defusedxml = [
|
|||
{file = "defusedxml-0.7.1-py2.py3-none-any.whl", hash = "sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61"},
|
||||
{file = "defusedxml-0.7.1.tar.gz", hash = "sha256:1bb3032db185915b62d7c6209c5a8792be6a32ab2fedacc84e01b52c51aa3e69"},
|
||||
]
|
||||
distlib = []
|
||||
distlib = [
|
||||
{file = "distlib-0.3.4-py2.py3-none-any.whl", hash = "sha256:6564fe0a8f51e734df6333d08b8b94d4ea8ee6b99b5ed50613f731fd4089f34b"},
|
||||
{file = "distlib-0.3.4.zip", hash = "sha256:e4b58818180336dc9c529bfb9a0b58728ffc09ad92027a3f30b7cd91e3458579"},
|
||||
]
|
||||
entrypoints = [
|
||||
{file = "entrypoints-0.4-py3-none-any.whl", hash = "sha256:f174b5ff827504fd3cd97cc3f8649f3693f51538c7e4bdf3ef002c8429d42f9f"},
|
||||
{file = "entrypoints-0.4.tar.gz", hash = "sha256:b706eddaa9218a19ebcd67b56818f05bb27589b1ca9e8d797b74affad4ccacd4"},
|
||||
|
|
@ -1917,13 +1925,19 @@ executing = [
|
|||
{file = "executing-0.8.3-py2.py3-none-any.whl", hash = "sha256:d1eef132db1b83649a3905ca6dd8897f71ac6f8cac79a7e58a1a09cf137546c9"},
|
||||
{file = "executing-0.8.3.tar.gz", hash = "sha256:c6554e21c6b060590a6d3be4b82fb78f8f0194d809de5ea7df1c093763311501"},
|
||||
]
|
||||
fastjsonschema = []
|
||||
fastjsonschema = [
|
||||
{file = "fastjsonschema-2.15.3-py3-none-any.whl", hash = "sha256:ddb0b1d8243e6e3abb822bd14e447a89f4ab7439342912d590444831fa00b6a0"},
|
||||
{file = "fastjsonschema-2.15.3.tar.gz", hash = "sha256:0a572f0836962d844c1fc435e200b2e4f4677e4e6611a2e3bdd01ba697c275ec"},
|
||||
]
|
||||
fcspline = []
|
||||
filelock = [
|
||||
{file = "filelock-3.7.1-py3-none-any.whl", hash = "sha256:37def7b658813cda163b56fc564cdc75e86d338246458c4c28ae84cabefa2404"},
|
||||
{file = "filelock-3.7.1.tar.gz", hash = "sha256:3a0fd85166ad9dbab54c9aec96737b744106dc5f15c0b09a6744a445299fcf04"},
|
||||
]
|
||||
fonttools = []
|
||||
fonttools = [
|
||||
{file = "fonttools-4.33.3-py3-none-any.whl", hash = "sha256:f829c579a8678fa939a1d9e9894d01941db869de44390adb49ce67055a06cc2a"},
|
||||
{file = "fonttools-4.33.3.zip", hash = "sha256:c0fdcfa8ceebd7c1b2021240bd46ef77aa8e7408cf10434be55df52384865f8e"},
|
||||
]
|
||||
frozenlist = [
|
||||
{file = "frozenlist-1.3.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d2257aaba9660f78c7b1d8fea963b68f3feffb1a9d5d05a18401ca9eb3e8d0a3"},
|
||||
{file = "frozenlist-1.3.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:4a44ebbf601d7bac77976d429e9bdb5a4614f9f4027777f9e54fd765196e9d3b"},
|
||||
|
|
@ -2067,7 +2081,10 @@ idna = [
|
|||
{file = "idna-3.3-py3-none-any.whl", hash = "sha256:84d9dd047ffa80596e0f246e2eab0b391788b0503584e8945f2368256d2735ff"},
|
||||
{file = "idna-3.3.tar.gz", hash = "sha256:9d643ff0a55b762d5cdb124b8eaa99c66322e2157b69160bc32796e824360e6d"},
|
||||
]
|
||||
ipykernel = []
|
||||
ipykernel = [
|
||||
{file = "ipykernel-6.15.0-py3-none-any.whl", hash = "sha256:b9ed519a29eb819eb82e87e0d3754088237b233e5c647b8bb0ff23c8c70ed16f"},
|
||||
{file = "ipykernel-6.15.0.tar.gz", hash = "sha256:b59f9d9672c3a483494bb75915a2b315e78b833a38b039b1ee36dc28683f0d89"},
|
||||
]
|
||||
ipython = [
|
||||
{file = "ipython-8.4.0-py3-none-any.whl", hash = "sha256:7ca74052a38fa25fe9bedf52da0be7d3fdd2fb027c3b778ea78dfe8c212937d1"},
|
||||
{file = "ipython-8.4.0.tar.gz", hash = "sha256:f2db3a10254241d9b447232cec8b424847f338d9d36f9a577a6192c332a46abd"},
|
||||
|
|
@ -2088,7 +2105,10 @@ jinja2 = [
|
|||
{file = "Jinja2-3.1.2-py3-none-any.whl", hash = "sha256:6088930bfe239f0e6710546ab9c19c9ef35e29792895fed6e6e31a023a182a61"},
|
||||
{file = "Jinja2-3.1.2.tar.gz", hash = "sha256:31351a702a408a9e7595a8fc6150fc3f43bb6bf7e319770cbc0db9df9437e852"},
|
||||
]
|
||||
jsonschema = []
|
||||
jsonschema = [
|
||||
{file = "jsonschema-4.6.1-py3-none-any.whl", hash = "sha256:5eb781753403847fb320f05e9ab2191725b58c5e7f97f1bed63285ca423159bc"},
|
||||
{file = "jsonschema-4.6.1.tar.gz", hash = "sha256:ec2802e6a37517f09d47d9ba107947589ae1d25ff557b925d83a321fc2aa5d3b"},
|
||||
]
|
||||
jupyter = [
|
||||
{file = "jupyter-1.0.0-py2.py3-none-any.whl", hash = "sha256:5b290f93b98ffbc21c0c7e749f054b3267782166d72fa5e3ed1ed4eaf34a2b78"},
|
||||
{file = "jupyter-1.0.0.tar.gz", hash = "sha256:d9dc4b3318f310e34c82951ea5d6683f67bed7def4b259fafbfe4f1beb1d8e5f"},
|
||||
|
|
@ -2102,7 +2122,10 @@ jupyter-console = [
|
|||
{file = "jupyter_console-6.4.4-py3-none-any.whl", hash = "sha256:756df7f4f60c986e7bc0172e4493d3830a7e6e75c08750bbe59c0a5403ad6dee"},
|
||||
{file = "jupyter_console-6.4.4.tar.gz", hash = "sha256:172f5335e31d600df61613a97b7f0352f2c8250bbd1092ef2d658f77249f89fb"},
|
||||
]
|
||||
jupyter-core = []
|
||||
jupyter-core = [
|
||||
{file = "jupyter_core-4.10.0-py3-none-any.whl", hash = "sha256:e7f5212177af7ab34179690140f188aa9bf3d322d8155ed972cbded19f55b6f3"},
|
||||
{file = "jupyter_core-4.10.0.tar.gz", hash = "sha256:a6de44b16b7b31d7271130c71a6792c4040f077011961138afed5e5e73181aec"},
|
||||
]
|
||||
jupyterlab-pygments = [
|
||||
{file = "jupyterlab_pygments-0.2.2-py2.py3-none-any.whl", hash = "sha256:2405800db07c9f770863bcf8049a529c3dd4d3e28536638bd7c1c01d2748309f"},
|
||||
{file = "jupyterlab_pygments-0.2.2.tar.gz", hash = "sha256:7405d7fde60819d905a9fa8ce89e4cd830e318cdad22a0030f7a901da705585d"},
|
||||
|
|
@ -2111,7 +2134,51 @@ jupyterlab-widgets = [
|
|||
{file = "jupyterlab_widgets-1.1.1-py3-none-any.whl", hash = "sha256:90ab47d99da03a3697074acb23b2975ead1d6171aa41cb2812041a7f2a08177a"},
|
||||
{file = "jupyterlab_widgets-1.1.1.tar.gz", hash = "sha256:67d0ef1e407e0c42c8ab60b9d901cd7a4c68923650763f75bf17fb06c1943b79"},
|
||||
]
|
||||
kiwisolver = []
|
||||
kiwisolver = [
|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
||||
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|
||||
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||||
{file = "kiwisolver-1.4.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:747190fcdadc377263223f8f72b038381b3b549a8a3df5baf4d067da4749b046"},
|
||||
{file = "kiwisolver-1.4.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:fd628e63ffdba0112e3ddf1b1e9f3db29dd8262345138e08f4938acbc6d0805a"},
|
||||
{file = "kiwisolver-1.4.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:22ccba48abae827a0f952a78a7b1a7ff01866131e5bbe1f826ce9bda406bf051"},
|
||||
{file = "kiwisolver-1.4.3-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:af24b21c2283ca69c416a8a42cde9764dc36c63d3389645d28c69b0e93db3cd7"},
|
||||
{file = "kiwisolver-1.4.3-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:547111ef7cf13d73546c2de97ce434935626c897bdec96a578ca100b5fcd694b"},
|
||||
{file = "kiwisolver-1.4.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:84f85adfebd7d3c3db649efdf73659e1677a2cf3fa6e2556a3f373578af14bf7"},
|
||||
{file = "kiwisolver-1.4.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ffd7cf165ff71afb202b3f36daafbf298932bee325aac9f58e1c9cd55838bef0"},
|
||||
{file = "kiwisolver-1.4.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6b3136eecf7e1b4a4d23e4b19d6c4e7a8e0b42d55f30444e3c529700cdacaa0d"},
|
||||
{file = "kiwisolver-1.4.3-cp39-cp39-win32.whl", hash = "sha256:46c6e5018ba31d5ee7582f323d8661498a154dea1117486a571db4c244531f24"},
|
||||
{file = "kiwisolver-1.4.3-cp39-cp39-win_amd64.whl", hash = "sha256:8395064d63b26947fa2c9faeea9c3eee35e52148c5339c37987e1d96fbf009b3"},
|
||||
{file = "kiwisolver-1.4.3-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:325fa1b15098e44fe4590a6c5c09a212ca10c6ebb5d96f7447d675f6c8340e4e"},
|
||||
{file = "kiwisolver-1.4.3-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:654280c5f41831ddcc5a331c0e3ce2e480bbc3d7c93c18ecf6236313aae2d61a"},
|
||||
{file = "kiwisolver-1.4.3-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1ae7aa0784aeadfbd693c27993727792fbe1455b84d49970bad5886b42976b18"},
|
||||
{file = "kiwisolver-1.4.3-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:130c6c35eded399d3967cf8a542c20b671f5ba85bd6f210f8b939f868360e9eb"},
|
||||
{file = "kiwisolver-1.4.3.tar.gz", hash = "sha256:ab8a15c2750ae8d53e31f77a94f846d0a00772240f1c12817411fa2344351f86"},
|
||||
]
|
||||
lmfit = [
|
||||
{file = "lmfit-1.0.3.tar.gz", hash = "sha256:d067c3ea501f035af5d3c079e6e6e35dc3cc1ac7d439429a425b0aeb5a7858a2"},
|
||||
]
|
||||
|
|
@ -2284,7 +2351,30 @@ notebook = [
|
|||
{file = "notebook-6.4.12-py3-none-any.whl", hash = "sha256:8c07a3bb7640e371f8a609bdbb2366a1976c6a2589da8ef917f761a61e3ad8b1"},
|
||||
{file = "notebook-6.4.12.tar.gz", hash = "sha256:6268c9ec9048cff7a45405c990c29ac9ca40b0bc3ec29263d218c5e01f2b4e86"},
|
||||
]
|
||||
numpy = []
|
||||
numpy = [
|
||||
{file = "numpy-1.23.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:58bfd40eb478f54ff7a5710dd61c8097e169bc36cc68333d00a9bcd8def53b38"},
|
||||
{file = "numpy-1.23.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:196cd074c3f97c4121601790955f915187736f9cf458d3ee1f1b46aff2b1ade0"},
|
||||
{file = "numpy-1.23.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f1d88ef79e0a7fa631bb2c3dda1ea46b32b1fe614e10fedd611d3d5398447f2f"},
|
||||
{file = "numpy-1.23.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d54b3b828d618a19779a84c3ad952e96e2c2311b16384e973e671aa5be1f6187"},
|
||||
{file = "numpy-1.23.0-cp310-cp310-win32.whl", hash = "sha256:2b2da66582f3a69c8ce25ed7921dcd8010d05e59ac8d89d126a299be60421171"},
|
||||
{file = "numpy-1.23.0-cp310-cp310-win_amd64.whl", hash = "sha256:97a76604d9b0e79f59baeca16593c711fddb44936e40310f78bfef79ee9a835f"},
|
||||
{file = "numpy-1.23.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:d8cc87bed09de55477dba9da370c1679bd534df9baa171dd01accbb09687dac3"},
|
||||
{file = "numpy-1.23.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:f0f18804df7370571fb65db9b98bf1378172bd4e962482b857e612d1fec0f53e"},
|
||||
{file = "numpy-1.23.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac86f407873b952679f5f9e6c0612687e51547af0e14ddea1eedfcb22466babd"},
|
||||
{file = "numpy-1.23.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ae8adff4172692ce56233db04b7ce5792186f179c415c37d539c25de7298d25d"},
|
||||
{file = "numpy-1.23.0-cp38-cp38-win32.whl", hash = "sha256:fe8b9683eb26d2c4d5db32cd29b38fdcf8381324ab48313b5b69088e0e355379"},
|
||||
{file = "numpy-1.23.0-cp38-cp38-win_amd64.whl", hash = "sha256:5043bcd71fcc458dfb8a0fc5509bbc979da0131b9d08e3d5f50fb0bbb36f169a"},
|
||||
{file = "numpy-1.23.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:1c29b44905af288b3919803aceb6ec7fec77406d8b08aaa2e8b9e63d0fe2f160"},
|
||||
{file = "numpy-1.23.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:98e8e0d8d69ff4d3fa63e6c61e8cfe2d03c29b16b58dbef1f9baa175bbed7860"},
|
||||
{file = "numpy-1.23.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:79a506cacf2be3a74ead5467aee97b81fca00c9c4c8b3ba16dbab488cd99ba10"},
|
||||
{file = "numpy-1.23.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:092f5e6025813e64ad6d1b52b519165d08c730d099c114a9247c9bb635a2a450"},
|
||||
{file = "numpy-1.23.0-cp39-cp39-win32.whl", hash = "sha256:d6ca8dabe696c2785d0c8c9b0d8a9b6e5fdbe4f922bde70d57fa1a2848134f95"},
|
||||
{file = "numpy-1.23.0-cp39-cp39-win_amd64.whl", hash = "sha256:fc431493df245f3c627c0c05c2bd134535e7929dbe2e602b80e42bf52ff760bc"},
|
||||
{file = "numpy-1.23.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:f9c3fc2adf67762c9fe1849c859942d23f8d3e0bee7b5ed3d4a9c3eeb50a2f07"},
|
||||
{file = "numpy-1.23.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d0d2094e8f4d760500394d77b383a1b06d3663e8892cdf5df3c592f55f3bff66"},
|
||||
{file = "numpy-1.23.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:94b170b4fa0168cd6be4becf37cb5b127bd12a795123984385b8cd4aca9857e5"},
|
||||
{file = "numpy-1.23.0.tar.gz", hash = "sha256:bd3fa4fe2e38533d5336e1272fc4e765cabbbde144309ccee8675509d5cd7b05"},
|
||||
]
|
||||
opt-einsum = [
|
||||
{file = "opt_einsum-3.3.0-py3-none-any.whl", hash = "sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147"},
|
||||
{file = "opt_einsum-3.3.0.tar.gz", hash = "sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549"},
|
||||
|
|
@ -2341,64 +2431,44 @@ pickleshare = [
|
|||
{file = "pickleshare-0.7.5.tar.gz", hash = "sha256:87683d47965c1da65cdacaf31c8441d12b8044cdec9aca500cd78fc2c683afca"},
|
||||
]
|
||||
pillow = [
|
||||
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|
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{file = "Pillow-9.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:510cef4a3f401c246cfd8227b300828715dd055463cdca6176c2e4036df8bd4f"},
|
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{file = "Pillow-9.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7888310f6214f19ab2b6df90f3f06afa3df7ef7355fc025e78a3044737fab1f5"},
|
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{file = "Pillow-9.2.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:831e648102c82f152e14c1a0938689dbb22480c548c8d4b8b248b3e50967b88c"},
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{file = "Pillow-9.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1cc1d2451e8a3b4bfdb9caf745b58e6c7a77d2e469159b0d527a4554d73694d1"},
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{file = "Pillow-9.2.0-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:6e8c66f70fb539301e064f6478d7453e820d8a2c631da948a23384865cd95544"},
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{file = "Pillow-9.2.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:37ff6b522a26d0538b753f0b4e8e164fdada12db6c6f00f62145d732d8a3152e"},
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{file = "Pillow-9.2.0-cp310-cp310-win32.whl", hash = "sha256:c79698d4cd9318d9481d89a77e2d3fcaeff5486be641e60a4b49f3d2ecca4e28"},
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{file = "Pillow-9.2.0-cp310-cp310-win_amd64.whl", hash = "sha256:254164c57bab4b459f14c64e93df11eff5ded575192c294a0c49270f22c5d93d"},
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{file = "Pillow-9.2.0-cp311-cp311-win32.whl", hash = "sha256:b6d5e92df2b77665e07ddb2e4dbd6d644b78e4c0d2e9272a852627cdba0d75cf"},
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||||
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||||
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{file = "Pillow-9.1.1-cp38-cp38-win_amd64.whl", hash = "sha256:f054b020c4d7e9786ae0404278ea318768eb123403b18453e28e47cdb7a0a4bf"},
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{file = "Pillow-9.1.1-cp39-cp39-win_amd64.whl", hash = "sha256:7c150dbbb4a94ea4825d1e5f2c5501af7141ea95825fadd7829f9b11c97aaf6c"},
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{file = "Pillow-9.1.1-pp38-pypy38_pp73-macosx_10_10_x86_64.whl", hash = "sha256:6e760cf01259a1c0a50f3c845f9cad1af30577fd8b670339b1659c6d0e7a41dd"},
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{file = "Pillow-9.1.1-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a4165205a13b16a29e1ac57efeee6be2dfd5b5408122d59ef2145bc3239fa340"},
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||||
{file = "Pillow-9.1.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:937a54e5694684f74dcbf6e24cc453bfc5b33940216ddd8f4cd8f0f79167f765"},
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||||
{file = "Pillow-9.1.1-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:baf3be0b9446a4083cc0c5bb9f9c964034be5374b5bc09757be89f5d2fa247b8"},
|
||||
{file = "Pillow-9.1.1.tar.gz", hash = "sha256:7502539939b53d7565f3d11d87c78e7ec900d3c72945d4ee0e2f250d598309a0"},
|
||||
]
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||||
platformdirs = [
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||||
{file = "platformdirs-2.5.2-py3-none-any.whl", hash = "sha256:027d8e83a2d7de06bbac4e5ef7e023c02b863d7ea5d079477e722bb41ab25788"},
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||||
|
|
@ -2552,11 +2622,11 @@ pywin32 = [
|
|||
{file = "pywin32-304-cp39-cp39-win_amd64.whl", hash = "sha256:d24a3382f013b21aa24a5cfbfad5a2cd9926610c0affde3e8ab5b3d7dbcf4ac9"},
|
||||
]
|
||||
pywinpty = [
|
||||
{file = "pywinpty-2.0.6-cp310-none-win_amd64.whl", hash = "sha256:7fadc5265484c7d7c84554b9f1cfd7acf6383a877c1cfb3ee77d51179145b3ce"},
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||||
{file = "pywinpty-2.0.6-cp37-none-win_amd64.whl", hash = "sha256:906a3048ecfec6ece1b141594ebbbcd5c4751960714c50524e8e907bb77c9207"},
|
||||
{file = "pywinpty-2.0.6-cp38-none-win_amd64.whl", hash = "sha256:5e4b2167e813575bf495b46adb2d88be5c470d9daf49d488900350853e95248f"},
|
||||
{file = "pywinpty-2.0.6-cp39-none-win_amd64.whl", hash = "sha256:f7ae5d29f1c3d028e06032f8d267b51fd72ea219b9bba3e2a972a7bc26a25a87"},
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||||
{file = "pywinpty-2.0.6.tar.gz", hash = "sha256:a91a77d23f29a58b44f62a9474a31ed67df1277cddb69665275f8d22429046ac"},
|
||||
{file = "pywinpty-2.0.5-cp310-none-win_amd64.whl", hash = "sha256:f86c76e2881c37e69678cbbf178109f8da1fa8584db24d58e1b9369b0276cfcb"},
|
||||
{file = "pywinpty-2.0.5-cp37-none-win_amd64.whl", hash = "sha256:ff9b52f182650cfdf3db1b264a6fe0963eb9d996a7a1fa843ac406c1e32111f8"},
|
||||
{file = "pywinpty-2.0.5-cp38-none-win_amd64.whl", hash = "sha256:651ee1467bd7eb6f64d44dbc954b7ab7d15ab6d8adacc4e13299692c67c5d5d2"},
|
||||
{file = "pywinpty-2.0.5-cp39-none-win_amd64.whl", hash = "sha256:e59a508ae78374febada3e53b5bbc90b5ad07ae68cbfd72a2e965f9793ae04f3"},
|
||||
{file = "pywinpty-2.0.5.tar.gz", hash = "sha256:e125d3f1804d8804952b13e33604ad2ca8b9b2cac92b27b521c005d1604794f8"},
|
||||
]
|
||||
pyyaml = [
|
||||
{file = "PyYAML-6.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d4db7c7aef085872ef65a8fd7d6d09a14ae91f691dec3e87ee5ee0539d516f53"},
|
||||
|
|
@ -2705,8 +2775,8 @@ ray = [
|
|||
{file = "ray-1.13.0-cp39-cp39-win_amd64.whl", hash = "sha256:6586fd313e0665f1d0e1fc6deca910421d1a963c56711383f89931e0521942fd"},
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||||
]
|
||||
requests = [
|
||||
{file = "requests-2.28.1-py3-none-any.whl", hash = "sha256:8fefa2a1a1365bf5520aac41836fbee479da67864514bdb821f31ce07ce65349"},
|
||||
{file = "requests-2.28.1.tar.gz", hash = "sha256:7c5599b102feddaa661c826c56ab4fee28bfd17f5abca1ebbe3e7f19d7c97983"},
|
||||
{file = "requests-2.28.0-py3-none-any.whl", hash = "sha256:bc7861137fbce630f17b03d3ad02ad0bf978c844f3536d0edda6499dafce2b6f"},
|
||||
{file = "requests-2.28.0.tar.gz", hash = "sha256:d568723a7ebd25875d8d1eaf5dfa068cd2fc8194b2e483d7b1f7c81918dbec6b"},
|
||||
]
|
||||
scipy = [
|
||||
{file = "scipy-1.8.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:65b77f20202599c51eb2771d11a6b899b97989159b7975e9b5259594f1d35ef4"},
|
||||
|
|
@ -2738,8 +2808,8 @@ send2trash = [
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|||
{file = "Send2Trash-1.8.0.tar.gz", hash = "sha256:d2c24762fd3759860a0aff155e45871447ea58d2be6bdd39b5c8f966a0c99c2d"},
|
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|
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setuptools-scm = [
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||||
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|
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{file = "setuptools_scm-7.0.2.tar.gz", hash = "sha256:53afbaa882f43e5ec8e14f2d93b9c268dc62eb3f6cc8b2790f8cb97903e53c02"},
|
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]
|
||||
six = [
|
||||
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
|
||||
|
|
@ -2800,17 +2870,47 @@ tomli = [
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|||
{file = "tomli-1.2.3.tar.gz", hash = "sha256:05b6166bff487dc068d322585c7ea4ef78deed501cc124060e0f238e89a9231f"},
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|
||||
tornado = [
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||||
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|
||||
{file = "tornado-6.1-cp35-cp35m-manylinux1_i686.whl", hash = "sha256:0d321a39c36e5f2c4ff12b4ed58d41390460f798422c4504e09eb5678e09998c"},
|
||||
{file = "tornado-6.1-cp35-cp35m-manylinux1_x86_64.whl", hash = "sha256:9de9e5188a782be6b1ce866e8a51bc76a0fbaa0e16613823fc38e4fc2556ad05"},
|
||||
{file = "tornado-6.1-cp35-cp35m-manylinux2010_i686.whl", hash = "sha256:61b32d06ae8a036a6607805e6720ef00a3c98207038444ba7fd3d169cd998910"},
|
||||
{file = "tornado-6.1-cp35-cp35m-manylinux2010_x86_64.whl", hash = "sha256:3e63498f680547ed24d2c71e6497f24bca791aca2fe116dbc2bd0ac7f191691b"},
|
||||
{file = "tornado-6.1-cp35-cp35m-manylinux2014_aarch64.whl", hash = "sha256:6c77c9937962577a6a76917845d06af6ab9197702a42e1346d8ae2e76b5e3675"},
|
||||
{file = "tornado-6.1-cp35-cp35m-win32.whl", hash = "sha256:6286efab1ed6e74b7028327365cf7346b1d777d63ab30e21a0f4d5b275fc17d5"},
|
||||
{file = "tornado-6.1-cp35-cp35m-win_amd64.whl", hash = "sha256:fa2ba70284fa42c2a5ecb35e322e68823288a4251f9ba9cc77be04ae15eada68"},
|
||||
{file = "tornado-6.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:0a00ff4561e2929a2c37ce706cb8233b7907e0cdc22eab98888aca5dd3775feb"},
|
||||
{file = "tornado-6.1-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:748290bf9112b581c525e6e6d3820621ff020ed95af6f17fedef416b27ed564c"},
|
||||
{file = "tornado-6.1-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:e385b637ac3acaae8022e7e47dfa7b83d3620e432e3ecb9a3f7f58f150e50921"},
|
||||
{file = "tornado-6.1-cp36-cp36m-manylinux2010_i686.whl", hash = "sha256:25ad220258349a12ae87ede08a7b04aca51237721f63b1808d39bdb4b2164558"},
|
||||
{file = "tornado-6.1-cp36-cp36m-manylinux2010_x86_64.whl", hash = "sha256:65d98939f1a2e74b58839f8c4dab3b6b3c1ce84972ae712be02845e65391ac7c"},
|
||||
{file = "tornado-6.1-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:e519d64089b0876c7b467274468709dadf11e41d65f63bba207e04217f47c085"},
|
||||
{file = "tornado-6.1-cp36-cp36m-win32.whl", hash = "sha256:b87936fd2c317b6ee08a5741ea06b9d11a6074ef4cc42e031bc6403f82a32575"},
|
||||
{file = "tornado-6.1-cp36-cp36m-win_amd64.whl", hash = "sha256:cc0ee35043162abbf717b7df924597ade8e5395e7b66d18270116f8745ceb795"},
|
||||
{file = "tornado-6.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:7250a3fa399f08ec9cb3f7b1b987955d17e044f1ade821b32e5f435130250d7f"},
|
||||
{file = "tornado-6.1-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:ed3ad863b1b40cd1d4bd21e7498329ccaece75db5a5bf58cd3c9f130843e7102"},
|
||||
{file = "tornado-6.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:dcef026f608f678c118779cd6591c8af6e9b4155c44e0d1bc0c87c036fb8c8c4"},
|
||||
{file = "tornado-6.1-cp37-cp37m-manylinux2010_i686.whl", hash = "sha256:70dec29e8ac485dbf57481baee40781c63e381bebea080991893cd297742b8fd"},
|
||||
{file = "tornado-6.1-cp37-cp37m-manylinux2010_x86_64.whl", hash = "sha256:d3f7594930c423fd9f5d1a76bee85a2c36fd8b4b16921cae7e965f22575e9c01"},
|
||||
{file = "tornado-6.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:3447475585bae2e77ecb832fc0300c3695516a47d46cefa0528181a34c5b9d3d"},
|
||||
{file = "tornado-6.1-cp37-cp37m-win32.whl", hash = "sha256:e7229e60ac41a1202444497ddde70a48d33909e484f96eb0da9baf8dc68541df"},
|
||||
{file = "tornado-6.1-cp37-cp37m-win_amd64.whl", hash = "sha256:cb5ec8eead331e3bb4ce8066cf06d2dfef1bfb1b2a73082dfe8a161301b76e37"},
|
||||
{file = "tornado-6.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:20241b3cb4f425e971cb0a8e4ffc9b0a861530ae3c52f2b0434e6c1b57e9fd95"},
|
||||
{file = "tornado-6.1-cp38-cp38-manylinux1_i686.whl", hash = "sha256:c77da1263aa361938476f04c4b6c8916001b90b2c2fdd92d8d535e1af48fba5a"},
|
||||
{file = "tornado-6.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:fba85b6cd9c39be262fcd23865652920832b61583de2a2ca907dbd8e8a8c81e5"},
|
||||
{file = "tornado-6.1-cp38-cp38-manylinux2010_i686.whl", hash = "sha256:1e8225a1070cd8eec59a996c43229fe8f95689cb16e552d130b9793cb570a288"},
|
||||
{file = "tornado-6.1-cp38-cp38-manylinux2010_x86_64.whl", hash = "sha256:d14d30e7f46a0476efb0deb5b61343b1526f73ebb5ed84f23dc794bdb88f9d9f"},
|
||||
{file = "tornado-6.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:8f959b26f2634a091bb42241c3ed8d3cedb506e7c27b8dd5c7b9f745318ddbb6"},
|
||||
{file = "tornado-6.1-cp38-cp38-win32.whl", hash = "sha256:34ca2dac9e4d7afb0bed4677512e36a52f09caa6fded70b4e3e1c89dbd92c326"},
|
||||
{file = "tornado-6.1-cp38-cp38-win_amd64.whl", hash = "sha256:6196a5c39286cc37c024cd78834fb9345e464525d8991c21e908cc046d1cc02c"},
|
||||
{file = "tornado-6.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f0ba29bafd8e7e22920567ce0d232c26d4d47c8b5cf4ed7b562b5db39fa199c5"},
|
||||
{file = "tornado-6.1-cp39-cp39-manylinux1_i686.whl", hash = "sha256:33892118b165401f291070100d6d09359ca74addda679b60390b09f8ef325ffe"},
|
||||
{file = "tornado-6.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:7da13da6f985aab7f6f28debab00c67ff9cbacd588e8477034c0652ac141feea"},
|
||||
{file = "tornado-6.1-cp39-cp39-manylinux2010_i686.whl", hash = "sha256:e0791ac58d91ac58f694d8d2957884df8e4e2f6687cdf367ef7eb7497f79eaa2"},
|
||||
{file = "tornado-6.1-cp39-cp39-manylinux2010_x86_64.whl", hash = "sha256:66324e4e1beede9ac79e60f88de548da58b1f8ab4b2f1354d8375774f997e6c0"},
|
||||
{file = "tornado-6.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:a48900ecea1cbb71b8c71c620dee15b62f85f7c14189bdeee54966fbd9a0c5bd"},
|
||||
{file = "tornado-6.1-cp39-cp39-win32.whl", hash = "sha256:d3d20ea5782ba63ed13bc2b8c291a053c8d807a8fa927d941bd718468f7b950c"},
|
||||
{file = "tornado-6.1-cp39-cp39-win_amd64.whl", hash = "sha256:548430be2740e327b3fe0201abe471f314741efcb0067ec4f2d7dcfb4825f3e4"},
|
||||
{file = "tornado-6.1.tar.gz", hash = "sha256:33c6e81d7bd55b468d2e793517c909b139960b6c790a60b7991b9b6b76fb9791"},
|
||||
]
|
||||
tqdm = [
|
||||
{file = "tqdm-4.64.0-py2.py3-none-any.whl", hash = "sha256:74a2cdefe14d11442cedf3ba4e21a3b84ff9a2dbdc6cfae2c34addb2a14a5ea6"},
|
||||
|
|
@ -2821,18 +2921,21 @@ traitlets = [
|
|||
{file = "traitlets-5.2.0.tar.gz", hash = "sha256:60474f39bf1d39a11e0233090b99af3acee93bbc2281777e61dd8c87da8a0014"},
|
||||
]
|
||||
typer = [
|
||||
{file = "typer-0.4.2-py3-none-any.whl", hash = "sha256:023bae00d1baf358a6cc7cea45851639360bb716de687b42b0a4641cd99173f1"},
|
||||
{file = "typer-0.4.2.tar.gz", hash = "sha256:b8261c6c0152dd73478b5ba96ba677e5d6948c715c310f7c91079f311f62ec03"},
|
||||
{file = "typer-0.4.1-py3-none-any.whl", hash = "sha256:e8467f0ebac0c81366c2168d6ad9f888efdfb6d4e1d3d5b4a004f46fa444b5c3"},
|
||||
{file = "typer-0.4.1.tar.gz", hash = "sha256:5646aef0d936b2c761a10393f0384ee6b5c7fe0bb3e5cd710b17134ca1d99cff"},
|
||||
]
|
||||
typing-extensions = [
|
||||
{file = "typing_extensions-4.3.0-py3-none-any.whl", hash = "sha256:25642c956049920a5aa49edcdd6ab1e06d7e5d467fc00e0506c44ac86fbfca02"},
|
||||
{file = "typing_extensions-4.3.0.tar.gz", hash = "sha256:e6d2677a32f47fc7eb2795db1dd15c1f34eff616bcaf2cfb5e997f854fa1c4a6"},
|
||||
{file = "typing_extensions-4.2.0-py3-none-any.whl", hash = "sha256:6657594ee297170d19f67d55c05852a874e7eb634f4f753dbd667855e07c1708"},
|
||||
{file = "typing_extensions-4.2.0.tar.gz", hash = "sha256:f1c24655a0da0d1b67f07e17a5e6b2a105894e6824b92096378bb3668ef02376"},
|
||||
]
|
||||
uncertainties = [
|
||||
{file = "uncertainties-3.1.7-py2.py3-none-any.whl", hash = "sha256:4040ec64d298215531922a68fa1506dc6b1cb86cd7cca8eca848fcfe0f987151"},
|
||||
{file = "uncertainties-3.1.7.tar.gz", hash = "sha256:80111e0839f239c5b233cb4772017b483a0b7a1573a581b92ab7746a35e6faab"},
|
||||
]
|
||||
urllib3 = []
|
||||
urllib3 = [
|
||||
{file = "urllib3-1.26.9-py2.py3-none-any.whl", hash = "sha256:44ece4d53fb1706f667c9bd1c648f5469a2ec925fcf3a776667042d645472c14"},
|
||||
{file = "urllib3-1.26.9.tar.gz", hash = "sha256:aabaf16477806a5e1dd19aa41f8c2b7950dd3c746362d7e3223dbe6de6ac448e"},
|
||||
]
|
||||
virtualenv = [
|
||||
{file = "virtualenv-20.15.1-py2.py3-none-any.whl", hash = "sha256:b30aefac647e86af6d82bfc944c556f8f1a9c90427b2fb4e3bfbf338cb82becf"},
|
||||
{file = "virtualenv-20.15.1.tar.gz", hash = "sha256:288171134a2ff3bfb1a2f54f119e77cd1b81c29fc1265a2356f3e8d14c7d58c4"},
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue