Refactor skcosmo to skmatter

* changes all instances of 'scikit-cosmo' and 'scikit-COSMO' to 'scikit-matter'

* changes instances of 'skcosmo' to 'skmatter'

* changes all instances of 'SKCOSMO' to 'SKMATTER'

* changes hyperlinks containing 'scikit-cosmo' to 'scikit-matter', which reflects the change in the github link and repo name after refactoring.

* renames base directory skcosmo to skmatter.

* changed descriptions of scikitmatter away from the COSMO lab.

Author: victorprincipe

.github/workflows/lint.yml

@@ -33,4 +33,4 @@ jobs:
           black --check .
       - name: Check imports
         run: |
-          isort skcosmo/*/*py -m 3 --tc --fgw --up -e -l 88 --check
+          isort skmatter/*/*py -m 3 --tc --fgw --up -e -l 88 --check

LICENSE

@@ -1,6 +1,6 @@
 BSD 3-Clause License
 
-Copyright (c) 2020 the sklearn-cosmo contributors
+Copyright (c) 2020 the sklearn-matter contributors
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without

MANIFEST.in

@@ -1,2 +1,2 @@
-recursive-include skcosmo/datasets/data/ *
-recursive-include skcosmo/datasets/descr/ *
+recursive-include skmatter/datasets/data/ *
+recursive-include skmatter/datasets/descr/ *

README.md

@@ -1,16 +1,10 @@
-# scikit-cosmo
+# scikit-matter
 
-[![Test](https://github.com/lab-cosmo/scikit-cosmo/workflows/Test/badge.svg)](https://github.com/lab-cosmo/scikit-cosmo/actions?query=workflow%3ATest)
-[![codecov](https://codecov.io/gh/lab-cosmo/scikit-cosmo/branch/main/graph/badge.svg?token=UZJPJG34SM)](https://codecov.io/gh/lab-cosmo/scikit-cosmo/)
+[![Test](https://github.com/lab-cosmo/scikit-matter/workflows/Test/badge.svg)](https://github.com/lab-cosmo/scikit-matter/actions?query=workflow%3ATest)
+[![codecov](https://codecov.io/gh/lab-cosmo/scikit-matter/branch/main/graph/badge.svg?token=UZJPJG34SM)](https://codecov.io/gh/lab-cosmo/scikit-matter/)
 
 A collection of scikit-learn compatible utilities that implement methods
-developed in the COSMO laboratory
-
-
-## Deprecation Warning
-__IMPORTANT:__ This package has been renamed to scikit-matter ([skmatter](https://github.com/lab-cosmo/scikit-matter)). This package will no longer be maintained and updated.
-
-Please install the new package, skmatter, using:
+born out of the materials science and chemistry communities.
 
 ```bash
 pip install skmatter
@@ -19,10 +13,10 @@ pip install skmatter
 ## Installation
 
 ```bash
-pip install skcosmo 
+pip install skmatter 
 ```
 
-You can then `import skcosmo` in your code!
+You can then `import skmatter` in your code!
 
 ## Developing the package
 
@@ -35,8 +29,8 @@ pip install tox black flake8
 Then this package itself
 
 ```bash
-git clone https://github.com/lab-cosmo/scikit-cosmo
-cd scikit-cosmo
+git clone https://github.com/lab-cosmo/scikit-matter
+cd scikit-matter
 pip install -e .
 ```
 
@@ -46,7 +40,7 @@ and allowing you to edit the code and directly use the updated version.
 ### Running the tests
 
 ```bash
-cd <scikit-cosmo PATH>
+cd <scikit-matter PATH>
 # run unit tests
 tox
 # run the code formatter

docs/source/conf.py

@@ -53,19 +53,19 @@
                 converted = exporter.from_filename(nb_in)[0]
                 out_stream.write(converted)
 
-import skcosmo  # noqa
+import skmatter  # noqa
 
 # -- Project information -----------------------------------------------------
 
 # The master toctree document.
 master_doc = "index"
 
-project = "scikit-COSMO"
+project = "scikit-matter"
 author = ", ".join(open(os.path.join(ROOT, "contributors.txt")))
 copyright = "2020, " + author
 
 # The full version, including alpha/beta/rc tags
-release = skcosmo.__version__
+release = skmatter.__version__
 
 
 # -- General configuration ---------------------------------------------------
@@ -188,7 +188,7 @@
 # html_search_scorer = 'scorer.js'
 
 # Output file base name for HTML help builder.
-htmlhelp_basename = "skcosmodoc"
+htmlhelp_basename = "skmatterdoc"
 
 # -- Options for LaTeX output ---------------------------------------------
 
@@ -207,7 +207,7 @@
 # (source start file, target name, title,
 #  author, documentclass [howto, manual, or own class]).
 latex_documents = [
-    (master_doc, "skcosmo.tex", "scikit-COSMO Documentation", author, "manual"),
+    (master_doc, "skmatter.tex", "scikit-matter Documentation", author, "manual"),
 ]
 
 # The name of an image file (relative to this directory) to place at the top of

docs/source/contributing.rst

@@ -14,8 +14,8 @@ Then this package itself
 
 .. code-block:: bash
 
-  git clone https://github.com/lab-cosmo/scikit-cosmo
-  cd scikit-cosmo
+  git clone https://github.com/lab-cosmo/scikit-matter
+  cd scikit-matter
   pip install -e .
 
 This install the package in development mode, making it importable globally
@@ -26,7 +26,7 @@ Running the tests
 
 .. code-block:: bash
 
-  cd <scikit-cosmo PATH>
+  cd <scikit-matter PATH>
   # run unit tests
   tox
   # run the code formatter
@@ -43,20 +43,20 @@ editors <https://black.readthedocs.io/en/stable/editor_integration.html>`_.
 Issues and Pull Requests
 ########################
 
-Having a problem with scikit-COSMO? Please let us know by `submitting an issue <https://github.com/lab-cosmo/scikit-cosmo/issues>`_.
+Having a problem with scikit-matter? Please let us know by `submitting an issue <https://github.com/lab-cosmo/scikit-matter/issues>`_.
 
-Submit new features or bug fixes through a `pull request <https://github.com/lab-cosmo/scikit-cosmo/pulls>`_.
+Submit new features or bug fixes through a `pull request <https://github.com/lab-cosmo/scikit-matter/pulls>`_.
 
 
 Contributing Datasets
 #####################
 
-Have an example dataset that would fit into scikit-COSMO?
+Have an example dataset that would fit into scikit-matter?
 
 Contributing a dataset is easy. First, copy your numpy file into
-``skcosmo/datasets/data/`` with an informative name. Here, we'll call it ``my-dataset.npz``.
+``skmatter/datasets/data/`` with an informative name. Here, we'll call it ``my-dataset.npz``.
 
-Next, create a documentation file in ``skcosmo/datasets/data/my-dataset.rst``.
+Next, create a documentation file in ``skmatter/datasets/data/my-dataset.rst``.
 This file should look like this:
 
 .. code-block::
@@ -71,7 +71,7 @@ This file should look like this:
   Function Call
   -------------
 
-  .. function:: skcosmo.datasets.load_my_dataset
+  .. function:: skmatter.datasets.load_my_dataset
 
   Data Set Characteristics
   ------------------------
@@ -100,8 +100,8 @@ This file should look like this:
   --------------
 
 
-Then, show ``scikit-cosmo`` how to load your data by adding a loader function to
-``skcosmo/datasets/_base.py``. It should look like this:
+Then, show ``scikit-matter`` how to load your data by adding a loader function to
+``skmatter/datasets/_base.py``. It should look like this:
 
 .. code-block:: python
 
@@ -132,9 +132,9 @@ Then, show ``scikit-cosmo`` how to load your data by adding a loader function to
 
       return Bunch(data=data, DESCR=fdescr)
 
-Add this function to ``skcosmo/datasets/__init__.py``.
+Add this function to ``skmatter/datasets/__init__.py``.
 
-Finally, add a test to ``skcosmo/tests/test_datasets.py`` to see that your dataset
+Finally, add a test to ``skmatter/tests/test_datasets.py`` to see that your dataset
 loads properly. It should look something like this:
 
 .. code-block:: python
@@ -152,7 +152,7 @@ loads properly. It should look something like this:
         self.my_data.DESCR
 
 
-You're good to go! Time to submit a `pull request. <https://github.com/lab-cosmo/scikit-cosmo/pulls>`_
+You're good to go! Time to submit a `pull request. <https://github.com/lab-cosmo/scikit-matter/pulls>`_
 
 
 License

docs/source/datasets.rst

@@ -1,7 +1,7 @@
 Datasets
 ========
 
-.. include:: ../../skcosmo/datasets/descr/degenerate_CH4_manifold.rst
+.. include:: ../../skmatter/datasets/descr/degenerate_CH4_manifold.rst
 
-.. include:: ../../skcosmo/datasets/descr/csd-1000r.rst
+.. include:: ../../skmatter/datasets/descr/csd-1000r.rst
 

docs/source/gfrm.rst

@@ -3,7 +3,7 @@
 Reconstruction Measures
 ======================================
 
-.. currentmodule:: skcosmo.metrics
+.. currentmodule:: skmatter.metrics
 
 
 .. _GRE-api:

docs/source/index.rst

@@ -1,9 +1,9 @@
-scikit-cosmo documentation
+scikit-matter documentation
 ===========================
 
-``scikit-cosmo`` is a collection of `scikit-learn <https://scikit.org/>`_
-compatible utilities that implement methods developed in the `COSMO laboratory
-<https://cosmo.epfl.ch>`_.
+``scikit-matter`` is a collection of `scikit-learn <https://scikit.org/>`_
+compatible utilities that implement methods born out of the materials science
+and chemistry communities. 
 
 Convenient-to-use libraries such as scikit-learn have accelerated the adoption and application
 of machine learning (ML) workflows and data-driven methods. Such libraries have gained great
@@ -12,10 +12,10 @@ While developments in the atomistic learning community have put forward general-
 learning methods, their deployment is commonly entangled with domain-specific functionalities,
 preventing access to a wider audience.
 
-scikit-COSMO targets domain-agnostic implementations of methods developed in the
+scikit-matter targets domain-agnostic implementations of methods developed in the
 computational chemical and materials science community, following the
 scikit-learn API and coding guidelines to promote usability and interoperability
-with existing workflows. scikit-COSMO contains a toolbox of methods for
+with existing workflows. scikit-matter contains a toolbox of methods for
 unsupervised and supervised analysis of ML datasets, including the comparison,
 decomposition, and selection of features and samples.
 

docs/source/installation.rst

@@ -1,16 +1,16 @@
 Installation
 ============
 
-scikit-COSMO is, by design, relatively lightweight, and only requires that `numpy <numpy.org>`_
+scikit-matter is, by design, relatively lightweight, and only requires that `numpy <numpy.org>`_
 and the most recent release of `scikit-learn <scikit-learn.org>`_ be installed.
 
 Install from source 
 ###################
 
 .. code-block:: bash
 
-  git clone https://github.com/lab-cosmo/scikit-cosmo
-  cd scikit-cosmo
+  git clone https://github.com/lab-cosmo/scikit-matter
+  cd scikit-matter
   python setup.py install --user
 
-You're ready to import skcosmo from your code! Have a look at the :ref:`api-reference` for how to use the code.
+You're ready to import skmatter from your code! Have a look at the :ref:`api-reference` for how to use the code.