[DOC] simplifying the install doc

INSTALL.md

@@ -1,82 +1,83 @@
 # How to install NARPS Open Pipelines ? 
 
-## 1 - Get the code
+## 1 - Fork the repository
 
-First, [fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo) the repository, so you have your own working copy of it.
+[Fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo) the repository, so you have your own working copy of it.
 
-Then, you have two options to [clone](https://docs.github.com/en/repositories/creating-and-managing-repositories/cloning-a-repository) the project :
+## 2 - Clone the code
 
-### Option 1: Using DataLad (recommended)
+First, install [Datalad](https://www.datalad.org/). This will allow you to get the code as well as "links" to the data, because the NARPS data is bundled in this repository as [datalad subdatasets](http://handbook.datalad.org/en/latest/basics/101-106-nesting.html).
 
-Cloning the fork using [Datalad](https://www.datalad.org/) will allow you to get the code as well as "links" to the data, because the NARPS data is bundled in this repository as [datalad subdatasets](http://handbook.datalad.org/en/latest/basics/101-106-nesting.html).
+Then, [clone](https://docs.github.com/en/repositories/creating-and-managing-repositories/cloning-a-repository) the project :
 
 ```bash
 datalad install --recursive https://github.com/YOUR_GITHUB_USERNAME/narps_open_pipelines.git
 ```
 
-### Option 2: Using Git
+> [!WARNING]  
+> It is still possible to clone the fork using [git](https://git-scm.com/) ; but doing this, you will only get the code, loosing the links to the data.
+> ```bash
+> git clone https://github.com/YOUR_GITHUB_USERNAME/narps_open_pipelines.git
+> ```
 
-Cloning the fork using [git](https://git-scm.com/) ; by doing this, you will only get the code.
+## 3 - Get the data
 
-```bash
-git clone https://github.com/YOUR_GITHUB_USERNAME/narps_open_pipelines.git
-```
-
-## 2 - Get the data
+Now that you cloned the repository using Datalad, you are able to get the data :
 
-Ignore this step if you used DataLad (option 1) in the previous step.
+```bash
+# Move inside the root directory of the repository.
+cd narps_open_pipelines
 
-Otherwise, there are several ways to get the data.
+# Select the data you want to download. Here is an example to get data of the first 4 subjects.
+datalad get data/original/ds001734/sub-00[1-4] -J 12
+datalad get data/original/ds001734/derivatives/fmriprep/sub-00[1-4] -J 12
+```
 
-## 3 - Set up the environment
+> [!NOTE]  
+> For further information and alternatives on how to get the data, see the corresponding documentation page [docs/data.md](docs/data.md).
 
-The Narps Open Pipelines project is build upon several dependencies, such as [Nipype](https://nipype.readthedocs.io/en/latest/) but also the original software packages used by the pipelines (SPM, FSL, AFNI...). 
+## 4 - Set up the environment
 
-To facilitate this step, we created a Docker container based on [Neurodocker](https://github.com/ReproNim/neurodocker) that contains the necessary Python packages and software. To install the Docker image, two options are available.
+The Narps Open Pipelines project is build upon several dependencies, such as [Nipype](https://nipype.readthedocs.io/en/latest/) but also the original software packages used by the pipelines (SPM, FSL, AFNI...).
 
-### Option 1: Using Dockerhub
+Therefore, we created a Docker container based on [Neurodocker](https://github.com/ReproNim/neurodocker) that contains the necessary Python packages and software. [Install Docker](https://docs.docker.com/engine/install/) then pull the Docker image :
 
 ```bash
 docker pull elodiegermani/open_pipeline:latest
 ```
 
-The image should install itself. Once it's done you can check the image is available on your system:
+Once it's done you can check the image is available on your system :
 
 ```bash
 docker images
    docker.io/elodiegermani/open_pipeline    latest    0f3c74d28406    9 months ago    22.7 GB
 ```
 
-### Option 2: Using a Dockerfile 
+> [!NOTE]  
+> Feel free to read this documentation page [docs/environment.md](docs/environment.md) to start the environment from it.
+
+## 5 - Run the project
+
+Start a Docker container from the Docker image :
+
+```bash
+docker run -it -v <path_to_the_repository>:/home/neuro/code/ elodiegermani/open_pipeline
+```
 
-The Dockerfile used to create the image stored on DockerHub is available at the root of the repository ([Dockerfile](Dockerfile)). But you might want to personalize this Dockerfile. To do so, change the command below that will generate a new Dockerfile: 
+Install NARPS Open Pipeline inside the container :
 
 ```bash
-docker run --rm repronim/neurodocker:0.7.0 generate docker \
-           --base neurodebian:stretch-non-free --pkg-manager apt \
-           --install git \
-           --fsl version=6.0.3 \
-           --afni version=latest method=binaries install_r=true install_r_pkgs=true install_python2=true install_python3=true \
-           --spm12 version=r7771 method=binaries \
-           --user=neuro \
-           --workdir /home \
-           --miniconda create_env=neuro \
-                       conda_install="python=3.8 traits jupyter nilearn graphviz nipype scikit-image" \
-                       pip_install="matplotlib" \
-                       activate=True \
-           --env LD_LIBRARY_PATH="/opt/miniconda-latest/envs/neuro:$LD_LIBRARY_PATH" \
-           --run-bash "source activate neuro" \
-           --user=root \
-           --run 'chmod 777 -Rf /home' \
-           --run 'chown -R neuro /home' \
-           --user=neuro \
-           --run 'mkdir -p ~/.jupyter && echo c.NotebookApp.ip = \"0.0.0.0\" > ~/.jupyter/jupyter_notebook_config.py' > Dockerfile
+source activate neuro
+cd /home/neuro/code/
+pip insall .
 ```
 
-When you are satisfied with your Dockerfile, just build the image:
+Finally, you are able to run pipelines :
 
 ```bash
-docker build --tag [name_of_the_image] - < Dockerfile
+python narps_open/runner.py
+  usage: runner.py [-h] -t TEAM (-r RSUBJECTS | -s SUBJECTS [SUBJECTS ...] | -n NSUBJECTS) [-g | -f] [-c]
 ```
 
-When the image is built, follow the instructions in [docs/environment.md](docs/environment.md) to start the environment from it.
+> [!NOTE]  
+> For further information, read [docs/running.md](docs/running.md).