Update README.rst

README.rst

@@ -8,19 +8,59 @@ Numerical Test Rig for Cascades.
 
 * Free software: MIT license
 * Documentation: https://ntrfc.readthedocs.io.
+* NTRfC is the base of the (NTRFlows)[https://gitlab.uni-hannover.de/tfd_public/tools/NTRFlows] repository, a workflow for cfd parameter studies
+
+
+Features
+--------
+
+- Easy geometry and postprocessing visualization and manipulation with (pyvista)[https://github.com/pyvista]
+- Tested methods and functions for math, timeseries and meshquality-analysis
+
+Dependencies
+--------
+
+NTRfC v0.1.0 and any following version is based on Python 3.10.
+Only older versions can be used with older versions of Python.
+
+Library-requirements will be installed with the package itself.
 
 Installation
 --------
 
-The easiest way to use this repository is to install ntrfc using 'pip install ntrfc'
-or install using 'python -m setup install'
+NTRfC is utilizing powerful and complex dependencies like pyvista and gmsh.
+It is strongly recommanded to use virtual environments [virtualenv](https://pypi.org/project/virtualenv/), conda-environments (see [miniconda](https://docs.conda.io/en/latest/miniconda.html), [anaconda](https://docs.anaconda.com/anaconda/install/index.html), [mamba](https://mamba.readthedocs.io/en/latest/installation.html) ) or to use a singularity container from (ntrfc singularity releases)[https://cloud.sylabs.io/library/nyhuma/ntrflows/ntr.sif].
+
+**Installation from gitlab with pip**
+
+You can install the package with pip from gitlab directly.
+Type:
+
+'''
+pip install git+https://gitlab.uni-hannover.de/tfd_public/tools/NTRfC.git
+'''
+
+
+**Installation from source**
+
+After cloning the repository, go to the project root dir and type
+
+'''
+python setup.py install
+'''
+
+
+**Editable installation from source with pip**
+
+After cloning the repository, go to the project root dir and type
 
-when installing from conda, you will run into issues with vtk while using a pip installation of ntrfc.
-simply run:
-    'conda install -c conda-forge vtk'
+'''
+pip install -e .
+'''
 
-as a dev use "pip install -e ntrfc" for a linked install. this way you dont have to reinstall the package after altering the sourcecode.
-you might also want to install the dev-libraries in the requirements_dev.txt ('pip install -r requirements_dev.txt')
+This way you have NTRfC installed but the code is not installed, but linked to the source-code.
+You don't have to reinstall the package after your edits.
+This speeds up testing and will lead to less debugging time.
 
 
 Credits