#759 merge in master

CHANGELOG.md

@@ -2,10 +2,13 @@
 
 ## Features
 
--   Added discontinuity event and ability for solvers to integrate over discontinuities. For models using heavyside functions in certain patterns, the discretisation class  automatically adds in discontinuity events required ([#759](https://github.com/pybamm-team/PyBaMM/issues/759)
+
+-   Added functionality to solve DAE models with non-smooth current inputs ([#808](https://github.com/pybamm-team/PyBaMM/pull/808))
+-   Added functionality to simulate experiments and testing protocols ([#807](https://github.com/pybamm-team/PyBaMM/pull/807))
 -   Added fuzzy string matching for parameters and variables ([#796](https://github.com/pybamm-team/PyBaMM/pull/796))
 -   Changed ParameterValues to raise an error when a parameter that wasn't previously defined is updated ([#796](https://github.com/pybamm-team/PyBaMM/pull/796))
 -   Added some basic models (BasicSPM and BasicDFN) in order to clearly demonstrate the PyBaMM model structure for battery models ([#795](https://github.com/pybamm-team/PyBaMM/pull/795))
+-   Allow initial conditions in the particle to depend on x ([#786](https://github.com/pybamm-team/PyBaMM/pull/786))
 -   Added the harmonic mean to the Finite Volume method, which is now used when computing fluxes ([#783](https://github.com/pybamm-team/PyBaMM/pull/783))
 -   Refactored `Solution` to make it a dictionary that contains all of the solution variables. This automatically creates `ProcessedVariable` objects when required, so that the solution can be obtained much more easily. ([#781](https://github.com/pybamm-team/PyBaMM/pull/781))
 -   Added notebook to explain broadcasts ([#776](https://github.com/pybamm-team/PyBaMM/pull/776))
@@ -65,6 +68,7 @@
 ## Breaking changes
 
 -   Model events are now represented as a list of `pybamm.Event` ([#759](https://github.com/pybamm-team/PyBaMM/issues/759)
+-   Removed `ParameterValues.update_model`, whose functionality is now replaced by `InputParameter` ([#801](https://github.com/pybamm-team/PyBaMM/pull/801))
 -   Removed `Outer` and `Kron` nodes as no longer used ([#777](https://github.com/pybamm-team/PyBaMM/pull/777))
 -   Moved `results` to separate repositories ([#761](https://github.com/pybamm-team/PyBaMM/pull/761))
 -   The parameters "Bruggeman coefficient" must now be specified separately as "Bruggeman coefficient (electrolyte)" and "Bruggeman coefficient (electrode)"

INSTALL-LINUX.md

@@ -39,26 +39,14 @@ PyBaMM can be installed via pip:
 pip install pybamm
 ```
 
+PyBaMM's dependencies (such as `numpy`, `scipy`, etc) will be installed automatically when you install PyBaMM using `pip`.
 
-PyBaMM has the following python libraries as dependencies: `numpy`, `scipy`, `pandas`,
-`matplotlib`. These will be installed automatically when you install PyBaMM using `pip`,
-following the instructions below. First, make sure you have activated your virtual
-environment as above, and that you have the latest version of pip installed:
-
-Then navigate to the path where you downloaded PyBaMM to (you will already be in the
-correct location if you followed the instructions above), and install both PyBaMM and
-its dependencies by typing:
-
-```bash
-pip install pybamm
-```
 For an introduction to virtual environments, see (https://realpython.com/python-virtual-environments-a-primer/).
 
-### developer install
+### Developer install
 
 If you wish to contribute to PyBaMM, you should get the latest version from the GitHub repository.
-To do so, you must have Git installed.
-For instance run
+To do so, you must have Git installed. For instance run
 ```bash
 sudo apt install git
 ```
@@ -70,7 +58,7 @@ To install PyBaMM, the first step is to get the code by cloning this repository
 git clone https://github.com/pybamm-team/PyBaMM.git
 cd PyBaMM
 ```
-Then, install PyBaMM as a develop per with [developer](CONTRIBUTING.md), use
+Then, to install PyBaMM as a [developer](CONTRIBUTING.md), type
 
 ```bash
 pip install -e .[dev,docs]
@@ -100,10 +88,10 @@ This can be done using `git`, running
 git clone https://github.com/pybamm-team/PyBaMM.git
 cd PyBaMM
 ```
-Alternatively, you can dowload the source code archive from [the PyBaMM GitHub repo](https://github.com/pybamm-team/PyBaMM.git) and extract it the location of your choice.
+Alternatively, you can download the source code archive from [the PyBaMM GitHub repo](https://github.com/pybamm-team/PyBaMM.git) and extract it to the location of your choice.
 
 Ideally you should have the python package `wget` installed.
-This allows for the automatic download of some of the dependencies has part of the installation process.
+This allows for the automatic download of some of the dependencies that are part of the installation process.
 You can install it using (within your virtual environment)
 ```bash
 pip install wget
@@ -113,7 +101,6 @@ pip install wget
 Users can install [scikits.odes](https://github.com/bmcage/odes) in order to use the
 wrapped SUNDIALS ODE and DAE
 [solvers](https://pybamm.readthedocs.io/en/latest/source/solvers/scikits_solvers.html).
-The Sundials DAE solver is required to solve the DFN battery model in PyBaMM.
 
 Before installing scikits.odes, you need to have installed:
 
@@ -139,15 +126,15 @@ Alternatively, you can specify a directory containing the source code of the Sun
 ```bash
 python setup.py install_odes --sundials-src=<path/to/sundials/source>
 ```
-By default, the sundials are installed in a `sundials` directory located at the root of the PyBaMM package.
+By default, sundials is installed in a `sundials` directory located at the root of the PyBaMM package.
 You can provide another location by using the `--sundials-inst=<path/to/other/location>` option.
 
 If you are installing `scikits.odes` within a virtual environment, the `activate` script will be automatically
 updated to add the sundials installation directory to your `LD_LIBRARY_PATH`.
 This is required in order to use `scikits.odes`.
 As a consequence, after installation you should restart your virtual environment.
 
-If you wish to install the scikits.odes outside of a virtual environment, your `.bashrc` will be modified instead.
+If you wish to install `scikits.odes` outside of a virtual environment, your `.bashrc` will be modified instead.
 After installation you should therefore run
 ```bash
 source ~/.bashrc
@@ -166,7 +153,7 @@ sparse solver.
 PyBaMM currently offers a direct interface to the sparse KLU solver within Sundials.
 
 #### Prerequisites
-The requirements are the same than for the installation of `scikits.odes` (see previous section).
+The requirements are the same as for the installation of `scikits.odes` (see previous section).
 Additionally, the [pybind11 GitHub repository](https://github.com/pybind/pybind11.git) should be located in `PyBaMM/third-party/`.
 First create a directory `third-party` and clone the repository:
 ```bash
@@ -198,14 +185,13 @@ python -c "import pybamm; print(pybamm.have_idaklu())
 ```
 
 ### Install everything
-It is possible to install both `scikits.odes` and KLU solver using the command
+It is possible to install both `scikits.odes` and the KLU solver using the command
 ```bash
 python setup.py install_all
 ```
 Note that options `--sundials-src`, `--sundials-inst` and  `suitesparse-src` are still usable
 here.
 
-You can make sure the install was successful by runing
 Finally, you can check your install by running
 ```bash
 python -c "import pybamm; print(pybamm.have_scikits_odes())

docs/index.rst

@@ -30,6 +30,7 @@ Contents
     source/meshes/index
     source/spatial_methods/index
     source/solvers/index
+    source/experiments/index
     source/processed_variable
     source/util
     source/simulation

docs/source/experiments/experiment.rst

@@ -0,0 +1,5 @@
+Base Experiment Class
+=====================
+
+.. autoclass:: pybamm.Experiment
+  :members:

docs/source/experiments/index.rst

@@ -0,0 +1,8 @@
+Experiments
+===========
+
+Classes to help set operating conditions for some standard battery modelling experiments
+
+.. toctree::
+
+  experiment

docs/source/solvers/solution.rst

@@ -1,5 +1,8 @@
 Solution
 ========
 
+.. autoclass:: pybamm._BaseSolution
+  :members:
+
 .. autoclass:: pybamm.Solution
   :members:

examples/scripts/DFN.py

@@ -7,15 +7,15 @@
 
 pybamm.set_logging_level("INFO")
 
+
 # load model
-model = pybamm.lithium_ion.DFN({"operating mode": "voltage"})
+model = pybamm.lithium_ion.DFN()
 
 # create geometry
 geometry = model.default_geometry
 
 # load parameter values and process model and geometry
 param = model.default_parameter_values
-param.update({"Voltage function [V]": 4.1}, check_already_exists=False)
 param.process_model(model)
 param.process_geometry(geometry)
 

examples/scripts/experimental_protocols/cccv.py

@@ -0,0 +1,39 @@
+#
+# Constant-current constant-voltage charge
+#
+import pybamm
+import matplotlib.pyplot as plt
+
+pybamm.set_logging_level("INFO")
+experiment = pybamm.Experiment(
+    [
+        "Discharge at C/10 for 13 hours or until 3.3 V",
+        "Rest for 1 hour",
+        "Charge at 1 A until 4.1 V",
+        "Hold at 4.1 V until 50 mA",
+        "Rest for 1 hour",
+    ]
+    * 3,
+    period="2 minutes",
+)
+model = pybamm.lithium_ion.DFN()
+sim = pybamm.Simulation(model, experiment=experiment, solver=pybamm.CasadiSolver())
+sim.solve()
+
+# Plot voltages from the discharge segments only
+fig, ax = plt.subplots()
+for i in range(3):
+    # Extract sub solutions
+    sol = sim.solution.sub_solutions[i * 5]
+    # Extract variables
+    t = sol["Time [h]"].entries
+    V = sol["Terminal voltage [V]"].entries
+    # Plot
+    ax.plot(t - t[0], V, label="Discharge {}".format(i + 1))
+    ax.set_xlabel("Time [h]")
+    ax.set_ylabel("Voltage [V]")
+    ax.set_xlim([0, 13])
+ax.legend()
+
+# Show all plots
+sim.plot()

examples/scripts/experimental_protocols/cccv_lead_acid.py

@@ -0,0 +1,19 @@
+#
+# Constant-current constant-voltage charge
+#
+import pybamm
+
+pybamm.set_logging_level("INFO")
+experiment = pybamm.Experiment(
+    [
+        "Discharge at C/2 until 11 V",
+        "Rest for 1 hour",
+        "Charge at C/2 until 14.5 V",
+        "Hold at 14.5 V until 200 mA",
+        "Rest for 1 hour",
+    ]
+)
+model = pybamm.lead_acid.Full()
+sim = pybamm.Simulation(model, experiment=experiment, solver=pybamm.CasadiSolver())
+sim.solve()
+sim.plot()

examples/scripts/experimental_protocols/gitt.py

@@ -0,0 +1,13 @@
+#
+# GITT discharge
+#
+import pybamm
+
+pybamm.set_logging_level("INFO")
+experiment = pybamm.Experiment(
+    ["Discharge at C/20 for 1 hour", "Rest for 1 hour"] * 20,
+)
+model = pybamm.lithium_ion.DFN()
+sim = pybamm.Simulation(model, experiment=experiment, solver=pybamm.CasadiSolver())
+sim.solve()
+sim.plot()

input/parameters/lithium-ion/anodes/graphite_mcmb2528_Marquis2019/parameters.csv

@@ -19,7 +19,6 @@ Negative electrode Bruggeman coefficient (electrode),1.5,Scott Moura FastDFN,
 # Interfacial reactions,,,
 Negative electrode cation signed stoichiometry,-1,,
 Negative electrode electrons in reaction,1,,
-Negative electrode reference exchange-current density [A.m-2(m3.mol)1.5],2E-05,Scott Moura FastDFN,Be careful how we implement BV
 Reference OCP vs SHE in the negative electrode [V],,,
 Negative electrode charge transfer coefficient,0.5,Scott Moura FastDFN,
 Negative electrode double-layer capacity [F.m-2],0.2,,

input/parameters/lithium-ion/cathodes/lico2_Marquis2019/parameters.csv

@@ -19,7 +19,6 @@ Positive electrode Bruggeman coefficient (electrode),1.5,Scott Moura FastDFN,
 # Interfacial reactions,,,
 Positive electrode cation signed stoichiometry,-1,,
 Positive electrode electrons in reaction,1,,
-Positive electrode reference exchange-current density [A.m-2(m3.mol)1.5],6E-07,Scott Moura FastDFN,Be careful how we implement BV
 Reference OCP vs SHE in the positive electrode [V],,,
 Positive electrode charge transfer coefficient,0.5,Scott Moura FastDFN,
 Positive electrode double-layer capacity [F.m-2],0.2,,

pybamm/__init__.py

@@ -237,7 +237,7 @@ def version(formatted=False):
 #
 # Solver classes
 #
-from .solvers.solution import Solution
+from .solvers.solution import Solution, _BaseSolution
 from .solvers.base_solver import BaseSolver
 from .solvers.algebraic_solver import AlgebraicSolver
 from .solvers.casadi_solver import CasadiSolver
@@ -246,6 +246,12 @@ def version(formatted=False):
 from .solvers.scipy_solver import ScipySolver
 from .solvers.idaklu_solver import IDAKLUSolver, have_idaklu
 
+#
+# Experiments
+#
+from .experiments.experiment import Experiment
+from . import experiments
+
 #
 # other
 #