diff --git a/lbmpy/sparse/mapping.py b/lbmpy/sparse/mapping.py
index 899fa68dbf9db8d3e2317321adea09ab32ffea6c..a1c8bc9ae485f435dbfa508dabc520be544d235f 100644
--- a/lbmpy/sparse/mapping.py
+++ b/lbmpy/sparse/mapping.py
@@ -22,7 +22,7 @@ def pdf_index(cell_index, direction_index, domain_size):
 
 def inverse_idx(stencil, idx):
     return stencil.index(tuple(-d_i for d_i in stencil[idx]))
-        
+
         
 class SparseLbMapper:
     """Manages the mapping of cell coordinates to indices and back.
@@ -129,8 +129,8 @@ class SparseLbMapper:
         no_slip_flag = self.no_slip_flag
         fluid_boundary_mask = self.ubb_flag | self.fluid_flag | self.density_flag
         result = []
-        print("flag:", self.flag_array)
-        fucking_counter = 0
+        #print("flag:", self.flag_array)
+        num_border_cell = 0
         for direction_idx, direction in enumerate(stencil):
             print("dir:", direction_idx)
             if all(d_i == 0 for d_i in direction):
@@ -138,12 +138,13 @@ class SparseLbMapper:
                 continue
             for own_cell_idx, cell in enumerate(self.fluid_coordinates):
                 if (cell[0] == 0 or cell[0] == self.domain_size[0]-1 or cell[1] == 0 or cell[1] == self.domain_size[1]-1):
-                    fucking_counter += 1 #count skipped border cells for reshape function later
+                    num_border_cell += 1 #count skipped border cells for reshape function later
                     continue #ignore fluid cells at the border ...
                 domain_size = (len(self.flag_array), len(self.flag_array[0]))
                 test = []
-                inv_neighbor_cell = np.array([cell_i - dir_i for cell_i, dir_i in zip(cell, direction)])
+                inv_neighbor_cell = np.array([cell_i - dir_i for cell_i, dir_i, ds_i in zip(cell, direction, self.domain_size)])
                 test.append(("Zelle", own_cell_idx))
+                print("write:", cell, "read:", inv_neighbor_cell)
                 if flag_arr[tuple(inv_neighbor_cell)] & fluid_boundary_mask:
                     neighbor_cell_idx = self.cell_idx(tuple(inv_neighbor_cell))
                     result.append(pdf_index(neighbor_cell_idx, direction_idx, len(self)))
@@ -172,16 +173,40 @@ class SparseLbMapper:
                 #print(test)
 
         index_array = np.array(result, dtype=np.uint32)
-        print("number of fluid:", self.num_fluid_cells, "counter:", fucking_counter//8)
-        index_arr = index_array.reshape([len(stencil) - 1, self.num_fluid_cells-fucking_counter//8])
+        #print("number of fluid:", self.num_fluid_cells, "counter:", num_border_cell//8)
+        #index_arr = index_array.reshape([len(stencil) - 1, self.num_fluid_cells])
+        index_arr = index_array.reshape([len(stencil) - 1, self.num_fluid_cells-num_border_cell//8])
         index_arr = index_arr.swapaxes(0, 1) 
         return index_arr
 
     
 class SparseLbPeriodicityMapper:
-
+    DIR_SYMBOL = TypedSymbol("dir", np.int64)
 
     def __init__(self, method, mapping: SparseLbMapper, dh):
+        
+        index_field = Field.create_generic("idx", spatial_dimensions=1, index_dimensions=1, dtype=np.int64)
+
+        #if isinstance(boundary_eqs, Assignment):
+        #    assignments = [boundary_eqs]
+
+        #if not isinstance(boundary_eqs, AssignmentCollection):
+        #    assignments = AssignmentCollection(boundary_eqs)
+
+        #accessor_subs = dict()
+        #for fa in assignments.atoms(Field.Access):
+        #    if fa.field == f_out:
+        #        f_dir = 'out'
+        #    elif fa.field == f_in:
+        #        f_dir = 'in'
+        #    else:
+        #        continue
+        #    i = 1 if f_dir == "in" else 2
+        #    accessor_subs[fa] = pdf_field_sparse.absolute_access((index_field(i),), ())
+        
+        #self.timestep_indexing = indexing
+        self.index_field = index_field
+            
         self.method = method
         self.mapping = mapping
         self.domain_size = dh.shape
@@ -191,223 +216,70 @@ class SparseLbPeriodicityMapper:
         self.no_slip_flag = mapping.no_slip_flag
         self.density_flag = mapping.density_flag
         self.ubb_flag = mapping.ubb_flag
-        
     
+    def direction_index(self, direction):
+        direction = tuple(direction)
+        for direction_idx, dir_coordinates in enumerate(self.mapping.stencil):
+            if dir_coordinates == direction:
+                return direction_idx
+        raise ValueError("Could not find index for direction {}".format(direction))
+        
     def get_read_idx(self, read, write_idx, direction_idx):  
         if self.flag_arr[tuple(read)] & self.no_slip_flag: # Read cell is no-slip: flip PDF!
             #read from write cell, inverse direction
             return pdf_index(write_idx, inverse_idx(self.method.stencil, direction_idx), len(self.mapping))
-            #periodic_idx_array.append([direction_idx, inverse_idx(self.method.stencil, direction_idx), write, write]) #nur zu debug Zwecken
         else:
             return pdf_index(self.mapping.cell_idx(tuple(read)), direction_idx, len(self.mapping))
-            #periodic_idx_array.append([direction_idx, write, read]) #nur zu debug Zwecken
     
-    def get_assignment(self, direction_idx, direction, own_cell_idx, cell):
+    def get_assignment(self, direction, cell):
+        cell_idx = self.mapping.cell_idx(cell)
+        direction_idx = self.direction_index(direction)
         inv_neighbor_cell = [(cell_i - dir_i)%ds_i for cell_i, dir_i, ds_i in zip(cell, direction, self.domain_size)]
-        write_idx = pdf_index(own_cell_idx, direction_idx, len(self.mapping))
-        read_idx = self.get_read_idx(inv_neighbor_cell, own_cell_idx, direction_idx)
-        print("write:", cell, "read:", inv_neighbor_cell)
+        write_idx = pdf_index(cell_idx, direction_idx, len(self.mapping))
+        read_idx = self.get_read_idx(inv_neighbor_cell, cell_idx, direction_idx)
+        #print("write:", cell, "read:", inv_neighbor_cell)
         return [direction_idx, write_idx, read_idx]
-        
     
-    def create_inner_index_arr(self):
-        stencil = self.method.stencil
+    def fluid_border(self):
         fluid_border_coord = []
-        for cell_idx, cell in enumerate(self.mapping.fluid_coordinates):
-            if (cell[0] == 0 or cell[0] == self.domain_size[0]-1 or cell[1] == 0 or cell[1] == self.domain_size[1]-1):
-                fluid_border_coord.append((cell_idx, cell))
-        result = []
-        fluid_boundary_mask = self.fluid_flag | self.ubb_flag | self.density_flag
-        for direction_idx, direction in enumerate(self.method.stencil):
-            if all(d_i == 0 for d_i in direction):# direction (0,0) irrelevant
-                continue
-            print("\n New direction:", direction, ", ", direction_idx)
-            naughty = [[int((ds_i-1)*(1-dir_i)/2)] if dir_i != 0 else [] for i, (dir_i, ds_i) in enumerate(zip(direction, self.domain_size))]
-            print(naughty)
-            for cell_description in fluid_border_coord:
-                cell = cell_description[1]
-                own_cell_idx = cell_description[0]
-                if cell[0] not in naughty[0] and cell[1] not in naughty[1]:
-                    result.append(self.get_assignment(direction_idx, direction, own_cell_idx, cell))
-        return result
-        
-    def create_index_arr(self): # erstellt index arrays für ALLE fluid Zellen, die sich am Rand der domain befinden.
-        # ein index array für alle Werte, die innerhalb des Blocks verschickt werden
-        # jeweils ein index array für Werte, die zu jeweils verschiedenen benachbarten Blocks geschickt werden (wenn verschiedene Kerne verschiedene Blöcke innerhalb einer Domain bearbeiten)
+        for cell in self.mapping.fluid_coordinates:
+            bool_border = [cell_i == 0 or cell_i == ds_i-1 for cell_i, ds_i in zip(cell, self.domain_size)]
+            if True in bool_border:
+                fluid_border_coord.append(cell)
+        return fluid_border_coord
+    
+    def create_periodic_index_array(self): 
         stencil = self.method.stencil
-        print("domain_size:", self.domain_size)
-        fluid_border_coord = []
-        for cell_idx, cell in enumerate(self.mapping.fluid_coordinates):
-            if (cell[0] == 0 or cell[0] == self.domain_size[0]-1 or cell[1] == 0 or cell[1] == self.domain_size[1]-1):
-                fluid_border_coord.append((cell_idx, cell))
-        result = []
-        print(fluid_border_coord)
-        inner_idx_array = []
-        fluid_boundary_mask = self.fluid_flag | self.ubb_flag | self.density_flag
-        for direction_idx, direction in enumerate(self.method.stencil):
-            if all(d_i == 0 for d_i in direction):# direction (0,0) irrelevant
-                continue
-            print("\n New direction:", direction, ", ", direction_idx)
-            for pos in range(0,2):
-                print("new periodic_index_array")
-                periodic_idx_array = []
-                sop = (pos+1)%2
-                print("first iteration over cells")
-                for cell_description in fluid_border_coord:
-                    cell = cell_description[1]
-                    own_cell_idx = cell_description[0]
-                    #print(cell)
-                    if direction[pos] != 0:
-                        slice_coord = int((self.domain_size[pos]-1)*(1-direction[pos])/2) #0 oder d_s-1
-                        start = 1 if direction[sop] == 1 else 0
-                        stop = self.domain_size[sop]-1 if direction[sop] == -1 else self.domain_size[sop]
-                        if cell[pos] == slice_coord and cell[sop] >= start and cell[sop] < stop:
-                            inv_neighbor_cell = [(cell_i - dir_i)%ds_i for cell_i, dir_i, ds_i in zip(cell, direction, self.domain_size)]
-                            write_idx = pdf_index(own_cell_idx, direction_idx, len(self.mapping))
-                            read_idx = self.get_read_idx(inv_neighbor_cell, own_cell_idx, direction_idx)
-                            print("(p  ) write:", cell)
-                            periodic_idx_array.append([direction_idx, write_idx, read_idx])
-                        slice_coord = [int((self.domain_size[sop]-1)*(1+direction[sop])/2)] if direction[sop] != 0 else [0, self.domain_size[sop]-1]
-                        if cell[sop] in slice_coord and cell[pos] >= 1 and cell[pos] < self.domain_size[pos]-1:
-                            inv_neighbor_cell = [(cell_i - dir_i)%ds_i for cell_i, dir_i, ds_i in zip(cell, direction, self.domain_size)]
-                            write_idx = pdf_index(own_cell_idx, direction_idx, len(self.mapping))
-                            read_idx = self.get_read_idx(inv_neighbor_cell, own_cell_idx, direction_idx)
-                            print("(i_1) write:", cell)
-                            inner_idx_array.append([direction_idx, write_idx, read_idx])
-                    else: #if direction[pos] == 0
-                        slice_coord = int((self.domain_size[sop]-1)*(1+direction[sop])/2)
-                        if cell[sop] == slice_coord:
-                            inv_neighbor_cell = [(cell_i - dir_i)%ds_i for cell_i, dir_i, ds_i in zip(cell, direction, self.domain_size)]
-                            write_idx = pdf_index(own_cell_idx, direction_idx, len(self.mapping))
-                            read_idx = self.get_read_idx(inv_neighbor_cell, own_cell_idx, direction_idx)
-                            print("(i_2) write:", cell)
-                            inner_idx_array.append([direction_idx, write_idx, read_idx])
-                print("feed result")
-                result.append(periodic_idx_array)
-            #Ecken
-            if (direction[0] == 0 or direction[1] == 0):
-                continue
-            print("second iteration over cells")
-            for cell_description in fluid_border_coord:
-                cell = cell_description[1]
-                own_cell_idx = cell_description[0]
-                corner = [int((ds_i-1)*(1-dir_i)/2) for dir_i, ds_i in zip(direction, self.domain_size)]
-                if cell[0] == corner[0] and cell[1] == corner[1]:
-                    inv_neighbor_cell = [(cell_i - dir_i)%ds_i for cell_i, dir_i, ds_i in zip(cell, direction, self.domain_size)]
-                    write_idx = pdf_index(own_cell_idx, direction_idx, len(self.mapping))
-                    read_idx = self.get_read_idx(inv_neighbor_cell, own_cell_idx, direction_idx)
-                    print("(c_p) write:", cell)
-                    result.append([[direction_idx, write_idx, read_idx]])
-                corner = [int((ds_i-1)*(1+dir_i)/2) for dir_i, ds_i in zip(direction, self.domain_size)]
-                if cell[0] == corner[0] and cell[1] == corner[1]:
-                    inv_neighbor_cell = [(cell_i - dir_i)%ds_i for cell_i, dir_i, ds_i in zip(cell, direction, self.domain_size)]
-                    write_idx = pdf_index(own_cell_idx, direction_idx, len(self.mapping))
-                    read_idx = self.get_read_idx(inv_neighbor_cell, own_cell_idx, direction_idx)
-                    print("(c_i) write:", cell)
-                    inner_idx_array.append([direction_idx, write_idx, read_idx])
-        print("End of Code")
-            
-                
-            
-                        
-        for direction_idx, direction in enumerate(self.method.stencil):
-            if all(d_i == 0 for d_i in direction):# direction (0,0) irrelevant
+        fluid_border_coord = self.fluid_border()
+        #print(fluid_border_coord)
+        result = [[[] for j in range(0, len(stencil)-1)] for i in range(0, len(stencil)-1)]
+        inner_index_array = []
+        for direction_idx, direction in enumerate(stencil):
+            if all(d_i == 0 for d_i in direction): # Direction (0,0) irrelevant
                 continue
-            print("\n New direction:", direction, ", ", direction_idx)
-                        
-                        
-                        
-                        
-            
-            
-            
-            for pos in range(0,2): # einmal für x, einmal für y Richtung ... 
-                print("pos is ", pos)
-                sop = (pos+1)%2
-                if direction[pos] != 0:
-                    # periodic/parallel: wird an anderen Block geschickt/periodisch gewrappt
-                    print("(periodic:)")
-                    periodic_idx_array = []
-                    coord = int((self.domain_size[pos]-1)*(1-direction[pos])/2)
-                    start = 1 if direction[sop] == 1 else 0
-                    end = self.domain_size[sop]-1 if direction[sop] == -1 else self.domain_size[sop]
-                    for i in range(start, end):
-                        write = [0,0]
-                        write[pos] = coord
-                        write[sop] = i
-                        if not (self.flag_arr[tuple(write)] & self.fluid_flag):
-                            continue
-                        read = [(write_i - dir_i)%ds_i for write_i, dir_i, ds_i in zip(write, direction, self.domain_size)]
-                        print("write:", write)
-                        write_idx = pdf_index(self.mapping.cell_idx(tuple(write)), direction_idx, len(self.mapping))
-                        read_idx = self.get_read_idx(read, self.mapping.cell_idx(tuple(write)), direction_idx)
-                        periodic_idx_array.append([direction_idx, write_idx, read_idx])
-                        # "Die Zelle "write" bekommt ihren neuen Wert der jeweiligen direction von der Zelle "read"
-                    result.append(tuple(periodic_idx_array))
-                    # inner: wird zwischen benachbarten Zellen *im gleichen Block* geschickt
-                    print("(inner1:)")
-                    pos_bound = int((self.domain_size[pos]-1)*(1+direction[pos])/2)
-                    pos_mid = pos_bound+direction[pos]*(-self.domain_size[pos]+1)
-                    sop_position = [int((self.domain_size[sop]-1)*(1+direction[sop])/2)] if direction[sop] != 0 else [0, self.domain_size[sop]-1]
-                    for b in sop_position:
-                        for i in range(pos_bound, pos_mid, -direction[pos]):
-                            write = [0,0]
-                            write[pos] = i
-                            write[sop] = b
-                            print("write:", write)
-                            if not (self.flag_arr[tuple(write)] & self.fluid_flag):
-                                continue
-                            read = [write_i - dir_i for write_i, dir_i in zip(write, direction)]
-                            write_idx = pdf_index(self.mapping.cell_idx(tuple(write)), direction_idx, len(self.mapping))
-                            read_idx = self.get_read_idx(read, write_idx, direction_idx)
-                            inner_idx_array.append([direction_idx, write_idx, read_idx])
-                if direction[pos] == 0: #spricht directions 1, 2, 3 und 4 an
-                    # inner: wird zwischen benachbarte Zellen *im gleichen Block* geschickt
-                    print("(inner2:)")
-                    pos_low = 1
-                    pos_high = self.domain_size[pos]-1
-                    sop_position = int((self.domain_size[sop]-1)*(1+direction[sop])/2)
-                    for i in range(pos_low, pos_high):
-                        write = [0,0]
-                        write[pos] = i
-                        write[sop] = sop_position
-                        print("write:", write)
-                        if not (self.flag_arr[tuple(write)] & self.fluid_flag):
-                            continue
-                        read = [write_i - dir_i for write_i, dir_i in zip(write, direction)]
-                        write_idx = pdf_index(self.mapping.cell_idx(tuple(write)), direction_idx, len(self.mapping))
-                        read_idx = self.get_read_idx(read, write_idx, direction_idx)
-                        inner_idx_array.append([direction_idx, write, read]) #for debug
-            #Four corners: extra periodic_idx_array for each direction 5, 6, 7, 8
-            if (direction[0]*direction[1] != 0):
-                write = [int((self.domain_size[0]-1)*(1-direction[0])/2),int((self.domain_size[1]-1)*(1-direction[1])/2)]
-                print("write:", write)
-                if not (self.flag_arr[tuple(write)] & self.fluid_flag):
-                    continue
-                read = [(write_i - dir_i)%ds_i for write_i, dir_i, ds_i in zip(write, direction, self.domain_size)]
-                write_idx = pdf_index(self.mapping.cell_idx(tuple(write)), direction_idx, len(self.mapping))
-                read_idx = self.get_read_idx(read, write_idx, direction_idx)
-                periodic_idx_array.append([direction_idx, write_idx, read_idx])
-                result.append(tuple(periodic_idx_array))
-            
-        # result enthält *mehrere* index arrays
-        #result = list(dict.fromkeys(result)) # entferne doppelte index_arrays: speziell Ecken der Domain
-        # result ist eine liste von tuples von tuples --> [((...), (...)), ((...), (...), (...))]
-        #print(result)
-        # wandel result in list_result (liste von liste von listen) um: -->[[[...], [...]], [[...], [...], [...]]]
-        list_result = [] 
-        for index_array in result:
-            list_index_array = []
-            for write_read_pair in index_array:
-                list_index_array.append(list(write_read_pair))
-            list_result.append(list_index_array)
-        
-        # zu den periodischen/parralel-orientierten index_arrays kommt noch der index array für die Werte, die nur innerhalb des Blocks verschickt werden:
-        list_result.append(inner_idx_array)
-        for index_array in list_result:
-            print(index_array)
-        return list_result
+            #print("\n New direction:", direction, ", ", direction_idx)
+            periodic_slice_coord = [[int((ds_i-1)*(1-dir_i)/2)] if dir_i != 0 else [] for i, (dir_i, ds_i) in enumerate(zip(direction, self.domain_size))]
+            for cell in fluid_border_coord:
+                bool_pos = [cell_i in slice_i for i, (cell_i, slice_i) in enumerate(zip(cell, periodic_slice_coord))]
+                #print(cell, ", ", periodic_slice_coord, ", ", bool_pos)
+                if  True in bool_pos: # This cell & direction is periodical
+                    block_direction = self.direction_index([int(bp_i)*dir_i for dir_i, bp_i in zip(direction, bool_pos)])
+                    result[direction_idx-1][block_direction-1].append(self.get_assignment(direction, cell))
+                    #print("Goes into", direction_idx-1, block_direction-1)
+                else: # This cell & direction is not periodical
+                    inner_index_array.append(self.get_assignment(direction, cell))
+                    #print("Inner")
+        result.append([inner_index_array]) 
+        #for a in result:
+        #    print(a)
+        return result
     
+    def assignments(self):
+        return [Assignment(self.index_field(1), self.index_field(2))]
+
+    def get_kernel(self):
+        kernel = create_kernel(self.assignments(), ghost_layers=0)
+        return kernel
     
 class SparseLbBoundaryMapper:
     NEIGHBOR_IDX_NAME = 'nidx{}'
@@ -467,7 +339,7 @@ class SparseLbBoundaryMapper:
         self.index_field_dtype = index_field_dtype
         self.neighbor_offsets = neighbor_offsets
         self.index_field = index_field
-        self.timesptep_indexing = indexing
+        self.timestep_indexing = indexing
         self.boundary_functor = boundary
 
     def _build_substitutions(self):
@@ -482,7 +354,7 @@ class SparseLbBoundaryMapper:
 
         for dir_idx, subs_dict in enumerate(result):
             inv_idx = stencil.index(tuple(-e for e in stencil[dir_idx]))
-            subs_dict[self.timesptep_indexing._index_array_symbol("in", True)] = inv_idx
+            subs_dict[self.timestep_indexing._index_array_symbol("in", True)] = inv_idx
         return result
 
     def create_index_arr(self, mapping: SparseLbMapper, boundary_mask, nr_of_ghost_layers=1):
@@ -521,7 +393,7 @@ class SparseLbBoundaryMapper:
     def get_kernel(self):
         kernel = create_kernel(self.assignments(), ghost_layers=0)
 
-        index_arrs_node = self.timesptep_indexing.create_code_node()
+        index_arrs_node = self.timestep_indexing.create_code_node()
         for node in self.boundary_functor.get_additional_code_nodes(self.method)[::-1]:
             kernel.body.insert_front(node)
         kernel.body.insert_front(index_arrs_node)
diff --git a/lbmpy_tests/simple_shear_flow.ipynb b/lbmpy_tests/simple_shear_flow.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..6a6f84a2240c6fbffd9c4fe83db9f599f972ad72
--- /dev/null
+++ b/lbmpy_tests/simple_shear_flow.ipynb
@@ -0,0 +1,303 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *\n",
+    "from lbmpy.session import *\n",
+    "\n",
+    "from lbmpy.relaxationrates import relaxation_rate_from_lattice_viscosity\n",
+    "from lbmpy.macroscopic_value_kernels import pdf_initialization_assignments\n",
+    "from lbmpy.advanced_streaming import LBMPeriodicityHandling\n",
+    "\n",
+    "from lbmpy.moments import *\n",
+    "from lbmpy.forcemodels import *\n",
+    "\n",
+    "from lbmpy.creationfunctions import create_lb_method\n",
+    "from lbmpy.methods.abstractlbmethod import RelaxationInfo"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "target = 'cpu'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "omega = 1.99"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stencil = get_stencil('D2Q9')\n",
+    "domain_size = (150, 50)\n",
+    "dim = len(domain_size)\n",
+    "\n",
+    "# timesteps = 200"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "dh = ps.create_data_handling(domain_size=domain_size, periodicity=(True, True), default_target=target)\n",
+    "\n",
+    "src = dh.add_array('src', values_per_cell=len(stencil))\n",
+    "dh.fill('src', 0.0, ghost_layers=True)\n",
+    "dst = dh.add_array('dst', values_per_cell=len(stencil))\n",
+    "dh.fill('dst', 0.0, ghost_layers=True)\n",
+    "\n",
+    "denstiy = dh.add_array('denstiy', values_per_cell=1)\n",
+    "dh.fill('denstiy', 1.0, ghost_layers=True)\n",
+    "\n",
+    "velField = dh.add_array('velField', values_per_cell=dh.dim)\n",
+    "dh.fill('velField', 0.0, ghost_layers=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# vtk_output_frequency = timesteps // 5\n",
+    "# vtk_writer = dh.create_vtk_writer(\"output/test/vtk\", [denstiy.name, velField.name], ghost_layers=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "velocity_magnitude = 0.05\n",
+    "shape = dh.cpu_arrays[velField.name].shape\n",
+    "\n",
+    "dh.cpu_arrays[velField.name][:, :, 0] = velocity_magnitude\n",
+    "dh.cpu_arrays[velField.name][:, shape[1]//3 : shape[1]//3*2, 0]= -velocity_magnitude\n",
+    "\n",
+    "dh.cpu_arrays[velField.name][:, :, 1] = 0.1 * velocity_magnitude * np.random.rand(shape[0], shape[1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.quiver.Quiver at 0x7f01e1a04070>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.vector_field(dh.cpu_arrays[velField.name], step=4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "method = create_lb_method(stencil='D2Q9', method='cumulant', relaxation_rate=omega, compressible=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Initialisation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "init = pdf_initialization_assignments(method, denstiy.center, velField.center_vector, src.center_vector)\n",
+    "\n",
+    "ast_init = ps.create_kernel(init, target=dh.default_target)\n",
+    "kernel_init = ast_init.compile()\n",
+    "\n",
+    "dh.run_kernel(kernel_init)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Update Rules"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "update = create_lb_update_rule(lb_method=method,\n",
+    "                               output={'density': denstiy,\n",
+    "                                       'velocity': velField},\n",
+    "                               optimization={\"symbolic_field\": src,\n",
+    "                                             \"symbolic_temporary_field\": dst,\n",
+    "                                            \"double_precision\": False},\n",
+    "                               kernel_type='stream_pull_collide')\n",
+    "\n",
+    "ast_kernel = ps.create_kernel(update, target=dh.default_target, cpu_openmp=True)\n",
+    "kernel = ast_kernel.compile()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Boundary Handling"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "periodic_BC = LBMPeriodicityHandling(stencil=stencil, data_handling=dh, pdf_field_name=src.name,\n",
+    "                                     streaming_pattern='pull')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def timeloop(timeSteps):\n",
+    "    for i in range(timeSteps):\n",
+    "        periodic_BC()\n",
+    "        dh.run_kernel(kernel)\n",
+    "        dh.swap(\"src\", \"dst\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# filenumber = 0\n",
+    "\n",
+    "# for i in range(timesteps):\n",
+    "#     if(i % vtk_output_frequency == 0):\n",
+    "#         if dh.default_target == 'gpu':\n",
+    "#             print(\"gpu\")\n",
+    "#             dh.to_cpu(velField.name)\n",
+    "#         vtk_writer(filenumber)\n",
+    "#         filenumber += 1\n",
+    "        \n",
+    "#     timeloop(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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\" type=\"video/mp4\">\n",
+       " Your browser does not support the video tag.\n",
+       "</video>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def run():\n",
+    "    result = dh.gather_array('velField')\n",
+    "    timeloop(100)\n",
+    "    return result\n",
+    "\n",
+    "animation = plt.vector_field_magnitude_animation(run, frames=50, rescale=True)\n",
+    "set_display_mode('video')\n",
+    "res = display_animation(animation)\n",
+    "\n",
+    "res"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/simple_sparse_shear_flow.ipynb b/lbmpy_tests/simple_sparse_shear_flow.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..e72288e96afd86073adaddbe3abdf03872262504
--- /dev/null
+++ b/lbmpy_tests/simple_sparse_shear_flow.ipynb
@@ -0,0 +1,364 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "from pystencils.session import *\n",
+    "from lbmpy.session import *\n",
+    "\n",
+    "from lbmpy.relaxationrates import relaxation_rate_from_lattice_viscosity\n",
+    "from lbmpy.macroscopic_value_kernels import pdf_initialization_assignments\n",
+    "from lbmpy.advanced_streaming import LBMPeriodicityHandling\n",
+    "\n",
+    "from lbmpy.moments import *\n",
+    "from lbmpy.forcemodels import *\n",
+    "\n",
+    "from lbmpy.creationfunctions import create_lb_method\n",
+    "from lbmpy.methods.abstractlbmethod import RelaxationInfo\n",
+    "\n",
+    "from lbmpy.sparse import *"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "target = 'cpu'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "omega = 1.99"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stencil = get_stencil('D2Q9')\n",
+    "domain_size = (150, 50)\n",
+    "dim = len(domain_size)\n",
+    "\n",
+    "# timesteps = 200"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "dh = ps.create_data_handling(domain_size=domain_size, periodicity=(True, True), default_target=target)\n",
+    "\n",
+    "src = dh.add_array('src', values_per_cell=len(stencil))\n",
+    "dh.fill('src', 0.0, ghost_layers=True)\n",
+    "dst = dh.add_array('dst', values_per_cell=len(stencil))\n",
+    "dh.fill('dst', 0.0, ghost_layers=True)\n",
+    "\n",
+    "denstiy = dh.add_array('denstiy', values_per_cell=1)\n",
+    "dh.fill('denstiy', 1.0, ghost_layers=True)\n",
+    "\n",
+    "velField = dh.add_array('velField', values_per_cell=dh.dim)\n",
+    "dh.fill('velField', 0.0, ghost_layers=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# vtk_output_frequency = timesteps // 5\n",
+    "# vtk_writer = dh.create_vtk_writer(\"output/test/vtk\", [denstiy.name, velField.name], ghost_layers=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "velocity_magnitude = 0.05\n",
+    "shape = dh.cpu_arrays[velField.name].shape\n",
+    "\n",
+    "dh.cpu_arrays[velField.name][:, :, 0] = velocity_magnitude\n",
+    "dh.cpu_arrays[velField.name][:, shape[1]//3 : shape[1]//3*2, 0]= -velocity_magnitude\n",
+    "\n",
+    "dh.cpu_arrays[velField.name][:, :, 1] = 0.1 * velocity_magnitude * np.random.rand(shape[0], shape[1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.quiver.Quiver at 0x7f1d8c6a6cd0>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.vector_field(dh.cpu_arrays[velField.name], step=4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "method = create_lb_method(stencil='D2Q9', method='cumulant', relaxation_rate=omega, compressible=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Initialize Flag Array\n",
+    "flags = {\n",
+    "    'fluid': 1, \n",
+    "}\n",
+    "flag_arr = np.zeros(domain_size, dtype=np.uint16)\n",
+    "flag_arr.fill(flags['fluid'])\n",
+    "\n",
+    "#Initialize mappings\n",
+    "mapping = SparseLbMapper(method.stencil, domain_size, flag_arr, flags['fluid'], 0, 0, 0) \n",
+    "index_arr = mapping.create_index_array(0)\n",
+    "\n",
+    "periodicity_mapper = SparseLbPeriodicityMapper(method, mapping, dh)\n",
+    "periodic_index_array = periodicity_mapper.create_periodic_index_array()\n",
+    "\n",
+    "pdf_arr = np.empty((len(mapping), len(method.stencil)), order='f')\n",
+    "pdf_arr_tmp = np.empty_like(pdf_arr)\n",
+    "\n",
+    "vel_arr = np.ones([mapping.num_fluid_cells, method.dim], order='f')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Initialisation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "init = pdf_initialization_assignments(method, denstiy.center, velField.center_vector, src.center_vector)\n",
+    "\n",
+    "ast_init = ps.create_kernel(init, target=dh.default_target)\n",
+    "kernel_init = ast_init.compile()\n",
+    "\n",
+    "dh.run_kernel(kernel_init)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Update Rules"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "update = create_lb_update_rule(lb_method=method,\n",
+    "                               output={'density': denstiy,\n",
+    "                                       'velocity': velField},\n",
+    "                               optimization={\"symbolic_field\": src,\n",
+    "                                             \"symbolic_temporary_field\": dst,\n",
+    "                                            \"double_precision\": False},\n",
+    "                               kernel_type='stream_pull_collide')\n",
+    "\n",
+    "ast_kernel = ps.create_kernel(update, target=dh.default_target, cpu_openmp=True)\n",
+    "kernel = ast_kernel.compile()\n",
+    "\n",
+    "periodicity_ast = periodicity_mapper.get_kernel()\n",
+    "periodicity_kernel = periodicity_ast.compile()\n",
+    "def handle_periodicity():\n",
+    "    for block in periodic_index_array:\n",
+    "            for i_a in block:\n",
+    "                if bool(i_a):\n",
+    "                    print(i_a)\n",
+    "                    periodicity_kernel(f=pdf_arr[:mapping.num_fluid_cells], idx=i_a)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Boundary Handling"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "periodic_BC = LBMPeriodicityHandling(stencil=stencil, data_handling=dh, pdf_field_name=src.name,\n",
+    "                                     streaming_pattern='pull')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def timeloop(timeSteps):\n",
+    "    for i in range(timeSteps):\n",
+    "        #periodic_BC()\n",
+    "        handle_periodicity()\n",
+    "        dh.run_kernel(kernel)\n",
+    "        dh.swap(\"src\", \"dst\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# filenumber = 0\n",
+    "\n",
+    "# for i in range(timesteps):\n",
+    "#     if(i % vtk_output_frequency == 0):\n",
+    "#         if dh.default_target == 'gpu':\n",
+    "#             print(\"gpu\")\n",
+    "#             dh.to_cpu(velField.name)\n",
+    "#         vtk_writer(filenumber)\n",
+    "#         filenumber += 1\n",
+    "        \n",
+    "#     timeloop(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[1, 7500, 7549], [1, 7550, 7599], [1, 7600, 7649], [1, 7650, 7699], [1, 7700, 7749], [1, 7750, 7799], [1, 7800, 7849], [1, 7850, 7899], [1, 7900, 7949], [1, 7950, 7999], [1, 8000, 8049], [1, 8050, 8099], [1, 8100, 8149], [1, 8150, 8199], [1, 8200, 8249], [1, 8250, 8299], [1, 8300, 8349], [1, 8350, 8399], [1, 8400, 8449], [1, 8450, 8499], [1, 8500, 8549], [1, 8550, 8599], [1, 8600, 8649], [1, 8650, 8699], [1, 8700, 8749], [1, 8750, 8799], [1, 8800, 8849], [1, 8850, 8899], [1, 8900, 8949], [1, 8950, 8999], [1, 9000, 9049], [1, 9050, 9099], [1, 9100, 9149], [1, 9150, 9199], [1, 9200, 9249], [1, 9250, 9299], [1, 9300, 9349], [1, 9350, 9399], [1, 9400, 9449], [1, 9450, 9499], [1, 9500, 9549], [1, 9550, 9599], [1, 9600, 9649], [1, 9650, 9699], [1, 9700, 9749], [1, 9750, 9799], [1, 9800, 9849], [1, 9850, 9899], [1, 9900, 9949], [1, 9950, 9999], [1, 10000, 10049], [1, 10050, 10099], [1, 10100, 10149], [1, 10150, 10199], [1, 10200, 10249], [1, 10250, 10299], [1, 10300, 10349], [1, 10350, 10399], [1, 10400, 10449], [1, 10450, 10499], [1, 10500, 10549], [1, 10550, 10599], [1, 10600, 10649], [1, 10650, 10699], [1, 10700, 10749], [1, 10750, 10799], [1, 10800, 10849], [1, 10850, 10899], [1, 10900, 10949], [1, 10950, 10999], [1, 11000, 11049], [1, 11050, 11099], [1, 11100, 11149], [1, 11150, 11199], [1, 11200, 11249], [1, 11250, 11299], [1, 11300, 11349], [1, 11350, 11399], [1, 11400, 11449], [1, 11450, 11499], [1, 11500, 11549], [1, 11550, 11599], [1, 11600, 11649], [1, 11650, 11699], [1, 11700, 11749], [1, 11750, 11799], [1, 11800, 11849], [1, 11850, 11899], [1, 11900, 11949], [1, 11950, 11999], [1, 12000, 12049], [1, 12050, 12099], [1, 12100, 12149], [1, 12150, 12199], [1, 12200, 12249], [1, 12250, 12299], [1, 12300, 12349], [1, 12350, 12399], [1, 12400, 12449], [1, 12450, 12499], [1, 12500, 12549], [1, 12550, 12599], [1, 12600, 12649], [1, 12650, 12699], [1, 12700, 12749], [1, 12750, 12799], [1, 12800, 12849], [1, 12850, 12899], [1, 12900, 12949], [1, 12950, 12999], [1, 13000, 13049], [1, 13050, 13099], [1, 13100, 13149], [1, 13150, 13199], [1, 13200, 13249], [1, 13250, 13299], [1, 13300, 13349], [1, 13350, 13399], [1, 13400, 13449], [1, 13450, 13499], [1, 13500, 13549], [1, 13550, 13599], [1, 13600, 13649], [1, 13650, 13699], [1, 13700, 13749], [1, 13750, 13799], [1, 13800, 13849], [1, 13850, 13899], [1, 13900, 13949], [1, 13950, 13999], [1, 14000, 14049], [1, 14050, 14099], [1, 14100, 14149], [1, 14150, 14199], [1, 14200, 14249], [1, 14250, 14299], [1, 14300, 14349], [1, 14350, 14399], [1, 14400, 14449], [1, 14450, 14499], [1, 14500, 14549], [1, 14550, 14599], [1, 14600, 14649], [1, 14650, 14699], [1, 14700, 14749], [1, 14750, 14799], [1, 14800, 14849], [1, 14850, 14899], [1, 14900, 14949], [1, 14950, 14999]]\n"
+     ]
+    },
+    {
+     "ename": "TypeError",
+     "evalue": "a bytes-like object is required, not 'list'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-16-5f33087bfa00>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0manimation\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvector_field_magnitude_animation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mframes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m50\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrescale\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m \u001b[0mset_display_mode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'video'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdisplay_animation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0manimation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.local/lib/python3.8/site-packages/pystencils/plot.py\u001b[0m in \u001b[0;36mvector_field_magnitude_animation\u001b[0;34m(run_function, plot_setup_function, rescale, plot_update_function, interval, frames, **kwargs)\u001b[0m\n\u001b[1;32m    278\u001b[0m     \u001b[0mfig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgcf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    279\u001b[0m     \u001b[0mim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 280\u001b[0;31m     \u001b[0mfield\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    281\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mrescale\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    282\u001b[0m         \u001b[0mfield\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m__scale_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfield\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-16-5f33087bfa00>\u001b[0m in \u001b[0;36mrun\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgather_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'velField'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0mtimeloop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-14-61c109a4483a>\u001b[0m in \u001b[0;36mtimeloop\u001b[0;34m(timeSteps)\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeSteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m         \u001b[0;31m#periodic_BC()\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m         \u001b[0mhandle_periodicity\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m         \u001b[0mdh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_kernel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkernel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m         \u001b[0mdh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mswap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"src\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"dst\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-12-f0d597861154>\u001b[0m in \u001b[0;36mhandle_periodicity\u001b[0;34m()\u001b[0m\n\u001b[1;32m     17\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mbool\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi_a\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     18\u001b[0m                     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi_a\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 19\u001b[0;31m                     \u001b[0mperiodicity_kernel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpdf_arr\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mmapping\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnum_fluid_cells\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0midx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mi_a\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;32m~/.local/lib/python3.8/site-packages/pystencils/kernel_wrapper.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m     16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 18\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkernel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     19\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     20\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mTypeError\u001b[0m: a bytes-like object is required, not 'list'"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1152x432 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def run():\n",
+    "    result = dh.gather_array('velField')\n",
+    "    timeloop(100)\n",
+    "    return result\n",
+    "\n",
+    "animation = plt.vector_field_magnitude_animation(run, frames=50, rescale=True)\n",
+    "set_display_mode('video')\n",
+    "res = display_animation(animation)\n",
+    "\n",
+    "res"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lbmpy_tests/test_sparse_lbm.ipynb b/lbmpy_tests/test_sparse_lbm.ipynb
index 80a0b103d12efe959535e3890a06dd5d7e57d1de..3eef7ed7b1a14729a68b05c5fe69f0db99e9bf2d 100644
--- a/lbmpy_tests/test_sparse_lbm.ipynb
+++ b/lbmpy_tests/test_sparse_lbm.ipynb
@@ -62,7 +62,7 @@
     "lid_velocity = 0.01\n",
     "force = 1e-6\n",
     "\n",
-    "channel = False\n",
+    "channel = True\n",
     "if channel:\n",
     "    kwargs={'force': (force, 0)}\n",
     "else:\n",
@@ -138,7 +138,9 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "data": {
@@ -167,10 +169,10 @@
     "flag_arr.fill(flags['fluid'])\n",
     "\n",
     "if channel:\n",
-    "    flag_arr[0, :] = 0\n",
-    "    flag_arr[-1, :] = 0   \n",
-    "    flag_arr[:, 0] = flags[noslip]\n",
-    "    flag_arr[:, -1] = flags[noslip]\n",
+    "    flag_arr[0, :] = flags['fluid']\n",
+    "    flag_arr[-1, :] = flags['fluid']\n",
+    "    flag_arr[:, 0] = flags['fluid']\n",
+    "    flag_arr[:, -1] = flags['fluid']\n",
     "#else:\n",
     "#    flag_arr[0, :] = 0\n",
     "#    flag_arr[-1, :] = 0   \n",
@@ -227,26 +229,65 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "flag: [[1 1 1]\n",
-      " [1 1 1]\n",
-      " [1 1 1]\n",
-      " [1 1 1]]\n",
       "dir: 0\n",
       "dir: 1\n",
+      "write: (1, 1) read: [1 0]\n",
+      "write: (2, 1) read: [2 0]\n",
       "dir: 2\n",
+      "write: (1, 1) read: [1 2]\n",
+      "write: (2, 1) read: [2 2]\n",
       "dir: 3\n",
+      "write: (1, 1) read: [2 1]\n",
+      "write: (2, 1) read: [3 1]\n",
       "dir: 4\n",
+      "write: (1, 1) read: [0 1]\n",
+      "write: (2, 1) read: [1 1]\n",
       "dir: 5\n",
+      "write: (1, 1) read: [2 0]\n",
+      "write: (2, 1) read: [3 0]\n",
       "dir: 6\n",
+      "write: (1, 1) read: [0 0]\n",
+      "write: (2, 1) read: [1 0]\n",
       "dir: 7\n",
+      "write: (1, 1) read: [2 2]\n",
+      "write: (2, 1) read: [3 2]\n",
       "dir: 8\n",
-      "number of fluid: 12 counter: 10\n"
+      "write: (1, 1) read: [0 2]\n",
+      "write: (2, 1) read: [1 2]\n"
      ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$\\displaystyle 12$"
+      ],
+      "text/plain": [
+       "12"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$\\displaystyle 12$"
+      ],
+      "text/plain": [
+       "12"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
     "mapping = SparseLbMapper(method.stencil, domain_size, flag_arr, flags['fluid'], flags[noslip], flags[ubb], flags[density]) #Warum müssen (dürfen!) hier Nullen stehen?\n",
-    "index_arr = mapping.create_index_array(ghost_layers) # funktioniert nicht solange am Rand fluid Zellen sind!\n",
+    "index_arr = mapping.create_index_array(ghost_layers)\n",
     "#print(index_arr)\n",
     "\n",
     "# Arrays\n",
@@ -257,7 +298,9 @@
     "pdf_arr_tmp = np.empty_like(pdf_arr)\n",
     "\n",
     "vel_arr = np.ones([mapping.num_fluid_cells, method.dim], order='f')\n",
-    "\n"
+    "\n",
+    "len(pdf_arr)\n",
+    "mapping.num_fluid_cells"
    ]
   },
   {
@@ -293,139 +336,22 @@
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
-    "scrolled": false
+    "scrolled": true
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " New direction: (0, 1) ,  1\n",
-      "[[], [0]]\n",
-      "write: (0, 1) read: [0, 0]\n",
-      "write: (0, 2) read: [0, 1]\n",
-      "write: (1, 2) read: [1, 1]\n",
-      "write: (2, 2) read: [2, 1]\n",
-      "write: (3, 1) read: [3, 0]\n",
-      "write: (3, 2) read: [3, 1]\n",
-      "\n",
-      " New direction: (0, -1) ,  2\n",
-      "[[], [2]]\n",
-      "write: (0, 0) read: [0, 1]\n",
-      "write: (0, 1) read: [0, 2]\n",
-      "write: (1, 0) read: [1, 1]\n",
-      "write: (2, 0) read: [2, 1]\n",
-      "write: (3, 0) read: [3, 1]\n",
-      "write: (3, 1) read: [3, 2]\n",
-      "\n",
-      " New direction: (-1, 0) ,  3\n",
-      "[[3], []]\n",
-      "write: (0, 0) read: [1, 0]\n",
-      "write: (0, 1) read: [1, 1]\n",
-      "write: (0, 2) read: [1, 2]\n",
-      "write: (1, 0) read: [2, 0]\n",
-      "write: (1, 2) read: [2, 2]\n",
-      "write: (2, 0) read: [3, 0]\n",
-      "write: (2, 2) read: [3, 2]\n",
-      "\n",
-      " New direction: (1, 0) ,  4\n",
-      "[[0], []]\n",
-      "write: (1, 0) read: [0, 0]\n",
-      "write: (1, 2) read: [0, 2]\n",
-      "write: (2, 0) read: [1, 0]\n",
-      "write: (2, 2) read: [1, 2]\n",
-      "write: (3, 0) read: [2, 0]\n",
-      "write: (3, 1) read: [2, 1]\n",
-      "write: (3, 2) read: [2, 2]\n",
-      "\n",
-      " New direction: (-1, 1) ,  5\n",
-      "[[3], [0]]\n",
-      "write: (0, 1) read: [1, 0]\n",
-      "write: (0, 2) read: [1, 1]\n",
-      "write: (1, 2) read: [2, 1]\n",
-      "write: (2, 2) read: [3, 1]\n",
-      "\n",
-      " New direction: (1, 1) ,  6\n",
-      "[[0], [0]]\n",
-      "write: (1, 2) read: [0, 1]\n",
-      "write: (2, 2) read: [1, 1]\n",
-      "write: (3, 1) read: [2, 0]\n",
-      "write: (3, 2) read: [2, 1]\n",
-      "\n",
-      " New direction: (-1, -1) ,  7\n",
-      "[[3], [2]]\n",
-      "write: (0, 0) read: [1, 1]\n",
-      "write: (0, 1) read: [1, 2]\n",
-      "write: (1, 0) read: [2, 1]\n",
-      "write: (2, 0) read: [3, 1]\n",
-      "\n",
-      " New direction: (1, -1) ,  8\n",
-      "[[0], [2]]\n",
-      "write: (1, 0) read: [0, 1]\n",
-      "write: (2, 0) read: [1, 1]\n",
-      "write: (3, 0) read: [2, 1]\n",
-      "write: (3, 1) read: [2, 2]\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[[1, 13, 12],\n",
-       " [1, 14, 13],\n",
-       " [1, 17, 16],\n",
-       " [1, 20, 19],\n",
-       " [1, 22, 21],\n",
-       " [1, 23, 22],\n",
-       " [2, 24, 25],\n",
-       " [2, 25, 26],\n",
-       " [2, 27, 28],\n",
-       " [2, 30, 31],\n",
-       " [2, 33, 34],\n",
-       " [2, 34, 35],\n",
-       " [3, 36, 39],\n",
-       " [3, 37, 40],\n",
-       " [3, 38, 41],\n",
-       " [3, 39, 42],\n",
-       " [3, 41, 44],\n",
-       " [3, 42, 45],\n",
-       " [3, 44, 47],\n",
-       " [4, 51, 48],\n",
-       " [4, 53, 50],\n",
-       " [4, 54, 51],\n",
-       " [4, 56, 53],\n",
-       " [4, 57, 54],\n",
-       " [4, 58, 55],\n",
-       " [4, 59, 56],\n",
-       " [5, 61, 63],\n",
-       " [5, 62, 64],\n",
-       " [5, 65, 67],\n",
-       " [5, 68, 70],\n",
-       " [6, 77, 73],\n",
-       " [6, 80, 76],\n",
-       " [6, 82, 78],\n",
-       " [6, 83, 79],\n",
-       " [7, 84, 88],\n",
-       " [7, 85, 89],\n",
-       " [7, 87, 91],\n",
-       " [7, 90, 94],\n",
-       " [8, 99, 97],\n",
-       " [8, 102, 100],\n",
-       " [8, 105, 103],\n",
-       " [8, 106, 104]]"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "periodic_mapper = SparseLbPeriodicityMapper(method, mapping, dh)\n",
-    "periodic_mapper.create_inner_index_arr()\n",
-    "#periodic_index_array"
+    "periodicity_mapper = SparseLbPeriodicityMapper(method, mapping, dh)\n",
+    "periodicity_idx_array = periodicity_mapper.create_periodic_index_array()\n",
+    "#inner_index_array = periodic_mapper.create_inner_index_array()\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -518,10 +444,152 @@
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    "metadata": {},
    "outputs": [
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+       "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_f</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_idx</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_size_idx_0</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_f_0</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_idx_0</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_idx_1</span><span class=\"p\">)</span>\n",
+       "<span class=\"p\">{</span>\n",
+       "   \n",
+       "   \n",
+       "   \n",
+       "   <span class=\"k\">const</span> <span class=\"kt\">double</span> <span class=\"n\">weights</span> <span class=\"p\">[]</span> <span class=\"o\">=</span> <span class=\"p\">{</span> <span class=\"mf\">0.444444444444444</span><span class=\"p\">,</span><span class=\"mf\">0.111111111111111</span><span class=\"p\">,</span><span class=\"mf\">0.111111111111111</span><span class=\"p\">,</span><span class=\"mf\">0.111111111111111</span><span class=\"p\">,</span><span class=\"mf\">0.111111111111111</span><span class=\"p\">,</span><span class=\"mf\">0.0277777777777778</span><span class=\"p\">,</span><span class=\"mf\">0.0277777777777778</span><span class=\"p\">,</span><span class=\"mf\">0.0277777777777778</span><span class=\"p\">,</span><span class=\"mf\">0.0277777777777778</span> <span class=\"p\">};</span>\n",
+       "   \n",
+       "   \n",
+       "   \n",
+       "   <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">neighbour_offset_x</span> <span class=\"p\">[]</span> <span class=\"o\">=</span> <span class=\"p\">{</span> <span class=\"mi\">0</span><span class=\"p\">,</span><span class=\"mi\">0</span><span class=\"p\">,</span><span class=\"mi\">0</span><span class=\"p\">,</span><span class=\"o\">-</span><span class=\"mi\">1</span><span class=\"p\">,</span><span class=\"mi\">1</span><span class=\"p\">,</span><span class=\"o\">-</span><span class=\"mi\">1</span><span class=\"p\">,</span><span class=\"mi\">1</span><span class=\"p\">,</span><span class=\"o\">-</span><span class=\"mi\">1</span><span class=\"p\">,</span><span class=\"mi\">1</span> <span class=\"p\">};</span> \n",
+       "   <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">neighbour_offset_y</span> <span class=\"p\">[]</span> <span class=\"o\">=</span> <span class=\"p\">{</span> <span class=\"mi\">0</span><span class=\"p\">,</span><span class=\"mi\">1</span><span class=\"p\">,</span><span class=\"o\">-</span><span class=\"mi\">1</span><span class=\"p\">,</span><span class=\"mi\">0</span><span class=\"p\">,</span><span class=\"mi\">0</span><span class=\"p\">,</span><span class=\"mi\">1</span><span class=\"p\">,</span><span class=\"mi\">1</span><span class=\"p\">,</span><span class=\"o\">-</span><span class=\"mi\">1</span><span class=\"p\">,</span><span class=\"o\">-</span><span class=\"mi\">1</span> <span class=\"p\">};</span> \n",
+       "   \n",
+       "   <span class=\"kt\">int64_t</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_idx_10</span> <span class=\"o\">=</span> <span class=\"n\">_data_idx</span><span class=\"p\">;</span>\n",
+       "   <span class=\"kt\">int64_t</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_idx_12</span> <span class=\"o\">=</span> <span class=\"n\">_data_idx</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">_stride_idx_1</span><span class=\"p\">;</span>\n",
+       "   <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_f_10</span> <span class=\"o\">=</span> <span class=\"n\">_data_f</span><span class=\"p\">;</span>\n",
+       "   <span class=\"kt\">int64_t</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_idx_11</span> <span class=\"o\">=</span> <span class=\"n\">_data_idx</span> <span class=\"o\">+</span> <span class=\"n\">_stride_idx_1</span><span class=\"p\">;</span>\n",
+       "   <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int64_t</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">0</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">&lt;</span> <span class=\"n\">_size_idx_0</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
+       "   <span class=\"p\">{</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">dir</span> <span class=\"o\">=</span> <span class=\"n\">_data_idx_10</span><span class=\"p\">[</span><span class=\"n\">_stride_idx_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">];</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">double</span> <span class=\"n\">vel0Term</span> <span class=\"o\">=</span> <span class=\"mf\">3.0</span><span class=\"o\">*</span><span class=\"n\">_data_f_10</span><span class=\"p\">[</span><span class=\"n\">_stride_f_0</span><span class=\"o\">*</span><span class=\"n\">_data_idx_12</span><span class=\"p\">[</span><span class=\"n\">_stride_idx_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]];</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">double</span> <span class=\"n\">vel1Term</span> <span class=\"o\">=</span> <span class=\"mf\">2.0</span><span class=\"o\">*</span><span class=\"n\">_data_f_10</span><span class=\"p\">[</span><span class=\"n\">_stride_f_0</span><span class=\"o\">*</span><span class=\"n\">_data_idx_12</span><span class=\"p\">[</span><span class=\"n\">_stride_idx_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]];</span>\n",
+       "      <span class=\"k\">const</span> <span class=\"kt\">double</span> <span class=\"n\">rho</span> <span class=\"o\">=</span> <span class=\"n\">vel0Term</span> <span class=\"o\">+</span> <span class=\"n\">vel1Term</span> <span class=\"o\">+</span> <span class=\"mf\">4.0</span><span class=\"o\">*</span><span class=\"n\">_data_f_10</span><span class=\"p\">[</span><span class=\"n\">_stride_f_0</span><span class=\"o\">*</span><span class=\"n\">_data_idx_12</span><span class=\"p\">[</span><span class=\"n\">_stride_idx_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]];</span>\n",
+       "      <span class=\"n\">_data_f_10</span><span class=\"p\">[</span><span class=\"n\">_stride_f_0</span><span class=\"o\">*</span><span class=\"n\">_data_idx_11</span><span class=\"p\">[</span><span class=\"n\">_stride_idx_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"n\">rho</span><span class=\"o\">*-</span><span class=\"mf\">0.059999999999999998</span><span class=\"o\">*</span><span class=\"n\">neighbour_offset_x</span><span class=\"p\">[</span><span class=\"n\">dir</span><span class=\"p\">]</span><span class=\"o\">*</span><span class=\"n\">weights</span><span class=\"p\">[</span><span class=\"n\">dir</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"n\">_data_f_10</span><span class=\"p\">[</span><span class=\"n\">_stride_f_0</span><span class=\"o\">*</span><span class=\"n\">_data_idx_12</span><span class=\"p\">[</span><span class=\"n\">_stride_idx_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]];</span>\n",
+       "   <span class=\"p\">}</span>\n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "FUNC_PREFIX void kernel(double * RESTRICT _data_f, int64_t * RESTRICT const _data_idx, int64_t const _size_idx_0, int64_t const _stride_f_0, int64_t const _stride_idx_0, int64_t const _stride_idx_1)\n",
+       "{\n",
+       "   \n",
+       "   \n",
+       "   \n",
+       "   const double weights [] = { 0.444444444444444,0.111111111111111,0.111111111111111,0.111111111111111,0.111111111111111,0.0277777777777778,0.0277777777777778,0.0277777777777778,0.0277777777777778 };\n",
+       "   \n",
+       "   \n",
+       "   \n",
+       "   const int64_t neighbour_offset_x [] = { 0,0,0,-1,1,-1,1,-1,1 }; \n",
+       "   const int64_t neighbour_offset_y [] = { 0,1,-1,0,0,1,1,-1,-1 }; \n",
+       "   \n",
+       "   int64_t * RESTRICT _data_idx_10 = _data_idx;\n",
+       "   int64_t * RESTRICT _data_idx_12 = _data_idx + 2*_stride_idx_1;\n",
+       "   double * RESTRICT _data_f_10 = _data_f;\n",
+       "   int64_t * RESTRICT _data_idx_11 = _data_idx + _stride_idx_1;\n",
+       "   for (int64_t ctr_0 = 0; ctr_0 < _size_idx_0; ctr_0 += 1)\n",
+       "   {\n",
+       "      const int64_t dir = _data_idx_10[_stride_idx_0*ctr_0];\n",
+       "      const double vel0Term = 3.0*_data_f_10[_stride_f_0*_data_idx_12[_stride_idx_0*ctr_0]];\n",
+       "      const double vel1Term = 2.0*_data_f_10[_stride_f_0*_data_idx_12[_stride_idx_0*ctr_0]];\n",
+       "      const double rho = vel0Term + vel1Term + 4.0*_data_f_10[_stride_f_0*_data_idx_12[_stride_idx_0*ctr_0]];\n",
+       "      _data_f_10[_stride_f_0*_data_idx_11[_stride_idx_0*ctr_0]] = rho*-0.059999999999999998*neighbour_offset_x[dir]*weights[dir] + _data_f_10[_stride_f_0*_data_idx_12[_stride_idx_0*ctr_0]];\n",
+       "   }\n",
+       "}"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "idx[0](0)\n",
       "domain: (4, 3)\n",
       "pdf size in bytes: 864\n",
       "pdf size: 108\n",
@@ -533,7 +601,7 @@
     }
    ],
    "source": [
-    "if not channel:\n",
+    "if channel:\n",
     "    if target == 'gpu':\n",
     "        raise NotImplementedError(\"UBB on GPU not working yet\")\n",
     "        \n",
@@ -543,12 +611,13 @@
     "    # when taken from pdf field, a wrong kernel is generated\n",
     "    ubb_ast = ubb_mapper.get_kernel()\n",
     "     \n",
-    "    # ps.show_code(ubb_ast)\n",
+    "    ps.show_code(ubb_ast)\n",
     "    \n",
     "    ubb_kernel = ubb_ast.compile()\n",
     "    ubb_idx_arr = ubb_mapper.create_index_arr(mapping, flags[ubb])\n",
     "    def handle_ubb():\n",
     "        ubb_kernel(f=pdf_arr[:mapping.num_fluid_cells], idx=ubb_idx_arr)\n",
+    "    print(ubb_mapper.index_field(0))\n",
     "        \n",
     "    density_mapper = SparseLbBoundaryMapper(density, method, pdf_field)\n",
     "    density_ast = density_mapper.get_kernel()\n",
@@ -556,9 +625,17 @@
     "    density_idx_arr = density_mapper.create_index_arr(mapping, flags[density])\n",
     "    def handle_density():\n",
     "        density_kernel(f=pdf_arr[:mapping.num_fluid_cells], idx=density_idx_arr)\n",
-    "else:\n",
-    "    def handle_ubb():\n",
-    "        pass\n",
+    "    \n",
+    "    periodicity_ast = periodicity_mapper.get_kernel()\n",
+    "    periodicity_kernel = periodicity_ast.compile()\n",
+    "    def handle_periodicity():\n",
+    "        for i_a in (block for block in periodicity_idx_array):\n",
+    "            if bool(i_a):\n",
+    "                print(i_a)\n",
+    "                periodicity_kernel(f=pdf_arr[:mapping.num_fluid_cells], idx=i_a)\n",
+    "#else:\n",
+    "#    def handle_ubb():\n",
+    "#        pass\n",
     "\n",
     "print(\"domain:\", domain_size)\n",
     "print(\"pdf size in bytes:\", pdf_arr.nbytes)\n",
@@ -603,7 +680,8 @@
     "                                  d=pdf_arr_tmp[:mapping.num_fluid_cells], \n",
     "                                  idx=index_arr)\n",
     "        pdf_arr_tmp, pdf_arr = pdf_arr, pdf_arr_tmp\n",
-    "    \n",
+    "        \n",
+    "        handle_periodicity()\n",
     "        handle_ubb()\n",
     "        handle_density()\n",
     "\n",
@@ -621,18 +699,88 @@
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAABoAAAASCAYAAABFGc6jAAAABHNCSVQICAgIfAhkiAAAAU5JREFUOI291L9LnEEQxvHPqf+BhZYmlYUQW6sYrNIE8UdpUmgnHAkRAiHCi1W6IBG0sLCwFQtRYqOIqQKBFCKSXKEiRIIIimChiSluDo71ziC5uweGmd13Zr6778LksizTCDUl6yF8xDbOcYPFKrWtGMMyCrjEGT5jNO3dkhS/wyNc4AiddxxyGLP4iU0cog0DmMfTyLmpBHoVgAIeR4Nq+o5nWMWfsv23+ILBgC5JrxeNf5RO8Q9tYCWBwDHmIu4tbaagWukq/HU9QS14HvGneoLeowtrWK8XKI/X2MNI+YdagsYxjV08wWk9QC8xg52AHKcJtQC9wQd8C8ivSkn/C5pUfPyv6MNJtcR0MvSHQXv4HixEfIKJiF9gCr8VZ2O+Qv/9Um0K6o4G5XoYBgdloAfhmxXfqJK2SqD012XI3WEd98jNacAIuqWGgf4CTG9DgbNIuvUAAAAASUVORK5CYII=\n",
+      "text/latex": [
+       "$\\displaystyle 12$"
+      ],
+      "text/plain": [
+       "12"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/latex": [
+       "$\\displaystyle 12$"
+      ],
+      "text/plain": [
+       "12"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAA0AAAASCAYAAACAa1QyAAAABHNCSVQICAgIfAhkiAAAAPZJREFUKJGd0r8rxWEUx/HX5f4HBrPdH3FlshjIiIFNSRmUUt9MNinFYLj/gAwiFhKTUgZJMsjiJimTwc/h+6jTt2/3fvnU0zmd57xP5/P01LIs81d1hbwH09jBHd7wijNMxd56gMawgUcc4wG9GMEWhlLPd4RuMYw9fIX6Is4xmgZsx/WOsFsAoIXNlDeKntrpPcWPqlAdEyk/qAqtoB/7OKwCzWIeNxj/LbaDZrCGawzgpRM0h3VcJaAVL8ugBaziMgFPxYYitCQ3foFBPJetEX/EJJbxiVP5IxR1j2aE+lLslnsq0wmacb0MtQ6nUeapkv4F/QC4NjEPV14CWgAAAABJRU5ErkJggg==\n",
+      "text/latex": [
+       "$\\displaystyle 2$"
+      ],
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[ 15  29  43  49  66  72  92  98]\n",
+      " [ 18  32  46  52  69  75  95 101]]\n"
+     ]
+    },
+    {
+     "ename": "TypeError",
+     "evalue": "Arrays must have same shape",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-16-8b7fec23f4ed>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex_arr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimesteps\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# get_velocity(ghost_layers=False) #\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     10\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvector_field\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-15-6ec52cdec57e>\u001b[0m in \u001b[0;36mrun\u001b[0;34m(steps)\u001b[0m\n\u001b[1;32m     25\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     26\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 27\u001b[0;31m     \u001b[0mtime_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     28\u001b[0m     \u001b[0;31m#for t in range(steps):\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     29\u001b[0m     \u001b[0;31m#    time_step()\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-15-6ec52cdec57e>\u001b[0m in \u001b[0;36mtime_step\u001b[0;34m(steps)\u001b[0m\n\u001b[1;32m     15\u001b[0m             \u001b[0mindex_arr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgpu_index_arr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m             kernel_stream_collide(f=pdf_arr[:mapping.num_fluid_cells], \n\u001b[0m\u001b[1;32m     18\u001b[0m                                   \u001b[0md\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpdf_arr_tmp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mmapping\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnum_fluid_cells\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m                                   idx=index_arr)\n",
+      "\u001b[0;32m~/.local/lib/python3.8/site-packages/pystencils/kernel_wrapper.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m     16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 18\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkernel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     19\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     20\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mTypeError\u001b[0m: Arrays must have same shape"
+     ]
+    }
+   ],
    "source": [
     "timesteps = 10\n",
     "\n",
-    "#init()\n",
-    "#result = run(timesteps) # get_velocity(ghost_layers=False) # \n",
-    "#plt.vector_field(result, step=1)"
+    "init()\n",
+    "len(pdf_arr)\n",
+    "len(pdf_arr_tmp)\n",
+    "len(index_arr)\n",
+    "print(index_arr)\n",
+    "\n",
+    "result = run(timesteps) # get_velocity(ghost_layers=False) # \n",
+    "plt.vector_field(result, step=1)\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -658,7 +806,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -672,7 +820,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -681,36 +829,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.quiver.Quiver at 0x7f941b6d7310>"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1152x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plt.vector_field(reference.velocity[:, :], step=1)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,