Issue 920 dimensional interp

CHANGELOG.md

@@ -45,6 +45,7 @@
 
 ## Breaking changes
 
+-   Calls to `ProcessedVariable` objects are now made using dimensional time and space ([#1028](https://github.com/pybamm-team/PyBaMM/pull/1028))
 -   For variables discretised using finite elements the result returned by calling `ProcessedVariable` is now transposed ([#1020](https://github.com/pybamm-team/PyBaMM/pull/1020))
 -   Renamed "surface area density" to "surface area to volume ratio" ([#975](https://github.com/pybamm-team/PyBaMM/pull/975))
 -   Replaced "reaction rate" with "exchange-current density" ([#975](https://github.com/pybamm-team/PyBaMM/pull/975))

examples/notebooks/Creating Models/1-an-ode-model.ipynb

@@ -253,6 +253,13 @@
    "source": [
     "In the [next notebook](./2-a-pde-model.ipynb) we show how to create, discretise and solve a PDE model in pybamm."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -271,7 +278,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.5"
+   "version": "3.6.9"
   }
  },
  "nbformat": 4,

examples/notebooks/Creating Models/2-a-pde-model.ipynb

@@ -280,6 +280,13 @@
    "source": [
     "In the [next notebook](./3-negative-particle-problem.ipynb) we build on the example here to to solve the problem of diffusion in the negative electrode particle within the single particle model. In doing so we will also cover how to include parameters in a model. "
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {

examples/notebooks/Creating Models/3-negative-particle-problem.ipynb

@@ -298,6 +298,13 @@
    "source": [
     "In the [next notebook](./4-comparing-full-and-reduced-order-models.ipynb) we consider the limit of fast diffusion in the particle. This leads to a reduced-order model for the particle behaviour, which we compare with the full (Fickian diffusion) model. "
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -316,7 +323,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.5"
+   "version": "3.6.9"
   }
  },
  "nbformat": 4,

examples/notebooks/Creating Models/4-comparing-full-and-reduced-order-models.ipynb

@@ -282,7 +282,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "dbcd70fa09c6404dab80036156401985",
+       "model_id": "a020dc7cd8574e698ef0e06d4392e689",
        "version_major": 2,
        "version_minor": 0
       },
@@ -357,6 +357,13 @@
    "source": [
     "In the [next notebook](./5-a-simple-SEI-model.ipynb) we consider a simple model for SEI growth, and show how to correctly pose the model in non-dimensional form and then create and solve it using pybamm."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -375,7 +382,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.5"
+   "version": "3.6.9"
   }
  },
  "nbformat": 4,

examples/notebooks/Creating Models/5-a-simple-SEI-model.ipynb

@@ -591,7 +591,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "efe1fe18458a42d88056baf689f6da80",
+       "model_id": "8d9c98b030934135908c6ddd5c92699b",
        "version_major": 2,
        "version_minor": 0
       },
@@ -635,6 +635,13 @@
    "source": [
     "The purpose of this notebook has been to go through the steps involved in getting a simple model working within PyBaMM. However, if you plan on reusing your model and want greater flexibility then we recommend that you create a new class for your model. We have set out instructions on how to do this in the \"Adding a Model\" tutorial in the documentation. "
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {