Merge branch 'release-0.1.0'

.readthedocs.yml

@@ -0,0 +1,9 @@
+# ReadTheDocs configuration
+
+version: 2
+
+# Optionally set the version of Python and requirements required to build your docs
+python:
+  version: 3.6
+  install:
+    - requirements: docs/requirements.txt

README.rst

@@ -18,6 +18,9 @@
      :target: https://requires.io/github/multiscale/muscle3/requirements/?branch=master
      :alt: Requirements Status
 
+.. image:: https://zenodo.org/badge/122876985.svg
+   :target: https://zenodo.org/badge/latestdoi/122876985
+
 ========
 MUSCLE 3
 ========

VERSION

@@ -1 +1 @@
-0.1.0-rc.1
+0.1.0

docs/requirements.txt

@@ -0,0 +1,8 @@
+grpcio==1.17.1
+grpcio-tools==1.17.1
+msgpack==0.6.1
+protobuf==3.8.0
+ruamel.yaml==0.15.64
+typing==3.6.6
+yatiml==0.4.2
+ymmsl==0.9.0

docs/source/api.rst

@@ -1,4 +1,4 @@
-libmuscle package
+API Documentation
 =================
 
 .. automodule:: libmuscle

docs/source/conf.py

@@ -22,6 +22,12 @@
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), '../../'))
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), '../../libmuscle/python/'))
 
+# create a libmuscle/version.py if needed (which it is on RTD)
+version_path = os.path.join(os.path.dirname(__file__), '../../libmuscle/python/libmuscle/version.py')
+if not os.path.exists(version_path):
+    with open(version_path, 'w') as f:
+        f.write("__version__ = '0.0.0'")
+
 # -- General configuration ------------------------------------------------
 
 # If your documentation needs a minimal Sphinx version, state it here.

docs/source/distributed_execution.rst

@@ -3,7 +3,7 @@ Distributed execution
 
 In the previous section, we created a simple macro-micro multiscale model with
 MUSCLE 3, and ran it as a single Python script. This section briefly explains
-how to go from there to a distributed simulation, possibly on multiple machines.
+how to go from there to a distributed simulation, possibly on multiple nodes.
 
 Note that distributed simulations are still somewhat experimental. They need a
 bit more testing, and more development (in particular integration with a
@@ -51,8 +51,8 @@ our previous example looks like this:
 
 
 As you can see, this looks very much like the object representation. You can
-load a yMMSL file to objects using `ymmsl.load` and save it back using
-`ymmsl.save`.
+load a yMMSL file to objects using ``ymmsl.load`` and save it back using
+``ymmsl.save``.
 
 Starting the manager
 --------------------
@@ -66,8 +66,8 @@ each other, and distributes settings to them. To start the manager, run
 
 
 in an environment in which you've installed MUSCLE 3. The manager will start,
-and will print its location on standard out. This is the network address on
-which it listens for connections from instances.
+and will print its location on the standard output. This is the network address
+on which it listens for connections from instances.
 
 Starting instances
 ------------------
@@ -82,17 +82,18 @@ Starting an instance works just like starting any other Python script:
 In the original script, we made a dictionary that mapped compute element names
 to Python functions, which MUSCLE 3 used to start the submodel instances. Here,
 we need to pass the same information. Instead of a function name, we start a
-particular script, and we pass the instance name using the `--muscle-instance=`
-argument. Note that the argument parser is not very flexible, so it needs to be
-written exactly like that, and of course the instance name needs to match the
-compute element name in the yMMSL file passed to the manager.
+particular script, and we pass the instance name using the
+``--muscle-instance=`` argument. Note that the argument parser is not very
+flexible, so it needs to be written exactly like that, and of course the
+instance name needs to match the compute element name in the yMMSL file passed
+to the manager.
 
 When the instance starts, it will register with the manager. Since we didn't
-pass a location using the `--muscle-manager=<host:port>` option, MUSCLE 3 tried
-to connect to the default location (localhost:9000), which the manager was
-conveniently listening on. The `micro` instance registered, and if you have a
-look at the `muscle3_manager.log` file produced by the manager (in the directory
-in which you started it), you should find a record of this there.
+pass a location using the ``--muscle-manager=<host:port>`` option, MUSCLE 3
+tried to connect to the default location (localhost:9000), which the manager
+was conveniently listening on. The ``micro`` instance registered, and if you
+have a look at the ``muscle3_manager.log`` file produced by the manager (in the
+directory in which you started it), you should find a record of this there.
 
 Now, we need to start the second submodel in the same way:
 

docs/source/examples/diffusion.py

@@ -36,7 +36,7 @@ def diffusion() -> None:
             Operator.S: ['state_in']})
 
     while instance.reuse_instance():
-        # f_init
+        # F_INIT
         t_max = instance.get_parameter_value('t_max', 'float')
         dt = instance.get_parameter_value('dt', 'float')
         x_max = instance.get_parameter_value('x_max', 'float')
@@ -51,7 +51,7 @@ def diffusion() -> None:
 
         t_cur = 0.0
         while t_cur + dt <= t_max:
-            # O_i
+            # O_I
             t_next = t_cur + dt
             if t_next + dt > t_max:
                 t_next = None

docs/source/examples/reaction.py

@@ -12,7 +12,7 @@ def reaction() -> None:
             Operator.O_F: ['final_state']})         # list of float
 
     while instance.reuse_instance():
-        # f_init
+        # F_INIT
         t_max = instance.get_parameter_value('t_max', 'float')
         dt = instance.get_parameter_value('dt', 'float')
         k = instance.get_parameter_value('k', 'float')
@@ -22,13 +22,13 @@ def reaction() -> None:
 
         t_cur = msg.timestamp
         while t_cur + dt < t_max:
-            # O_i
+            # O_I
 
             # S
             U += k * U * dt
             t_cur += dt
 
-        # O_f
+        # O_F
         instance.send('final_state', Message(t_cur, None, U.tolist()))
 
 

docs/source/examples/reaction_diffusion.py

@@ -18,7 +18,7 @@ def reaction() -> None:
             Operator.O_F: ['final_state']})         # list of float
 
     while instance.reuse_instance():
-        # f_init
+        # F_INIT
         t_max = instance.get_parameter_value('t_max', 'float')
         dt = instance.get_parameter_value('dt', 'float')
         k = instance.get_parameter_value('k', 'float')
@@ -28,13 +28,13 @@ def reaction() -> None:
 
         t_cur = msg.timestamp
         while t_cur + dt < t_max:
-            # O_i
+            # O_I
 
             # S
             U += k * U * dt
             t_cur += dt
 
-        # O_f
+        # O_F
         instance.send('final_state', Message(t_cur, None, U.tolist()))
 
 
@@ -66,7 +66,7 @@ def diffusion() -> None:
             Operator.S: ['state_in']})
 
     while instance.reuse_instance():
-        # f_init
+        # F_INIT
         t_max = instance.get_parameter_value('t_max', 'float')
         dt = instance.get_parameter_value('dt', 'float')
         x_max = instance.get_parameter_value('x_max', 'float')
@@ -81,7 +81,7 @@ def diffusion() -> None:
 
         t_cur = 0.0
         while t_cur + dt <= t_max:
-            # O_i
+            # O_I
             t_next = t_cur + dt
             if t_next + dt > t_max:
                 t_next = None

docs/source/examples/reaction_diffusion_qmc.py

@@ -18,7 +18,7 @@ def reaction() -> None:
             Operator.O_F: ['final_state']})         # list of float
 
     while instance.reuse_instance():
-        # f_init
+        # F_INIT
         t_max = instance.get_parameter_value('t_max', 'float')
         dt = instance.get_parameter_value('dt', 'float')
         k = instance.get_parameter_value('k', 'float')
@@ -28,13 +28,13 @@ def reaction() -> None:
 
         t_cur = msg.timestamp
         while t_cur + dt < t_max:
-            # O_i
+            # O_I
 
             # S
             U += k * U * dt
             t_cur += dt
 
-        # O_f
+        # O_F
         instance.send('final_state', Message(t_cur, None, U.tolist()))
 
 
@@ -67,7 +67,7 @@ def diffusion() -> None:
             Operator.O_F: ['final_state_out']})
 
     while instance.reuse_instance():
-        # f_init
+        # F_INIT
         t_max = instance.get_parameter_value('t_max', 'float')
         dt = instance.get_parameter_value('dt', 'float')
         x_max = instance.get_parameter_value('x_max', 'float')
@@ -82,7 +82,7 @@ def diffusion() -> None:
 
         t_cur = 0.0
         while t_cur + dt <= t_max:
-            # O_i
+            # O_I
             t_next = t_cur + dt
             if t_next + dt > t_max:
                 t_next = None
@@ -104,7 +104,7 @@ def diffusion() -> None:
             Us = np.vstack((Us, U))
             t_cur += dt
 
-        # O_f
+        # O_F
         instance.send('final_state_out', Message(t_cur, None, U.tolist()))
 
 
@@ -133,7 +133,7 @@ def load_balancer() -> None:
             Operator.O_F: ['front_out[]']})
 
     while instance.reuse_instance(False):
-        # f_init
+        # F_INIT
         started = 0     # number started and index of next to start
         done = 0        # number done and index of next to return
 
@@ -163,7 +163,7 @@ def qmc_driver() -> None:
             Operator.S: ['states_in[]']})
 
     while instance.reuse_instance():
-        # f_init
+        # F_INIT
         # get and check parameters
         n_samples = instance.get_parameter_value('n_samples', 'int')
         d_min = instance.get_parameter_value('d_min', 'float')
@@ -192,7 +192,7 @@ def qmc_driver() -> None:
 
         # run ensemble
         Us = None
-        # O_i
+        # O_I
         for sample in range(n_samples):
             uq_parameters = Settings({
                 'd': ds[sample],
@@ -210,6 +210,7 @@ def qmc_driver() -> None:
             else:
                 Us = np.vstack((Us, U))
 
+        mean = np.mean(Us, axis=0)
         plt.figure()
         plt.imshow(np.log(Us + 1e-20))
         plt.show()

docs/source/releasing.rst

@@ -121,11 +121,12 @@ Make a GitHub release
 ---------------------
 
 In order to get a DOI for this release, we need to make a release on GitHub. Go
-to the `MUSCLE 3 GitHub repository`_ and click 'Releases'. Select 'Create a new
+to the `MUSCLE 3 GitHub repository`_ and click 'Releases'. Select 'Draft a new
 release', select the x.y.z. tag that we just uploaded, and use 'Release x.y.z'
-as the title. Then copy-paste the description from the change log, and maybe
-prepend some text if there is something interesting to mention. Optionally
-select 'This is a pre-release' if it's not a final version, then publish it.
+as the title. Then copy-paste the description from the change log, convert it
+from ReStructuredText to MarkDown and maybe prepend some text if there is
+something interesting to mention. Optionally select 'This is a pre-release' if
+it's not a final version, then publish it.
 
 Build and release to PyPI
 -------------------------