Updated install instruction, corrected github link

README.md

@@ -32,8 +32,8 @@ If you wish to know more about the instrument please check the
 If you are having trouble operating the Goodman Pipeline we suggest the following
 procedure.
 
-* Check [existing issues](https://github.com/soar-telescope/goodman/issues) or 
-open a [new Issue](https://github.com/soar-telescope/goodman/issues/new) on GitHub.
+* Check [existing issues](https://github.com/soar-telescope/goodman_pipeline/issues) or 
+open a [new Issue](https://github.com/soar-telescope/goodman_pipeline/issues/new) on GitHub.
 
 ## Development Team
 

docs/_install_dcr.rst

@@ -18,7 +18,7 @@ of ``dcr`` to help with the pipeline's workflow. It is included under
 
   ``<path_to_download_location>/goodman_pipeline/goodman_pipeline/data/dcr-source/dcr/``
 
-``goodman`` is the folder that will be created once you untar or unzip the latest
+``goodman_pipeline-<version>`` is the folder that will be created once you untar or unzip the latest
 release of the |pipeline name|.
 
 .. important::
@@ -90,3 +90,4 @@ executable binary in your ``$PATH`` variable.
 
     ``source ~/.bashrc``
 
+.. include:: _shortcuts.rst

docs/install.rst

@@ -2,109 +2,102 @@
 
 Install
 #######
-Using the pipeline remotely is the recommended method, in which case you don't need
-to worry about software requirements.
 
-However, for users who wish to go ahead with a local installation, we provide
-simple instructions in the current section.
+We do not have the resources to provide installation support, thus we provide
+a server with the latest and older versions installed that users with access rights
+can use, however, the installation process is simple.
 
-Requirements
-************
-
-The |pipeline name| is completely written in Python 3.x and relies on several
-libraries like:
-
-* NumPy
-* SciPy
-* MatPlotLib
-* Pandas
-* AstroPy
-* AstroPy/ccdproc
-* AstroPy/astroplan
-* DCR
-
-Using Conda
-***********
+Installation Overview
+*********************
 
-We **do not** recommend the installation of these libraries or the
-|pipeline name| in your system since updates and upgrades may ruin it. We rather
-recommend the use of Virtual Environments. If you are not familiar with this
-term, please check the official documentation by visiting the links below:
+The required steps for a successful installation may vary, but here is a general
+list.
 
-    https://docs.python.org/3/tutorial/venv.html
+Install *astroconda*.
+  Visit `AstroConda site <https://astroconda.readthedocs.io/en/latest/>`_ and use
+  their instructions on how to install and basic setup. Make sure you add
+  the `astroconda channel <https://astroconda.readthedocs.io/en/latest/installation.html#configure-conda-to-use-the-astroconda-channel>`_
 
-    or
+Create a *virtual environment*.
+  This will depend on the method of installation but here is the official
+  documentation on `virtual environment management <https://conda.io/docs/user-guide/tasks/manage-environments.html>`_.
 
-    http://docs.python-guide.org/en/latest/dev/virtualenvs/
+Install all requirements.
+  This can be done along with the virtual environment creation, but it might be
+  necessary to manually install dependencies.
 
-Another option is to install **Conda**, a Virtual Environment Manager, or
-**AstroConda**, the same but for astronomers. Everything you need to know
-about installing both can be found in the link below:
+Run test code.
+  This is optional only possible if you are installing from source code.
 
-    https://astroconda.readthedocs.io/
+Install the goodman pipeline.
+  The most important step (of course).
 
+Getting the code
+****************
 
-.. include:: _working_with_virtualenv.rst
+There are several ways to get the goodman pipeline code on your computer.
 
-Using PIP
-*********
+1. Clone the repository: Cloning the `repository <https://github.com/soar-telescope/goodman_pipeline>`_ will
+   get you the latest version of the code, this could be a very unstable version,
+   so is not recommended. Also is very likely that you will download things you don't need.
 
-.. warning::
+2. Get a release: A release is like a snapshot of a very special stage of development.
+   Though is not easy to guarantee that the code will not break a released version should
+   be stable in the sense that no experimental code should exist. Also, is a
+   special packaging of the necessary parts for operation. The releases are listed
+   `here <https://github.com/soar-telescope/goodman_pipeline/releases>`_. make sure
+   it has a green tag that says **Latest Release**.
 
-    You may find that `ccdproc` and `astroplan` do not come with Astroconda.
-    They are not available on any Conda channel either. That means that you will
-    have to install them separately. You can do so by downloading the source files
-    and installing them by hand, or simply
-    `activate your Virtual Environment <https://conda.io/docs/user-guide/tasks/manage-environments.html#activating-an-environment>`_ and
-    then install these two packages using pip with
+3. Using pip: Since version :ref:`1.1.2 <v1.1.2>` the goodman pipeline can be installed using
+   pip: ``pip install goodman-pipeline`` however this does not install astroconda
+   neither creates the virtual environment.
 
-    ``pip install ccdproc astroplan``
 
+Dependencies
+************
 
+We have made an enormous effort to maintain dependencies under control, with
+one exception, but don't worry that we have :ref:`detailed instruccions <dcr>` for
+dealing with it.
 
-Setup for local installation
-****************************
-System installation is not recommended because it can mess things up specially in
-Linux and Mac OS. Before you proceed, make sure that your system has all
-the required libraries, as described in `Requirements`_.
+For the ordinary dependencies we make use of the great tools provided by astroconda.
+With one step we can create a virtual environment with all the dependencies on it.
+This does not work for the pip installation, but either by cloning the repository or
+by downloading a release you get a file called `environment.yml` that can be used by
+conda in the following way:
 
-Once you have Python running and all the libraries installed either using
-Conda/AstroConda or not, you may download the last version available in the
-following address:
+  ``conda env create -f environment.yml``
 
-    https://github.com/soar-telescope/goodman/releases/latest
+This will create a virtual environment called ``goodman_pipeline`` that you can start
+using by running.
 
-Before continuing, make sure that your Virtual Environment is active if this is
-the case. There are several ways of doing this but normally the command below
-should work:
+  ``source activate goodman_pipeline``
 
-    ``$ source activate <my_environment_name>``
+.. include:: _install_dcr.rst
 
-Where ``<my_environment_name>`` is the name of your Virtual Environment (e.g.
-astroconda).
+Running tests
+*************
 
-Now you can finally install the |pipeline name|. Download the file, decompress
-it, and enter the directory created during the file decompression. Test the
-installation by typing:
+*Test code is code to test the code*, yes, that's right, and the |pipeline full name|
+comes with a lot of it. Ideally the 100% of the code should be covered, we are not
+there yet but we are getting closer. Running the test code is not a requirement
+but it helps a lot to identify problems. Go to the extraction folder
+(where the file ``setup.py`` exist) and execute the following instruction:
 
-    ``$ python setup.py test``
+  ``python setup.py test``
 
-If you have any errors, check the traceback. If you find difficulties carring
-on at this poing, you may contact us by `opening a new issue <https://github.com/soar-telescope/goodman/issues>`_     or using the e-mail
-`goodman-pipeline@ctio.noao.edu`.
+This will detect the test code and execute it. Failure or success will be informed.
 
-If no error messages start popping up in your screen, you are good to carry
-on with the installation.
+Installation
+************
 
-    ``$ python setup.py install``
+If the previous steps ended successfully this should be easy. Go to the extraction
+folder and execute the following instruction:
 
-.. note::
+  ``python setup.py install``
 
-    This will install the pipeline in the currently active Python version.
-    If you have Virtual Environments, make sure that it is active. If not,
-    you can add the ``--user`` option to install only for your user and avoid
-    needing root access.
 
-.. include:: _install_dcr.rst
+Alternatively, after the creation of the virtual environment you can install the pipeline
+using pip.
 
-.. include:: _shortcuts.rst
+  ``pip install goodman-pipeline``

docs/overview.rst

@@ -12,7 +12,7 @@ spectra can be produced shortly after the shutter closes.
 The pipeline is primarily intended to be run on a data reduction dedicated
 computer though it is available for local installation. The |pipeline full name|
 project is hosted at GitHub at
-`it's GitHub Repository <https://github.com/soar-telescope/goodman>`_.
+`it's GitHub Repository <https://github.com/soar-telescope/goodman_pipeline>`_.
 
 Instructions for running the software are provided in the :ref:`usage` section
 of this guide. How to access the the data reduction server is on

goodman_pipeline/images/goodman_ccd.py

@@ -216,7 +216,7 @@ def __call__(self, args=None):
                     "not found inside headers. This keyword contains what "
                     "is the Goodman Wavelength Configuration that was used"
                     " for this observation. Please add it manually (see "
-                    "https://github.com/soar-telescope/goodman/blob/development/goodman_modes.md) "
+                    "https://github.com/soar-telescope/goodman_pipeline/blob/development/goodman_modes.md) "
                     "and run again. Leaving the program now.")
                 sys.exit(1)