Merge pull request #3656 from Saransh-cpp/ruff-format

Migrate to ruff format
pybamm-team · Dec 24, 2023 · 8dc0421 · 8dc0421
2 parents 691057f + d8eedf1
commit 8dc0421
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diff --git a/.git-blame-ignore-revs b/.git-blame-ignore-revs
@@ -4,7 +4,9 @@
 a63e49ece0f9336d1f5c2562f7459e555c6e6693
 # activated standard pre-commits - https://github.com/pybamm-team/PyBaMM/pull/3192
 5273214b585c5a4286609aed40e0b092d0e05f42
-# migrate config to pyproject.toml - https://github.com/pybamm-team/PyBaMM/pull/3557
+# migrated config to pyproject.toml - https://github.com/pybamm-team/PyBaMM/pull/3557
 12c5d77203bd93542785d237bac00bad5ed5469a
 # activated pyupgrade - https://github.com/pybamm-team/PyBaMM/pull/3579
 ff6d81c01331c7d269303b4a8321d9881bdf98fa
+# migrated to ruff-format - https://github.com/pybamm-team/PyBaMM/pull/3655
+60ebd4148059a95428a496f4f55c1175ead362d3
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -9,12 +9,14 @@ repos:
       - id: ruff
         args: [--fix, --show-fixes]
         types_or: [python, pyi, jupyter]
+      - id: ruff-format
+        types_or: [python, pyi, jupyter]
 
   - repo: https://github.com/adamchainz/blacken-docs
     rev: "1.16.0"
     hooks:
        - id: blacken-docs
-         additional_dependencies: [black==22.12.0]
+         additional_dependencies: [black==23.*]
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v4.5.0

diff --git a/docs/source/examples/notebooks/batch_study.ipynb b/docs/source/examples/notebooks/batch_study.ipynb
@@ -136,7 +136,9 @@
     "parameter_values = {\"Chen2020\": pybamm.ParameterValues(\"Chen2020\")}\n",
     "\n",
     "# creating a BatchStudy object and solving the simulation\n",
-    "batch_study = pybamm.BatchStudy(models=models, parameter_values=parameter_values, permutations=True)\n",
+    "batch_study = pybamm.BatchStudy(\n",
+    "    models=models, parameter_values=parameter_values, permutations=True\n",
+    ")\n",
     "batch_study.solve(t_eval=[0, 3600])\n",
     "batch_study.plot()"
    ]
@@ -195,13 +197,17 @@
     "# different values for \"Current function [A]\"\n",
     "current_values = [4.5, 4.75, 5]\n",
     "\n",
-    "# changing the value of \"Current function [A]\" in all the parameter values present in the \n",
+    "# changing the value of \"Current function [A]\" in all the parameter values present in the\n",
     "# parameter_values dictionary\n",
-    "for k, v, current_value in zip(parameter_values.keys(), parameter_values.values(), current_values):\n",
-    "    v[\"Current function [A]\"] = current_value \n",
+    "for k, v, current_value in zip(\n",
+    "    parameter_values.keys(), parameter_values.values(), current_values\n",
+    "):\n",
+    "    v[\"Current function [A]\"] = current_value\n",
     "\n",
     "# creating a BatchStudy object with permutations set to True to create a cartesian product\n",
-    "batch_study = pybamm.BatchStudy(models=model, parameter_values=parameter_values, permutations=True)\n",
+    "batch_study = pybamm.BatchStudy(\n",
+    "    models=model, parameter_values=parameter_values, permutations=True\n",
+    ")\n",
     "batch_study.solve(t_eval=[0, 3600])\n",
     "\n",
     "# generating the required labels and plotting\n",
@@ -474,19 +480,19 @@
     "# using the cccv experiment with 10 cycles\n",
     "cccv = pybamm.Experiment(\n",
     "    [\n",
-    "        (\"Discharge at C/10 for 10 hours or until 3.3 V\",\n",
-    "        \"Rest for 1 hour\",\n",
-    "        \"Charge at 1 A until 4.1 V\",\n",
-    "        \"Hold at 4.1 V until 50 mA\",\n",
-    "        \"Rest for 1 hour\")\n",
+    "        (\n",
+    "            \"Discharge at C/10 for 10 hours or until 3.3 V\",\n",
+    "            \"Rest for 1 hour\",\n",
+    "            \"Charge at 1 A until 4.1 V\",\n",
+    "            \"Hold at 4.1 V until 50 mA\",\n",
+    "            \"Rest for 1 hour\",\n",
+    "        )\n",
     "    ]\n",
     "    * 10,\n",
     ")\n",
     "\n",
     "# creating the experiment dict\n",
-    "experiment = {\n",
-    "    \"cccv\": cccv\n",
-    "}\n",
+    "experiment = {\"cccv\": cccv}\n",
     "\n",
     "# populating a dictionary with 3 same parameter values (Mohtat2020 chemistry)\n",
     "parameter_values = {\n",
@@ -499,23 +505,31 @@
     "inner_sei_oc_v_values = [2.0e-4, 2.7e-4, 3.4e-4]\n",
     "\n",
     "# updating the value of \"Inner SEI open-circuit potential [V]\" in all the dictionary items\n",
-    "for k, v, inner_sei_oc_v in zip(parameter_values.keys(), parameter_values.values(), inner_sei_oc_v_values):\n",
+    "for k, v, inner_sei_oc_v in zip(\n",
+    "    parameter_values.keys(), parameter_values.values(), inner_sei_oc_v_values\n",
+    "):\n",
     "    v.update(\n",
-    "        {\n",
-    "            \"Inner SEI open-circuit potential [V]\": inner_sei_oc_v\n",
-    "        },\n",
+    "        {\"Inner SEI open-circuit potential [V]\": inner_sei_oc_v},\n",
     "    )\n",
     "\n",
     "# creating a Single Particle Model with \"electron-mitigation limited\" SEI\n",
     "model = {\"spm\": pybamm.lithium_ion.SPM({\"SEI\": \"electron-migration limited\"})}\n",
     "\n",
     "# creating a BatchStudy object with the given experimen, model and parameter_values\n",
-    "batch_study = pybamm.BatchStudy(models=model, experiments=experiment, parameter_values=parameter_values, permutations=True)\n",
+    "batch_study = pybamm.BatchStudy(\n",
+    "    models=model,\n",
+    "    experiments=experiment,\n",
+    "    parameter_values=parameter_values,\n",
+    "    permutations=True,\n",
+    ")\n",
     "\n",
-    "#solving and plotting the result\n",
+    "# solving and plotting the result\n",
     "batch_study.solve(initial_soc=1)\n",
     "\n",
-    "labels = [f\"Inner SEI open-circuit potential [V]: {inner_sei_oc_v}\" for inner_sei_oc_v in inner_sei_oc_v_values]\n",
+    "labels = [\n",
+    "    f\"Inner SEI open-circuit potential [V]: {inner_sei_oc_v}\"\n",
+    "    for inner_sei_oc_v in inner_sei_oc_v_values\n",
+    "]\n",
     "batch_study.plot(labels=labels)"
    ]
   },

diff --git a/docs/source/examples/notebooks/change-settings.ipynb b/docs/source/examples/notebooks/change-settings.ipynb
@@ -48,7 +48,8 @@
     "import numpy as np\n",
     "import os\n",
     "import matplotlib.pyplot as plt\n",
-    "os.chdir(pybamm.__path__[0]+'/..')\n",
+    "\n",
+    "os.chdir(pybamm.__path__[0] + \"/..\")\n",
     "\n",
     "# create the model\n",
     "model = pybamm.lithium_ion.SPM()\n",
@@ -378,9 +379,9 @@
     }
    ],
    "source": [
-    "format_str = '{:<75}  {:>20}'\n",
-    "print(format_str.format('PARAMETER', 'VALUE'))\n",
-    "print(\"-\"*97)\n",
+    "format_str = \"{:<75}  {:>20}\"\n",
+    "print(format_str.format(\"PARAMETER\", \"VALUE\"))\n",
+    "print(\"-\" * 97)\n",
     "for key, value in model.default_parameter_values.items():\n",
     "    try:\n",
     "        print(format_str.format(key, value))\n",
@@ -417,8 +418,8 @@
     "old_value = param[variable]\n",
     "param[variable] = 1.4\n",
     "new_value = param[variable]\n",
-    "print(variable,'was',old_value)\n",
-    "print(variable,'now is',param[variable])"
+    "print(variable, \"was\", old_value)\n",
+    "print(variable, \"now is\", param[variable])"
    ]
   },
   {
@@ -514,8 +515,8 @@
     }
    ],
    "source": [
-    "print(format_str.format('DOMAIN', 'DISCRETISED BY'))\n",
-    "print(\"-\"*82)\n",
+    "print(format_str.format(\"DOMAIN\", \"DISCRETISED BY\"))\n",
+    "print(\"-\" * 82)\n",
     "for key, value in model.default_spatial_methods.items():\n",
     "    print(format_str.format(key, value.__class__.__name__))"
    ]
@@ -553,7 +554,9 @@
    "outputs": [],
    "source": [
     "submesh_types = model.default_submesh_types\n",
-    "submesh_types[\"negative particle\"] = pybamm.MeshGenerator(pybamm.SpectralVolume1DSubMesh)"
+    "submesh_types[\"negative particle\"] = pybamm.MeshGenerator(\n",
+    "    pybamm.SpectralVolume1DSubMesh\n",
+    ")"
    ]
   },
   {
@@ -621,7 +624,7 @@
     }
    ],
    "source": [
-    "print('Default solver for SPM model:',type(model.default_solver).__name__)"
+    "print(\"Default solver for SPM model:\", type(model.default_solver).__name__)"
    ]
   },
   {

diff --git a/docs/source/examples/notebooks/creating_models/1-an-ode-model.ipynb b/docs/source/examples/notebooks/creating_models/1-an-ode-model.ipynb
@@ -117,7 +117,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model.rhs = {x: dxdt, y: dydt} "
+    "model.rhs = {x: dxdt, y: dydt}"
    ]
   },
   {

diff --git a/docs/source/examples/notebooks/creating_models/2-a-pde-model.ipynb b/docs/source/examples/notebooks/creating_models/2-a-pde-model.ipynb
@@ -180,7 +180,9 @@
     "r = pybamm.SpatialVariable(\n",
     "    \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n",
     ")\n",
-    "geometry = {\"negative particle\": {r: {\"min\": pybamm.Scalar(0), \"max\": pybamm.Scalar(1)}}}"
+    "geometry = {\n",
+    "    \"negative particle\": {r: {\"min\": pybamm.Scalar(0), \"max\": pybamm.Scalar(1)}}\n",
+    "}"
    ]
   },
   {

diff --git a/docs/source/examples/notebooks/creating_models/3-negative-particle-problem.ipynb b/docs/source/examples/notebooks/creating_models/3-negative-particle-problem.ipynb
@@ -106,14 +106,14 @@
     "# governing equations\n",
     "N = -D * pybamm.grad(c)  # flux\n",
     "dcdt = -pybamm.div(N)\n",
-    "model.rhs = {c: dcdt}  \n",
+    "model.rhs = {c: dcdt}\n",
     "\n",
-    "# boundary conditions \n",
+    "# boundary conditions\n",
     "lbc = pybamm.Scalar(0)\n",
     "rbc = -j / F / D\n",
     "model.boundary_conditions = {c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}}\n",
     "\n",
-    "# initial conditions \n",
+    "# initial conditions\n",
     "model.initial_conditions = {c: c0}"
    ]
   },
@@ -193,7 +193,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "r = pybamm.SpatialVariable(\"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\")\n",
+    "r = pybamm.SpatialVariable(\n",
+    "    \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n",
+    ")\n",
     "geometry = {\"negative particle\": {r: {\"min\": pybamm.Scalar(0), \"max\": R}}}"
    ]
   },
@@ -305,7 +307,7 @@
     "ax1.set_xlabel(\"Time [s]\")\n",
     "ax1.set_ylabel(\"Surface concentration [mol.m-3]\")\n",
     "\n",
-    "r = mesh[\"negative particle\"].nodes # radial position\n",
+    "r = mesh[\"negative particle\"].nodes  # radial position\n",
     "time = 1000  # time in seconds\n",
     "ax2.plot(r * 1e6, c(t=time, r=r), label=f\"t={time}[s]\")\n",
     "ax2.set_xlabel(\"Particle radius [microns]\")\n",

diff --git a/...source/examples/notebooks/creating_models/4-comparing-full-and-reduced-order-models.ipynb b/...source/examples/notebooks/creating_models/4-comparing-full-and-reduced-order-models.ipynb
@@ -144,11 +144,11 @@
     "# governing equations for full model\n",
     "N = -D * pybamm.grad(c)  # flux\n",
     "dcdt = -pybamm.div(N)\n",
-    "full_model.rhs = {c: dcdt} \n",
+    "full_model.rhs = {c: dcdt}\n",
     "\n",
     "# governing equations for reduced model\n",
     "dc_avdt = -3 * j / R / F\n",
-    "reduced_model.rhs = {c_av: dc_avdt} \n",
+    "reduced_model.rhs = {c_av: dc_avdt}\n",
     "\n",
     "# initial conditions (these are the same for both models)\n",
     "full_model.initial_conditions = {c: c0}\n",
@@ -157,7 +157,9 @@
     "# boundary conditions (only required for full model)\n",
     "lbc = pybamm.Scalar(0)\n",
     "rbc = -j / F / D\n",
-    "full_model.boundary_conditions = {c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}}"
+    "full_model.boundary_conditions = {\n",
+    "    c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n",
+    "}"
    ]
   },
   {
@@ -186,7 +188,7 @@
     "# reduced model\n",
     "reduced_model.variables = {\n",
     "    \"Concentration [mol.m-3]\": pybamm.PrimaryBroadcast(c_av, \"negative particle\"),\n",
-    "    \"Surface concentration [mol.m-3]\": c_av,  # in this model the surface concentration is just equal to the scalar average concentration \n",
+    "    \"Surface concentration [mol.m-3]\": c_av,  # in this model the surface concentration is just equal to the scalar average concentration\n",
     "    \"Average concentration [mol.m-3]\": c_av,\n",
     "}"
    ]
@@ -239,7 +241,9 @@
    "outputs": [],
    "source": [
     "# geometry\n",
-    "r = pybamm.SpatialVariable(\"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\")\n",
+    "r = pybamm.SpatialVariable(\n",
+    "    \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n",
+    ")\n",
     "geometry = {\"negative particle\": {r: {\"min\": pybamm.Scalar(0), \"max\": R}}}\n",
     "param.process_geometry(geometry)\n",
     "\n",
@@ -273,7 +277,7 @@
     "\n",
     "# process models\n",
     "for model in models:\n",
-    "    disc.process_model(model);"
+    "    disc.process_model(model)"
    ]
   },
   {
@@ -346,38 +350,38 @@
     "c_av_reduced = solutions[1][\"Average concentration [mol.m-3]\"]\n",
     "\n",
     "# plot\n",
-    "r = mesh[\"negative particle\"].nodes # radial position\n",
+    "r = mesh[\"negative particle\"].nodes  # radial position\n",
     "\n",
     "\n",
     "def plot(t):\n",
     "    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(13, 4))\n",
-    "    \n",
+    "\n",
     "    # Plot concetration as a function of r\n",
-    "    ax1.plot(r * 1e6, c_full(t=t,r=r), label=\"Full Model\")\n",
-    "    ax1.plot(r * 1e6, c_reduced(t=t,r=r), label=\"Reduced Model\")    \n",
+    "    ax1.plot(r * 1e6, c_full(t=t, r=r), label=\"Full Model\")\n",
+    "    ax1.plot(r * 1e6, c_reduced(t=t, r=r), label=\"Reduced Model\")\n",
     "    ax1.set_xlabel(\"Particle radius [microns]\")\n",
     "    ax1.set_ylabel(\"Concentration [mol.m-3]\")\n",
     "    ax1.legend()\n",
-    "    \n",
+    "\n",
     "    # Plot average concentration over time\n",
     "    t_hour = np.linspace(0, 3600, 600)  # plot over full hour\n",
-    "    c_min = c_av_reduced(t=3600) * 0.98  # minimum axes limit \n",
-    "    c_max = param[\"Initial concentration [mol.m-3]\"] * 1.02   # maximum axes limit \n",
-    "    \n",
+    "    c_min = c_av_reduced(t=3600) * 0.98  # minimum axes limit\n",
+    "    c_max = param[\"Initial concentration [mol.m-3]\"] * 1.02  # maximum axes limit\n",
+    "\n",
     "    ax2.plot(t_hour, c_av_full(t=t_hour), label=\"Full Model\")\n",
-    "    ax2.plot(t_hour, c_av_reduced(t=t_hour), label=\"Reduced Model\") \n",
+    "    ax2.plot(t_hour, c_av_reduced(t=t_hour), label=\"Reduced Model\")\n",
     "    ax2.plot([t, t], [c_min, c_max], \"k--\")  # plot line to track time\n",
     "    ax2.set_xlabel(\"Time [s]\")\n",
-    "    ax2.set_ylabel(\"Average concentration [mol.m-3]\") \n",
+    "    ax2.set_ylabel(\"Average concentration [mol.m-3]\")\n",
     "    ax2.legend()\n",
     "\n",
     "    plt.tight_layout()\n",
     "    plt.show()\n",
-    "                   \n",
+    "\n",
     "\n",
     "import ipywidgets as widgets\n",
-    "widgets.interact(plot, t=widgets.FloatSlider(min=0,max=3600,step=1,value=0));\n",
-    "   "
+    "\n",
+    "widgets.interact(plot, t=widgets.FloatSlider(min=0, max=3600, step=1, value=0));"
    ]
   },
   {