update deps

python/energy_flow_proper/10_antizeno_engine/poetry.lock

@@ -1530,6 +1530,20 @@ tornado = ">=6.1.0"
 [package.extras]
 test = ["pre-commit", "pytest-timeout", "pytest (>=6.0)"]
 
+[[package]]
+name = "tikzplotlib"
+version = "0.10.1"
+description = "Convert matplotlib figures into TikZ/PGFPlots"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+matplotlib = ">=1.4.0"
+numpy = "*"
+Pillow = "*"
+webcolors = "*"
+
 [[package]]
 name = "tinycss2"
 version = "1.1.1"
@@ -1670,6 +1684,14 @@ category = "main"
 optional = false
 python-versions = "*"
 
+[[package]]
+name = "webcolors"
+version = "1.12"
+description = "A library for working with color names and color values formats defined by HTML and CSS."
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
 [[package]]
 name = "webencodings"
 version = "0.5.1"
@@ -1692,7 +1714,7 @@ notebook = ">=4.4.1"
 [metadata]
 lock-version = "1.1"
 python-versions = ">=3.9,<3.11"
-content-hash = "9607f8fb913cf9aad27f1a425d1e82d72f652c7d908bb6566c929b66586c394a"
+content-hash = "7be6f6b3cb3b948e49d1daa7ba89def726afeb68ba1128f1b0ba6f4344f85fe3"
 
 [metadata.files]
 aiosignal = [
@@ -2895,6 +2917,10 @@ terminado = [
     {file = "terminado-0.15.0-py3-none-any.whl", hash = "sha256:0d5f126fbfdb5887b25ae7d9d07b0d716b1cc0ccaacc71c1f3c14d228e065197"},
     {file = "terminado-0.15.0.tar.gz", hash = "sha256:ab4eeedccfcc1e6134bfee86106af90852c69d602884ea3a1e8ca6d4486e9bfe"},
 ]
+tikzplotlib = [
+    {file = "tikzplotlib-0.10.1-py3-none-any.whl", hash = "sha256:bf0451b86fe4db40aa742f7e5a180dfaaadf57c746ddb2ab7e58a5163d8be75f"},
+    {file = "tikzplotlib-0.10.1.tar.gz", hash = "sha256:93d141342d143804fc1dfabe03e6d4e38e547cf72803bdf124615affdd56f59d"},
+]
 tinycss2 = [
     {file = "tinycss2-1.1.1-py3-none-any.whl", hash = "sha256:fe794ceaadfe3cf3e686b22155d0da5780dd0e273471a51846d0a02bc204fec8"},
     {file = "tinycss2-1.1.1.tar.gz", hash = "sha256:b2e44dd8883c360c35dd0d1b5aad0b610e5156c2cb3b33434634e539ead9d8bf"},
@@ -2948,6 +2974,10 @@ wcwidth = [
     {file = "wcwidth-0.2.5-py2.py3-none-any.whl", hash = "sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784"},
     {file = "wcwidth-0.2.5.tar.gz", hash = "sha256:c4d647b99872929fdb7bdcaa4fbe7f01413ed3d98077df798530e5b04f116c83"},
 ]
+webcolors = [
+    {file = "webcolors-1.12-py3-none-any.whl", hash = "sha256:d98743d81d498a2d3eaf165196e65481f0d2ea85281463d856b1e51b09f62dce"},
+    {file = "webcolors-1.12.tar.gz", hash = "sha256:16d043d3a08fd6a1b1b7e3e9e62640d09790dce80d2bdd4792a175b35fe794a9"},
+]
 webencodings = [
     {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"},
     {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},

python/energy_flow_proper/10_antizeno_engine/pyproject.toml

@@ -19,6 +19,7 @@ Cython = "^0.29.30"
 statsmodels = "^0.13.2"
 protobuf = "==3.20.1"
 tabulate = "^0.8.9"
+tikzplotlib = "^0.10.1"
 
 [tool.poetry.dev-dependencies]
 black = "^21.12b0"

python/energy_flow_proper/11_new_ho_comparison/ho_analytic_zero_temperature.org

@@ -106,7 +106,7 @@
 #+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_2022-07-25_10-06-10_321700_2896957/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-07-25_10-06-10_321700_2896957/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-07-25_10-06-10_321700_2896957', 'metrics_export_port': 62937, 'gcs_address': '141.30.17.225:61225', 'address': '141.30.17.225:61225', 'node_id': '33637dfe594aa8dfbe572b47f0dfa94fad6f32191ef2d5f269609c0d'})
+: 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_2022-07-25_15-58-15_167539_2941624/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-07-25_15-58-15_167539_2941624/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-07-25_15-58-15_167539_2941624', 'metrics_export_port': 48616, 'gcs_address': '141.30.17.225:64543', 'address': '141.30.17.225:64543', 'node_id': '59156e19ccf152f9b6c218e104c8ee997f882e9ac2ede555e0cebbc0'})
 
 
 #+begin_src jupyter-python
@@ -119,7 +119,7 @@
               data_name="zero_t",
           )
         print(supervisor.get_data(True).hdf5_name)
-        supervisor.integrate()
+        #supervisor.integrate()
         supervisors.append(supervisor)
 
 #+end_src
@@ -128,8 +128,8 @@
 : ho_data/zero_t/_e/zero_t_e5bb719aebf17ce48e7338370309f454_1.h5
 : ho_data/zero_t/_7/zero_t_716813e927dc901d29acbdbbac7d5148_1.h5
 : ho_data/zero_t/_5/zero_t_56871e76eaf4e301c1938ea4a855cfdf_1.h5
-: ho_data/zero_t/_7/zero_t_716813e927dc901d29acbdbbac7d5148_1.h5
 : ho_data/zero_t/_1/zero_t_1bc1f6d01789a17e0081e545ecadbb29_1.h5
+: ho_data/zero_t/_0/zero_t_03786afe10c6c708b87cc332607b1b48_1.h5
 
 * Flow
 #+begin_src jupyter-python :results none
@@ -152,6 +152,100 @@
 #+end_src
 
 #+RESULTS:
+:RESULTS:
+: Loading:   0% 2/417 [00:02<09:53,  1.43s/it]
+# [goto error]
+#+begin_example
+  ---------------------------------------------------------------------------
+  KeyboardInterrupt                         Traceback (most recent call last)
+  Input In [17], in <cell line: 2>()
+        2 for supervisor in supervisors:
+        3     hf_sys = hopsflow.SystemParams.from_hi_params(supervisor.params)
+        4     flow_hops.append(
+  ----> 5         hopsflow.heat_flow_from_data(
+        6             supervisor.get_data(True),
+        7             hf_sys,
+        8             every=1000,
+        9             save=f"flow_zero",
+       10         )
+       11     )
+
+  File ~/src/hopsflow/hopsflow/hopsflow.py:556, in heat_flow_from_data(data, thermal_params, *args, **kwargs)
+      550 if thermal_params is not None:
+      551     kwargs["thermal_params"] = (
+      552         d.valid_sample_iterator(d.rng_seed),
+      553         thermal_params,
+      554     )
+  --> 556 return heat_flow_ensemble(
+      557     d.valid_sample_iterator(d.stoc_traj),
+      558     d.valid_sample_iterator(d.aux_states),
+      559     *args,
+      560     **(dict(N=data.samples) | kwargs),
+      561 )
+
+  File ~/src/hopsflow/hopsflow/hopsflow.py:520, in heat_flow_ensemble(ψ_0s, ψ_1s, params, therm_args, only_therm, **kwargs)
+      516         flow += flow_trajectory_therm(run, therm_run)
+      518     return flow
+  --> 520 return util.ensemble_mean(
+      521     iter(zip(ψ_0s, ψ_1s, therm_args[0]))
+      522     if therm_args
+      523     else iter(zip(ψ_0s, ψ_1s, itertools.repeat(0))),
+      524     flow_worker,
+      525     **kwargs,
+      526 )
+
+  File ~/src/hopsflow/hopsflow/util.py:778, in ensemble_mean(arg_iter, function, N, every, save, overwrite_cache, chunk_size, in_flight, gc_sleep)
+      776 while True:
+      777     try:
+  --> 778         next_val = next(chunk_iterator)
+      779     except StopIteration:
+      780         next_val = None
+
+  File /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/tqdm/std.py:1195, in tqdm.__iter__(self)
+     1192 time = self._time
+     1194 try:
+  -> 1195     for obj in iterable:
+     1196         yield obj
+     1197         # Update and possibly print the progressbar.
+     1198         # Note: does not call self.update(1) for speed optimisation.
+
+  File ~/src/hopsflow/hopsflow/util.py:693, in _grouper(n, iterable)
+      690 """Groups the iteartor into tuples of at most length ``n``."""
+      692 while True:
+  --> 693     chunk = tuple(itertools.islice(iterable, n))
+      694     if not chunk:
+      695         return
+
+  File ~/src/hops/hops/core/hierarchy_data.py:1240, in HIData.valid_sample_iterator(self, iterator)
+     1233 def valid_sample_iterator(self, iterator: Iterator[T]) -> Iterator[T]:
+     1234     """
+     1235     Takes an ``iterator`` that yields a sequence of items related to
+     1236     the sequence of samples and yields them if the sample is
+     1237     actually present in the data.
+     1238     """
+  -> 1240     for i, item in enumerate(iterator):
+     1241         if self.has_sample(i):
+     1242             yield item
+
+  File /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/h5py/_hl/dataset.py:695, in Dataset.__iter__(self)
+      693     raise TypeError("Can't iterate over a scalar dataset")
+      694 for i in range(shape[0]):
+  --> 695     yield self[i]
+
+  File h5py/_objects.pyx:54, in h5py._objects.with_phil.wrapper()
+
+  File h5py/_objects.pyx:55, in h5py._objects.with_phil.wrapper()
+
+  File /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/h5py/_hl/dataset.py:824, in Dataset.__getitem__(self, args, new_dtype)
+      822 mspace = h5s.create_simple(selection.mshape)
+      823 fspace = selection.id
+  --> 824 self.id.read(mspace, fspace, arr, mtype, dxpl=self._dxpl)
+      826 # Patch up the output for NumPy
+      827 if arr.shape == ():
+
+  KeyboardInterrupt:
+#+end_example
+:END:
 
 #+begin_src jupyter-python
   fig, ax = plt.subplots()
@@ -168,8 +262,8 @@
 #+RESULTS:
 :RESULTS:
 : WARNING:matplotlib.legend:No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
-: <matplotlib.legend.Legend at 0x7f56044adb50>
-[[file:./.ob-jupyter/89ae9af00f7aa3e773df6d7875eeff5e91d76f4e.svg]]
+: <matplotlib.legend.Legend at 0x7f2c381dd4c0>
+[[file:./.ob-jupyter/f3f1da415527bff6b99872e7c62dfdf0f63fbc24.svg]]
 :END:
 
 * Analytic