diff --git a/Manuals/assigning_nodal_values_to_function_at_boundary_values.py b/Manuals/assigning_nodal_values_to_function_at_boundary_values.py
deleted file mode 100755
index 453802f0a8cbb583e8357d2bc593ad0d8ff08489..0000000000000000000000000000000000000000
--- a/Manuals/assigning_nodal_values_to_function_at_boundary_values.py
+++ /dev/null
@@ -1,173 +0,0 @@
-#!/usr/bin/python3
-# I have been struggling about having a list of node indices:
-#
-# nodes = [1, 10, 22, ..., 32]
-#
-# of nodes at the boundary and an associated list of values
-#
-# node_values = [10.2, 1.2,0.1, ..., -0.2]
-#
-# and how to assign this to a function defined on the mesh, in order to use it as boundary conditions, instead of using an analytical function or a constant.
-#
-# After searchin thoroughly I manage to find a solution that works for low order basis functions, for both scalars and vector. I put here my solution to see if this is the way to do it and how can I extend it to higher order basis functions. Also, if it helps someone:
-
-import numpy
-from time import time
-from dolfin import *
-
-def dofs_to_verts(mesh,boundaryFunction,boundaryValue):
- """
- Compute the mapping from vertices to degrees of freedom only at the boundary.
- This saves time, since we do not have to loop over all the cells of the domain.
- If the for loop was replaced by a simple c++ function call, it would be much faster.
-
- INPUTS ::
- mesh :: The mesh where we want to compute the mapping between vertices
- and degrees of freedom.
-
- boundaryFunction :: A MeshFunction which assigns integer values to
- edges of the mesh.
-
- boundaryValue :: An integer value which we use to identify the boundary
- edges we want to use. The MeshFunction should have
- this value assigned to some of the edges.
- """
-
- # get the connectivity of the mesh
- mesh.init(1) # initialize edges
- mesh_topology = mesh.topology() # get the mesh topology
- conn12 = mesh_topology(1,2) # get the cells to which an edge belongs
-
- # get the number of edges
- n_edges = boundaryFunction.size()
-
- # get the indices of the boundary edges, as given by the boundaryFunction
- boundaryEdges = numpy.arange(n_edges)
- boundaryEdges = boundaryEdges[boundaryFunction.array() == boundaryValue]
-
- # Define the function spaces associated to the mesh
- # for now only CG of order 1 works for sure
- V = FunctionSpace(mesh, "CG", 1)
- Vv = VectorFunctionSpace(mesh, "CG", 1, dim=2)
-
- # Allocate memory space of the array that stores the mapping from
- # vertex number to degree of freedom number for both scalar and vector
- # valued functions (note that for vector valued functions we need to indices
- # since the x component and the y component have different indices)
- vert_to_dofs = numpy.zeros(mesh.num_vertices(), dtype=numpy.uintp)
- vectordofs_to_vert = numpy.zeros([2,mesh.num_vertices()], dtype=numpy.uintp)
-
- # Get the degree of freedom maps
- dm = V.dofmap()
- dms = [Vv.sub(i).dofmap() for i in range(2)] # the i=0 refers to x component
- # the i=1 refers to y component
-
- # get the cells of the mesh
- mesh_cells = mesh.cells()
-
- # Since we are only interested in the boundary vertices we just loop over
- # the boundary edges as given by the MeshFunction and stored in boundaryEdges
- # each time we loop we get the numbering of the degrees of freedom of the
- # vertices of the cell that contains the boundary edge and we construct
- # the mapping from vertex number to degree of freedom number
- for edge in boundaryEdges:
- # get the cell index to which the edge belongs
- cell_ind = conn12(edge)[0]
- # get the vertices of the cell
- vert_inds = mesh_cells[cell_ind]
-
- # add the degree of freedom numbering to the vertices
- vert_to_dofs[vert_inds] = numpy.array(dm.cell_dofs(cell_ind),dtype=numpy.uintp)
-
- # now we do the same but for vector valued quantites
- # since, in this case, our vector have two quantities (the x and y components)
- # we have to iterate over the two sub dof maps
- for i, (dms_i, dmcs_i) in enumerate(zip(dms, dms)):
- vectordofs_to_vert[i,vert_inds] = numpy.array(dms_i.cell_dofs(cell_ind),dtype=numpy.uintp)
-
- # Return vertex to dof mapping
- return vert_to_dofs, vectordofs_to_vert
-
-# this is an example of how to assign values at the nodes for both a scalar
-# and a vector valued function to a function
-
-# create a unit square mesh (any other mesh works)
-mesh = UnitSquareMesh(20,20)
-
-# --------------------------------------------------------------------------
-# this part is optional, if you already know the indices of the vertices at
-# the boundary just skip this part
-
-# define the boundary mesh
-boundaryMesh = BoundaryMesh(mesh)
-
-# if you already don't have the boundary nodes indices
-# get the boundary nodes indices
-nodes = boundaryMesh.vertex_map().array()
-
-# --------------------------------------------------------------------------
-
-# --------------------------------------------------------------------------
-# This part is just to generate a boundary function which assigns a value
-# boundary_value to the boundary edges
-
-boundary_value = 10
-# get the global number of the boundary edges
-edge_map = boundaryMesh.cell_map().array()
-# get the number of edges at the boundary
-n_boundaryEdges = edge_map.size
-
-# define the boundary function which defines the boundary
-boundaryFunction = MeshFunction('int',mesh,1)
-n_edges = boundaryFunction.array().size # the total number of edges
-
-# allocate memory space to boundary values
-boundary_values = numpy.zeros(n_edges,dtype='uintp')
-# assign the boundary_value to the array of boundary_values
-boundary_values[edge_map] = boundary_value
-# assign the boundary_values to the boundary_function
-boundaryFunction.set_values(boundary_values)
-
-# --------------------------------------------------------------------------
-
-# generate some random values for the values to assign to the scalar function at the nodes
-node_values_scalar = numpy.random.rand(nodes.size)
-# generate some random values for the values to assign to the vector function at the nodes
-node_values_vector = numpy.random.rand(2,nodes.size)
-
-start = time()
-# get the mapping of vertices at boundary to degrees of freedom
-vert_to_dofs, vectordofs_to_vert = dofs_to_verts(mesh,boundaryFunction,boundary_value)
-
-#print("It took :: %f s" %(time()-start)
-
-# assign vertex values at the boundary for the scalar function
-
-# generate the function space
-V = FunctionSpace(mesh,'Lagrange',1)
-# generate the scalar function
-myFunction = Function(V)
-# get the vector containing the data values at the degrees of freedom
-myFunction_vector = myFunction.vector()
-# use the mapping from vertices (nodes) to degrees of freedom to assign the
-# vertex values of the scalar function
-myFunction_vector[vert_to_dofs[nodes]] = node_values_scalar
-
-plot(myFunction)
-
-# assign vertex values at the boundary for the vector function
-
-# generate the function space
-Vv = VectorFunctionSpace(mesh, "Lagrange", 1, dim=2)
-# generate the vector function
-myVectorFunction = Function(Vv)
-# get the vector containing the data values at the degrees of freedom
-myVectorFunction_vector = myVectorFunction.vector()
-# use the mapping from vertices (nodes) to degrees of freedom to assign the
-# vertex values of the scalar function
-myVectorFunction_vector[vectordofs_to_vert[0,nodes]] = node_values_vector[0,:] # x component
-myVectorFunction_vector[vectordofs_to_vert[1,nodes]] = node_values_vector[1,:] # y component
-
-plot(myVectorFunction)
-
-interactive()
diff --git a/Manuals/doNix.manual.md b/Manuals/doNix.manual.md
deleted file mode 100644
index 41ca3d18268369eaa09013a2df27bf9fb60baee3..0000000000000000000000000000000000000000
--- a/Manuals/doNix.manual.md
+++ /dev/null
@@ -1,131 +0,0 @@
-# Using FeMuX in Docker
-
-
-## Build the docker image:
-
-
- docker build -t femux .
-
-## Run docker container with graphical display, share folder `pwd`:
-
- docker run -it --env HOST_UID=$(id -u $USER) --env HOST_GID=$(id -g $USER) --env
-DISPLAY=unix$DISPLAY --device /dev/dri --volume /tmp/.X11-unix:/tmp/.X11-unix:rw --volume
-$(pwd):/home/fenics/shared --name femux femux /bin/bash
-
-If you want the container do be automatically deleted after exiting add `--rm` option.
-
-If you have trouble with internet connection inside the container use
-
- --dns=YOUR_DNS_SERVER
-
-
-## Step into the container:
-
- docker start femux & docker exec -ti -u fenics femux /bin/bash -l
-
-
-## Install NSAC and dumux-fenics:
- ./install_femux.sh
-
-## Usefull docker commands:
-
-List all docker container
-
- docker ps -a
-
-Remove container
-
- docker rm $container
-
-Remove all stopped container
-
- docker container prune
-
-List all images
-
- docker images
-
-Remove image
-
- docker rmi $image
-
-
-
-
-# Troubleshooting:
-
-**Problem**
-1. I can't install packages via `apt-get install` inside the container
-
-**Solution**
-
-1. If the package is not found first `apt-get update` and then try again. If there is no connection
-check your dns settings.
-
-
-
-# Navier-Stokes-Allen-Cahn Framework
-## Installation for anaconda.
-### Tested with [minconda3 v4.3.31](https://conda.io/miniconda.html)
---------------------------------------------------------------------
-```
-conda create -n NSAC -c mikaem/label/docker-conda-gcc hdf5-parallel
-source activate NSAC
-conda install -c mikaem/label/docker-conda-gcc h5py-parallel
-conda install -c mikaem/label/docker-conda-gcc fenics
-conda install -c mikaem/label/docker-conda-gcc mshr
-pip install -r requirements.txt
-```
-
-
-[fenicstools](https://github.com/mikaem/fenicstools) for postprocessing
-```
-git clone https://github.com/mikaem/fenicstools.git fenicstools
-python fenicstools/setup.py install;
-```
-
---------------------------------------------------------------------
-## Installation for [Docker](https://www.docker.com/).
-
-Install Docker following https://docs.docker.com/engine/getstarted/step_one/
-
-Pull the latest fenics Docker image
-```
-docker pull quay.io/fenicsproject/stable:latest;
-```
-Run Docker with the dns option for the uni-network
-```
-docker run --dns=129.69.252.252 -ti -v $(pwd):/home/fenics/shared --name NSAC
-quay.io/fenicsproject/stable:latest;
-echo "export PYTHONPATH=/home/fenics/shared/" >> fenics.env.conf
-source fenics.env.conf
-```
-Clone this git repo and install dependencies
-```
-git clone https://gitlab.mathematik.uni-stuttgart.de/ostrowls/NSAC.git shared/NSAC
-pip3 install --user -r NSAC/requirements.txt;
-```
-Install fenicstools for postprocessing (might not be possible without sudo)
-```
-git clone https://github.com/mikaem/fenicstools.git fenicstools;
-cd fenicstools;
-sudo python3 setup.py install;
-cd ..
-rm -rvf fenicstools;
-```
-
-Start/stop the Container with
-```
-docker start/stop NSAC
-```
-After starting enter the container with
-```
-docker exec -ti -u fenics LDD-scheme /bin/bash -l
-```
-Exit the container with
-```
-exit
-```
-
-
-docker run --dns=129.69.252.252 -it --env HOST_UID=$(id -u $USER) --env HOST_GID=$(id -g $USER) --env DISPLAY=unix$DISPLAY --device /dev/dri --volume /tmp/.X11-unix:/tmp/.X11-unix:rw --volume $(pwd):/home/fenics/shared --name LDD-TPR quay.io/fenicsproject/stable:latest /bin/bash