mirror of
https://github.com/vale981/master-thesis
synced 2025-03-05 18:11:42 -05:00
update and try to use their ridiculous temperatures
This commit is contained in:
parent
1eadea8aeb
commit
3d0fe1d7d5
3 changed files with 156 additions and 96 deletions
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@ -14,7 +14,7 @@ import matplotlib
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import ray
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ray.shutdown()
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ray.init()
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ray.init(address="auto")
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from hops.util.logging_setup import logging_setup
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import logging
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@ -42,6 +42,7 @@ def anti_zeno_engine(
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L_mat=qt.sigmax().full(),
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therm_methods=["fft", "fft"],
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terms=5,
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sp_tol=1e-5,
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):
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# τ_bath = 1 / ω_c
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τ_mod = 2 * np.pi / Δ
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@ -125,7 +126,7 @@ def anti_zeno_engine(
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)
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)
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* np.sqrt(δ_init),
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ConstantMatrix(np.zeros((2,2))),
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ConstantMatrix(np.zeros((2, 2))),
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Shift(
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L,
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initializing_period + τ_off,
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@ -149,8 +150,8 @@ def anti_zeno_engine(
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k_max=4,
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bcf_terms=[terms, terms],
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truncation_scheme="simplex",
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driving_process_tolerances=[StocProcTolerances(1e-5, 1e-5)] * 2,
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thermal_process_tolerances=[StocProcTolerances(1e-5, 1e-5)] * 2,
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driving_process_tolerances=[StocProcTolerances(sp_tol, sp_tol)] * 2,
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thermal_process_tolerances=[StocProcTolerances(sp_tol, sp_tol)] * 2,
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T=[T_c, T_h],
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L=[L] * 2,
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H=H,
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@ -185,12 +186,12 @@ def anti_zeno_engine(
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ε=.05,#.1,
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ω_c=1,
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ε_couple=0.7,
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n=5,
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n=2,
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detune=.5,
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ω_0=20,
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T_c=10,
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T_h=40,
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δ=[2.2, 1],
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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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γ=.2,
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switch_cycles=1,
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therm_initial_state=False,
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@ -198,6 +199,7 @@ def anti_zeno_engine(
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ε_init=0.1,
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terms=6,
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dt=0.01,
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sp_tol=1e-4,
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)
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model.k_max = 4
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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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@ -240,7 +242,7 @@ ts = np.linspace(0,50,1000)
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fig, ax = fs.plot_complex(ts, model.bcf(0)(ts))
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fs.plot_complex(ts, model.thermal_correlations(0)(ts))
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proc = model.thermal_process(0)
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proc = model.thermal_process(1)
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import hops
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z=hops.core.utility.uni_to_gauss(np.random.rand(proc.get_num_y() * 2))
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proc.new_process(z)
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@ -255,7 +257,7 @@ 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, 10000)
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aux.integrate(model, 10)
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#_, ax = fs.plot_energy_overview(model, markersize=1, ensemble_args=dict(gc_sleep=0.05))
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@ -22,11 +22,14 @@ Init ray and silence stocproc.
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#+begin_src jupyter-python
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import ray
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ray.shutdown()
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ray.init()
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ray.init(address="auto")
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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_2022-07-19_10-51-39_214259_16834/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-07-19_10-51-39_214259_16834/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-07-19_10-51-39_214259_16834', 'metrics_export_port': 60152, 'gcs_address': '141.30.17.225:63172', 'address': '141.30.17.225:63172', 'node_id': '252db7cc012cbe0a60910f26a48f27f9f26859d4f26657a03a5bf00a'})
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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'})2022-07-19 16:17:37,436 INFO worker.py:956 -- Connecting to existing Ray cluster at address: 141.30.17.16:6379
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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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:END:
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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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@ -58,6 +61,7 @@ Init ray and silence stocproc.
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L_mat=qt.sigmax().full(),
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therm_methods=["fft", "fft"],
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terms=5,
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sp_tol=1e-5,
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):
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# τ_bath = 1 / ω_c
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τ_mod = 2 * np.pi / Δ
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@ -141,7 +145,7 @@ Init ray and silence stocproc.
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)
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)
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,* np.sqrt(δ_init),
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ConstantMatrix(np.zeros((2,2))),
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ConstantMatrix(np.zeros((2, 2))),
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Shift(
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L,
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initializing_period + τ_off,
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@ -165,8 +169,8 @@ Init ray and silence stocproc.
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k_max=4,
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bcf_terms=[terms, terms],
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truncation_scheme="simplex",
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driving_process_tolerances=[StocProcTolerances(1e-5, 1e-5)] * 2,
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thermal_process_tolerances=[StocProcTolerances(1e-5, 1e-5)] * 2,
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driving_process_tolerances=[StocProcTolerances(sp_tol, sp_tol)] * 2,
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thermal_process_tolerances=[StocProcTolerances(sp_tol, sp_tol)] * 2,
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T=[T_c, T_h],
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L=[L] * 2,
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H=H,
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@ -204,12 +208,12 @@ Init ray and silence stocproc.
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ε=.05,#.1,
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ω_c=1,
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ε_couple=0.7,
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n=5,
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n=2,
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detune=.5,
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ω_0=20,
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T_c=10,
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T_h=40,
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δ=[2.2, 1],
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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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γ=.2,
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switch_cycles=1,
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therm_initial_state=False,
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@ -217,6 +221,7 @@ Init ray and silence stocproc.
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ε_init=0.1,
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terms=6,
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dt=0.01,
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sp_tol=1e-4,
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)
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model.k_max = 4
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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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@ -255,7 +260,7 @@ Init ray and silence stocproc.
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#+end_src
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#+RESULTS:
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| \(α(0)=1.1\) | \(ω_0=20\) | \(γ=0.5\) | \(Δ=11\) | \(T_c=10\) | \(T_h=40\) |
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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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Let's test the assumptions of the paper.
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@ -284,18 +289,17 @@ Let's test the assumptions of the paper.
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#+RESULTS:
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:RESULTS:
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: <matplotlib.legend.Legend at 0x7fec4ac9fee0>
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[[file:./.ob-jupyter/e87eb72fe5dfd2a77714413ec7469c1c591aced9.svg]]
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: <matplotlib.legend.Legend at 0x7fb9d2c70850>
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[[file:./.ob-jupyter/e3bbb4efab98d84348844c37a4aa9384d48cdc15.svg]]
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:END:
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#+begin_src jupyter-python :tangle nil
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ωs = np.linspace(0.01, 4 * ω_0, 10000)
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def total_sd(n, ω):
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return model.bcf_scales[n] * (
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model.spectral_density(n)(ω)
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* (1/(np.expm1(ω / model.T[n]) - 1) + np.heaviside(ω, 0))
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,* (1/(np.expm1(ω / model.T[n])) + np.heaviside(ω, 0))
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)
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@ -338,8 +342,8 @@ Let's test the assumptions of the paper.
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#+RESULTS:
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:RESULTS:
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[[file:./.ob-jupyter/dc15ee10981f51398bfde454ebb8808a8da10037.svg]]
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[[file:./.ob-jupyter/a643f51530ed06a31439d0e6949011fccef4e3e6.svg]]
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[[file:./.ob-jupyter/48e681a6140e19141ec80f8e22cfb5c578e97452.svg]]
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[[file:./.ob-jupyter/d13566fe82dc8c85a4376af366ddb38f4643c6e4.svg]]
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:END:
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#+begin_src jupyter-python
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@ -351,12 +355,12 @@ Let's test the assumptions of the paper.
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#+RESULTS:
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:RESULTS:
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| <Figure | size | 432x288 | with | 1 | Axes> | <AxesSubplot:> |
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[[file:./.ob-jupyter/4341159d7693d59e6f76c5305942671c13587b7a.svg]]
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[[file:./.ob-jupyter/71cba43a3ab882492f3132c0c621975f4a1cd86d.svg]]
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[[file:./.ob-jupyter/533ffeef663f158f1eb3ebccbf211ec3a6ff45b2.svg]]
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[[file:./.ob-jupyter/b9dca795dc334e8536ef2fdc9e04e574651ae7f7.svg]]
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:END:
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#+begin_src jupyter-python
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proc = model.thermal_process(0)
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proc = model.thermal_process(1)
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import hops
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z=hops.core.utility.uni_to_gauss(np.random.rand(proc.get_num_y() * 2))
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proc.new_process(z)
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@ -364,10 +368,7 @@ Let's test the assumptions of the paper.
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#+end_src
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#+RESULTS:
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:RESULTS:
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| <Figure | size | 432x288 | with | 1 | Axes> | <AxesSubplot:> |
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[[file:./.ob-jupyter/ed0e8d32f6fd3956cb0c72e0c52e3d695c31f5e2.svg]]
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:END:
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: bbc5aaaa-6ed1-4dfb-b3af-7e0a7857708b
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#+begin_src jupyter-python :results none
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@ -390,11 +391,94 @@ Let's test the assumptions of the paper.
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:END:
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** TODO Integration
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** Integration
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#+begin_src jupyter-python
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aux.integrate(model, 10000)
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aux.integrate(model, 10)
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#+end_src
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#+RESULTS:
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:RESULTS:
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#+begin_example
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[INFO hops.core.integration 92605] Choosing the nonlinear integrator.
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[INFO hops.core.integration 92605] Using 9 integrators.
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[INFO hops.core.integration 92605] Some 10 trajectories have to be integrated.
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[INFO hops.core.integration 92605] Using 1820 hierarchy states.
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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.
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[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.
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[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.
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[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.
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[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.
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[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.
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[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.
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[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.
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[INFO hops.core.signal_delay 92605] caught sig 'SIGINT'
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[INFO hops.core.signal_delay 92605] caught sig 'SIGINT'
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10% 1/10 [06:48<1:01:14, 408.33s/it]
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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.
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[INFO hops.core.signal_delay 92605] caught 2 signal(s)
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[INFO hops.core.signal_delay 92605] emit signal 'SIGINT'
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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#+end_example
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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 [10][0m, in [0;36m<cell line: 1>[0;34m()[0m
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[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
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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
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[1;32m 98[0m [38;5;66;03m# with model_db(data_path) as db:[39;00m
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[1;32m 99[0m [38;5;66;03m# if hash in db and "data" db[hash][39;00m
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[1;32m 101[0m supervisor [38;5;241m=[39m HOPSSupervisor(
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[1;32m 102[0m model[38;5;241m.[39mhops_config,
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[1;32m 103[0m n,
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[1;32m 104[0m data_path[38;5;241m=[39mdata_path,
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[1;32m 105[0m data_name[38;5;241m=[39m[38;5;28mhash[39m,
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[1;32m 106[0m )
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[0;32m--> 108[0m [43msupervisor[49m[38;5;241;43m.[39;49m[43mintegrate[49m[43m([49m[43mclear_pd[49m[43m)[49m
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[1;32m 110[0m [38;5;28;01mwith[39;00m supervisor[38;5;241m.[39mget_data([38;5;28;01mTrue[39;00m) [38;5;28;01mas[39;00m data:
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[1;32m 111[0m [38;5;28;01mwith[39;00m model_db(data_path) [38;5;28;01mas[39;00m db:
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File [0;32m~/src/hops/hops/core/integration.py:1288[0m, in [0;36mHOPSSupervisor.integrate[0;34m(self, clear_pd)[0m
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[1;32m 1285[0m [38;5;28;01mbreak[39;00m
|
||||
[1;32m 1287[0m integration[38;5;241m.[39mupdate()
|
||||
[0;32m-> 1288[0m data[38;5;241m.[39mnew_samples(
|
||||
[1;32m 1289[0m idx[38;5;241m=[39mindex,
|
||||
[1;32m 1290[0m incomplete[38;5;241m=[39mincomplete,
|
||||
[1;32m 1291[0m psi0[38;5;241m=[39mpsi0,
|
||||
[1;32m 1292[0m aux_states[38;5;241m=[39maux_states,
|
||||
[1;32m 1293[0m stoc_proc[38;5;241m=[39mstoc_proc,
|
||||
[1;32m 1294[0m result_type[38;5;241m=[39m[38;5;28mself[39m[38;5;241m.[39mparams[38;5;241m.[39mHiP[38;5;241m.[39mresult_type,
|
||||
[1;32m 1295[0m normed[38;5;241m=[39m[38;5;28mself[39m[38;5;241m.[39m_normed_average,
|
||||
[1;32m 1296[0m rng_seed[38;5;241m=[39mseed,
|
||||
[1;32m 1297[0m )
|
||||
|
||||
File [0;32m~/src/hops/hops/core/signal_delay.py:87[0m, in [0;36msig_delay.__exit__[0;34m(self, exc_type, exc_val, exc_tb)[0m
|
||||
[1;32m 84[0m [38;5;28;01mif[39;00m [38;5;28mlen[39m([38;5;28mself[39m[38;5;241m.[39msigh[38;5;241m.[39msigs_caught) [38;5;241m>[39m [38;5;241m0[39m [38;5;129;01mand[39;00m [38;5;28mself[39m[38;5;241m.[39mhandler [38;5;129;01mis[39;00m [38;5;129;01mnot[39;00m [38;5;28;01mNone[39;00m:
|
||||
[1;32m 85[0m [38;5;28mself[39m[38;5;241m.[39mhandler([38;5;28mself[39m[38;5;241m.[39msigh[38;5;241m.[39msigs_caught)
|
||||
[0;32m---> 87[0m [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43m_restore[49m[43m([49m[43m)[49m
|
||||
|
||||
File [0;32m~/src/hops/hops/core/signal_delay.py:68[0m, in [0;36msig_delay._restore[0;34m(self)[0m
|
||||
[1;32m 66[0m [38;5;28;01mfor[39;00m i, s [38;5;129;01min[39;00m [38;5;28menumerate[39m([38;5;28mself[39m[38;5;241m.[39msigs):
|
||||
[1;32m 67[0m signal[38;5;241m.[39msignal(s, [38;5;28mself[39m[38;5;241m.[39mold_handlers[i])
|
||||
[0;32m---> 68[0m [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43msigh[49m[38;5;241;43m.[39;49m[43memit[49m[43m([49m[43m)[49m
|
||||
|
||||
File [0;32m~/src/hops/hops/core/signal_delay.py:42[0m, in [0;36mSigHandler.emit[0;34m(self)[0m
|
||||
[1;32m 40[0m [38;5;28;01mfor[39;00m s [38;5;129;01min[39;00m [38;5;28mself[39m[38;5;241m.[39msigs_caught:
|
||||
[1;32m 41[0m log[38;5;241m.[39minfo([38;5;124m"[39m[38;5;124memit signal [39m[38;5;124m'[39m[38;5;132;01m{}[39;00m[38;5;124m'[39m[38;5;124m"[39m[38;5;241m.[39mformat(SIG_MAP[s]))
|
||||
[0;32m---> 42[0m [43mos[49m[38;5;241;43m.[39;49m[43mkill[49m[43m([49m[43mos[49m[38;5;241;43m.[39;49m[43mgetpid[49m[43m([49m[43m)[49m[43m,[49m[43m [49m[43ms[49m[43m)[49m
|
||||
|
||||
[0;31mKeyboardInterrupt[0m:
|
||||
#+end_example
|
||||
:END:
|
||||
|
||||
|
||||
#+begin_src jupyter-python
|
||||
#_, ax = fs.plot_energy_overview(model, markersize=1, ensemble_args=dict(gc_sleep=0.05))
|
||||
|
|
@ -486,6 +570,30 @@ We need the time points where we sample the total energy.
|
|||
#+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
|
||||
|
|
|
|||
|
|
@ -304,7 +304,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
|||
|
||||
[[package]]
|
||||
name = "distlib"
|
||||
version = "0.3.4"
|
||||
version = "0.3.5"
|
||||
description = "Distribution utilities"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -328,7 +328,7 @@ python-versions = "*"
|
|||
|
||||
[[package]]
|
||||
name = "fastjsonschema"
|
||||
version = "2.15.3"
|
||||
version = "2.16.1"
|
||||
description = "Fastest Python implementation of JSON schema"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -650,7 +650,7 @@ i18n = ["Babel (>=2.7)"]
|
|||
|
||||
[[package]]
|
||||
name = "jsonschema"
|
||||
version = "4.7.1"
|
||||
version = "4.7.2"
|
||||
description = "An implementation of JSON Schema validation for Python"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -752,7 +752,7 @@ python-versions = ">=3.6"
|
|||
|
||||
[[package]]
|
||||
name = "kiwisolver"
|
||||
version = "1.4.3"
|
||||
version = "1.4.4"
|
||||
description = "A fast implementation of the Cassowary constraint solver"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -1407,7 +1407,7 @@ win32 = ["pywin32"]
|
|||
|
||||
[[package]]
|
||||
name = "setuptools-scm"
|
||||
version = "7.0.4"
|
||||
version = "7.0.5"
|
||||
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 = "0035c0185a1dbc717d30ac22485020d59c865094"
|
||||
resolved_reference = "3a9bd00a454239411b4f110f1884ccac068894a4"
|
||||
|
||||
[[package]]
|
||||
name = "tabulate"
|
||||
|
|
@ -1908,10 +1908,7 @@ 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 = [
|
||||
{file = "distlib-0.3.4-py2.py3-none-any.whl", hash = "sha256:6564fe0a8f51e734df6333d08b8b94d4ea8ee6b99b5ed50613f731fd4089f34b"},
|
||||
{file = "distlib-0.3.4.zip", hash = "sha256:e4b58818180336dc9c529bfb9a0b58728ffc09ad92027a3f30b7cd91e3458579"},
|
||||
]
|
||||
distlib = []
|
||||
entrypoints = [
|
||||
{file = "entrypoints-0.4-py3-none-any.whl", hash = "sha256:f174b5ff827504fd3cd97cc3f8649f3693f51538c7e4bdf3ef002c8429d42f9f"},
|
||||
{file = "entrypoints-0.4.tar.gz", hash = "sha256:b706eddaa9218a19ebcd67b56818f05bb27589b1ca9e8d797b74affad4ccacd4"},
|
||||
|
|
@ -1920,10 +1917,7 @@ 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 = [
|
||||
{file = "fastjsonschema-2.15.3-py3-none-any.whl", hash = "sha256:ddb0b1d8243e6e3abb822bd14e447a89f4ab7439342912d590444831fa00b6a0"},
|
||||
{file = "fastjsonschema-2.15.3.tar.gz", hash = "sha256:0a572f0836962d844c1fc435e200b2e4f4677e4e6611a2e3bdd01ba697c275ec"},
|
||||
]
|
||||
fastjsonschema = []
|
||||
fcspline = []
|
||||
filelock = [
|
||||
{file = "filelock-3.7.1-py3-none-any.whl", hash = "sha256:37def7b658813cda163b56fc564cdc75e86d338246458c4c28ae84cabefa2404"},
|
||||
|
|
@ -2117,51 +2111,7 @@ 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 = [
|
||||
{file = "kiwisolver-1.4.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:fd2842a0faed9ab9aba0922c951906132d9384be89690570f0ed18cd4f20e658"},
|
||||
{file = "kiwisolver-1.4.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:caa59e2cae0e23b1e225447d7a9ddb0f982f42a6a22d497a484dfe62a06f7c0e"},
|
||||
{file = "kiwisolver-1.4.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1d2c744aeedce22c122bb42d176b4aa6d063202a05a4abdacb3e413c214b3694"},
|
||||
{file = "kiwisolver-1.4.3-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:afe173ac2646c2636305ab820cc0380b22a00a7bca4290452e7166b4f4fa49d0"},
|
||||
{file = "kiwisolver-1.4.3-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:40240da438c0ebfe2aa76dd04b844effac6679423df61adbe3437d32f23468d9"},
|
||||
{file = "kiwisolver-1.4.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:21a3a98f0a21fc602663ca9bce2b12a4114891bdeba2dea1e9ad84db59892fca"},
|
||||
{file = "kiwisolver-1.4.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:51078855a16b7a4984ed2067b54e35803d18bca9861cb60c60f6234b50869a56"},
|
||||
{file = "kiwisolver-1.4.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c16635f8dddbeb1b827977d0b00d07b644b040aeb9ff8607a9fc0997afa3e567"},
|
||||
{file = "kiwisolver-1.4.3-cp310-cp310-win32.whl", hash = "sha256:2d76780d9c65c7529cedd49fa4802d713e60798d8dc3b0d5b12a0a8f38cca51c"},
|
||||
{file = "kiwisolver-1.4.3-cp310-cp310-win_amd64.whl", hash = "sha256:3a297d77b3d6979693f5948df02b89431ae3645ec95865e351fb45578031bdae"},
|
||||
{file = "kiwisolver-1.4.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:ca3eefb02ef17257fae8b8555c85e7c1efdfd777f671384b0e4ef27409b02720"},
|
||||
{file = "kiwisolver-1.4.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d248c46c0aa406695bda2abf99632db991f8b3a6d46018721a2892312a99f069"},
|
||||
{file = "kiwisolver-1.4.3-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cb55258931448d61e2d50187de4ee66fc9d9f34908b524949b8b2b93d0c57136"},
|
||||
{file = "kiwisolver-1.4.3-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:86bcf0009f2012847a688f2f4f9b16203ca4c835979a02549aa0595d9f457cc8"},
|
||||
{file = "kiwisolver-1.4.3-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e7cf940af5fee00a92e281eb157abe8770227a5255207818ea9a34e54a29f5b2"},
|
||||
{file = "kiwisolver-1.4.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:dd22085446f3eca990d12a0878eeb5199dc9553b2e71716bfe7bed9915a472ab"},
|
||||
{file = "kiwisolver-1.4.3-cp37-cp37m-win32.whl", hash = "sha256:d2578e5149ff49878934debfacf5c743fab49eca5ecdb983d0b218e1e554c498"},
|
||||
{file = "kiwisolver-1.4.3-cp37-cp37m-win_amd64.whl", hash = "sha256:5fb73cc8a34baba1dfa546ae83b9c248ef6150c238b06fc53d2773685b67ec67"},
|
||||
{file = "kiwisolver-1.4.3-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:f70f3d028794e31cf9d1a822914efc935aadb2438ec4e8d4871d95eb1ce032d6"},
|
||||
{file = "kiwisolver-1.4.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:71af5b43e4fa286a35110fc5bb740fdeae2b36ca79fbcf0a54237485baeee8be"},
|
||||
{file = "kiwisolver-1.4.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:26b5a70bdab09e6a2f40babc4f8f992e3771751e144bda1938084c70d3001c09"},
|
||||
{file = "kiwisolver-1.4.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1858ad3cb686eccc7c6b7c5eac846a1cfd45aacb5811b2cf575e80b208f5622a"},
|
||||
{file = "kiwisolver-1.4.3-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4dc350cb65fe4e3f737d50f0465fa6ea0dcae0e5722b7edf5d5b0a0e3cd2c3c7"},
|
||||
{file = "kiwisolver-1.4.3-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:007799c7fa934646318fc128b033bb6e6baabe7fbad521bfb2279aac26225cd7"},
|
||||
{file = "kiwisolver-1.4.3-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:46fb56fde006b7ef5f8eaa3698299b0ea47444238b869ff3ced1426aa9fedcb5"},
|
||||
{file = "kiwisolver-1.4.3-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:b9eb88593159a53a5ee0b0159daee531ff7dd9c87fa78f5d807ca059c7eb1b2b"},
|
||||
{file = "kiwisolver-1.4.3-cp38-cp38-win32.whl", hash = "sha256:3b1dcbc49923ac3c973184a82832e1f018dec643b1e054867d04a3a22255ec6a"},
|
||||
{file = "kiwisolver-1.4.3-cp38-cp38-win_amd64.whl", hash = "sha256:7118ca592d25b2957ff7b662bc0fe4f4c2b5d5b27814b9b1bc9f2fb249a970e7"},
|
||||
{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"},
|
||||
]
|
||||
kiwisolver = []
|
||||
lmfit = [
|
||||
{file = "lmfit-1.0.3.tar.gz", hash = "sha256:d067c3ea501f035af5d3c079e6e6e35dc3cc1ac7d439429a425b0aeb5a7858a2"},
|
||||
]
|
||||
|
|
@ -2788,8 +2738,8 @@ send2trash = [
|
|||
{file = "Send2Trash-1.8.0.tar.gz", hash = "sha256:d2c24762fd3759860a0aff155e45871447ea58d2be6bdd39b5c8f966a0c99c2d"},
|
||||
]
|
||||
setuptools-scm = [
|
||||
{file = "setuptools_scm-7.0.4-py3-none-any.whl", hash = "sha256:53a6f51451a84d891ca485cec700a802413bbc5e76ee65da134e54c733a6e44d"},
|
||||
{file = "setuptools_scm-7.0.4.tar.gz", hash = "sha256:c27bc1f48593cfc9527251f1f0fc41ce282ea57bbc7fd5a1ea3acb99325fab4c"},
|
||||
{file = "setuptools_scm-7.0.5-py3-none-any.whl", hash = "sha256:7930f720905e03ccd1e1d821db521bff7ec2ac9cf0ceb6552dd73d24a45d3b02"},
|
||||
{file = "setuptools_scm-7.0.5.tar.gz", hash = "sha256:031e13af771d6f892b941adb6ea04545bbf91ebc5ce68c78aaf3fff6e1fb4844"},
|
||||
]
|
||||
six = [
|
||||
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue