code updates

python/otto_motor/baseline.py

@@ -0,0 +1,46 @@
+import figsaver as fs
+import plot_utils as pu
+from hiro_models.one_qubit_model import StocProcTolerances
+from hiro_models.otto_cycle import OttoEngine
+import hiro_models.model_auxiliary as aux
+import numpy as np
+import qutip as qt
+import utilities as ut
+import stocproc
+import matplotlib.pyplot as plt
+import otto_utilities as ot
+
+import ray
+ray.shutdown()
+
+ray.init(address='auto')
+#ray.init()
+from hops.util.logging_setup import logging_setup
+import logging
+logging_setup(logging.INFO)
+plt.rcParams['figure.figsize'] = (12,4)
+
+model = OttoEngine(
+    δ=[0.4, 0.4],
+    ω_c=[1, 1],
+    ψ_0=qt.basis([2], [1]),
+    description=f"A basic near-markovian, weakly coupled Otto Cycle that actually works.",
+    k_max=4,
+    bcf_terms=[6] * 2,
+    truncation_scheme="simplex",
+    driving_process_tolerances=[StocProcTolerances(1e-4, 1e-4)] * 2,
+    thermal_process_tolerances=[StocProcTolerances(1e-4, 1e-4)] * 2,
+    T=[1, 10],
+    therm_methods=["tanhsinh", "fft"],
+    Δ=1,
+    num_cycles=5,
+    Θ=1.5 / 0.05,
+    dt=0.001,
+    timings_H=(0, 0.1, 0.5, 0.6),
+    timings_L=((0.6, 0.7, 0.9, 1), (0.1, 0.2, 0.4, 0.5)),
+    streaming_mode=True,
+)
+
+ot.plot_cycle(model)
+
+ot.full_report(model)

python/otto_motor/baseline_cc.py

@@ -0,0 +1,46 @@
+import figsaver as fs
+import plot_utils as pu
+from hiro_models.one_qubit_model import StocProcTolerances
+from hiro_models.otto_cycle import OttoEngine
+import hiro_models.model_auxiliary as aux
+import numpy as np
+import qutip as qt
+import utilities as ut
+import stocproc
+import matplotlib.pyplot as plt
+import otto_utilities as ot
+
+import ray
+ray.shutdown()
+
+ray.init(address='auto')
+#ray.init()
+from hops.util.logging_setup import logging_setup
+import logging
+logging_setup(logging.INFO)
+plt.rcParams['figure.figsize'] = (12,4)
+
+model = OttoEngine(
+    δ=[0.4, 0.4],
+    ω_c=[1, 1],
+    ψ_0=qt.basis([2], [1]),
+    description=f"A basic near-markovian, weakly coupled Otto Cycle that actually works.",
+    k_max=4,
+    bcf_terms=[6] * 2,
+    truncation_scheme="simplex",
+    driving_process_tolerances=[StocProcTolerances(1e-4, 1e-4)] * 2,
+    thermal_process_tolerances=[StocProcTolerances(1e-4, 1e-4)] * 2,
+    T=[1, 10],
+    therm_methods=["tanhsinh", "fft"],
+    Δ=1,
+    num_cycles=5,
+    Θ=1.5 / 0.05,
+    dt=0.001,
+    timings_H=(0, 0.1, 0.5, 0.6),
+    timings_L=(None, None),
+    streaming_mode=True,
+)
+
+ot.plot_cycle(model)
+
+ot.integrate_online(model, 5000)

python/otto_motor/otto_baseline.org

@@ -2,7 +2,7 @@
 
 * Boilerplate
 #+name: boilerplate
-#+begin_src jupyter-python :results none :tangle otto_boilerplate.py
+#+begin_src jupyter-python :results none
     import figsaver as fs
     import plot_utils as pu
     from hiro_models.one_qubit_model import StocProcTolerances
@@ -73,7 +73,7 @@ A basic otto cycle that has a finite power output.
 : [INFO    hops.core.integration     143440] Using 1820 hierarchy states.
 : 0it [00:00, ?it/s]
 
-#+begin_src jupyter-python :tangle nilorg basics
+#+begin_src jupyter-python
   ot.full_report(model)
 #+end_src
 :RESULTS:
@@ -135,19 +135,19 @@ A basic otto cycle that has a finite power output without coupling modulation.
 :END:
 
 
-#+begin_src jupyter-python :tangle nil
+#+begin_src jupyter-python
   ot.integrate_online(model, 5000)
 #+end_src
 
 #+RESULTS:
 : [INFO    hops.core.integration     211210] Choosing the nonlinear integrator.
 : [INFO    root                      211210] Starting analysis process.
-: [INFO    root                      211210] Started analysis process with pid 621102.
+: [INFO    root                      211210] Started analysis process with pid 630343.
 : [INFO    hops.core.hierarchy_data  211210] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results_fea83562df42901b66a85396f98a6c69d504e3a6d3dcc59cb83c5f34ec4077ca.fifo
 : [INFO    hops.core.integration     211210] Using 32 integrators.
-: [INFO    hops.core.integration     211210] Some 343 trajectories have to be integrated.
+: [INFO    hops.core.integration     211210] Some 0 trajectories have to be integrated.
 : [INFO    hops.core.integration     211210] Using 1820 hierarchy states.
-: 100% 343/343 [06:21<00:00,  1.11s/it]
+: 0it [00:00, ?it/s]
 
 ** Results
 :PROPERTIES:

python/otto_motor/otto_baseline.py

@@ -1,45 +1,21 @@
-model = OttoEngine(
-    δ=[0.4, 0.4],
-    ω_c=[1, 1],
-    ψ_0=qt.basis([2], [1]),
-    description=f"A basic near-markovian, weakly coupled Otto Cycle that actually works.",
-    k_max=4,
-    bcf_terms=[6] * 2,
-    truncation_scheme="simplex",
-    driving_process_tolerances=[StocProcTolerances(1e-4, 1e-4)] * 2,
-    thermal_process_tolerances=[StocProcTolerances(1e-4, 1e-4)] * 2,
-    T=[1, 10],
-    therm_methods=["tanhsinh", "fft"],
-    Δ=1,
-    num_cycles=5,
-    Θ=1.5 / 0.05,
-    dt=0.001,
-    timings_H=(0, 0.1, 0.5, 0.6),
-    timings_L=((0.6, 0.7, 0.9, 1), (0.1, 0.2, 0.4, 0.5)),
-    streaming_mode=True,
-)
+import figsaver as fs
+import plot_utils as pu
+from hiro_models.one_qubit_model import StocProcTolerances
+from hiro_models.otto_cycle import OttoEngine
+import hiro_models.model_auxiliary as aux
+import numpy as np
+import qutip as qt
+import utilities as ut
+import stocproc
+import matplotlib.pyplot as plt
+import otto_utilities as ot
 
-# model = OttoEngine(
-#     δ=[0.4, 0.4],
-#     ω_c=[1, 1],
-#     ψ_0=qt.basis([2], [1]),
-#     description=f"An otto cycle with longer cooling.",
-#     k_max=3,
-#     bcf_terms=[4] * 2,
-#     truncation_scheme="simplex",
-#     driving_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
-#     thermal_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
-#     T=[1, 10],
-#     therm_methods=["tanhsinh", "fft"],
-#     Δ=1,
-#     num_cycles=4,
-#     Θ=1.5 / 0.05,
-#     dt=0.001,
-#     timings_H=(0, 0.1, 0.3, 0.4),
-#     timings_L=((0.4, 0.5, 0.9, 1), (0.1, 0.11, 0.29, 0.3)),
-#     streaming_mode=True,
-# )
+import ray
+ray.shutdown()
 
-ot.plot_cycle(model)
-
-ot.plot_sd_overview(model)
+ray.init(address='auto')
+#ray.init()
+from hops.util.logging_setup import logging_setup
+import logging
+logging_setup(logging.INFO)
+plt.rcParams['figure.figsize'] = (12,4)

python/otto_motor/otto_utilities.py

@@ -0,0 +1,103 @@
+import matplotlib.pyplot as plt
+import plot_utils as pu
+from hiro_models.otto_cycle import OttoEngine
+import numpy as np
+import figsaver as fs
+import hiro_models.model_auxiliary as aux
+
+
+@pu.wrap_plot
+def plot_cycle(model: OttoEngine, ax=None):
+    assert ax is not None
+    ax.plot(
+        model.t, model.coupling_operators[0].operator_norm(model.t) * 2, label=r"$L_c$"
+    )
+    ax.plot(
+        model.t, model.coupling_operators[1].operator_norm(model.t) * 2, label=r"$L_h$"
+    )
+
+    ax.plot(
+        model.t,
+        (model.H.operator_norm(model.t)) / model.H.operator_norm(model.τ_compressed),
+        label="H",
+    )
+
+    ax.set_xlim((0, model.Θ))
+    ax.set_xlabel(r"$\tau$")
+    ax.set_ylabel(r"Operator Norm")
+    ax.legend()
+
+
+@pu.wrap_plot
+def plot_sd_overview(model: OttoEngine, ax=None):
+    assert ax is not None
+
+    gaps = model.energy_gaps
+    ω = np.linspace(0.001, gaps[-1] + gaps[0], 1000)
+
+    for ω_i, label, i in zip(gaps, ["Cold", "Hot"], range(len(gaps))):
+        lines = ax.plot(
+            ω,
+            model.full_thermal_spectral_density(i)(ω) * model.bcf_scales[i],
+            label=f"{label} $T={model.T[i]}$",
+        )
+
+        ax.plot(
+            ω,
+            model.spectral_density(i)(ω) * model.bcf_scales[i],
+            label=f"{label} $T=0$",
+            color=pu.lighten_color(lines[0].get_color()),
+            linestyle="--",
+        )
+
+        ax.plot(
+            ω_i,
+            model.full_thermal_spectral_density(i)(ω_i) * model.bcf_scales[i],
+            marker="o",
+            color=lines[0].get_color(),
+        )
+
+    # plt.plot(ω, model.full_thermal_spectral_density(1)(ω) * model.bcf_scales[1])
+    # plt.plot(
+    #     2, model.full_thermal_spectral_density(1)(2) * model.bcf_scales[1], marker="o"
+    # )
+
+    ax.set_xlabel(r"$\omega$")
+    ax.set_ylabel(r"Spectral Density")
+    ax.legend()
+
+
+def full_report(model):
+    cyc = plot_cycle(model)
+    sd = plot_sd_overview(model)
+
+    f, a = plot_energy(model)
+    pu.plot_with_σ(model.t, model.total_energy(), ax=a)
+
+    power = model.power()
+    η = model.efficiency() * 100
+
+    print(
+        fs.tex_value(power.value, err=power.σ, prefix="P="),
+    )
+    print(
+        fs.tex_value(η.value, err=η.σ, prefix=r"\eta="),
+    )
+
+
+def plot_energy(model):
+    f, a = pu.plot_energy_overview(
+        model,
+        strobe_frequency=model.Ω,
+        hybrid=True,
+        bath_names=["Cold", "Hot"],
+        online=True,
+    )
+
+    a.legend()
+
+    return f, a
+
+
+def integrate_online(model, n):
+    aux.integrate(model, n, stream_file=f"results_{model.hexhash}.fifo", analyze=True)