Merge pull request #141 from CPJKU/develop

New release v1.0.0

.github/workflows/partitura_unittests.yml

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+name: Partitura Unittests
+
+on:
+  push:
+    branches: [master, develop]
+  pull_request:
+    branches: [master, develop]
+
+jobs:
+  test:
+    strategy:
+      max-parallel: 5
+      matrix:
+        platform: [ubuntu-latest, macos-latest, windows-latest]
+
+    runs-on: ${{ matrix.platform }}
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python 3.8
+      uses: actions/setup-python@v2
+      with:
+        python-version: 3.8
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -r requirements.txt
+        pip install .
+    - name: Run Tests
+      run: |
+        pip install coverage
+        python -m unittest discover ./tests/ 'test*.py'
+        coverage run -m unittest discover ./tests/ 'test*.py'
+        coverage xml
+
+    - name: Check coverage with CodeCov
+      uses: codecov/codecov-action@v1
+      with:
+        file: ./coverage.xml
+        verbose: true
+

.gitignore

@@ -146,3 +146,6 @@ static
 .DS_Store
 *#
 *~
+
+# vscode
+.vscode

README.md

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+[//]: # (<p align="center"> )
+
+[//]: # (<img src="./partitura/assets/partitura_logo_final.jpg" height="200">)
+
+[//]: # (</p>)
+<p align="center">
+    <img src="partitura/assets/partitura_logo_black.png#gh-light-mode-only" height="200">
+    <img align="center" src="./partitura/assets/partitura_logo_white.png#gh-dark-mode-only" height="200">
+</p>
+
+[![Latest Release](https://img.shields.io/github/v/release/cpjku/partitura)](https://github.com/cpjku/partitura/releases)
+[![Pypi Package](https://badge.fury.io/py/partitura.svg)](https://badge.fury.io/py/partitura)
+[![Unittest Status](https://github.com/CPJKU/partitura/workflows/Partitura%20Unittests/badge.svg)](https://github.com/CPJKU/partitura/actions?query=workflow%3A%22Partitura+Unittests%22)
+[![CodeCov Status](https://codecov.io/gh/CPJKU/partitura/branch/develop/graph/badge.svg?token=mnZ234sGSA)](https://codecov.io/gh/CPJKU/partitura)
+
+
+
+
+**Partitura** is a Python package for handling symbolic musical information. It
+supports loading from and exporting to *MusicXML* and *MIDI* files. It also supports loading from _Humdrum *kern*_ and *MEI*.
+
+The full documentation for `partitura` is available online at [readthedocs.org](https://partitura.readthedocs.io/en/latest/index.html).
+
+User Installation
+==========
+
+The easiest way to install the package is via `pip` from the [PyPI (Python
+Package Index)](https://pypi.python.org/pypi>):
+```shell
+pip install partitura
+```
+This will install the latest release of the package and will install all dependencies automatically.
+
+
+Quickstart
+==========
+
+The following code loads the contents of an example MusicXML file included in
+the package:
+```python
+import partitura as pt
+my_xml_file = pt.EXAMPLE_MUSICXML
+part = pt.load_score(my_xml_file)
+```
+The following shows the contents of the part:
+
+```python
+print(part.pretty())
+```
+Output:
+```shell
+Part id="P1" name="Piano"
+ │
+ ├─ TimePoint t=0 quarter=12
+ │   │
+ │   └─ starting objects
+ │       │
+ │       ├─ 0--48 Measure number=1
+ │       ├─ 0--48 Note id=n01 voice=1 staff=2 type=whole pitch=A4
+ │       ├─ 0--48 Page number=1
+ │       ├─ 0--24 Rest id=r01 voice=2 staff=1 type=half
+ │       ├─ 0--48 System number=1
+ │       └─ 0-- TimeSignature 4/4
+ │
+ ├─ TimePoint t=24 quarter=12
+ │   │
+ │   ├─ ending objects
+ │   │   │
+ │   │   └─ 0--24 Rest id=r01 voice=2 staff=1 type=half
+ │   │
+ │   └─ starting objects
+ │       │
+ │       ├─ 24--48 Note id=n02 voice=2 staff=1 type=half pitch=C5
+ │       └─ 24--48 Note id=n03 voice=2 staff=1 type=half pitch=E5
+ │
+ └─ TimePoint t=48 quarter=12
+     │
+     └─ ending objects
+         │
+         ├─ 0--48 Measure number=1
+         ├─ 0--48 Note id=n01 voice=1 staff=2 type=whole pitch=A4
+         ├─ 24--48 Note id=n02 voice=2 staff=1 type=half pitch=C5
+         ├─ 24--48 Note id=n03 voice=2 staff=1 type=half pitch=E5
+         ├─ 0--48 Page number=1
+         └─ 0--48 System number=1
+
+```
+If `lilypond` or `MuseScore` are installed on the system, the following command
+renders the part to an image and displays it:
+
+```python
+pt.render(part)
+```
+![Score example](https://raw.githubusercontent.com/CPJKU/partitura/master/docs/images/score_example.png)
+
+
+The notes in this part can be accessed through the property
+`part.notes`:
+
+```python
+part.notes
+> [<partitura.score.Note object at 0x...>, <partitura.score.Note object at 0x...>, 
+> <partitura.score.Note object at 0x...>]
+
+```
+
+
+The following code stores the start, end, and midi pitch of the notes in a numpy
+array:
+
+```python
+import numpy as np
+pianoroll = np.array([(n.start.t, n.end.t, n.midi_pitch) for n in part.notes])
+print(pianoroll)
+> [[ 0 48 69]
+>  [24 48 72]
+>  [24 48 76]]
+```
+
+
+The note start and end times are in the units specified by the
+`divisions` element of the MusicXML file. This element specifies the
+duration of a quarter note. The `divisions` value can vary within an
+MusicXML file, so it is generally better to work with musical time in
+beats.
+
+The part object has a property :`part.beat_map` that converts timeline
+times into beat times:
+
+```python
+beat_map = part.beat_map
+print(beat_map(pianoroll[:, 0]))
+> [0. 2. 2.]
+print(beat_map(pianoroll[:, 1]))
+> [4. 4. 4.]
+```
+
+
+The following commands save the part to MIDI and MusicXML, respectively:
+
+```python
+# Save Score MIDI to file.
+pt.save_score_midi(part, 'mypart.mid')
+
+# Save Score MusicXML to file.
+pt.save_musicxml(part, 'mypart.musicxml')
+```
+
+
+More elaborate examples can be found in the `documentation
+<https://partitura.readthedocs.io/en/latest/index.html>`_.
+
+Import other formats
+====================
+For **MusicXML** files do:
+
+```python
+import partitura as pt
+my_xml_file = pt.EXAMPLE_MUSICXML
+part = pt.load_musicxml(my_xml_file)
+```
+
+For **Kern** files do:
+
+```python
+import partitura as pt
+my_kern_file = pt.EXAMPLE_KERN
+part = pt.load_kern(my_kern_file)
+```
+
+For **MEI** files do:
+
+```python
+import partitura as pt
+my_mei_file = pt.EXAMPLE_MEI
+part = pt.load_mei(my_mei_file)
+```
+
+
+One can also import any of the above formats by just using:
+
+```python
+import partitura as pt
+any_score_format_path = pt.EXAMPLE_MUSICXML
+part = pt.load_score(any_score_format_path)
+```
+
+
+License
+=======
+
+The code in this package is licensed under the Apache 2.0 License. For details,
+please see the [LICENSE](LICENSE) file.
+
+
+Citing Partitura
+================
+
+If you find Partitura useful, we would appreciate if you could cite us!
+
+```
+@inproceedings{partitura_mec,
+  title={{Partitura: A Python Package for Symbolic Music Processing}},
+  author={Cancino-Chac\'{o}n, Carlos Eduardo and Peter, Silvan David and Karystinaios, Emmanouil and Foscarin, Francesco and Grachten, Maarten and Widmer, Gerhard},
+  booktitle={{Proceedings of the Music Encoding Conference (MEC2022)}},
+  address={Halifax, Canada},
+  year={2022}
+}
+```
+
+[//]: # (    | `Grachten, M. <https://maarten.grachten.eu>`__, `Cancino-Chacón, C. <http://www.carloscancinochacon.com>`__ and `Gadermaier, T. <https://www.jku.at/en/institute-of-computational-perception/about-us/people/thassilo-gadermaier/>`__)
+
+[//]: # (    | "`partitura: A Python Package for Handling Symbolic Musical Data <http://carloscancinochacon.com/documents/extended_abstracts/GrachtenEtAl-ISMIR2019-LBD-ext-abstract.pdf>`__\ ".)
+
+[//]: # (    | Late Breaking/Demo Session at the 20th International Society for)
+
+[//]: # (    Music Information Retrieval Conference, Delft, The Netherlands,)
+
+[//]: # (    2019.)
+
+
+
+Acknowledgments
+===============
+
+This project receives funding from the European Research Council (ERC) under 
+the European Union's Horizon 2020 research and innovation programme under grant 
+agreement No 101019375 ["Whither Music?"](https://www.jku.at/en/institute-of-computational-perception/research/projects/whither-music/).
+
+
+
+This work has received support from the European Research Council (ERC) under
+the European Union’s Horizon 2020 research and innovation programme under grant
+agreement No. 670035 project ["Con Espressione"](https://www.jku.at/en/institute-of-computational-perception/research/projects/con-espressione/)
+and the Austrian Science Fund (FWF) under grant P 29840-G26 (project
+["Computer-assisted Analysis of Herbert von Karajan's Musical Conducting Style"](https://karajan-research.org/programs/musical-interpretation-karajan))
+![](https://raw.githubusercontent.com/CPJKU/partitura/master/docs/images/erc_fwf_logos.jpg "Con_espressione") 
+
+[//]: # ()
+[//]: # (.. image:: https://raw.githubusercontent.com/CPJKU/partitura/master/docs/images/erc_fwf_logos.jpg)
+
+[//]: # (   :width: 600 px)
+
+[//]: # (   :scale: 1%)
+
+[//]: # (   :align: center)