#623 flake8

Author: valentinsulzer

examples/scripts/SPMe_SOC.py

@@ -1,7 +1,8 @@
 import pybamm
 import numpy as np
 import matplotlib.pyplot as plt
-plt.close('all')
+
+plt.close("all")
 pybamm.set_logging_level("INFO")
 
 # load model
@@ -13,26 +14,28 @@
 # load parameter values and process model and geometry
 param = model.default_parameter_values
 
-param.update({'Negative electrode surface area density [m-1]': 180000.0,
-              'Positive electrode surface area density [m-1]': 150000.0})
+param.update(
+    {
+        "Negative electrode surface area density [m-1]": 180000.0,
+        "Positive electrode surface area density [m-1]": 150000.0,
+    }
+)
 
 
-max_neg = param['Maximum concentration in negative electrode [mol.m-3]']
-max_pos = param['Maximum concentration in positive electrode [mol.m-3]']
-a_neg = param['Negative electrode surface area density [m-1]']
-a_pos = param['Positive electrode surface area density [m-1]']
-l_neg = param['Negative electrode thickness [m]']
-l_pos = param['Positive electrode thickness [m]']
-por_neg = param['Negative electrode porosity']
-por_pos = param['Positive electrode porosity']
+max_neg = param["Maximum concentration in negative electrode [mol.m-3]"]
+max_pos = param["Maximum concentration in positive electrode [mol.m-3]"]
+a_neg = param["Negative electrode surface area density [m-1]"]
+a_pos = param["Positive electrode surface area density [m-1]"]
+l_neg = param["Negative electrode thickness [m]"]
+l_pos = param["Positive electrode thickness [m]"]
+por_neg = param["Negative electrode porosity"]
+por_pos = param["Positive electrode porosity"]
 
 param.process_model(model)
 param.process_geometry(geometry)
 
 s_var = pybamm.standard_spatial_vars
-var_pts = {s_var.x_n: 5, s_var.x_s: 5,
-           s_var.x_p: 5, s_var.r_n: 5,
-           s_var.r_p: 10}
+var_pts = {s_var.x_n: 5, s_var.x_s: 5, s_var.x_p: 5, s_var.r_n: 5, s_var.r_p: 10}
 # set mesh
 mesh = pybamm.Mesh(geometry, model.default_submesh_types, var_pts)
 
@@ -45,34 +48,31 @@
 sol = model.default_solver.solve(model, t_eval)
 
 # plot
-out_vars = ['RX-averaged positive particle concentration [mol.m-3]',
-            'RX-averaged negative particle concentration [mol.m-3]',
-            'X-averaged electrolyte concentration [mol.m-3]',
-            'X-averaged positive electrode porosity',
-            'X-averaged negative electrode porosity',
-            'X-averaged separator porosity']
+out_vars = [
+    "RX-averaged positive particle concentration [mol.m-3]",
+    "RX-averaged negative particle concentration [mol.m-3]",
+    "X-averaged electrolyte concentration [mol.m-3]",
+    "X-averaged positive electrode porosity",
+    "X-averaged negative electrode porosity",
+    "X-averaged separator porosity",
+]
 plot = pybamm.QuickPlot(model, mesh, sol, output_variables=out_vars)
 plot.dynamic_plot()
 keys = list(model.variables.keys())
 keys.sort()
 
-xppc = pybamm.ProcessedVariable(model.variables[out_vars[0]],
-                                sol.t, sol.y, mesh=mesh)
-xnpc = pybamm.ProcessedVariable(model.variables[out_vars[1]],
-                                sol.t, sol.y, mesh=mesh)
-xec = pybamm.ProcessedVariable(model.variables[out_vars[2]],
-                               sol.t, sol.y, mesh=mesh)
+xppc = pybamm.ProcessedVariable(model.variables[out_vars[0]], sol.t, sol.y, mesh=mesh)
+xnpc = pybamm.ProcessedVariable(model.variables[out_vars[1]], sol.t, sol.y, mesh=mesh)
+xec = pybamm.ProcessedVariable(model.variables[out_vars[2]], sol.t, sol.y, mesh=mesh)
 rp = np.linspace(0, 1.0, 11)
 
 plt.figure()
 rplt = 0.0
-plt.plot(np.ones(len(sol.t))*max_neg*por_neg, 'r--', label='Max Neg')
-plt.plot(xnpc(sol.t, r=rplt)*por_neg, 'r', label='Neg Li')
-plt.plot(np.ones(len(sol.t))*max_pos*por_pos, 'b--', label='Max Pos')
-plt.plot(xppc(sol.t, r=rplt)*por_pos, 'b', label='Pos Li')
-plt.plot(xec(sol.t, r=rplt), 'g', label='Elec Li')
-tot = (xnpc(sol.t, r=rplt) * por_neg +
-       xppc(sol.t, r=rplt) * por_pos +
-       xec(sol.t, r=rplt))
-plt.plot(tot, 'k-', label='Total Li')
+plt.plot(np.ones(len(sol.t)) * max_neg * por_neg, "r--", label="Max Neg")
+plt.plot(xnpc(sol.t, r=rplt) * por_neg, "r", label="Neg Li")
+plt.plot(np.ones(len(sol.t)) * max_pos * por_pos, "b--", label="Max Pos")
+plt.plot(xppc(sol.t, r=rplt) * por_pos, "b", label="Pos Li")
+plt.plot(xec(sol.t, r=rplt), "g", label="Elec Li")
+tot = xnpc(sol.t, r=rplt) * por_neg + xppc(sol.t, r=rplt) * por_pos + xec(sol.t, r=rplt)
+plt.plot(tot, "k-", label="Total Li")
 plt.legend()

pybamm/models/submodels/particle/base_particle.py

@@ -31,8 +31,7 @@ def _get_standard_concentration_variables(self, c_s, c_s_xav):
             c_scale = self.param.c_n_max
         elif self.domain == "Positive":
             c_scale = self.param.c_p_max
-        rad = pybamm.SpatialVariable("r", [self.domain.lower() + " particle"])
-#        c_s_r_av = pybamm.r_average(pybamm.x_average(c_s))
+        # c_s_r_av = pybamm.r_average(pybamm.x_average(c_s))
         c_s_r_av = pybamm.r_average(c_s_xav)
         variables = {
             self.domain + " particle concentration": c_s,