#1100 merge

Author: valentinsulzer

examples/notebooks/Getting Started/Tutorial 4 - Setting parameter values.ipynb

@@ -887,7 +887,7 @@
     "\n",
     "# Create interpolant\n",
     "timescale = parameter_values.evaluate(model.timescale)\n",
-    "current_interpolant = pybamm.Interpolant(drive_cycle, timescale * pybamm.t)\n",
+    "current_interpolant = pybamm.Interpolant(drive_cycle[:, 0], drive_cycle[:, 1], timescale * pybamm.t)\n",
     "\n",
     "# Set drive cycle\n",
     "parameter_values[\"Current function [A]\"] = current_interpolant"

examples/notebooks/Getting Started/Tutorial 6 - Managing simulation outputs.ipynb

@@ -22,23 +22,23 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "\u001b[33mWARNING: You are using pip version 20.2.1; however, version 20.2.4 is available.\n",
+      "\u001b[33mWARNING: You are using pip version 20.2.4; however, version 20.3.3 is available.\n",
       "You should consider upgrading via the '/Users/vsulzer/Documents/Energy_storage/PyBaMM/.tox/dev/bin/python -m pip install --upgrade pip' command.\u001b[0m\n",
       "Note: you may need to restart the kernel to use updated packages.\n"
      ]
     },
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
-       "<pybamm.solvers.solution.Solution at 0x1467c6820>"
+       "<pybamm.solvers.solution.Solution at 0x1479dff10>"
       ]
      },
+     "execution_count": 1,
      "metadata": {},
-     "execution_count": 1
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -102,33 +102,33 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
-       "array([3.77047806, 3.75305163, 3.74567013, 3.74038819, 3.73581198,\n",
-       "       3.73153388, 3.72742394, 3.72343938, 3.71956644, 3.71580196,\n",
-       "       3.71214617, 3.70860034, 3.70516557, 3.70184247, 3.69863116,\n",
-       "       3.69553115, 3.69254136, 3.6896602 , 3.68688564, 3.68421527,\n",
+       "array([3.77047806, 3.75305182, 3.74567027, 3.74038822, 3.73581196,\n",
+       "       3.73153391, 3.72742393, 3.72343929, 3.71956623, 3.71580184,\n",
+       "       3.71214621, 3.7086004 , 3.70516561, 3.70184253, 3.69863121,\n",
+       "       3.69553118, 3.69254137, 3.68966018, 3.68688562, 3.68421526,\n",
        "       3.68164637, 3.67917591, 3.6768006 , 3.67451688, 3.67232094,\n",
-       "       3.6702087 , 3.66817572, 3.66621717, 3.66432763, 3.66250091,\n",
-       "       3.66072975, 3.65900537, 3.65731692, 3.65565067, 3.65398896,\n",
-       "       3.65230898, 3.65058136, 3.6487688 , 3.64682545, 3.64469796,\n",
-       "       3.64232964, 3.63966968, 3.63668791, 3.63339298, 3.62984705,\n",
-       "       3.62616685, 3.62250444, 3.61901236, 3.61580864, 3.61295718,\n",
-       "       3.61046845, 3.60831404, 3.60644483, 3.60480596, 3.60334607,\n",
+       "       3.67020869, 3.66817572, 3.66621717, 3.66432762, 3.6625009 ,\n",
+       "       3.66072974, 3.65900536, 3.65731692, 3.65565066, 3.65398895,\n",
+       "       3.65230898, 3.65058135, 3.6487688 , 3.64682546, 3.64469798,\n",
+       "       3.64232968, 3.63966973, 3.63668796, 3.63339303, 3.62984711,\n",
+       "       3.62616692, 3.6225045 , 3.61901241, 3.61580868, 3.6129572 ,\n",
+       "       3.61046847, 3.60831405, 3.60644483, 3.60480596, 3.60334607,\n",
        "       3.60202167, 3.60079822, 3.5996495 , 3.59855637, 3.59750531,\n",
        "       3.59648723, 3.59549638, 3.59452954, 3.59358541, 3.59266405,\n",
        "       3.59176646, 3.59089417, 3.59004885, 3.58923192, 3.58844407,\n",
        "       3.58768477, 3.58695179, 3.58624057, 3.58554372, 3.58485045,\n",
        "       3.58414611, 3.58341187, 3.58262441, 3.58175587, 3.58077378,\n",
        "       3.57964098, 3.57831538, 3.5767492 , 3.57488745, 3.57266504,\n",
-       "       3.5700019 , 3.56679523, 3.56290767, 3.5581495 , 3.55225276,\n",
-       "       3.54483362, 3.53533853, 3.52296795, 3.50656968, 3.48449277,\n",
-       "       3.45439366, 3.41299183, 3.35578872, 3.27680073, 3.16842637])"
+       "       3.5700019 , 3.56679523, 3.56290766, 3.5581495 , 3.55225276,\n",
+       "       3.54483361, 3.53533853, 3.52296795, 3.50656968, 3.48449277,\n",
+       "       3.45439366, 3.41299182, 3.35578871, 3.27680072, 3.16842636])"
       ]
      },
+     "execution_count": 4,
      "metadata": {},
-     "execution_count": 4
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -148,7 +148,6 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "array([   0.        ,   36.36363636,   72.72727273,  109.09090909,\n",
@@ -178,8 +177,9 @@
        "       3490.90909091, 3527.27272727, 3563.63636364, 3600.        ])"
       ]
      },
+     "execution_count": 5,
      "metadata": {},
-     "execution_count": 5
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -199,14 +199,14 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
-       "array([3.72947891, 3.70860034, 3.67810702, 3.65400558])"
+       "array([3.72947892, 3.7086004 , 3.67810702, 3.65400557])"
       ]
      },
+     "execution_count": 6,
      "metadata": {},
-     "execution_count": 6
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -265,16 +265,18 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "interactive(children=(FloatSlider(value=0.0, description='t', max=1.0, step=0.01), Output()), _dom_classes=('w…",
       "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8ceaea70446149079f0194450d7828dc",
        "version_major": 2,
-       "version_minor": 0,
-       "model_id": "0b4ebac3fdd947218f9444b2b381cf04"
-      }
+       "version_minor": 0
+      },
+      "text/plain": [
+       "interactive(children=(FloatSlider(value=0.0, description='t', max=1.0, step=0.01), Output()), _dom_classes=('w…"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -311,26 +313,28 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "interactive(children=(FloatSlider(value=0.0, description='t', max=1.0, step=0.01), Output()), _dom_classes=('w…",
       "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9c9e516a7aef46688f03aaea77505636",
        "version_major": 2,
-       "version_minor": 0,
-       "model_id": "f4a1b65b2bf945099197135c5598084b"
-      }
+       "version_minor": 0
+      },
+      "text/plain": [
+       "interactive(children=(FloatSlider(value=0.0, description='t', max=1.0, step=0.01), Output()), _dom_classes=('w…"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
-       "<pybamm.plotting.quick_plot.QuickPlot at 0x14be13b80>"
+       "<pybamm.plotting.quick_plot.QuickPlot at 0x149685400>"
       ]
      },
+     "execution_count": 11,
      "metadata": {},
-     "execution_count": 11
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -425,9 +429,22 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5-final"
+   "version": "3.8.6"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": true
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}

examples/notebooks/change-input-current.ipynb

@@ -158,7 +158,7 @@
     "\n",
     "# create interpolant - must be a function of *dimensional* time\n",
     "timescale = param.evaluate(model.timescale)\n",
-    "current_interpolant = pybamm.Interpolant(drive_cycle, timescale * pybamm.t)\n",
+    "current_interpolant = pybamm.Interpolant(drive_cycle[:, 0], drive_cycle[:, 1], timescale * pybamm.t)\n",
     "\n",
     "# set drive cycle\n",
     "param[\"Current function [A]\"] = current_interpolant\n",

examples/notebooks/initialize-model-with-solution.ipynb

@@ -82,7 +82,7 @@
     "# create interpolant\n",
     "param = model.default_parameter_values\n",
     "timescale = param.evaluate(model.timescale)\n",
-    "current_interpolant = pybamm.Interpolant(drive_cycle, timescale * pybamm.t)\n",
+    "current_interpolant = pybamm.Interpolant(drive_cycle[:, 0], drive_cycle[:, 1], timescale * pybamm.t)\n",
     "# set drive cycle\n",
     "param[\"Current function [A]\"] = current_interpolant"
    ]

examples/notebooks/models/pouch-cell-model.ipynb

@@ -1,5 +1,4 @@
 import pybamm
-import numpy as np
 import os
 import pickle
 import scipy.interpolate as interp
@@ -78,29 +77,17 @@ def get_interp_fun(variable_name, domain):
         comsol_x = comsol_variables["x_p"]
     elif domain == whole_cell:
         comsol_x = comsol_variables["x"]
+
     # Make sure to use dimensional space
     pybamm_x = mesh.combine_submeshes(*domain).nodes * L_x
     variable = interp.interp1d(comsol_x, variable, axis=0)(pybamm_x)
 
-    def myinterp(t):
-        try:
-            return interp.interp1d(
-                comsol_t, variable, fill_value="extrapolate", bounds_error=False
-            )(t)[:, np.newaxis]
-        except ValueError as err:
-            raise ValueError(
-                (
-                    "Failed to interpolate '{}' with time range [{}, {}] at time {}."
-                    + "Original error: {}"
-                ).format(variable_name, comsol_t[0], comsol_t[-1], t, err)
-            )
-
-    # Make sure to use dimensional time
-    fun = pybamm.Function(
-        myinterp,
+    fun = pybamm.Interpolant(
+        comsol_t,
+        variable.T,
         pybamm.t * pybamm_model.timescale.evaluate(),
-        name=variable_name + "_comsol",
     )
+
     fun.domain = domain
     fun.mesh = mesh.combine_submeshes(*domain)
     fun.secondary_mesh = None
@@ -113,15 +100,12 @@ def myinterp(t):
 comsol_phi_n = get_interp_fun("phi_n", ["negative electrode"])
 comsol_phi_e = get_interp_fun("phi_e", whole_cell)
 comsol_phi_p = get_interp_fun("phi_p", ["positive electrode"])
-comsol_voltage = pybamm.Function(
-    interp.interp1d(
-        comsol_t,
-        comsol_variables["voltage"],
-        fill_value="extrapolate",
-        bounds_error=False,
-    ),
+comsol_voltage = pybamm.Interpolant(
+    comsol_t,
+    comsol_variables["voltage"],
     pybamm.t * pybamm_model.timescale.evaluate(),
 )
+
 comsol_voltage.mesh = None
 comsol_voltage.secondary_mesh = None
 

examples/scripts/compare_comsol/compare_comsol_DFN.py

@@ -21,7 +21,9 @@
 
 # create interpolant
 timescale = param.evaluate(model.timescale)
-current_interpolant = pybamm.Interpolant(drive_cycle, timescale * pybamm.t)
+current_interpolant = pybamm.Interpolant(
+    drive_cycle[:, 0], drive_cycle[:, 1], timescale * pybamm.t
+)
 
 # set drive cycle
 param["Current function [A]"] = current_interpolant

examples/scripts/drive_cycle.py

@@ -4,18 +4,18 @@
 import pybamm
 import matplotlib.pyplot as plt
 
-pybamm.set_logging_level("DEBUG")
+pybamm.set_logging_level("INFO")
 experiment = pybamm.Experiment(
     [
-        "Discharge at C/1 for 1 hours or until 3.3 V",
+        "Discharge at C/10 for 10 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
 )
-model = pybamm.lithium_ion.SPM()
+model = pybamm.lithium_ion.DFN()
 sim = pybamm.Simulation(model, experiment=experiment, solver=pybamm.CasadiSolver())
 sim.solve()
 

examples/scripts/experimental_protocols/cccv.py

@@ -792,8 +792,8 @@ def process_dict(self, var_eqn_dict):
         """
         new_var_eqn_dict = {}
         for eqn_key, eqn in var_eqn_dict.items():
-            # Broadcast if the equation evaluates to a number(e.g. Scalar)
-            if eqn.evaluates_to_number() and not isinstance(eqn_key, str):
+            # Broadcast if the equation evaluates to a number (e.g. Scalar)
+            if np.prod(eqn.shape_for_testing) == 1 and not isinstance(eqn_key, str):
                 eqn = pybamm.FullBroadcast(
                     eqn, eqn_key.domain, eqn_key.auxiliary_domains
                 )