From 5e2743706c8246750e07ccdd4536e91bcc380fc5 Mon Sep 17 00:00:00 2001
From: David Seus <david.seus@ians.uni-stuttgart.de>
Date: Wed, 24 Jun 2020 20:58:40 +0200
Subject: [PATCH] add parallelisationtest

---
 ...ith_inner_patch-realistic_parallel_test.py | 1134 +++++++++++++++++
 1 file changed, 1134 insertions(+)
 create mode 100755 Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/TP-R-layered_soil_with_inner_patch-realistic_parallel_test.py

diff --git a/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/TP-R-layered_soil_with_inner_patch-realistic_parallel_test.py b/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/TP-R-layered_soil_with_inner_patch-realistic_parallel_test.py
new file mode 100755
index 0000000..e0047b6
--- /dev/null
+++ b/Two-phase-Richards/multi-patch/layered_soil_with_inner_patch/TP-R-layered_soil_with_inner_patch-realistic_parallel_test.py
@@ -0,0 +1,1134 @@
+#!/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
+import multiprocessing as mp
+
+
+# init sympy session
+sym.init_printing()
+
+# PREREQUISITS  ###############################################################
+# check if output directory "./output" exists. This will be used in
+# the generation of the output string.
+if not os.path.exists('./output'):
+    os.mkdir('./output')
+    print("Directory ", './output',  " created ")
+else:
+    print("Directory ", './output',  " already exists. Will use as output \
+    directory")
+
+date = datetime.datetime.now()
+datestr = date.strftime("%Y-%m-%d")
+
+# Name of the usecase that will be printed during simulation.
+use_case = "TP-R-layered-soil-with-inner-patch-realistic-split-interface45"
+# The name of this very file. Needed for creating log output.
+thisfile = "TP-R-layered_soil_with_inner_patch-realistic.py"
+
+# GENERAL SOLVER CONFIG  ######################################################
+# maximal iteration per timestep
+max_iter_num = 1
+FEM_Lagrange_degree = 1
+
+# GRID AND MESH STUDY SPECIFICATIONS  #########################################
+mesh_study = True
+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: 8e-6, # h=0.1412
+                # 32: 5e-6,
+                # 64: 2e-6,
+                # 128: 2e-6
+                }
+
+# starttimes gives a list of starttimes to run the simulation from.
+# The list is looped over and a simulation is run with t_0 as initial time
+#  for each element t_0 in starttimes.
+starttimes = [0.0]
+timestep_size = 0.001
+number_of_timesteps = 1
+
+# LDD scheme parameters  ######################################################
+
+Lw1 = 0.5  # /timestep_size
+Lnw1 = Lw1
+
+Lw2 = 0.5  # /timestep_size
+Lnw2 = Lw2
+
+Lw3 = 0.5  # /timestep_size
+Lnw3 = Lw3
+
+Lw4 = 0.5  # /timestep_size
+Lnw4 = Lw4
+
+Lw5 = 0.5  # /timestep_size
+Lnw5 = Lw5
+
+Lw6 = 0.5  # /timestep_size
+Lnw6 = Lw6
+
+lambda12_w = 4
+lambda12_nw = 4
+
+lambda23_w = 4
+lambda23_nw = 4
+
+lambda24_w = 4
+lambda24_nw= 4
+
+lambda25_w= 4
+lambda25_nw= 4
+
+lambda34_w = 4
+lambda34_nw = 4
+
+lambda36_w = 4
+lambda36_nw = 4
+
+lambda45_w = 4
+lambda45_nw = 4
+
+lambda46_w = 4
+lambda46_nw = 4
+
+lambda56_w = 4
+lambda56_nw = 4
+
+include_gravity = True
+debugflag = True
+analyse_condition = False
+
+# I/O CONFIG  #################################################################
+# when number_of_timesteps is high, it might take a long time to write all
+# timesteps to disk. Therefore, you can choose to only write data of every
+# plot_timestep_every timestep to disk.
+plot_timestep_every = 1
+# Decide how many timesteps you want analysed. Analysed means, that
+# subsequent errors of the L-iteration within the timestep are written out.
+number_of_timesteps_to_analyse = 1
+
+# fine grained control over data to be written to disk in the mesh study case
+# as well as for a regular simuation for a fixed grid.
+if mesh_study:
+    write_to_file = {
+        # output the relative errornorm (integration in space) w.r.t. an exact
+        # solution for each timestep into a csv file.
+        'space_errornorms': True,
+        # save the mesh and marker functions to disk
+        'meshes_and_markers': True,
+        # save xdmf/h5 data for each LDD iteration for timesteps determined by
+        # number_of_timesteps_to_analyse. I/O intensive!
+        'L_iterations_per_timestep': False,
+        # save solution to xdmf/h5.
+        'solutions': True,
+        # save absolute differences w.r.t an exact solution to xdmf/h5 file
+        # to monitor where on the domains errors happen
+        'absolute_differences': True,
+        # analyise condition numbers for timesteps determined by
+        # number_of_timesteps_to_analyse and save them over time to csv.
+        'condition_numbers': analyse_condition,
+        # output subsequent iteration errors measured in L^2  to csv for
+        # timesteps determined by number_of_timesteps_to_analyse.
+        # Usefull to monitor convergence of the acutal LDD solver.
+        '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
+    }
+
+# OUTPUT FILE STRING  #########################################################
+output_string = "./output/{}-{}_timesteps{}_P{}".format(
+    datestr, use_case, number_of_timesteps, FEM_Lagrange_degree
+    )
+
+
+# DOMAIN AND INTERFACES  #######################################################
+# 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]]
+
+# Interface 45 needs to be split, because of the shape. There can be triangles
+# with two facets on the interface and this creates a rogue dof type error when
+# integrating over that particular interface. Accordingly, the lambda_param
+# dictionary has two entries for that interface.
+interface45_vertices_a = [interface56_vertices[0],
+                        df.Point(0.7, -0.2),#df.Point(0.7, -0.2),
+                        ]
+interface45_vertices_b = [df.Point(0.7, -0.2),#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_a,
+                        interface45_vertices_b,
+                        interface46_vertices,
+                        interface56_vertices,
+                        ]
+adjacent_subdomains = [[1,2],
+                       [2,3],
+                       [2,4],
+                       [2,5],
+                       [3,4],
+                       [3,6],
+                       [4,5],
+                       [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],
+                       interface45_vertices_a[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_b[1],
+                       interface45_vertices_b[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
+}
+
+# MODEL CONFIGURATION #########################################################
+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': 997.0,  #997
+         'nonwetting': 1.225},  #1},  #1.225},
+    2: {'wetting': 997.0,  #997
+         'nonwetting': 1.225},  #1.225},
+    3: {'wetting': 997.0,  #997
+         'nonwetting': 1.225},  #1.225},
+    4: {'wetting': 997.0,  #997
+         'nonwetting': 1.225},  #1.225}
+    5: {'wetting': 997.0,  #997
+         'nonwetting': 1.225},  #1.225},
+    6: {'wetting': 997.0,  #997
+         'nonwetting': 1.225}  #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: 0.2,  #0.2,  # Clayey gravels, clayey sandy gravels
+    2: 0.2,  #0.22, # Silty gravels, silty sandy gravels
+    3: 0.2,  #0.37, # Clayey sands
+    4: 0.2,  #0.2 # Silty or sandy clay
+    5: 0.2,  #
+    6: 0.2,  #
+}
+
+# subdom_num : subdomain L for L-scheme
+L = {
+    1: {'wetting' :Lw1,
+         'nonwetting': Lnw1},
+    2: {'wetting' :Lw2,
+         'nonwetting': Lnw2},
+    3: {'wetting' :Lw3,
+         'nonwetting': Lnw3},
+    4: {'wetting' :Lw4,
+         'nonwetting': Lnw4},
+    5: {'wetting' :Lw5,
+         'nonwetting': Lnw5},
+    6: {'wetting' :Lw6,
+         'nonwetting': Lnw6}
+}
+
+
+# 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_a,
+#                         interface45_vertices_b,
+#                         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': lambda45_w,
+         'nonwetting': lambda45_nw},
+    8: {'wetting': lambda46_w,
+         'nonwetting': lambda46_nw},
+    9: {'wetting': lambda56_w,
+         'nonwetting': lambda56_nw},
+}
+
+
+# after Lewis, see pdf file
+intrinsic_permeability = {
+    1: 0.01,  # sand
+    2: 0.01,  # sand, there is a range
+    3: 0.01,  #10e-2,  # clay has a range
+    4: 0.01,  #10e-3
+    5: 0.01,  #10e-2,  # clay has a range
+    6: 0.01,  #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*t },
+    2: {'wetting': -7.0 - (1.0 + t*t)*(1.0 + x*x + y*y),
+        'nonwetting': 0*t },
+    3: {'wetting': (-7.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1.0 -t*(1.0 + x**2) - sym.sqrt(2+t**2)**2)*y**2 },
+    4: {'wetting': (-7.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1.0 -t*(1.0 + x**2) - sym.sqrt(2+t**2)**2)*y**2 },
+    5: {'wetting': (-7.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1.0 -t*(1.0 + x**2) - sym.sqrt(2+t**2)**2)*y**2 },
+    6: {'wetting': (-7.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1.0 -t*(1.0 + x**2) - sym.sqrt(2+t**2)**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'].copy()})
+    else:
+        pc_e_sym.update({subdomain: p_e_sym[subdomain]['nonwetting'].copy()
+                                        - p_e_sym[subdomain]['wetting'].copy()})
+
+
+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']
+
+# BOUNDARY CONDITIONS #########################################################
+# 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():
+    # subdomain can have no outer boundary
+    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]}
+                )
+
+
+# LOG FILE OUTPUT #############################################################
+# 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()
+
+
+# RUN #########################################################################
+def run_simulation(
+        starttime: float = 0.0,
+        mesh_resolution: float = 32,
+        **kwargs
+        ) -> None:
+    """Setup and run LDD simulation
+
+    Setup and run LDD simulation for starttime starttime and mesh resolution
+    mesh_resolution.
+
+    PARAMETERS
+    starttime       #type float     number >= 0 specifying the starting point
+                                    of the simulation.
+    mesh_resolution #type float     mesh resolution parameter for Fenics.
+    """
+    for key, value in kwargs.items():
+        print ("%s == %s" %(key, value))
+
+    parameter=kwargs
+    # initialise LDD simulation class
+    simulation = ldd.LDDsimulation(
+        # tol=1E-14,  #parameter["tol"],
+        LDDsolver_tol=parameter['solver_tol'],
+        debug=parameter["debugflag"],
+        max_iter_num=parameter["max_iter_num"],
+        FEM_Lagrange_degree=parameter["FEM_Lagrange_degree"],
+        mesh_study=parameter["mesh_study"]
+        )
+
+    simulation.set_parameters(
+        use_case=parameter["use_case"],
+        output_dir=parameter["output_string"],
+        subdomain_def_points=parameter["subdomain_def_points"],
+        isRichards=parameter["isRichards"],
+        interface_def_points=parameter["interface_def_points"],
+        outer_boundary_def_points=parameter["outer_boundary_def_points"],
+        adjacent_subdomains=parameter["adjacent_subdomains"],
+        mesh_resolution=parameter["mesh_resolution"],
+        viscosity=parameter["viscosity"],
+        porosity=parameter["porosity"],
+        L=parameter["L"],
+        lambda_param=parameter["lambda_param"],
+        relative_permeability=parameter["relative_permeability"],
+        saturation=parameter["sat_pressure_relationship"],
+        starttime=parameter["starttime"],
+        number_of_timesteps=parameter["number_of_timesteps"],
+        number_of_timesteps_to_analyse=parameter["number_of_timesteps_to_analyse"],
+        plot_timestep_every=parameter["plot_timestep_every"],
+        timestep_size=parameter["timestep_size"],
+        sources=parameter["source_expression"],
+        initial_conditions=parameter["initial_condition"],
+        dirichletBC_expression_strings=parameter["dirichletBC"],
+        exact_solution=parameter["exact_solution"],
+        densities=parameter["densities"],
+        include_gravity=parameter["include_gravity"],
+        gravity_acceleration=parameter["gravity_acceleration"],
+        write2file=parameter["write_to_file"],
+        )
+
+    simulation.initialise()
+    output_dir = simulation.output_dir
+    # simulation.write_exact_solution_to_xdmf()
+    output = simulation.run(analyse_condition=parameter["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_meshrez{}.csv".format(
+                    phase,
+                    mesh_resolution
+                    )
+            # 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
+                    )
+
+
+def info(title):
+    """show process ids of multiprocessing simulation"""
+    print(title)
+    print('module name:', __name__)
+    print('parent process:', os.getppid())
+    print('process id:', os.getpid())
+
+
+# MAIN ########################################################################
+if __name__ == '__main__':
+    # mp.set_start_method('spawn')
+    # dictionary of simualation parameters to pass to the run function.
+    # mesh_resolution and starttime are excluded, as they get passed explicitly
+    # to achieve parallelisation in these parameters in these parameters for
+    # mesh studies etc.
+    simulation_parameter = {
+        "tol": 1E-14,
+        "debugflag": debugflag,
+        "max_iter_num": max_iter_num,
+        "FEM_Lagrange_degree": FEM_Lagrange_degree,
+        "mesh_study": mesh_study,
+        "use_case": use_case,
+        "output_string": 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,
+        "sat_pressure_relationship": 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,
+        "source_expression": source_expression,
+        "initial_condition": initial_condition,
+        "dirichletBC": dirichletBC,
+        "exact_solution": exact_solution,
+        "densities": densities,
+        "include_gravity": include_gravity,
+        "gravity_acceleration": gravity_acceleration,
+        "write_to_file": write_to_file,
+        "analyse_condition": analyse_condition
+    }
+    for starttime in starttimes:
+        for mesh_resolution, solver_tol in resolutions.items():
+            simulation_parameter.update(
+                {"solver_tol": solver_tol,
+                 "mesh_resolution": mesh_resolution,
+                 "starttime": starttime}
+            )
+            # info(simulation_parameter["use_case"])
+            # LDDsim = mp.Process(
+            #             target=run_simulation,
+            #             args=(
+            #                 starttime,
+            #                 mesh_resolution,
+            #                 simulation_parameter
+            #                 )
+            #             )
+            # LDDsim.start()
+            # LDDsim.join()
+            run_simulation(
+                starttime=starttime,
+                mesh_resolution=mesh_resolution,
+                kwargs=simulation_parameter
+                )
-- 
GitLab