Fix PyPi bug during imports

.github/workflows/runfitbot.yml

@@ -46,7 +46,7 @@ jobs:
       - name: Install project 🔨
         # it is required to repeat extras, otherwise they will be removed from
         # the environment
-        run: poetry install --no-interaction ${{ inputs.poetry-extras }}
+        run: poetry install --no-interaction
 
       - name: Perform a fit 🚀
         shell: bash --login {0}

.github/workflows/unittests.yml

@@ -35,6 +35,8 @@ jobs:
         # it is required to repeat extras, otherwise they will be removed from
         # the environment
         run: poetry install --no-interaction ${{ inputs.poetry-extras }}
+      - name: Download the theory
+        run: poetry run nns get theory
       - name: Install task runner 🔨
         run: pip install poethepoet
       - name: Lint with pylint 🚀

README.md

@@ -25,9 +25,6 @@
 - [Tutorials](https://nnpdf.github.io/nnusf/tutorials/datasets.html)
 - [Delivery & Usage](https://nnpdf.github.io/nnusf/delivery/lhapdf.html)
 
-> **Note**
-> For the time being, we recommend the user to use the 
-> [development](https://nnpdf.github.io/nnusf/quickstart/installation.html#development-installation) installation.
 
 # Citation
 

docs/source/index.rst

@@ -55,24 +55,29 @@ To reference NNSFν in a scientific publication please use the following:
 
 .. code-block:: latex
 
-   @article {reference_id,
-      author = {A. Candido, A. Garcia, G. Magni, T. R. Rabemananjara, J. Rojo, R. Stegeman},
-      title = {Neutrino Structure Functions from GeV to EeV Energies},
-      year = {2023},
-      doi = {10.1101/2020.07.15.204701},
-      eprint = {https://arxiv.org/list/hep-ph/},
-      journal = {aRxiv}
+   @article{Candido:2023utz,
+       author = "Candido, Alessandro and Garcia, Alfonso and Magni, Giacomo and Rabemananjara, Tanjona and Rojo, Juan and Stegeman, Roy",
+       title = "{Neutrino Structure Functions from GeV to EeV Energies}",
+       eprint = "2302.08527",
+       archivePrefix = "arXiv",
+       primaryClass = "hep-ph",
+       reportNumber = "Nikhef 2022-014, Edinburgh 2022/27, TIF-UNIMI-2023-5",
+       month = "2",
+       year = "2023"
    }
 
 If NNSFν proves to be useful in your work, please also reference the codes:
 
 .. code-block:: latex
 
-   @article {reference_id,
-      author = {A. Candido, A. Garcia, G. Magni, T. R. Rabemananjara, J. Rojo, R. Stegeman},
-      title = {Neutrino Structure Functions from GeV to EeV Energies},
-      year = {2023},
-      doi = {10.1101/2020.07.15.204701},
+   @misc{https://doi.org/10.5281/zenodo.7657132,
+     doi = {10.5281/ZENODO.7657132},
+     url = {https://zenodo.org/record/7657132},
+     author = "Candido, Alessandro and Garcia, Alfonso and Magni, Giacomo and Rabemananjara, Tanjona and Rojo, Juan and Stegeman, Roy",
+     title = "{Neutrino Structure Functions from GeV to EeV Energies}",
+     publisher = {Zenodo},
+     year = {2023},
+     copyright = {Open Access}
    }
 
 

docs/source/mbadges.md

@@ -1,6 +1,8 @@
 <p align="center">
-  <img alt="Zenodo" src="https://zenodo.org/badge/DOI/10.1101/2023.02.15.204701.svg">
+  <a href="https://zenodo.org/account/settings/github/repository/NNPDF/nnusf#"><img alt="Zenodo" src="https://zenodo.org/badge/DOI/10.5281/zenodo.7657132 .svg"></a>
+  <a href="https://arxiv.org/abs/2302.08527"><img alt="arXiv" src="https://img.shields.io/badge/arXiv-2302.08527-b31b1b?labelColor=222222"></a>
+  <a href="https://pypi.org/project/nnusf/"><img alt="PyPI" src="https://img.shields.io/pypi/v/nnusf"/></a>
   <img alt="Docs" src="https://assets.readthedocs.org/static/projects/badges/passing-flat.svg">
   <img alt="Status" src="https://www.repostatus.org/badges/latest/active.svg">
-  <img alt="License" src="https://img.shields.io/badge/License-MIT-yellow.svg">
+  <img alt="License" src="https://img.shields.io/badge/License-GPL3-blue.svg">
 </p>

docs/source/quickstart/installation.rst

@@ -11,6 +11,25 @@ via the `Python Package Index <https://pypi.org/>`_ using the following command:
 
    pip install nnusf
 
+.. note::
+
+   In order to use NNSFν one needs to download the the :mod:`commondata`
+   and :mod:`theory` files and store them into the user directory
+   (which is platform/system dependent).
+
+   NNSFν provides an easy way to download and install these input data files
+   by simply running the following commands:
+
+   .. code-block:: console
+
+      nns get theory
+
+   To see where the files have been installed, type the following commands:
+
+   .. code-block:: console
+
+      nns get print_userdir_path
+
 To check that the package has been installed correctly, just run the following
 which will print out all the available subcommands:
 
@@ -31,30 +50,45 @@ Once this is done, first clone the repository and enter into the directory:
    git clone https://github.com/NNPDF/nnusf.git --depth 1
    cd nnusf
 
-Then, to install the NNSF:math:`\nu` package just type:
+Then, to install the NNSFν package just type:
 
 .. code-block:: bash
 
    poetry install
 
-Note that when installing using :mod:`poetry` one has the choice of doing so in
-a :mod:`poetry` virtual environment or not. To install the package in the current
-active environment, before :mod:`poetry install` type the following command:
+.. note::
 
-.. code-block:: bash
+   Note that when installing using :mod:`poetry` one has the choice of doing so in
+   a :mod:`poetry` virtual environment or not. To install the package in the current
+   active environment, before :mod:`poetry install` type the following command:
 
-   poetry config virtualenvs.create false --local
+   .. code-block:: console
 
-If instead you choose to install the package in a clean environment, first you
-need to save the path to the environment into an environment variable:
+      poetry config virtualenvs.create false --local
 
-.. code-block:: bash
+   If instead you choose to install the package in a clean environment, first you
+   need to save the path to the environment into an environment variable:
 
-   export PREFIX=$(realpath $(poetry env --path))
+   .. code-block:: console
 
-Then download the scripts from `N3PDF/workflows/packages/lhapdf <https://github.com/N3PDF/workflows/tree/v2/packages/lhapdf>`_
-and install :mod:`LHAPDF`:
+      export PREFIX=$(realpath $(poetry env --path))
 
-.. code-block:: bash
+   Then download the scripts from
+   `N3PDF/workflows/packages/lhapdf <https://github.com/N3PDF/workflows/tree/v2/packages/lhapdf>`_
+   and install :mod:`LHAPDF`:
+
+   .. code-block:: console
+
+      sh install.sh
+
+.. tip::
+
+   If NNSFv was instead installed in a :mod:`poetry` virtual environment then
+   it may be useful to enter in a :mod:`poetry` shell by invoking the following
+   command:
+
+   .. code-block:: console
+
+      poetry shell
 
-   sh install.sh
+   otherwise prepending all the commands by :mod:`poetry` will be required.

docs/source/tutorials/datasets.rst

@@ -24,7 +24,7 @@ Once this is done run the following command:
 
 .. code-block:: bash
 
-   nnu data filter ./commondata/rawdata/*
+   nnu data filter ${NNUSF_USERDIR}/commondata/rawdata/*
 
 This will dump the pandas tables containing the input kinematics,
 central values, and uncertainties in :mod:`commondata/kinematics`,
@@ -43,7 +43,7 @@ To do so, just run the following:
 
 .. code-block:: bash
 
-   nnu data coefficients ./commondata/data/*
+   nnu data coefficients ${NNUSF_USERDIR}/commondata/data/*
 
 
 Yadism pseudo-data
@@ -58,7 +58,7 @@ to generate the input kinematics, just run the following command:
 
 .. code-block:: bash
 
-   nnu data matching_grids_empty ./commondata/data/DATA_${EXPERIMENT}_${OBSERVABLE}.csv
+   nnu data matching_grids_empty ${NNUSF_USERDIR}/commondata/data/DATA_${EXPERIMENT}_${OBSERVABLE}.csv
 
 This will generate inside :mod:`commondata/kinematics` a table named
 :mod:`KIN_${EXPERIMENT}_${OBSERVABLE}_MATCHING.csv` containing the input
@@ -103,4 +103,4 @@ just need to run the same command as before:
 
 .. code-block:: bash
 
-   nnu data coefficients ./commondata/data/*
+   nnu data coefficients ${NNUSF_USERDIR}/commondata/data/*