looking good, need longer init

python/energy_flow_proper/10_antizeno_engine/10_first_anti_zeno.py

@@ -313,9 +313,7 @@ with aux.get_data(model) as data:
 
     ρ_ee = data.rho_t_accum.mean[:, 0, 0].real
 
-# plt.plot(model.t, ρ_ee)
-
-plt.plot(model.t, ut.smoothen(model.t, ρ_ee, frac=.06, it=0))
+plt.plot(model.t, ut.smoothen(model.t, ρ_ee, frac=.5, it=0))
 
 with aux.get_data(model) as data:
   _, ax = plt.subplots()
@@ -326,7 +324,6 @@ with aux.get_data(model) as data:
 
   pu.plot_with_σ(model.t, model.total_energy(data), ax=ax)
   #pu.plot_with_σ(model.t, model.interaction_energy(data).for_bath(1), ax=ax)
-
   #pu.plot_with_σ(model.t, model.system_energy(data), ax=ax)
   #pu.plot_with_σ(model.t, model.system_energy(data) + model.bath_energy(data).sum_baths(), ax=ax)
   #ax.plot(model.t, ut.smoothen(model.t, model.total_energy(data).value, frac=.1))
@@ -367,7 +364,7 @@ for begin, end in zip(ind_begin, ind_end):
         (tot_power.slice(begin, end)).mean
     )
 
-steady_index = 4
+steady_index = 0
 power = sum(powers[steady_index:]) * (1/(len(powers[steady_index:])))
 
 ax.set_ylabel(r"$\langle{P}\rangle$")

python/energy_flow_proper/10_antizeno_engine/anti_zeno_engine.org

@@ -27,7 +27,62 @@ Init ray and silence stocproc.
 #+end_src
 
 #+RESULTS:
-: 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_2022-08-04_11-17-18_747252_106699/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-08-04_11-17-18_747252_106699/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-08-04_11-17-18_747252_106699', 'metrics_export_port': 62354, 'gcs_address': '141.30.17.225:53570', 'address': '141.30.17.225:53570', 'node_id': '079f1adbf34279fae2fd8852983a78a23ac1e68ab6ead506e1bb1467'})
+:RESULTS:
+# [goto error]
+#+begin_example
+  ---------------------------------------------------------------------------
+  ConnectionError                           Traceback (most recent call last)
+  Input In [2], in <cell line: 3>()
+        1 import ray
+        2 ray.shutdown()
+  ----> 3 ray.init(address="auto")
+
+  File /nix/store/zm0dbvm6kc79il5713w847760r9wxs2m-python3-3.9.13-env/lib/python3.9/site-packages/ray/_private/client_mode_hook.py:105, in client_mode_hook.<locals>.wrapper(*args, **kwargs)
+      103     if func.__name__ != "init" or is_client_mode_enabled_by_default:
+      104         return getattr(ray, func.__name__)(*args, **kwargs)
+  --> 105 return func(*args, **kwargs)
+
+  File /nix/store/zm0dbvm6kc79il5713w847760r9wxs2m-python3-3.9.13-env/lib/python3.9/site-packages/ray/worker.py:954, in init(address, num_cpus, num_gpus, resources, object_store_memory, local_mode, ignore_reinit_error, include_dashboard, dashboard_host, dashboard_port, job_config, configure_logging, logging_level, logging_format, log_to_driver, namespace, runtime_env, storage, _enable_object_reconstruction, _redis_max_memory, _plasma_directory, _node_ip_address, _driver_object_store_memory, _memory, _redis_password, _temp_dir, _metrics_export_port, _system_config, _tracing_startup_hook, _node_name, **kwargs)
+      952 bootstrap_address, redis_address, gcs_address = None, None, None
+      953 if address:
+  --> 954     bootstrap_address = services.canonicalize_bootstrap_address(address)
+      955     assert bootstrap_address is not None
+      956     logger.info(
+      957         f"Connecting to existing Ray cluster at address: {bootstrap_address}"
+      958     )
+
+  File /nix/store/zm0dbvm6kc79il5713w847760r9wxs2m-python3-3.9.13-env/lib/python3.9/site-packages/ray/_private/services.py:451, in canonicalize_bootstrap_address(addr)
+      441 """Canonicalizes Ray cluster bootstrap address to host:port.
+      442 Reads address from the environment if needed.
+      443 
+     (...)
+      448     Ray cluster address string in <host:port> format.
+      449 """
+      450 if addr is None or addr == "auto":
+  --> 451     addr = get_ray_address_from_environment()
+      452 try:
+      453     bootstrap_address = resolve_ip_for_localhost(addr)
+
+  File /nix/store/zm0dbvm6kc79il5713w847760r9wxs2m-python3-3.9.13-env/lib/python3.9/site-packages/ray/_private/services.py:358, in get_ray_address_from_environment()
+      356 addr = os.environ.get(ray_constants.RAY_ADDRESS_ENVIRONMENT_VARIABLE)
+      357 if addr is None or addr == "auto":
+  --> 358     addr = _find_gcs_address_or_die()
+      359 return addr
+
+  File /nix/store/zm0dbvm6kc79il5713w847760r9wxs2m-python3-3.9.13-env/lib/python3.9/site-packages/ray/_private/services.py:333, in _find_gcs_address_or_die()
+      331 gcs_addresses = _find_address_from_flag("--gcs-address")
+      332 if len(gcs_addresses) > 1:
+  --> 333     raise ConnectionError(
+      334         f"Found multiple active Ray instances: {gcs_addresses}. "
+      335         "Please specify the one to connect to by setting `--address` flag "
+      336         "or `RAY_ADDRESS` environment variable."
+      337     )
+      338     sys.exit(1)
+      339 elif not gcs_addresses:
+
+  ConnectionError: Found multiple active Ray instances: {'141.30.17.225:62313', '141.30.17.225:50182', '141.30.17.225:65147'}. Please specify the one to connect to by setting `--address` flag or `RAY_ADDRESS` environment variable.
+#+end_example
+:END:
 
 #+begin_src jupyter-python :results none
   from hops.util.logging_setup import logging_setup
@@ -319,8 +374,8 @@ Let's test the assumptions of the paper.
 
 #+RESULTS:
 :RESULTS:
-: <matplotlib.legend.Legend at 0x7ff47b5d8f70>
-[[file:./.ob-jupyter/84c423a9401fb0410819d4df4fd07089f24fa24e.svg]]
+: <matplotlib.legend.Legend at 0x7f13b3f72e20>
+[[file:./.ob-jupyter/6731a563bc8b20945d52b785667f2e8efee540e9.svg]]
 :END:
 
 #+begin_src jupyter-python :tangle nil
@@ -439,7 +494,7 @@ Let's test the assumptions of the paper.
 #+end_src
 
 #+RESULTS:
-[[file:./.ob-jupyter/50d1bb2a98247cea870e723c788bae09a3eb04ea.svg]]
+[[file:./.ob-jupyter/cce3efaf063c82f06c7cf8127c730600cde163dc.svg]]
 
 - **too fast decoupling kills it**
 - no anti-zeno effects without detuning?
@@ -466,31 +521,29 @@ Let's test the assumptions of the paper.
 
 #+RESULTS:
 :RESULTS:
-: /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/cbook/__init__.py:1298: ComplexWarning: Casting complex values to real discards the imaginary part
+: /nix/store/zm0dbvm6kc79il5713w847760r9wxs2m-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/cbook/__init__.py:1298: ComplexWarning: Casting complex values to real discards the imaginary part
 :   return np.asarray(x, float)
-: /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5218: ComplexWarning: Casting complex values to real discards the imaginary part
+: /nix/store/zm0dbvm6kc79il5713w847760r9wxs2m-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5218: ComplexWarning: Casting complex values to real discards the imaginary part
 :   pts[0] = start
-: /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5219: ComplexWarning: Casting complex values to real discards the imaginary part
+: /nix/store/zm0dbvm6kc79il5713w847760r9wxs2m-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5219: ComplexWarning: Casting complex values to real discards the imaginary part
 :   pts[N + 1] = end
-: /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5222: ComplexWarning: Casting complex values to real discards the imaginary part
+: /nix/store/zm0dbvm6kc79il5713w847760r9wxs2m-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5222: ComplexWarning: Casting complex values to real discards the imaginary part
 :   pts[1:N+1, 1] = dep1slice
-: /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5224: ComplexWarning: Casting complex values to real discards the imaginary part
+: /nix/store/zm0dbvm6kc79il5713w847760r9wxs2m-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5224: ComplexWarning: Casting complex values to real discards the imaginary part
 :   pts[N+2:, 1] = dep2slice[::-1]
-[[file:./.ob-jupyter/6c7dd6320634995333544d0d20997d252a9cfece.svg]]
+[[file:./.ob-jupyter/510fac6208b7950e74134f1538f5e47e04e48f53.svg]]
 :END:
 
 - no steady state ... but we have to average...
 
 #+begin_src jupyter-python
-  # plt.plot(model.t, ρ_ee)
-
-  plt.plot(model.t, ut.smoothen(model.t, ρ_ee, frac=.06, it=0))
+  plt.plot(model.t, ut.smoothen(model.t, ρ_ee, frac=.5, it=0))
 #+end_src
 
 #+RESULTS:
 :RESULTS:
-| <matplotlib.lines.Line2D | at | 0x7ff47bc9ebb0> |
-[[file:./.ob-jupyter/585df3b23fc95829cde1d1a31b416a1cb10d760d.svg]]
+| <matplotlib.lines.Line2D | at | 0x7f13b1ab4040> |
+[[file:./.ob-jupyter/26cbfca7cad147a1687d01c495ee0148dba1f8a8.svg]]
 :END:
 
 ** TODO Power and Efficiency
@@ -508,7 +561,6 @@ We need the time points where we sample the total energy.
 
     pu.plot_with_σ(model.t, model.total_energy(data), ax=ax)
     #pu.plot_with_σ(model.t, model.interaction_energy(data).for_bath(1), ax=ax)
-
     #pu.plot_with_σ(model.t, model.system_energy(data), ax=ax)
     #pu.plot_with_σ(model.t, model.system_energy(data) + model.bath_energy(data).sum_baths(), ax=ax)
     #ax.plot(model.t, ut.smoothen(model.t, model.total_energy(data).value, frac=.1))
@@ -516,7 +568,10 @@ We need the time points where we sample the total energy.
 #+end_src
 
 #+RESULTS:
-[[file:./.ob-jupyter/a7a655d96af4b59356371e5f4164ad83ea2a6f15.svg]]
+:RESULTS:
+: Loading:   0% 0/99999 [00:00<?, ?it/s]
+[[file:./.ob-jupyter/da54924ee7a3023ba22115cfd2d2c480e1194adc.svg]]
+:END:
 
 #+begin_src jupyter-python
   ts_begin =  τ_init + τ_off + ((τ_c + τ_off) * np.arange(0, n))
@@ -559,7 +614,7 @@ We need the time points where we sample the total energy.
           (tot_power.slice(begin, end)).mean
       )
 
-  steady_index = 4
+  steady_index = 0
   power = sum(powers[steady_index:]) * (1/(len(powers[steady_index:])))
 
   ax.set_ylabel(r"$\langle{P}\rangle$")
@@ -577,8 +632,8 @@ We need the time points where we sample the total energy.
 
 #+RESULTS:
 :RESULTS:
-: \(P=-0.0007\pm 0.0018\)
-[[file:./.ob-jupyter/d5776ec43522109db1d102212062ba37099e86fb.svg]]
+: \(P=-0.00081\pm 0.00020\)
+[[file:./.ob-jupyter/c6e1343e89d39c704cbb2e1c0d6de97ef9db8d44.svg]]
 :END: