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‎.requirements-docs.txt

+1
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@@ -8,3 +8,4 @@ scikit-fem>=0.2.0
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casadi>=3.5.0
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guzzle-sphinx-theme
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sphinx>=1.5
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python-Levenshtein>=0.12.0

‎.travis.yml

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@@ -79,7 +79,8 @@ matrix:
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env:
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- PYBAMM_UNIT=true
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- PYBAMM_SCIKITS_ODES=true
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# Unit testing on Python3.7 on Ubuntu without scikit odes
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- PYBAMM_KLU=true
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# Unit and example testing on Python3.7 on Ubuntu without optional dependencies
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- python: "3.7"
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addons:
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apt:
@@ -95,6 +96,7 @@ matrix:
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- libsuitesparse-dev
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env:
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- PYBAMM_UNIT=true
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- PYBAMM_EXAMPLES=true
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if: type != cron
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# Cover, docs and style checking, latest Python version only
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- python: "3.7"

‎CHANGELOG.md

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@@ -2,6 +2,9 @@
22

33
## Features
44

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- Added fuzzy string matching for parameters and variables ([#796](https://github.com/pybamm-team/PyBaMM/pull/796))
6+
- 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))
7+
- 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))
58
- 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))
69
- 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))
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- Added notebook to explain broadcasts ([#776](https://github.com/pybamm-team/PyBaMM/pull/776))
@@ -33,6 +36,7 @@
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## Optimizations
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- Simplified solver interface ([#800](https://github.com/pybamm-team/PyBaMM/pull/800))
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- Added caching for shape evaluation, used during discretisation ([#780](https://github.com/pybamm-team/PyBaMM/pull/780))
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- Added an option to skip model checks during discretisation, which could be slow for large models ([#739](https://github.com/pybamm-team/PyBaMM/pull/739))
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- Use CasADi's automatic differentation algorithms by default when solving a model ([#714](https://github.com/pybamm-team/PyBaMM/pull/714))
@@ -41,6 +45,8 @@
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## Bug fixes
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- Fixed examples to run with basic pip installation ([#800](https://github.com/pybamm-team/PyBaMM/pull/800))
49+
- Added events for CasADi solver when stepping ([#800](https://github.com/pybamm-team/PyBaMM/pull/800))
4450
- Improved implementation of broadcasts ([#776](https://github.com/pybamm-team/PyBaMM/pull/776))
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- Fixed a bug which meant that the Ohmic heating in the current collectors was incorrect if using the Finite Element Method ([#767](https://github.com/pybamm-team/PyBaMM/pull/767))
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- Improved automatic broadcasting ([#747](https://github.com/pybamm-team/PyBaMM/pull/747))

‎docs/source/expression_tree/variable.rst

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@@ -3,3 +3,6 @@ Variable
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.. autoclass:: pybamm.Variable
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:members:
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.. autoclass:: pybamm.ExternalVariable
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:members:

‎docs/source/models/lithium_ion/dfn.rst

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@@ -3,3 +3,6 @@ Doyle-Fuller-Newman (DFN)
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.. autoclass:: pybamm.lithium_ion.DFN
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:members:
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.. autoclass:: pybamm.lithium_ion.BasicDFN
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:members:

‎docs/source/models/lithium_ion/spm.rst

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@@ -3,3 +3,6 @@ Single Particle Model (SPM)
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.. autoclass:: pybamm.lithium_ion.SPM
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:members:
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.. autoclass:: pybamm.lithium_ion.BasicSPM
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:members:

‎docs/source/solvers/base_solvers.rst

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@@ -3,9 +3,3 @@ Base Solvers
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.. autoclass:: pybamm.BaseSolver
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:members:
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.. autoclass:: pybamm.OdeSolver
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:members:
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.. autoclass:: pybamm.DaeSolver
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:members:

‎docs/tutorials/add-solver.rst

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@@ -27,29 +27,29 @@ The role of solvers is to solve a model at a given set of time points, returning
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Base solver classes vs specific solver classes
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----------------------------------------------
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There is one general base solver class, :class:`pybamm.BaseSolver`, and two specialised base classes, :class:`pybamm.OdeSolver` and :class:`pybamm.DaeSolver`. The general base class simply sets up some useful solver properties such as tolerances. The specialised base classes implement a method :meth:`self.solve()` that solves a model at a given set of time points.
30+
There is one general base solver class, :class:`pybamm.BaseSolver`, which sets up some useful solver properties such as tolerances and implement a method :meth:`self.solve()` that solves a model at a given set of time points.
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The ``solve`` method unpacks the model, simplifies it by removing extraneous operations, (optionally) creates or calls the mass matrix and/or jacobian, and passes the appropriate attributes to another method, called ``integrate``, which does the time-stepping. The role of specific solver classes is simply to implement this ``integrate`` method for an arbitrary set of derivative function, initial conditions etc.
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The base DAE solver class also computes a consistent set of initial conditions for the algebraic equations, using ``model.concatenated_initial_conditions`` as an initial guess.
34+
The base solver class also computes a consistent set of initial conditions for the algebraic equations, using ``model.concatenated_initial_conditions`` as an initial guess.
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Implementing a new solver
3737
-------------------------
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To add a new solver (e.g. My Fast DAE Solver), first create a new file (``my_fast_dae_solver.py``) in ``pybamm/solvers/``,
40-
with a single class that inherits from either :class:`pybamm.OdeSolver` or :class:`pybamm.DaeSolver`, depending on whether the new solver can solve DAE systems. For example:
40+
with a single class that inherits from :class:`pybamm.BaseSolver`. For example:
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.. code-block:: python
4343
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def MyFastDaeSolver(pybamm.DaeSolver):
44+
def MyFastDaeSolver(pybamm.BaseSolver):
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Also add the class to ``pybamm/__init__.py``:
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.. code-block:: python
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from .solvers.my_fast_dae_solver import MyFastDaeSolver
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You can then start implementing the solver by adding the ``integrate`` function to the class (the interfaces are slightly different for an ODE Solver and a DAE Solver, see :meth:`pybamm.OdeSolver.integrate` vs :meth:`pybamm.DaeSolver.integrate`)
52+
You can then start implementing the solver by adding the ``integrate`` function to the class.
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For an example of an existing solver implementation, see the Scikits DAE solver
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`API docs <https://pybamm.readthedocs.io/en/latest/source/solvers/scikits_solvers.html>`_

‎examples/notebooks/README.md

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@@ -48,7 +48,9 @@ The following notebooks are specific to different stages of the PyBaMM pipeline,
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### Models
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The following models are implemented and can easily be used or [compared](./models/lead-acid.ipynb). We always welcome [new models](https://pybamm.readthedocs.io/en/latest/tutorials/add-model.html)!
51+
Several battery models are implemented and can easily be used or [compared](./models/lead-acid.ipynb). The notebooks below show the solution of each individual model. We always welcome [new models](https://pybamm.readthedocs.io/en/latest/tutorials/add-model.html)!
52+
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Once you are comfortable with the expression tree structure, a good starting point to understand the models in PyBaMM is to take a look at the [basic SPM](https://github.com/pybamm-team/PyBaMM/blob/master/pybamm/models/full_battery_models/lithium_ion/basic_spm.py) and [basic DFN](https://github.com/pybamm-team/PyBaMM/blob/master/pybamm/models/full_battery_models/lithium_ion/basic_dfn.py), since these define the entire model (variables, equations, initial and boundary conditions, events) in a single class and so are easier to understand. However, we recommend that you subsequently use the full models as they offer much greater flexibility for coupling different physical effects and visualising a greater range of variables.
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#### Lithium-ion models
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@@ -72,10 +74,9 @@ See [here](https://pybamm.readthedocs.io/en/latest/tutorials/add-spatial-method.
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### Solvers
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The following solvers are implemented
76-
- Scipy ODE solver
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- [Scikits ODE solver](./solvers/scikits-ode-solver.ipynb)
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- [Scikits DAE solver](./solvers/scikits-dae-solver.ipynb)
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- CasADi DAE solver
77+
The following notebooks show examples for generic ODE and DAE solvers. Several solvers are implemented in PyBaMM and we encourage users to try different ones to find the most appropriate one for their models.
78+
79+
- [ODE solver](./solvers/ode-solver.ipynb)
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- [DAE solver](./solvers/dae-solver.ipynb)
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See [here](https://pybamm.readthedocs.io/en/latest/tutorials/add-solver.html) for instructions on adding new solvers.

‎examples/notebooks/change-settings.ipynb

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@@ -123,6 +123,26 @@
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<bound method ParameterValues.items of <pybamm.parameters.parameter_values.ParameterValues object at 0x1113519e8>>"
131+
]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"model.default_parameter_values.items"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
@@ -155,8 +175,8 @@
155175
"Typical current [A] 0.680616\n",
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"Negative electrode conductivity [S.m-1] 100.0\n",
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"Maximum concentration in negative electrode [mol.m-3] 24983.2619938437\n",
158-
"Negative electrode diffusivity [m2.s-1] <function graphite_mcmb2528_diffusivity_Dualfoil1998 at 0x13e6f9840>\n",
159-
"Negative electrode OCP [V] <function graphite_mcmb2528_ocp_Dualfoil1998 at 0x13e6f96a8>\n",
178+
"Negative electrode diffusivity [m2.s-1] <function graphite_mcmb2528_diffusivity_Dualfoil1998 at 0x13dad4400>\n",
179+
"Negative electrode OCP [V] <function graphite_mcmb2528_ocp_Dualfoil1998 at 0x13dad4598>\n",
160180
"Negative electrode porosity 0.3\n",
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"Negative electrode active material volume fraction 0.7\n",
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"Negative particle radius [m] 1e-05\n",
@@ -173,15 +193,15 @@
173193
"Negative electrode density [kg.m-3] 1657.0\n",
174194
"Negative electrode specific heat capacity [J.kg-1.K-1] 700.0\n",
175195
"Negative electrode thermal conductivity [W.m-1.K-1] 1.7\n",
176-
"Negative electrode OCP entropic change [V.K-1] <function graphite_entropic_change_Moura2016 at 0x13e6f9730>\n",
196+
"Negative electrode OCP entropic change [V.K-1] <function graphite_entropic_change_Moura2016 at 0x13dad4488>\n",
177197
"Reference temperature [K] 298.15\n",
178-
"Negative electrode reaction rate <function graphite_electrolyte_reaction_rate_Dualfoil1998 at 0x13e6f98c8>\n",
198+
"Negative electrode reaction rate <function graphite_electrolyte_reaction_rate_Dualfoil1998 at 0x13dad4620>\n",
179199
"Negative reaction rate activation energy [J.mol-1] 37480.0\n",
180200
"Negative solid diffusion activation energy [J.mol-1] 42770.0\n",
181201
"Positive electrode conductivity [S.m-1] 10.0\n",
182202
"Maximum concentration in positive electrode [mol.m-3] 51217.9257309275\n",
183-
"Positive electrode diffusivity [m2.s-1] <function lico2_diffusivity_Dualfoil1998 at 0x13e6f97b8>\n",
184-
"Positive electrode OCP [V] <function lico2_ocp_Dualfoil1998 at 0x13e6f9950>\n",
203+
"Positive electrode diffusivity [m2.s-1] <function lico2_diffusivity_Dualfoil1998 at 0x13dad4510>\n",
204+
"Positive electrode OCP [V] <function lico2_ocp_Dualfoil1998 at 0x13dad46a8>\n",
185205
"Positive electrode porosity 0.3\n",
186206
"Positive electrode active material volume fraction 0.7\n",
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"Positive particle radius [m] 1e-05\n",
@@ -198,8 +218,8 @@
198218
"Positive electrode density [kg.m-3] 3262.0\n",
199219
"Positive electrode specific heat capacity [J.kg-1.K-1] 700.0\n",
200220
"Positive electrode thermal conductivity [W.m-1.K-1] 2.1\n",
201-
"Positive electrode OCP entropic change [V.K-1] <function lico2_entropic_change_Moura2016 at 0x13e6f9a60>\n",
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"Positive electrode reaction rate <function lico2_electrolyte_reaction_rate_Dualfoil1998 at 0x13e6f9ae8>\n",
221+
"Positive electrode OCP entropic change [V.K-1] <function lico2_entropic_change_Moura2016 at 0x13dad47b8>\n",
222+
"Positive electrode reaction rate <function lico2_electrolyte_reaction_rate_Dualfoil1998 at 0x13dad4840>\n",
203223
"Positive reaction rate activation energy [J.mol-1] 39570.0\n",
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"Positive solid diffusion activation energy [J.mol-1] 18550.0\n",
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"Separator porosity 1.0\n",
@@ -210,8 +230,8 @@
210230
"Separator thermal conductivity [W.m-1.K-1] 0.16\n",
211231
"Typical electrolyte concentration [mol.m-3] 1000.0\n",
212232
"Cation transference number 0.4\n",
213-
"Electrolyte diffusivity [m2.s-1] <function electrolyte_diffusivity_Capiglia1999 at 0x13e6f9c80>\n",
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"Electrolyte conductivity [S.m-1] <function electrolyte_conductivity_Capiglia1999 at 0x13e6f99d8>\n",
233+
"Electrolyte diffusivity [m2.s-1] <function electrolyte_diffusivity_Capiglia1999 at 0x13dad49d8>\n",
234+
"Electrolyte conductivity [S.m-1] <function electrolyte_conductivity_Capiglia1999 at 0x13dad4730>\n",
215235
"Electrolyte diffusion activation energy [J.mol-1] 37040.0\n",
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"Electrolyte conductivity activation energy [J.mol-1] 34700.0\n",
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"Heat transfer coefficient [W.m-2.K-1] 10.0\n",
@@ -250,7 +270,7 @@
250270
},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 5,
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"metadata": {},
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{
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"execution_count": 6,
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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},
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{
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"execution_count": 8,
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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"execution_count": 11,
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"metadata": {},
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{
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},
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"execution_count": 12,
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"metadata": {},
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},
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{
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"execution_count": 13,
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"metadata": {},
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{

‎examples/notebooks/parameter-values.ipynb

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"name": "stdout",
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"text": [
50-
"parameter values are {'a': 1, 'b': 2, 'c': 3}\n"
50+
"parameter values are <pybamm.parameters.parameter_values.ParameterValues object at 0x13dd5e0f0>\n"
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5252
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"name": "stdout",
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76-
"parameter values are {'a': 4, 'b': 5, 'c': 6}\n"
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"parameter values are <pybamm.parameters.parameter_values.ParameterValues object at 0x13dd5e860>\n"
7777
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126126
"cell_type": "markdown",
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128128
"source": [
129-
"We can input functions into the parameter values, either directly"
129+
"We can input functions into the parameter values, either directly (note we bypass the check that the parameter already exists)"
130130
]
131131
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@@ -138,14 +138,14 @@
138138
"name": "stdout",
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"output_type": "stream",
140140
"text": [
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"parameter values are {'a': 4, 'b': 5, 'c': 6, 'cube function': <function cubed at 0x136260a60>}\n"
141+
"parameter values are <pybamm.parameters.parameter_values.ParameterValues object at 0x13dd5e860>\n"
142142
]
143143
}
144144
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"source": [
146146
"def cubed(x):\n",
147147
" return x ** 3\n",
148-
"parameter_values.update({\"cube function\": cubed})\n",
148+
"parameter_values.update({\"cube function\": cubed}, check_already_exists=False)\n",
149149
"print(\"parameter values are {}\".format(parameter_values))"
150150
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151151
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@@ -165,7 +165,7 @@
165165
"name": "stdout",
166166
"output_type": "stream",
167167
"text": [
168-
"parameter values are {'a': 4, 'b': 5, 'c': 6, 'cube function': <function cubed at 0x136260a60>, 'square function': <function squared at 0x136260ae8>}\n"
168+
"parameter values are <pybamm.parameters.parameter_values.ParameterValues object at 0x13dd5e860>\n"
169169
]
170170
}
171171
],
@@ -178,7 +178,7 @@
178178
"\"\"\"\n",
179179
")\n",
180180
"f.close()\n",
181-
"parameter_values.update({\"square function\": pybamm.load_function(\"squared.py\")})\n",
181+
"parameter_values.update({\"square function\": pybamm.load_function(\"squared.py\")}, check_already_exists=False)\n",
182182
"print(\"parameter values are {}\".format(parameter_values))"
183183
]
184184
},
@@ -405,7 +405,7 @@
405405
{
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"data": {
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"text/plain": [
408-
"{Variable(-0x53753a8d5f6f95de, u, children=[], domain=[], auxiliary_domains={}): Multiplication(0x3e1bde14593f44cc, *, children=['-a', 'y[0:1]'], domain=[], auxiliary_domains={})}"
408+
"{Variable(0x1b4aef6f668c631, u, children=[], domain=[], auxiliary_domains={}): Multiplication(-0x36caade7fdf02dac, *, children=['-a', 'y[0:1]'], domain=[], auxiliary_domains={})}"
409409
]
410410
},
411411
"execution_count": 12,

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