diff --git a/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/TP-R-layered_soil_with_inner_patch-all-params-one.py b/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/TP-R-layered_soil_with_inner_patch-all-params-one.py
new file mode 100644
index 0000000000000000000000000000000000000000..d96b0f28ffae9d46342c958e01f7ea4498627ac0
--- /dev/null
+++ b/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/TP-R-layered_soil_with_inner_patch-all-params-one.py
@@ -0,0 +1,1000 @@
+#!/usr/bin/python3
+"""Layered soil simulation with inner patch.
+
+This program sets up an LDD simulation
+"""
+
+import dolfin as df
+import sympy as sym
+import functools as ft
+import LDDsimulation as ldd
+import helpers as hlp
+import datetime
+import os
+import pandas as pd
+
+# check if output directory exists
+if not os.path.exists('./output'):
+    os.mkdir('./output')
+    print("Directory ", './output',  " created ")
+else:
+    print("Directory ", './output',  " already exists. Will use as output \
+    directory")
+
+
+# init sympy session
+sym.init_printing()
+# solver_tol = 6E-7
+use_case = "TP-R-layered-soil-with-inner-patch-realistic"
+# name of this very file. Needed for log output.
+thisfile = "TP-R-layered_soil_with_inner_patch-all-params-one.py"
+
+max_iter_num = 300
+FEM_Lagrange_degree = 1
+mesh_study = False
+resolutions = {
+                # 1: 2e-6,  # h=2
+                # 2: 2e-6,  # h=1.1180
+                # 4: 2e-6,  # h=0.5590
+                # 8: 2e-6,  # h=0.2814
+                16: 2e-6, # h=0.1412
+                # 32: 2e-6,
+                # 64: 2e-6,
+                # 128: 2e-6
+                }
+
+# GRID #######################
+# mesh_resolution = 20
+timestep_size = 0.001
+number_of_timesteps = 5
+plot_timestep_every = 1
+# decide how many timesteps you want analysed. Analysed means, that we write
+# out subsequent errors of the L-iteration within the timestep.
+number_of_timesteps_to_analyse = 5
+starttimes = [0.0]
+
+Lw1 = 0.025  # /timestep_size
+Lnw1 = Lw1
+
+Lw2 = 0.025  # /timestep_size
+Lnw2 = Lw2
+
+Lw3 = 0.025  # /timestep_size
+Lnw3 = Lw3
+
+Lw4 = 0.025  # /timestep_size
+Lnw4 = Lw4
+
+Lw5 = 0.025  # /timestep_size
+Lnw5 = Lw5
+
+Lw6 = 0.025  # /timestep_size
+Lnw6 = Lw6
+
+lambda12_w = 40
+lambda12_nw = 40
+
+lambda23_w = 40
+lambda23_nw = 40
+
+lambda24_w = 40
+lambda24_nw= 40
+
+lambda25_w= 40
+lambda25_nw= 40
+
+lambda34_w = 40
+lambda34_nw = 40
+
+lambda36_w = 40
+lambda36_nw = 40
+
+lambda45_w = 40
+lambda45_nw = 40
+
+lambda46_w = 40
+lambda46_nw = 40
+
+lambda56_w = 40
+lambda56_nw = 40
+
+include_gravity = False
+debugflag = True
+analyse_condition = True
+
+if mesh_study:
+    output_string = "./output/{}-{}_timesteps{}_P{}".format(
+        datestr, use_case, number_of_timesteps, FEM_Lagrange_degree
+        )
+else:
+    for tol in resolutions.values():
+        solver_tol = tol
+    output_string = "./output/{}-{}_timesteps{}_P{}_solver_tol{}".format(
+        datestr, use_case, number_of_timesteps, FEM_Lagrange_degree, solver_tol
+        )
+
+
+# toggle what should be written to files
+if mesh_study:
+    write_to_file = {
+        'space_errornorms': True,
+        'meshes_and_markers': True,
+        'L_iterations_per_timestep': False,
+        'solutions': True,
+        'absolute_differences': True,
+        'condition_numbers': analyse_condition,
+        'subsequent_errors': True
+    }
+else:
+    write_to_file = {
+        'space_errornorms': True,
+        'meshes_and_markers': True,
+        'L_iterations_per_timestep': False,
+        'solutions': True,
+        'absolute_differences': True,
+        'condition_numbers': analyse_condition,
+        'subsequent_errors': True
+    }
+
+
+# global domain
+subdomain0_vertices = [df.Point(-1.0,-1.0), #
+                        df.Point(1.0,-1.0),#
+                        df.Point(1.0,1.0),#
+                        df.Point(-1.0,1.0)]
+
+interface12_vertices = [df.Point(-1.0, 0.8),
+                        df.Point(0.3, 0.8),
+                        df.Point(0.5, 0.9),
+                        df.Point(0.8, 0.7),
+                        df.Point(1.0, 0.65)]
+
+
+                        # interface23
+interface23_vertices = [df.Point(-1.0, 0.0),
+                        df.Point(-0.35, 0.0),
+                        # df.Point(6.5, 4.5),
+                        df.Point(0.0, 0.0)]
+
+interface24_vertices = [interface23_vertices[2],
+                        df.Point(0.6, 0.0),
+                        ]
+
+interface25_vertices = [interface24_vertices[1],
+                        df.Point(1.0, 0.0)
+                        ]
+
+
+interface32_vertices = [interface23_vertices[2],
+                        interface23_vertices[1],
+                        interface23_vertices[0]]
+
+
+interface36_vertices = [df.Point(-1.0, -0.6),
+                        df.Point(-0.6, -0.45)]
+
+
+interface46_vertices = [interface36_vertices[1],
+                        df.Point(0.3, -0.25)]
+
+interface56_vertices = [interface46_vertices[1],
+                        df.Point(0.65, -0.6),
+                        df.Point(1.0, -0.7)]
+
+
+
+
+interface34_vertices = [interface36_vertices[1],
+                        interface23_vertices[2]]
+# interface36
+
+interface45_vertices = [interface56_vertices[0],
+                        df.Point(0.7, -0.2),
+                        interface25_vertices[0]
+                        ]
+
+
+# interface_vertices introduces a global numbering of interfaces.
+interface_def_points = [interface12_vertices,
+                        interface23_vertices,
+                        interface24_vertices,
+                        interface25_vertices,
+                        interface34_vertices,
+                        interface36_vertices,
+                        interface45_vertices,
+                        interface46_vertices,
+                        interface56_vertices,
+                        ]
+
+adjacent_subdomains = [[1,2],
+                       [2,3],
+                       [2,4],
+                       [2,5],
+                       [3,4],
+                       [3,6],
+                       [4,5],
+                       [4,6],
+                       [5,6]
+                       ]
+
+# subdomain1.
+subdomain1_vertices = [interface12_vertices[0],
+                        interface12_vertices[1],
+                        interface12_vertices[2],
+                        interface12_vertices[3],
+                        interface12_vertices[4],  # southern boundary, 12 interface
+                        subdomain0_vertices[2],  # eastern boundary, outer boundary
+                        subdomain0_vertices[3]]  # northern boundary, outer on_boundary
+
+# vertex coordinates of the outer boundaries. If it can not be specified as a
+# polygon, use an entry per boundary polygon.
+# This information is used for defining
+# the Dirichlet boundary conditions. If a domain is completely internal, the
+# dictionary entry should be 0: None
+subdomain1_outer_boundary_verts = {
+    0: [subdomain1_vertices[4],
+        subdomain1_vertices[5],  # eastern boundary, outer boundary
+        subdomain1_vertices[6],
+        subdomain1_vertices[0]]
+}
+
+#subdomain1
+subdomain2_vertices = [interface23_vertices[0],
+                        interface23_vertices[1],
+                        interface23_vertices[2],
+                        interface24_vertices[1],
+                        interface25_vertices[1],  # southern boundary, 23 interface
+                        subdomain1_vertices[4],  # eastern boundary, outer boundary
+                        subdomain1_vertices[3],
+                        subdomain1_vertices[2],
+                        subdomain1_vertices[1],
+                        subdomain1_vertices[0] ]  # northern boundary, 12 interface
+
+subdomain2_outer_boundary_verts = {
+    0: [subdomain2_vertices[9],
+        subdomain2_vertices[0]],
+    1: [subdomain2_vertices[4],
+        subdomain2_vertices[5]]
+}
+
+
+subdomain3_vertices = [interface36_vertices[0],
+                       interface36_vertices[1],
+                       # interface34_vertices[0],
+                       interface34_vertices[1],
+                       # interface32_vertices[0],
+                       interface32_vertices[1],
+                       interface32_vertices[2]
+                       ]
+
+subdomain3_outer_boundary_verts = {
+    0: [subdomain3_vertices[4],
+        subdomain3_vertices[0]]
+}
+
+
+# subdomain3
+subdomain4_vertices = [interface46_vertices[0],
+                       interface46_vertices[1],
+                       interface45_vertices[1],
+                       interface24_vertices[1],
+                       interface24_vertices[0],
+                       interface34_vertices[1]
+                       ]
+
+subdomain4_outer_boundary_verts = None
+
+subdomain5_vertices = [interface56_vertices[0],
+                       interface56_vertices[1],
+                       interface56_vertices[2],
+                       interface25_vertices[1],
+                       interface25_vertices[0],
+                       interface45_vertices[1],
+                       interface45_vertices[0]
+]
+
+subdomain5_outer_boundary_verts = {
+    0: [subdomain5_vertices[2],
+        subdomain5_vertices[3]]
+}
+
+
+
+subdomain6_vertices = [subdomain0_vertices[0],
+                       subdomain0_vertices[1], # southern boundary, outer boundary
+                       interface56_vertices[2],
+                       interface56_vertices[1],
+                       interface56_vertices[0],
+                       interface36_vertices[1],
+                       interface36_vertices[0]
+                       ]
+
+subdomain6_outer_boundary_verts = {
+    0: [subdomain6_vertices[6],
+        subdomain6_vertices[0],
+        subdomain6_vertices[1],
+        subdomain6_vertices[2]]
+}
+
+
+subdomain_def_points = [subdomain0_vertices,#
+                      subdomain1_vertices,#
+                      subdomain2_vertices,#
+                      subdomain3_vertices,#
+                      subdomain4_vertices,
+                      subdomain5_vertices,
+                      subdomain6_vertices
+                      ]
+
+
+# if a subdomain has no outer boundary write None instead, i.e.
+# i: None
+# if i is the index of the inner subdomain.
+outer_boundary_def_points = {
+    # subdomain number
+    1: subdomain1_outer_boundary_verts,
+    2: subdomain2_outer_boundary_verts,
+    3: subdomain3_outer_boundary_verts,
+    4: subdomain4_outer_boundary_verts,
+    5: subdomain5_outer_boundary_verts,
+    6: subdomain6_outer_boundary_verts
+}
+
+
+isRichards = {
+    1: True,
+    2: True,
+    3: False,
+    4: False,
+    5: False,
+    6: False
+    }
+
+# isRichards = {
+#     1: True,
+#     2: True,
+#     3: True,
+#     4: True,
+#     5: True,
+#     6: True
+#     }
+
+# Dict of the form: { subdom_num : viscosity }
+viscosity = {
+    1: {'wetting' :1,
+         'nonwetting': 1},
+    2: {'wetting' :1,
+         'nonwetting': 1},
+    3: {'wetting' :1,
+         'nonwetting': 1},
+    4: {'wetting' :1,
+         'nonwetting': 1},
+    5: {'wetting' :1,
+         'nonwetting': 1},
+    6: {'wetting' :1,
+         'nonwetting': 1},
+}
+
+# Dict of the form: { subdom_num : density }
+densities = {
+    1: {'wetting': 1,  #997
+         'nonwetting': 1},  #1},  #1.225},
+    2: {'wetting': 1,  #997
+         'nonwetting': 1},  #1.225},
+    3: {'wetting': 1,  #997
+         'nonwetting': 1},  #1.225},
+    4: {'wetting': 1,  #997
+         'nonwetting': 1},  #1.225}
+    5: {'wetting': 1,  #997
+         'nonwetting': 1},  #1.225},
+    6: {'wetting': 1,  #997
+         'nonwetting': 1}  #1.225}
+}
+
+gravity_acceleration = 9.81
+# porosities taken from
+# https://www.geotechdata.info/parameter/soil-porosity.html
+# Dict of the form: { subdom_num : porosity }
+porosity = {
+    1: 1,  #0.2,  # Clayey gravels, clayey sandy gravels
+    2: 1,  #0.22, # Silty gravels, silty sandy gravels
+    3: 1,  #0.37, # Clayey sands
+    4: 1,  #0.2 # Silty or sandy clay
+    5: 1,  #
+    6: 1,  #
+}
+
+# subdom_num : subdomain L for L-scheme
+L = {
+    1: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    2: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    3: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    4: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    5: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    6: {'wetting' :Lw,
+         'nonwetting': Lnw}
+}
+
+
+# interface_num : lambda parameter for the L-scheme on that interface.
+# Note that interfaces are numbered starting from 0, because
+# adjacent_subdomains is a list and not a dict. Historic fuckup, I know
+# We have defined above as interfaces
+# # interface_vertices introduces a global numbering of interfaces.
+# interface_def_points = [interface12_vertices,
+#                         interface23_vertices,
+#                         interface24_vertices,
+#                         interface25_vertices,
+#                         interface34_vertices,
+#                         interface36_vertices,
+#                         interface45_vertices,
+#                         interface46_vertices,
+#                         interface56_vertices,
+#                         ]
+lambda_param = {
+    0: {'wetting': lambda12_w,
+         'nonwetting': lambda12_nw},#
+    1: {'wetting': lambda23_w,
+         'nonwetting': lambda23_nw},#
+    2: {'wetting': lambda24_w,
+         'nonwetting': lambda24_nw},#
+    3: {'wetting': lambda25_w,
+         'nonwetting': lambda25_nw},#
+    4: {'wetting': lambda34_w,
+         'nonwetting': lambda34_nw},#
+    5: {'wetting': lambda36_w,
+         'nonwetting': lambda36_nw},#
+    6: {'wetting': lambda45_w,
+         'nonwetting': lambda45_nw},#
+    7: {'wetting': lambda46_w,
+         'nonwetting': lambda46_nw},#
+    8: {'wetting': lambda56_w,
+         'nonwetting': lambda56_nw},#
+}
+
+
+# after Lewis, see pdf file
+intrinsic_permeability = {
+    1: 1,  # sand
+    2: 1,  # sand, there is a range
+    3: 1,  #10e-2,  # clay has a range
+    4: 1,  #10e-3
+    5: 1,  #10e-2,  # clay has a range
+    6: 1,  #10e-3
+}
+
+
+# relative permeabilty functions on subdomain 1
+def rel_perm1w(s):
+    # relative permeabilty wetting on subdomain1
+    return intrinsic_permeability[1]*s**2
+
+
+def rel_perm1nw(s):
+    # relative permeabilty nonwetting on subdomain1
+    return intrinsic_permeability[1]*(1-s)**2
+
+
+# relative permeabilty functions on subdomain 2
+def rel_perm2w(s):
+    # relative permeabilty wetting on subdomain2
+    return intrinsic_permeability[2]*s**2
+
+
+def rel_perm2nw(s):
+    # relative permeabilty nonwetting on subdomain2
+    return intrinsic_permeability[2]*(1-s)**2
+
+
+# relative permeabilty functions on subdomain 3
+def rel_perm3w(s):
+    # relative permeabilty wetting on subdomain3
+    return intrinsic_permeability[3]*s**3
+
+
+def rel_perm3nw(s):
+    # relative permeabilty nonwetting on subdomain3
+    return intrinsic_permeability[3]*(1-s)**3
+
+
+# relative permeabilty functions on subdomain 4
+def rel_perm4w(s):
+    # relative permeabilty wetting on subdomain4
+    return intrinsic_permeability[4]*s**3
+
+
+def rel_perm4nw(s):
+    # relative permeabilty nonwetting on subdomain4
+    return intrinsic_permeability[4]*(1-s)**3
+
+
+# relative permeabilty functions on subdomain 5
+def rel_perm5w(s):
+    # relative permeabilty wetting on subdomain5
+    return intrinsic_permeability[5]*s**3
+
+
+def rel_perm5nw(s):
+    # relative permeabilty nonwetting on subdomain5
+    return intrinsic_permeability[5]*(1-s)**3
+
+
+# relative permeabilty functions on subdomain 6
+def rel_perm6w(s):
+    # relative permeabilty wetting on subdomain6
+    return intrinsic_permeability[6]*s**3
+
+
+def rel_perm6nw(s):
+    # relative permeabilty nonwetting on subdomain6
+    return intrinsic_permeability[6]*(1-s)**3
+
+
+_rel_perm1w = ft.partial(rel_perm1w)
+_rel_perm1nw = ft.partial(rel_perm1nw)
+
+_rel_perm2w = ft.partial(rel_perm2w)
+_rel_perm2nw = ft.partial(rel_perm2nw)
+
+_rel_perm3w = ft.partial(rel_perm3w)
+_rel_perm3nw = ft.partial(rel_perm3nw)
+
+_rel_perm4w = ft.partial(rel_perm4w)
+_rel_perm4nw = ft.partial(rel_perm4nw)
+
+_rel_perm5w = ft.partial(rel_perm5w)
+_rel_perm5nw = ft.partial(rel_perm5nw)
+
+_rel_perm6w = ft.partial(rel_perm6w)
+_rel_perm6nw = ft.partial(rel_perm6nw)
+
+subdomain1_rel_perm = {
+    'wetting': _rel_perm1w,
+    'nonwetting': _rel_perm1nw
+}
+
+subdomain2_rel_perm = {
+    'wetting': _rel_perm2w,
+    'nonwetting': _rel_perm2nw
+}
+
+subdomain3_rel_perm = {
+    'wetting': _rel_perm3w,
+    'nonwetting': _rel_perm3nw
+}
+
+subdomain4_rel_perm = {
+    'wetting': _rel_perm4w,
+    'nonwetting': _rel_perm4nw
+}
+
+subdomain5_rel_perm = {
+    'wetting': _rel_perm5w,
+    'nonwetting': _rel_perm5nw
+}
+
+subdomain6_rel_perm = {
+    'wetting': _rel_perm6w,
+    'nonwetting': _rel_perm6nw
+}
+
+# dictionary of relative permeabilties on all domains.
+relative_permeability = {
+    1: subdomain1_rel_perm,
+    2: subdomain2_rel_perm,
+    3: subdomain3_rel_perm,
+    4: subdomain4_rel_perm,
+    5: subdomain5_rel_perm,
+    6: subdomain6_rel_perm
+}
+
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 1
+def rel_perm1w_prime(s):
+    # relative permeabilty on subdomain1
+    return intrinsic_permeability[1]*2*s
+
+
+def rel_perm1nw_prime(s):
+    # relative permeabilty on subdomain1
+    return -1*intrinsic_permeability[1]*2*(1-s)
+
+
+def rel_perm2w_prime(s):
+    # relative permeabilty on subdomain2
+    return intrinsic_permeability[2]*2*s
+
+
+def rel_perm2nw_prime(s):
+    # relative permeabilty on subdomain2
+    return -1*intrinsic_permeability[2]*2*(1-s)
+
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 3
+def rel_perm3w_prime(s):
+    # relative permeabilty on subdomain3
+    return intrinsic_permeability[3]*3*s**2
+
+
+def rel_perm3nw_prime(s):
+    # relative permeabilty on subdomain3
+    return -1*intrinsic_permeability[3]*3*(1-s)**2
+
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 4
+def rel_perm4w_prime(s):
+    # relative permeabilty on subdomain4
+    return intrinsic_permeability[4]*3*s**2
+
+
+def rel_perm4nw_prime(s):
+    # relative permeabilty on subdomain4
+    return -1*intrinsic_permeability[4]*3*(1-s)**2
+
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 5
+def rel_perm5w_prime(s):
+    # relative permeabilty on subdomain5
+    return intrinsic_permeability[5]*3*s**2
+
+
+def rel_perm5nw_prime(s):
+    # relative permeabilty on subdomain5
+    return -1*intrinsic_permeability[5]*3*(1-s)**2
+
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 6
+def rel_perm6w_prime(s):
+    # relative permeabilty on subdomain6
+    return intrinsic_permeability[6]*3*s**2
+
+
+def rel_perm6nw_prime(s):
+    # relative permeabilty on subdomain6
+    return -1*intrinsic_permeability[6]*3*(1-s)**2
+
+
+_rel_perm1w_prime = ft.partial(rel_perm1w_prime)
+_rel_perm1nw_prime = ft.partial(rel_perm1nw_prime)
+_rel_perm2w_prime = ft.partial(rel_perm2w_prime)
+_rel_perm2nw_prime = ft.partial(rel_perm2nw_prime)
+_rel_perm3w_prime = ft.partial(rel_perm3w_prime)
+_rel_perm3nw_prime = ft.partial(rel_perm3nw_prime)
+_rel_perm4w_prime = ft.partial(rel_perm4w_prime)
+_rel_perm4nw_prime = ft.partial(rel_perm4nw_prime)
+_rel_perm5w_prime = ft.partial(rel_perm5w_prime)
+_rel_perm5nw_prime = ft.partial(rel_perm5nw_prime)
+_rel_perm6w_prime = ft.partial(rel_perm6w_prime)
+_rel_perm6nw_prime = ft.partial(rel_perm6nw_prime)
+
+subdomain1_rel_perm_prime = {
+    'wetting': _rel_perm1w_prime,
+    'nonwetting': _rel_perm1nw_prime
+}
+
+
+subdomain2_rel_perm_prime = {
+    'wetting': _rel_perm2w_prime,
+    'nonwetting': _rel_perm2nw_prime
+}
+
+subdomain3_rel_perm_prime = {
+    'wetting': _rel_perm3w_prime,
+    'nonwetting': _rel_perm3nw_prime
+}
+
+
+subdomain4_rel_perm_prime = {
+    'wetting': _rel_perm4w_prime,
+    'nonwetting': _rel_perm4nw_prime
+}
+
+subdomain5_rel_perm_prime = {
+    'wetting': _rel_perm5w_prime,
+    'nonwetting': _rel_perm5nw_prime
+}
+
+subdomain6_rel_perm_prime = {
+    'wetting': _rel_perm6w_prime,
+    'nonwetting': _rel_perm6nw_prime
+}
+
+
+# dictionary of relative permeabilties on all domains.
+ka_prime = {
+    1: subdomain1_rel_perm_prime,
+    2: subdomain2_rel_perm_prime,
+    3: subdomain3_rel_perm_prime,
+    4: subdomain4_rel_perm_prime,
+    5: subdomain5_rel_perm_prime,
+    6: subdomain6_rel_perm_prime,
+}
+
+
+
+# S-pc-relation ship. We use the van Genuchten approach, i.e.
+# pc = 1/alpha*(S^{-1/m} -1)^1/n, where we set alpha = 0, assume
+# m = 1-1/n (see Helmig) and assume that residual saturation is Sw
+# this function needs to be monotonically decreasing in the capillary pressure
+# pc.
+# Since in the richards case pc=-pw, this becomes as a function of pw a mono
+# tonically INCREASING function like in our Richards-Richards paper. However
+# since we unify the treatment in the code for Richards and two-phase, we need
+# the same requierment
+# for both cases, two-phase and Richards.
+# def saturation(pc, n_index, alpha):
+#     # inverse capillary pressure-saturation-relationship
+#     return df.conditional(pc > 0, 1/((1 + (alpha*pc)**n_index)**((n_index - 1)/n_index)), 1)
+#
+# # S-pc-relation ship. We use the van Genuchten approach, i.e. pc = 1/alpha*(S^{-1/m} -1)^1/n, where
+# # we set alpha = 0, assume m = 1-1/n (see Helmig) and assume that residual saturation is Sw
+# def saturation_sym(pc, n_index, alpha):
+#     # inverse capillary pressure-saturation-relationship
+#     #df.conditional(pc > 0,
+#     return 1/((1 + (alpha*pc)**n_index)**((n_index - 1)/n_index))
+#
+#
+# # derivative of S-pc relationship with respect to pc. This is needed for the
+# # construction of a analytic solution.
+# def saturation_sym_prime(pc, n_index, alpha):
+#     # inverse capillary pressure-saturation-relationship
+#     return -(alpha*(n_index - 1)*(alpha*pc)**(n_index - 1)) / ( (1 + (alpha*pc)**n_index)**((2*n_index - 1)/n_index) )
+##
+# # note that the conditional definition of S-pc in the nonsymbolic part will be
+# # incorporated in the construction of the exact solution below.
+# S_pc_sym = {
+#     1: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     2: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     3: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     4: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     5: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     6: ft.partial(saturation_sym, n_index=3, alpha=0.001)
+# }
+#
+# S_pc_sym_prime = {
+#     1: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     2: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     3: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     4: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     5: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     6: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001)
+# }
+#
+# sat_pressure_relationship = {
+#     1: ft.partial(saturation, n_index=3, alpha=0.001),
+#     2: ft.partial(saturation, n_index=3, alpha=0.001),
+#     3: ft.partial(saturation, n_index=3, alpha=0.001),
+#     4: ft.partial(saturation, n_index=3, alpha=0.001),
+#     5: ft.partial(saturation, n_index=3, alpha=0.001),
+#     6: ft.partial(saturation, n_index=3, alpha=0.001)
+# }
+
+def saturation(pc, n_index):
+    # inverse capillary pressure-saturation-relationship
+    return df.conditional(pc > 0, 1/((1 + pc)**(1/(n_index + 1))), 1)
+
+
+def saturation_sym(pc, n_index):
+    # inverse capillary pressure-saturation-relationship
+    return 1/((1 + pc)**(1/(n_index + 1)))
+
+
+def saturation_sym_prime(pc, n_index):
+    # inverse capillary pressure-saturation-relationship
+    return -1/((n_index+1)*(1 + pc)**((n_index+2)/(n_index+1)))
+
+
+S_pc_sym = {
+    1: ft.partial(saturation_sym, n_index=1),
+    2: ft.partial(saturation_sym, n_index=1),
+    3: ft.partial(saturation_sym, n_index=2),
+    4: ft.partial(saturation_sym, n_index=2),
+    5: ft.partial(saturation_sym, n_index=2),
+    6: ft.partial(saturation_sym, n_index=2)
+}
+
+S_pc_sym_prime = {
+    1: ft.partial(saturation_sym_prime, n_index=1),
+    2: ft.partial(saturation_sym_prime, n_index=1),
+    3: ft.partial(saturation_sym_prime, n_index=2),
+    4: ft.partial(saturation_sym_prime, n_index=2),
+    5: ft.partial(saturation_sym_prime, n_index=2),
+    6: ft.partial(saturation_sym_prime, n_index=2)
+}
+
+sat_pressure_relationship = {
+    1: ft.partial(saturation, n_index=1),
+    2: ft.partial(saturation, n_index=1),
+    3: ft.partial(saturation, n_index=2),
+    4: ft.partial(saturation, n_index=2),
+    5: ft.partial(saturation, n_index=2),
+    6: ft.partial(saturation, n_index=2)
+}
+
+#############################################
+# Manufacture source expressions with sympy #
+#############################################
+x, y = sym.symbols('x[0], x[1]')  # needed by UFL
+t = sym.symbols('t', positive=True)
+
+
+p_e_sym = {
+    1: {'wetting': (-7.0 - (1.0 + t*t)*(1.0 + x*x + y*y)),
+        'nonwetting': 0.0*t },
+    2: {'wetting': (-7.0 - (1.0 + t*t)*(1.0 + x*x + y*y)),
+        'nonwetting': 0.0*t },
+    3: {'wetting': (-7.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2)*y**2 },
+    4: {'wetting': (-7.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2)*y**2 },
+    5: {'wetting': (-7.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2)*y**2 },
+    6: {'wetting': (-7.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2)*y**2 },
+}
+
+pc_e_sym = dict()
+for subdomain, isR in isRichards.items():
+    if isR:
+        pc_e_sym.update({subdomain: -p_e_sym[subdomain]['wetting']})
+    else:
+        pc_e_sym.update(
+            {subdomain: p_e_sym[subdomain]['nonwetting']
+                - p_e_sym[subdomain]['wetting']}
+            )
+
+
+symbols = {"x": x,
+           "y": y,
+           "t": t}
+# turn above symbolic code into exact solution for dolphin and
+# construct the rhs that matches the above exact solution.
+exact_solution_example = hlp.generate_exact_solution_expressions(
+                        symbols=symbols,
+                        isRichards=isRichards,
+                        symbolic_pressure=p_e_sym,
+                        symbolic_capillary_pressure=pc_e_sym,
+                        saturation_pressure_relationship=S_pc_sym,
+                        saturation_pressure_relationship_prime=S_pc_sym_prime,
+                        viscosity=viscosity,
+                        porosity=porosity,
+                        relative_permeability=relative_permeability,
+                        relative_permeability_prime=ka_prime,
+                        densities=densities,
+                        gravity_acceleration=gravity_acceleration,
+                        include_gravity=include_gravity,
+                        )
+source_expression = exact_solution_example['source']
+exact_solution = exact_solution_example['exact_solution']
+initial_condition = exact_solution_example['initial_condition']
+
+# Dictionary of dirichlet boundary conditions.
+dirichletBC = dict()
+# similarly to the outer boundary dictionary, if a patch has no outer boundary
+# None should be written instead of an expression.
+# This is a bit of a brainfuck:
+# dirichletBC[ind] gives a dictionary of the outer boundaries of subdomain ind.
+# Since a domain patch can have several disjoint outer boundary parts, the
+# expressions need to get an enumaration index which starts at 0.
+# So dirichletBC[ind][j] is the dictionary of outer dirichlet conditions of
+# subdomain ind and boundary part j.
+# Finally, dirichletBC[ind][j]['wetting'] and dirichletBC[ind][j]['nonwetting']
+# return the actual expression needed for the dirichlet condition for both
+# phases if present.
+
+# subdomain index: {outer boudary part index: {phase: expression}}
+for subdomain in isRichards.keys():
+    # if subdomain has no outer boundary, outer_boundary_def_points[subdomain]
+    # is None
+    if outer_boundary_def_points[subdomain] is None:
+        dirichletBC.update({subdomain: None})
+    else:
+        dirichletBC.update({subdomain: dict()})
+        # set the dirichlet conditions to be the same code as exact solution on
+        # the subdomain.
+        for outer_boundary_ind in outer_boundary_def_points[subdomain].keys():
+            dirichletBC[subdomain].update(
+                {outer_boundary_ind: exact_solution[subdomain]}
+                )
+
+
+# read this file and print it to std out. This way the simulation can produce a
+# log file with ./TP-R-layered_soil.py | tee simulation.log
+f = open(thisfile, 'r')
+print(f.read())
+f.close()
+
+
+for starttime in starttimes:
+    for mesh_resolution, solver_tol in resolutions.items():
+        # initialise LDD simulation class
+        simulation = ldd.LDDsimulation(
+            tol=1E-14,
+            LDDsolver_tol=solver_tol,
+            debug=debugflag,
+            max_iter_num=max_iter_num,
+            FEM_Lagrange_degree=FEM_Lagrange_degree,
+            mesh_study=mesh_study
+            )
+
+        simulation.set_parameters(
+            use_case=use_case,
+            output_dir=output_string,
+            subdomain_def_points=subdomain_def_points,
+            isRichards=isRichards,
+            interface_def_points=interface_def_points,
+            outer_boundary_def_points=outer_boundary_def_points,
+            adjacent_subdomains=adjacent_subdomains,
+            mesh_resolution=mesh_resolution,
+            viscosity=viscosity,
+            porosity=porosity,
+            L=L,
+            lambda_param=lambda_param,
+            relative_permeability=relative_permeability,
+            saturation=sat_pressure_relationship,
+            starttime=starttime,
+            number_of_timesteps=number_of_timesteps,
+            number_of_timesteps_to_analyse=number_of_timesteps_to_analyse,
+            plot_timestep_every=plot_timestep_every,
+            timestep_size=timestep_size,
+            sources=source_expression,
+            initial_conditions=initial_condition,
+            dirichletBC_expression_strings=dirichletBC,
+            exact_solution=exact_solution,
+            densities=densities,
+            include_gravity=include_gravity,
+            write2file=write_to_file,
+            )
+
+        simulation.initialise()
+        output_dir = simulation.output_dir
+        # simulation.write_exact_solution_to_xdmf()
+        output = simulation.run(analyse_condition=analyse_condition)
+        for subdomain_index, subdomain_output in output.items():
+            mesh_h = subdomain_output['mesh_size']
+            for phase, error_dict in subdomain_output['errornorm'].items():
+                filename = output_dir \
+                    + "subdomain{}".format(subdomain_index)\
+                    + "-space-time-errornorm-{}-phase.csv".format(phase)
+                # for errortype, errornorm in error_dict.items():
+
+                # eocfile = open("eoc_filename", "a")
+                # eocfile.write( str(mesh_h) + " " + str(errornorm) + "\n" )
+                # eocfile.close()
+                # if subdomain.isRichards:mesh_h
+                data_dict = {
+                    'mesh_parameter': mesh_resolution,
+                    'mesh_h': mesh_h,
+                }
+                for norm_type, errornorm in error_dict.items():
+                    data_dict.update(
+                        {norm_type: errornorm}
+                    )
+                errors = pd.DataFrame(data_dict, index=[mesh_resolution])
+                # check if file exists
+                if os.path.isfile(filename) is True:
+                    with open(filename, 'a') as f:
+                        errors.to_csv(
+                            f,
+                            header=False,
+                            sep='\t',
+                            encoding='utf-8',
+                            index=False
+                            )
+                else:
+                    errors.to_csv(
+                        filename,
+                        sep='\t',
+                        encoding='utf-8',
+                        index=False
+                        )
diff --git a/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/TP-R-layered_soil_with_inner_patch-realistic.py b/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/TP-R-layered_soil_with_inner_patch-realistic.py
new file mode 100755
index 0000000000000000000000000000000000000000..370f9c7507e802582d2e3cdf1af937655aabe284
--- /dev/null
+++ b/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/TP-R-layered_soil_with_inner_patch-realistic.py
@@ -0,0 +1,1003 @@
+#!/usr/bin/python3
+"""Layered soil simulation with inner patch.
+
+This program sets up an LDD simulation
+"""
+
+import dolfin as df
+# import mshr
+# import numpy as np
+import sympy as sym
+# import typing as tp
+import functools as ft
+# import domainPatch as dp
+import LDDsimulation as ldd
+import helpers as hlp
+import datetime
+import os
+import pandas as pd
+
+# check if output directory exists
+if not os.path.exists('./output'):
+    os.mkdir('./output')
+    print("Directory ", './output',  " created ")
+else:
+    print("Directory ", './output',  " already exists. Will use as output \
+    directory")
+
+
+# init sympy session
+sym.init_printing()
+# solver_tol = 6E-7
+use_case = "TP-R-layered-soil-with-inner-patch-realistic"
+# name of this very file. Needed for log output.
+thisfile = "TP-R-layered_soil_with_inner_patch.py"
+max_iter_num = 300
+FEM_Lagrange_degree = 1
+mesh_study = False
+resolutions = {
+                # 1: 2e-6,  # h=2
+                # 2: 2e-6,  # h=1.1180
+                # 4: 2e-6,  # h=0.5590
+                # 8: 2e-6,  # h=0.2814
+                16: 2e-6, # h=0.1412
+                # 32: 2e-6,
+                # 64: 2e-6,
+                # 128: 2e-6
+                }
+
+# GRID #######################
+# mesh_resolution = 20
+timestep_size = 0.001
+number_of_timesteps = 5
+plot_timestep_every = 1
+# decide how many timesteps you want analysed. Analysed means, that we write
+# out subsequent errors of the L-iteration within the timestep.
+number_of_timesteps_to_analyse = 5
+starttimes = [0.0]
+
+Lw1 = 0.025  # /timestep_size
+Lnw1 = Lw1
+
+Lw2 = 0.025  # /timestep_size
+Lnw2 = Lw2
+
+Lw3 = 0.025  # /timestep_size
+Lnw3 = Lw3
+
+Lw4 = 0.025  # /timestep_size
+Lnw4 = Lw4
+
+Lw5 = 0.025  # /timestep_size
+Lnw5 = Lw5
+
+Lw6 = 0.025  # /timestep_size
+Lnw6 = Lw6
+
+lambda12_w = 40
+lambda12_nw = 40
+
+lambda23_w = 40
+lambda23_nw = 40
+
+lambda24_w = 40
+lambda24_nw= 40
+
+lambda25_w= 40
+lambda25_nw= 40
+
+lambda34_w = 40
+lambda34_nw = 40
+
+lambda36_w = 40
+lambda36_nw = 40
+
+lambda45_w = 40
+lambda45_nw = 40
+
+lambda46_w = 40
+lambda46_nw = 40
+
+lambda56_w = 40
+lambda56_nw = 40
+
+include_gravity = False
+debugflag = True
+analyse_condition = True
+
+if mesh_study:
+    output_string = "./output/{}-{}_timesteps{}_P{}".format(
+        datestr, use_case, number_of_timesteps, FEM_Lagrange_degree
+        )
+else:
+    for tol in resolutions.values():
+        solver_tol = tol
+    output_string = "./output/{}-{}_timesteps{}_P{}_solver_tol{}".format(
+        datestr, use_case, number_of_timesteps, FEM_Lagrange_degree, solver_tol
+        )
+
+
+# toggle what should be written to files
+if mesh_study:
+    write_to_file = {
+        'space_errornorms': True,
+        'meshes_and_markers': True,
+        'L_iterations_per_timestep': False,
+        'solutions': True,
+        'absolute_differences': True,
+        'condition_numbers': analyse_condition,
+        'subsequent_errors': True
+    }
+else:
+    write_to_file = {
+        'space_errornorms': True,
+        'meshes_and_markers': True,
+        'L_iterations_per_timestep': False,
+        'solutions': True,
+        'absolute_differences': True,
+        'condition_numbers': analyse_condition,
+        'subsequent_errors': True
+    }
+
+
+# global domain
+subdomain0_vertices = [df.Point(-1.0,-1.0), #
+                        df.Point(1.0,-1.0),#
+                        df.Point(1.0,1.0),#
+                        df.Point(-1.0,1.0)]
+
+interface12_vertices = [df.Point(-1.0, 0.8),
+                        df.Point(0.3, 0.8),
+                        df.Point(0.5, 0.9),
+                        df.Point(0.8, 0.7),
+                        df.Point(1.0, 0.65)]
+
+
+                        # interface23
+interface23_vertices = [df.Point(-1.0, 0.0),
+                        df.Point(-0.35, 0.0),
+                        # df.Point(6.5, 4.5),
+                        df.Point(0.0, 0.0)]
+
+interface24_vertices = [interface23_vertices[2],
+                        df.Point(0.6, 0.0),
+                        ]
+
+interface25_vertices = [interface24_vertices[1],
+                        df.Point(1.0, 0.0)
+                        ]
+
+
+interface32_vertices = [interface23_vertices[2],
+                        interface23_vertices[1],
+                        interface23_vertices[0]]
+
+
+interface36_vertices = [df.Point(-1.0, -0.6),
+                        df.Point(-0.6, -0.45)]
+
+
+interface46_vertices = [interface36_vertices[1],
+                        df.Point(0.3, -0.25)]
+
+interface56_vertices = [interface46_vertices[1],
+                        df.Point(0.65, -0.6),
+                        df.Point(1.0, -0.7)]
+
+
+
+
+interface34_vertices = [interface36_vertices[1],
+                        interface23_vertices[2]]
+# interface36
+
+interface45_vertices = [interface56_vertices[0],
+                        df.Point(0.7, -0.2),
+                        interface25_vertices[0]
+                        ]
+
+
+# interface_vertices introduces a global numbering of interfaces.
+interface_def_points = [interface12_vertices,
+                        interface23_vertices,
+                        interface24_vertices,
+                        interface25_vertices,
+                        interface34_vertices,
+                        interface36_vertices,
+                        interface45_vertices,
+                        interface46_vertices,
+                        interface56_vertices,
+                        ]
+
+adjacent_subdomains = [[1,2],
+                       [2,3],
+                       [2,4],
+                       [2,5],
+                       [3,4],
+                       [3,6],
+                       [4,5],
+                       [4,6],
+                       [5,6]
+                       ]
+
+# subdomain1.
+subdomain1_vertices = [interface12_vertices[0],
+                        interface12_vertices[1],
+                        interface12_vertices[2],
+                        interface12_vertices[3],
+                        interface12_vertices[4],  # southern boundary, 12 interface
+                        subdomain0_vertices[2],  # eastern boundary, outer boundary
+                        subdomain0_vertices[3]]  # northern boundary, outer on_boundary
+
+# vertex coordinates of the outer boundaries. If it can not be specified as a
+# polygon, use an entry per boundary polygon.
+# This information is used for defining
+# the Dirichlet boundary conditions. If a domain is completely internal, the
+# dictionary entry should be 0: None
+subdomain1_outer_boundary_verts = {
+    0: [subdomain1_vertices[4],
+        subdomain1_vertices[5],  # eastern boundary, outer boundary
+        subdomain1_vertices[6],
+        subdomain1_vertices[0]]
+}
+
+#subdomain1
+subdomain2_vertices = [interface23_vertices[0],
+                        interface23_vertices[1],
+                        interface23_vertices[2],
+                        interface24_vertices[1],
+                        interface25_vertices[1],  # southern boundary, 23 interface
+                        subdomain1_vertices[4],  # eastern boundary, outer boundary
+                        subdomain1_vertices[3],
+                        subdomain1_vertices[2],
+                        subdomain1_vertices[1],
+                        subdomain1_vertices[0] ]  # northern boundary, 12 interface
+
+subdomain2_outer_boundary_verts = {
+    0: [subdomain2_vertices[9],
+        subdomain2_vertices[0]],
+    1: [subdomain2_vertices[4],
+        subdomain2_vertices[5]]
+}
+
+
+subdomain3_vertices = [interface36_vertices[0],
+                       interface36_vertices[1],
+                       # interface34_vertices[0],
+                       interface34_vertices[1],
+                       # interface32_vertices[0],
+                       interface32_vertices[1],
+                       interface32_vertices[2]
+                       ]
+
+subdomain3_outer_boundary_verts = {
+    0: [subdomain3_vertices[4],
+        subdomain3_vertices[0]]
+}
+
+
+# subdomain3
+subdomain4_vertices = [interface46_vertices[0],
+                       interface46_vertices[1],
+                       interface45_vertices[1],
+                       interface24_vertices[1],
+                       interface24_vertices[0],
+                       interface34_vertices[1]
+                       ]
+
+subdomain4_outer_boundary_verts = None
+
+subdomain5_vertices = [interface56_vertices[0],
+                       interface56_vertices[1],
+                       interface56_vertices[2],
+                       interface25_vertices[1],
+                       interface25_vertices[0],
+                       interface45_vertices[1],
+                       interface45_vertices[0]
+]
+
+subdomain5_outer_boundary_verts = {
+    0: [subdomain5_vertices[2],
+        subdomain5_vertices[3]]
+}
+
+
+
+subdomain6_vertices = [subdomain0_vertices[0],
+                       subdomain0_vertices[1], # southern boundary, outer boundary
+                       interface56_vertices[2],
+                       interface56_vertices[1],
+                       interface56_vertices[0],
+                       interface36_vertices[1],
+                       interface36_vertices[0]
+                       ]
+
+subdomain6_outer_boundary_verts = {
+    0: [subdomain6_vertices[6],
+        subdomain6_vertices[0],
+        subdomain6_vertices[1],
+        subdomain6_vertices[2]]
+}
+
+
+subdomain_def_points = [subdomain0_vertices,#
+                      subdomain1_vertices,#
+                      subdomain2_vertices,#
+                      subdomain3_vertices,#
+                      subdomain4_vertices,
+                      subdomain5_vertices,
+                      subdomain6_vertices
+                      ]
+
+
+# if a subdomain has no outer boundary write None instead, i.e.
+# i: None
+# if i is the index of the inner subdomain.
+outer_boundary_def_points = {
+    # subdomain number
+    1: subdomain1_outer_boundary_verts,
+    2: subdomain2_outer_boundary_verts,
+    3: subdomain3_outer_boundary_verts,
+    4: subdomain4_outer_boundary_verts,
+    5: subdomain5_outer_boundary_verts,
+    6: subdomain6_outer_boundary_verts
+}
+
+
+isRichards = {
+    1: True,
+    2: True,
+    3: False,
+    4: False,
+    5: False,
+    6: False
+    }
+
+# isRichards = {
+#     1: True,
+#     2: True,
+#     3: True,
+#     4: True,
+#     5: True,
+#     6: True
+#     }
+
+# Dict of the form: { subdom_num : viscosity }
+viscosity = {
+    1: {'wetting' :1,
+         'nonwetting': 1/50},
+    2: {'wetting' :1,
+         'nonwetting': 1/50},
+    3: {'wetting' :1,
+         'nonwetting': 1/50},
+    4: {'wetting' :1,
+         'nonwetting': 1/50},
+    5: {'wetting' :1,
+         'nonwetting': 1/50},
+    6: {'wetting' :1,
+         'nonwetting': 1/50},
+}
+
+# Dict of the form: { subdom_num : density }
+densities = {
+    1: {'wetting': 1,  #997
+         'nonwetting': 1},  #1},  #1.225},
+    2: {'wetting': 1,  #997
+         'nonwetting': 1},  #1.225},
+    3: {'wetting': 1,  #997
+         'nonwetting': 1},  #1.225},
+    4: {'wetting': 1,  #997
+         'nonwetting': 1},  #1.225}
+    5: {'wetting': 1,  #997
+         'nonwetting': 1},  #1.225},
+    6: {'wetting': 1,  #997
+         'nonwetting': 1}  #1.225}
+}
+
+gravity_acceleration = 9.81
+# porosities taken from
+# https://www.geotechdata.info/parameter/soil-porosity.html
+# Dict of the form: { subdom_num : porosity }
+porosity = {
+    1: 1,  #0.2,  # Clayey gravels, clayey sandy gravels
+    2: 1,  #0.22, # Silty gravels, silty sandy gravels
+    3: 1,  #0.37, # Clayey sands
+    4: 1,  #0.2 # Silty or sandy clay
+    5: 1,  #
+    6: 1,  #
+}
+
+# subdom_num : subdomain L for L-scheme
+L = {
+    1: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    2: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    3: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    4: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    5: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    6: {'wetting' :Lw,
+         'nonwetting': Lnw}
+}
+
+
+# interface_num : lambda parameter for the L-scheme on that interface.
+# Note that interfaces are numbered starting from 0, because
+# adjacent_subdomains is a list and not a dict. Historic fuckup, I know
+# We have defined above as interfaces
+# # interface_vertices introduces a global numbering of interfaces.
+# interface_def_points = [interface12_vertices,
+#                         interface23_vertices,
+#                         interface24_vertices,
+#                         interface25_vertices,
+#                         interface34_vertices,
+#                         interface36_vertices,
+#                         interface45_vertices,
+#                         interface46_vertices,
+#                         interface56_vertices,
+#                         ]
+lambda_param = {
+    0: {'wetting': lambda12_w,
+         'nonwetting': lambda12_nw},#
+    1: {'wetting': lambda23_w,
+         'nonwetting': lambda23_nw},#
+    2: {'wetting': lambda24_w,
+         'nonwetting': lambda24_nw},#
+    3: {'wetting': lambda25_w,
+         'nonwetting': lambda25_nw},#
+    4: {'wetting': lambda34_w,
+         'nonwetting': lambda34_nw},#
+    5: {'wetting': lambda36_w,
+         'nonwetting': lambda36_nw},#
+    6: {'wetting': lambda45_w,
+         'nonwetting': lambda45_nw},#
+    7: {'wetting': lambda46_w,
+         'nonwetting': lambda46_nw},#
+    8: {'wetting': lambda56_w,
+         'nonwetting': lambda56_nw},#
+}
+
+
+# after Lewis, see pdf file
+intrinsic_permeability = {
+    1: 0.1,  # sand
+    2: 0.1,  # sand, there is a range
+    3: 0.001,  #10e-2,  # clay has a range
+    4: 0.001,  #10e-3
+    5: 0.001,  #10e-2,  # clay has a range
+    6: 0.001,  #10e-3
+}
+
+
+# relative permeabilty functions on subdomain 1
+def rel_perm1w(s):
+    # relative permeabilty wetting on subdomain1
+    return intrinsic_permeability[1]*s**2
+
+
+def rel_perm1nw(s):
+    # relative permeabilty nonwetting on subdomain1
+    return intrinsic_permeability[1]*(1-s)**2
+
+
+# relative permeabilty functions on subdomain 2
+def rel_perm2w(s):
+    # relative permeabilty wetting on subdomain2
+    return intrinsic_permeability[2]*s**2
+
+
+def rel_perm2nw(s):
+    # relative permeabilty nonwetting on subdomain2
+    return intrinsic_permeability[2]*(1-s)**2
+
+
+# relative permeabilty functions on subdomain 3
+def rel_perm3w(s):
+    # relative permeabilty wetting on subdomain3
+    return intrinsic_permeability[3]*s**3
+
+
+def rel_perm3nw(s):
+    # relative permeabilty nonwetting on subdomain3
+    return intrinsic_permeability[3]*(1-s)**3
+
+
+# relative permeabilty functions on subdomain 4
+def rel_perm4w(s):
+    # relative permeabilty wetting on subdomain4
+    return intrinsic_permeability[4]*s**3
+
+
+def rel_perm4nw(s):
+    # relative permeabilty nonwetting on subdomain4
+    return intrinsic_permeability[4]*(1-s)**3
+
+
+# relative permeabilty functions on subdomain 5
+def rel_perm5w(s):
+    # relative permeabilty wetting on subdomain5
+    return intrinsic_permeability[5]*s**3
+
+
+def rel_perm5nw(s):
+    # relative permeabilty nonwetting on subdomain5
+    return intrinsic_permeability[5]*(1-s)**3
+
+
+# relative permeabilty functions on subdomain 6
+def rel_perm6w(s):
+    # relative permeabilty wetting on subdomain6
+    return intrinsic_permeability[6]*s**3
+
+
+def rel_perm6nw(s):
+    # relative permeabilty nonwetting on subdomain6
+    return intrinsic_permeability[6]*(1-s)**3
+
+
+_rel_perm1w = ft.partial(rel_perm1w)
+_rel_perm1nw = ft.partial(rel_perm1nw)
+
+_rel_perm2w = ft.partial(rel_perm2w)
+_rel_perm2nw = ft.partial(rel_perm2nw)
+
+_rel_perm3w = ft.partial(rel_perm3w)
+_rel_perm3nw = ft.partial(rel_perm3nw)
+
+_rel_perm4w = ft.partial(rel_perm4w)
+_rel_perm4nw = ft.partial(rel_perm4nw)
+
+_rel_perm5w = ft.partial(rel_perm5w)
+_rel_perm5nw = ft.partial(rel_perm5nw)
+
+_rel_perm6w = ft.partial(rel_perm6w)
+_rel_perm6nw = ft.partial(rel_perm6nw)
+
+subdomain1_rel_perm = {
+    'wetting': _rel_perm1w,
+    'nonwetting': _rel_perm1nw
+}
+
+subdomain2_rel_perm = {
+    'wetting': _rel_perm2w,
+    'nonwetting': _rel_perm2nw
+}
+
+subdomain3_rel_perm = {
+    'wetting': _rel_perm3w,
+    'nonwetting': _rel_perm3nw
+}
+
+subdomain4_rel_perm = {
+    'wetting': _rel_perm4w,
+    'nonwetting': _rel_perm4nw
+}
+
+subdomain5_rel_perm = {
+    'wetting': _rel_perm5w,
+    'nonwetting': _rel_perm5nw
+}
+
+subdomain6_rel_perm = {
+    'wetting': _rel_perm6w,
+    'nonwetting': _rel_perm6nw
+}
+
+# dictionary of relative permeabilties on all domains.
+relative_permeability = {
+    1: subdomain1_rel_perm,
+    2: subdomain2_rel_perm,
+    3: subdomain3_rel_perm,
+    4: subdomain4_rel_perm,
+    5: subdomain5_rel_perm,
+    6: subdomain6_rel_perm
+}
+
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 1
+def rel_perm1w_prime(s):
+    # relative permeabilty on subdomain1
+    return intrinsic_permeability[1]*2*s
+
+
+def rel_perm1nw_prime(s):
+    # relative permeabilty on subdomain1
+    return -1*intrinsic_permeability[1]*2*(1-s)
+
+
+def rel_perm2w_prime(s):
+    # relative permeabilty on subdomain2
+    return intrinsic_permeability[2]*2*s
+
+
+def rel_perm2nw_prime(s):
+    # relative permeabilty on subdomain2
+    return -1*intrinsic_permeability[2]*2*(1-s)
+
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 3
+def rel_perm3w_prime(s):
+    # relative permeabilty on subdomain3
+    return intrinsic_permeability[3]*3*s**2
+
+
+def rel_perm3nw_prime(s):
+    # relative permeabilty on subdomain3
+    return -1*intrinsic_permeability[3]*3*(1-s)**2
+
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 4
+def rel_perm4w_prime(s):
+    # relative permeabilty on subdomain4
+    return intrinsic_permeability[4]*3*s**2
+
+
+def rel_perm4nw_prime(s):
+    # relative permeabilty on subdomain4
+    return -1*intrinsic_permeability[4]*3*(1-s)**2
+
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 5
+def rel_perm5w_prime(s):
+    # relative permeabilty on subdomain5
+    return intrinsic_permeability[5]*3*s**2
+
+
+def rel_perm5nw_prime(s):
+    # relative permeabilty on subdomain5
+    return -1*intrinsic_permeability[5]*3*(1-s)**2
+
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 6
+def rel_perm6w_prime(s):
+    # relative permeabilty on subdomain6
+    return intrinsic_permeability[6]*3*s**2
+
+
+def rel_perm6nw_prime(s):
+    # relative permeabilty on subdomain6
+    return -1*intrinsic_permeability[6]*3*(1-s)**2
+
+
+_rel_perm1w_prime = ft.partial(rel_perm1w_prime)
+_rel_perm1nw_prime = ft.partial(rel_perm1nw_prime)
+_rel_perm2w_prime = ft.partial(rel_perm2w_prime)
+_rel_perm2nw_prime = ft.partial(rel_perm2nw_prime)
+_rel_perm3w_prime = ft.partial(rel_perm3w_prime)
+_rel_perm3nw_prime = ft.partial(rel_perm3nw_prime)
+_rel_perm4w_prime = ft.partial(rel_perm4w_prime)
+_rel_perm4nw_prime = ft.partial(rel_perm4nw_prime)
+_rel_perm5w_prime = ft.partial(rel_perm5w_prime)
+_rel_perm5nw_prime = ft.partial(rel_perm5nw_prime)
+_rel_perm6w_prime = ft.partial(rel_perm6w_prime)
+_rel_perm6nw_prime = ft.partial(rel_perm6nw_prime)
+
+subdomain1_rel_perm_prime = {
+    'wetting': _rel_perm1w_prime,
+    'nonwetting': _rel_perm1nw_prime
+}
+
+
+subdomain2_rel_perm_prime = {
+    'wetting': _rel_perm2w_prime,
+    'nonwetting': _rel_perm2nw_prime
+}
+
+subdomain3_rel_perm_prime = {
+    'wetting': _rel_perm3w_prime,
+    'nonwetting': _rel_perm3nw_prime
+}
+
+
+subdomain4_rel_perm_prime = {
+    'wetting': _rel_perm4w_prime,
+    'nonwetting': _rel_perm4nw_prime
+}
+
+subdomain5_rel_perm_prime = {
+    'wetting': _rel_perm5w_prime,
+    'nonwetting': _rel_perm5nw_prime
+}
+
+subdomain6_rel_perm_prime = {
+    'wetting': _rel_perm6w_prime,
+    'nonwetting': _rel_perm6nw_prime
+}
+
+
+# dictionary of relative permeabilties on all domains.
+ka_prime = {
+    1: subdomain1_rel_perm_prime,
+    2: subdomain2_rel_perm_prime,
+    3: subdomain3_rel_perm_prime,
+    4: subdomain4_rel_perm_prime,
+    5: subdomain5_rel_perm_prime,
+    6: subdomain6_rel_perm_prime,
+}
+
+
+
+# S-pc-relation ship. We use the van Genuchten approach, i.e.
+# pc = 1/alpha*(S^{-1/m} -1)^1/n, where we set alpha = 0, assume
+# m = 1-1/n (see Helmig) and assume that residual saturation is Sw
+# this function needs to be monotonically decreasing in the capillary pressure
+# pc.
+# Since in the richards case pc=-pw, this becomes as a function of pw a mono
+# tonically INCREASING function like in our Richards-Richards paper. However
+# since we unify the treatment in the code for Richards and two-phase, we need
+# the same requierment
+# for both cases, two-phase and Richards.
+# def saturation(pc, n_index, alpha):
+#     # inverse capillary pressure-saturation-relationship
+#     return df.conditional(pc > 0, 1/((1 + (alpha*pc)**n_index)**((n_index - 1)/n_index)), 1)
+#
+# # S-pc-relation ship. We use the van Genuchten approach, i.e. pc = 1/alpha*(S^{-1/m} -1)^1/n, where
+# # we set alpha = 0, assume m = 1-1/n (see Helmig) and assume that residual saturation is Sw
+# def saturation_sym(pc, n_index, alpha):
+#     # inverse capillary pressure-saturation-relationship
+#     #df.conditional(pc > 0,
+#     return 1/((1 + (alpha*pc)**n_index)**((n_index - 1)/n_index))
+#
+#
+# # derivative of S-pc relationship with respect to pc. This is needed for the
+# # construction of a analytic solution.
+# def saturation_sym_prime(pc, n_index, alpha):
+#     # inverse capillary pressure-saturation-relationship
+#     return -(alpha*(n_index - 1)*(alpha*pc)**(n_index - 1)) / ( (1 + (alpha*pc)**n_index)**((2*n_index - 1)/n_index) )
+##
+# # note that the conditional definition of S-pc in the nonsymbolic part will be
+# # incorporated in the construction of the exact solution below.
+# S_pc_sym = {
+#     1: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     2: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     3: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     4: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     5: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     6: ft.partial(saturation_sym, n_index=3, alpha=0.001)
+# }
+#
+# S_pc_sym_prime = {
+#     1: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     2: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     3: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     4: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     5: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     6: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001)
+# }
+#
+# sat_pressure_relationship = {
+#     1: ft.partial(saturation, n_index=3, alpha=0.001),
+#     2: ft.partial(saturation, n_index=3, alpha=0.001),
+#     3: ft.partial(saturation, n_index=3, alpha=0.001),
+#     4: ft.partial(saturation, n_index=3, alpha=0.001),
+#     5: ft.partial(saturation, n_index=3, alpha=0.001),
+#     6: ft.partial(saturation, n_index=3, alpha=0.001)
+# }
+
+def saturation(pc, n_index):
+    # inverse capillary pressure-saturation-relationship
+    return df.conditional(pc > 0, 1/((1 + pc)**(1/(n_index + 1))), 1)
+
+
+def saturation_sym(pc, n_index):
+    # inverse capillary pressure-saturation-relationship
+    return 1/((1 + pc)**(1/(n_index + 1)))
+
+
+def saturation_sym_prime(pc, n_index):
+    # inverse capillary pressure-saturation-relationship
+    return -1/((n_index+1)*(1 + pc)**((n_index+2)/(n_index+1)))
+
+
+S_pc_sym = {
+    1: ft.partial(saturation_sym, n_index=1),
+    2: ft.partial(saturation_sym, n_index=1),
+    3: ft.partial(saturation_sym, n_index=2),
+    4: ft.partial(saturation_sym, n_index=2),
+    5: ft.partial(saturation_sym, n_index=2),
+    6: ft.partial(saturation_sym, n_index=2)
+}
+
+S_pc_sym_prime = {
+    1: ft.partial(saturation_sym_prime, n_index=1),
+    2: ft.partial(saturation_sym_prime, n_index=1),
+    3: ft.partial(saturation_sym_prime, n_index=2),
+    4: ft.partial(saturation_sym_prime, n_index=2),
+    5: ft.partial(saturation_sym_prime, n_index=2),
+    6: ft.partial(saturation_sym_prime, n_index=2)
+}
+
+sat_pressure_relationship = {
+    1: ft.partial(saturation, n_index=1),
+    2: ft.partial(saturation, n_index=1),
+    3: ft.partial(saturation, n_index=2),
+    4: ft.partial(saturation, n_index=2),
+    5: ft.partial(saturation, n_index=2),
+    6: ft.partial(saturation, n_index=2)
+}
+
+#############################################
+# Manufacture source expressions with sympy #
+#############################################
+x, y = sym.symbols('x[0], x[1]')  # needed by UFL
+t = sym.symbols('t', positive=True)
+
+
+p_e_sym = {
+    1: {'wetting': -5.0 - (1.0 + t*t)*(1.0 + x*x + y*y),
+        'nonwetting': (-1 -t*(1.1 + y + x**2)) },
+    2: {'wetting': -5.0 - (1.0 + t*t)*(1.0 + x*x + y*y),
+        'nonwetting': (-1 -t*(1.1 + y + x**2)) },
+    3: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
+    4: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
+    5: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
+    6: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
+}
+
+pc_e_sym = dict()
+for subdomain, isR in isRichards.items():
+    if isR:
+        pc_e_sym.update({subdomain: -p_e_sym[subdomain]['wetting']})
+    else:
+        pc_e_sym.update(
+            {subdomain: p_e_sym[subdomain]['nonwetting']
+                - p_e_sym[subdomain]['wetting']}
+            )
+
+
+symbols = {"x": x,
+           "y": y,
+           "t": t}
+# turn above symbolic code into exact solution for dolphin and
+# construct the rhs that matches the above exact solution.
+exact_solution_example = hlp.generate_exact_solution_expressions(
+                        symbols=symbols,
+                        isRichards=isRichards,
+                        symbolic_pressure=p_e_sym,
+                        symbolic_capillary_pressure=pc_e_sym,
+                        saturation_pressure_relationship=S_pc_sym,
+                        saturation_pressure_relationship_prime=S_pc_sym_prime,
+                        viscosity=viscosity,
+                        porosity=porosity,
+                        relative_permeability=relative_permeability,
+                        relative_permeability_prime=ka_prime,
+                        densities=densities,
+                        gravity_acceleration=gravity_acceleration,
+                        include_gravity=include_gravity,
+                        )
+source_expression = exact_solution_example['source']
+exact_solution = exact_solution_example['exact_solution']
+initial_condition = exact_solution_example['initial_condition']
+
+# Dictionary of dirichlet boundary conditions.
+dirichletBC = dict()
+# similarly to the outer boundary dictionary, if a patch has no outer boundary
+# None should be written instead of an expression.
+# This is a bit of a brainfuck:
+# dirichletBC[ind] gives a dictionary of the outer boundaries of subdomain ind.
+# Since a domain patch can have several disjoint outer boundary parts, the
+# expressions need to get an enumaration index which starts at 0.
+# So dirichletBC[ind][j] is the dictionary of outer dirichlet conditions of
+# subdomain ind and boundary part j.
+# Finally, dirichletBC[ind][j]['wetting'] and dirichletBC[ind][j]['nonwetting']
+# return the actual expression needed for the dirichlet condition for both
+# phases if present.
+
+# subdomain index: {outer boudary part index: {phase: expression}}
+for subdomain in isRichards.keys():
+    # if subdomain has no outer boundary, outer_boundary_def_points[subdomain]
+    # is None
+    if outer_boundary_def_points[subdomain] is None:
+        dirichletBC.update({subdomain: None})
+    else:
+        dirichletBC.update({subdomain: dict()})
+        # set the dirichlet conditions to be the same code as exact solution on
+        # the subdomain.
+        for outer_boundary_ind in outer_boundary_def_points[subdomain].keys():
+            dirichletBC[subdomain].update(
+                {outer_boundary_ind: exact_solution[subdomain]}
+                )
+
+
+# read this file and print it to std out. This way the simulation can produce a
+# log file with ./TP-R-layered_soil.py | tee simulation.log
+f = open(thisfile, 'r')
+print(f.read())
+f.close()
+
+
+for starttime in starttimes:
+    for mesh_resolution, solver_tol in resolutions.items():
+        # initialise LDD simulation class
+        simulation = ldd.LDDsimulation(
+            tol=1E-14,
+            LDDsolver_tol=solver_tol,
+            debug=debugflag,
+            max_iter_num=max_iter_num,
+            FEM_Lagrange_degree=FEM_Lagrange_degree,
+            mesh_study=mesh_study
+            )
+
+        simulation.set_parameters(
+            use_case=use_case,
+            output_dir=output_string,
+            subdomain_def_points=subdomain_def_points,
+            isRichards=isRichards,
+            interface_def_points=interface_def_points,
+            outer_boundary_def_points=outer_boundary_def_points,
+            adjacent_subdomains=adjacent_subdomains,
+            mesh_resolution=mesh_resolution,
+            viscosity=viscosity,
+            porosity=porosity,
+            L=L,
+            lambda_param=lambda_param,
+            relative_permeability=relative_permeability,
+            saturation=sat_pressure_relationship,
+            starttime=starttime,
+            number_of_timesteps=number_of_timesteps,
+            number_of_timesteps_to_analyse=number_of_timesteps_to_analyse,
+            plot_timestep_every=plot_timestep_every,
+            timestep_size=timestep_size,
+            sources=source_expression,
+            initial_conditions=initial_condition,
+            dirichletBC_expression_strings=dirichletBC,
+            exact_solution=exact_solution,
+            densities=densities,
+            include_gravity=include_gravity,
+            write2file=write_to_file,
+            )
+
+        simulation.initialise()
+        output_dir = simulation.output_dir
+        # simulation.write_exact_solution_to_xdmf()
+        output = simulation.run(analyse_condition=analyse_condition)
+        for subdomain_index, subdomain_output in output.items():
+            mesh_h = subdomain_output['mesh_size']
+            for phase, error_dict in subdomain_output['errornorm'].items():
+                filename = output_dir \
+                    + "subdomain{}".format(subdomain_index)\
+                    + "-space-time-errornorm-{}-phase.csv".format(phase)
+                # for errortype, errornorm in error_dict.items():
+
+                # eocfile = open("eoc_filename", "a")
+                # eocfile.write( str(mesh_h) + " " + str(errornorm) + "\n" )
+                # eocfile.close()
+                # if subdomain.isRichards:mesh_h
+                data_dict = {
+                    'mesh_parameter': mesh_resolution,
+                    'mesh_h': mesh_h,
+                }
+                for norm_type, errornorm in error_dict.items():
+                    data_dict.update(
+                        {norm_type: errornorm}
+                    )
+                errors = pd.DataFrame(data_dict, index=[mesh_resolution])
+                # check if file exists
+                if os.path.isfile(filename) is True:
+                    with open(filename, 'a') as f:
+                        errors.to_csv(
+                            f,
+                            header=False,
+                            sep='\t',
+                            encoding='utf-8',
+                            index=False
+                            )
+                else:
+                    errors.to_csv(
+                        filename,
+                        sep='\t',
+                        encoding='utf-8',
+                        index=False
+                        )
diff --git a/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/run-simulation b/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/run-simulation
new file mode 100755
index 0000000000000000000000000000000000000000..0eb497502a082a0fec07a5449b1fe946d59c8cc7
--- /dev/null
+++ b/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/run-simulation
@@ -0,0 +1,16 @@
+#!/bin/bash
+
+[ $# -eq 0 ] && { echo "Usage: $0 simulation_file [logfile_name]"; exit 1; }
+
+SIMULATION_FILE=$1
+SIMULATION=${SIMULATION_FILE%.py}
+LOGFILE_DEFAULT="$SIMULATION.log"
+
+DATE=$(date -I)
+LOGFILE=${2:-$DATE-$LOGFILE_DEFAULT}
+
+GREETING="Simulation $SIMULATION is run on $DATE by $USER"
+
+echo $GREETING
+echo "running $SIMULATION_FILE | tee $LOGFILE"
+./$SIMULATION_FILE | tee $LOGFILE