diff --git a/.gitignore b/.gitignore
index 3b93ce0..5298f42 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,5 +1,9 @@
 .idea/
-__pycache__
 *.h5
-*.pyc
+
+__pycache__
+*.py[cod]
+build/
+dist/
+*.egg-info/
 
diff --git a/opencl_fdtd/kernels/common.cl b/opencl_fdtd/kernels/common.cl
index deecec9..769c248 100644
--- a/opencl_fdtd/kernels/common.cl
+++ b/opencl_fdtd/kernels/common.cl
@@ -2,7 +2,7 @@
 /* Common code for E, H updates
  *
  * Template parameters:
- *  ftype	type name (e.g. float or double)
+ *  ftype       type name (e.g. float or double)
  *  shape       list of 3 ints specifying shape of fields
  */
 #}
@@ -78,7 +78,8 @@ int p{{r}} = + (int) di{{r}};
 int wrap_{{r}} = (s{{r}} - 1) * (int) di{{r}};
 if ( {{r}} == 0 ) {
   m{{r}} = wrap_{{r}};
-} else if ( {{r}} == s{{r}} - 1 ) {
+}
+if ( {{r}} == s{{r}} - 1 ) {
   p{{r}} = -wrap_{{r}};
-} 
+}
 {% endfor %}
diff --git a/opencl_fdtd/kernels/update_j.cl b/opencl_fdtd/kernels/update_j.cl
index 4d7f64d..2682f39 100644
--- a/opencl_fdtd/kernels/update_j.cl
+++ b/opencl_fdtd/kernels/update_j.cl
@@ -1,11 +1,11 @@
 /*
- *  Update E-field from J field 
+ *  Update E-field from J field
  *
  *  Template parameters:
  *   common_header: Rendered contents of common.cl
  *
  *  OpenCL args:
- *   E, Jr, Ji, c, s, xmin, xmax, ymin, ymax, zmin, zmax   
+ *   E, Jr, Ji, c, s, xmin, xmax, ymin, ymax, zmin, zmax
  */
 
 {{common_header}}
diff --git a/opencl_fdtd/simulation.py b/opencl_fdtd/simulation.py
index 9dd90c0..c5d0005 100644
--- a/opencl_fdtd/simulation.py
+++ b/opencl_fdtd/simulation.py
@@ -170,7 +170,7 @@ class Simulation(object):
         ctype = type_to_C(self.arg_type)
 
         def ptr(arg: str) -> str:
-            return ctype + ' * restrict ' + arg
+            return ctype + ' *' + arg
 
         base_fields = OrderedDict()
         base_fields[ptr('E')] = self.E
@@ -286,13 +286,13 @@ class Simulation(object):
             alpha_max = pml['cfs_alpha']
 
             def par(x):
-                scaling = ((x / (pml['thickness'])) ** pml['m'])
+                scaling = (x / pml['thickness']) ** pml['m']
                 sigma = scaling * sigma_max
                 kappa = 1 + scaling * (kappa_max - 1)
                 alpha = ((1 - x / pml['thickness']) ** pml['ma']) * alpha_max
                 p0 = numpy.exp(-(sigma / kappa + alpha) * self.dt)
                 p1 = sigma / (sigma + kappa * alpha) * (p0 - 1)
-                p2 = 1/kappa
+                p2 = 1 / kappa
                 return p0, p1, p2
 
             xe, xh = (numpy.arange(1, pml['thickness'] + 1, dtype=self.arg_type)[::-1] for _ in range(2))