Scikit-maad

**Fixes:**
* Improved multiprocessing context in example.
* Corrected default plot values.
* Addressed column name issues in date_parser.
* Enhanced plot axis display.
* General fixes in plotting and template matching.
* Replaced 'selem' with 'footprint' for compatibility with scikit-image.
* Improved input validation for metadata retrieval.

**Enhancements:**
* Added metadata reading for any wav files.
* Parallelized graphical_soundscapes function.
* Enhanced verbose task execution display.
* Added local maxima detection in spectrograms.

Documentation:
* Updated examples for new date_parser.
* Refreshed version 1.4.2 documentation.
* Added new examples and images to the gallery.

**Development:**
* Universal date_parser modification.
* Introduced heatmap functions for better visualization.
* Added tests for template matching and spectrogram peaks.

We encourage users to upgrade to this latest version to take advantage of these improvements and enhancements.

We're excited to announce the release of a new minor version of our package, incorporating several enhancements, bug fixes, and documentation improvements. Here's a summary of the updates:

*Enhancements:*
- Added the possibility to read metadata from any WAV file, similar to the functionality in sox -i.
- Improved verbose display of execution of tasks.
- Added functionality to parallelize graphical soundscapes.
- Introduced a new function to find local maxima in spectrograms.
- Enhanced the verbose display of task execution.
- Added a new feature to compute graphical soundscapes.
- Included a new example for graphical soundscapes.

*Bug Fixes:*
- Fixed NaN issues for ACTmean and TFSD.
- Addressed a minor bug for plotting graphical soundscapes.
- Ensured the time column is formatted as a string.
- Resolved an issue with the time column.
- Fixed a bug when saving Audacity annotations with labels.
- Improved input validation and file search for the get_metadata_dir function.
- Fixed a bug related to plotting and removed unnecessary plt.show() calls.
- Replaced selem with footprint in scikit-image.
- Made minor adjustments to ensure generalization in the usage of the graphical_soundscape function.
- Corrected an issue with template matching function.

*Documentation:*
- Updated README.md.
- Edited docstrings for proper display with Sphinx.
- Fixed examples to work with macOS.
- Added images for the example gallery in documentation.

Additionally, various tests were adjusted and added to ensure the reliability and functionality of the package.

This new release adheres to the guidelines for a more robust, stable, and responsive package, aiming to enhance performance and enable more reproducible scientific research.

We now integrate a continuous integration and continuous development process to ensure that scikit-maad is supported on different operating systems (UNIX, Windows and MacOSX) with different versions of Python.

With this update, we can easily track deprecated functions and anticipate future releases of the required packages.

Additionally, we have addressed all the detected bugs and made necessary fixes.

In particular, we have added the following functionalities:

**New features**
Template matching: new spectrogram template matching function to easily find stereotyped signals in audio recordings.
Acoustic features: new functions to compute robust spectral (peak frequency, spectral quantiles, bandwidth) and temporal features (duration, temporal_quantile) on audio signals.

**Documentation**
The updated documentation with new functions is still here: [scikit-maad.github.io](https://scikit-maad.github.io/)

**Fixed bugs**
Ensured swift integration with latest versions of scipy, numpy, pandas and scikit-image.

**Enhancements**
We worked to meet all of the standards listed on [pyOpenSci](https://www.pyopensci.org/software-peer-review/how-to/author-guide.html)

- Advances in packaging best practices to ensure continuous integration and continuous development
- Shifted to project.toml for packaging
- CONTRIBUTING.md file: helps newcomers understand the project's contribution process and encourages active participation.
- Github workflows for testing on multiple platforms and multiple versions of Python
- Templates for reporting issues on GitHub
- Community guidelines including contribution guidelines in the CONTRIBUTING.md file

**Test**
We improved the test coverage by adding tests for most of the main functions: spectrogram, alpha_indices, shape_features, and more. We used both, pytest with specific tests and doctest that tests the examples provided for each function in the documentation.

**Note**
Be aware that the v1.4.0 may be not compatible with older versions of Python (<=3.7).

**Contributors**
We would like to extend our sincere gratitude to all the contributors who have taken the time to submit issues and provide advice. Your valuable input and feedback have been instrumental in improving our software and ensuring its continued development. Thank you for your support and for helping us create a better experience for all users. In particular, we would like to thank:

- [saguileran](https://github.com/saguileran) [Sebastian Aguilera Novoa]
- [Bengt](https://github.com/Bengt) [Bengt Lüer]
- [NickleDave](https://github.com/NickleDave) [[David Nicholson](https://github.com/NickleDave)]
- [thealejandroperilla](https://github.com/thealejandroperilla) [Gabriel Perilla]
- [pierromond](https://github.com/pierromond) [Pierre Aumond]
- [modantailleur](https://github.com/modantailleur)

This release is a minor update of the release [v1.3.6](https://github.com/scikit-maad/scikit-maad/releases/tag/1.3.6).

Update of the Xeno-Canto functions to fix the problem when a query contains the keyword "type".
The updated function xc_query now is able to deal with the new API of Xeno-Canto.

This release is a minor update of the release [v1.3.6](https://github.com/scikit-maad/scikit-maad/releases/tag/1.3.6).

This release fix minor problems in xeno-canto functions and update setup.py in order to avoid warning or error when installing scikit-maad on Google Colab.

New examples
--------
- add a new example to use multiCPU functionality to compute indices

New functionalities
-------------------
**In module util :**

Audio metadata utilities with new functions :
- check_file_format : Check Wave file consistency. Check if WAVE format is correct and if file name follows standard format. The standard format is SITENAME_DATE_TIME.WAV, with DATE as YYYYMMDD and TIME as HHMMSS
- audio_header : Get audio header information from WAVE file. Header information includes, sample rate, bit depth, number of channels, number of samples, file size and duration.
- filename_info : Get information from filename when using standard format. The standard format is SITENAME_DATE_TIME.WAV, with DATE as YYYYMMDD and TIME as HHMMSS.
- get_metadata_file : Get metadata asociated with audio recordings in audio file. Metadata includes basic information of the audio file format (sample rate, number of channels, bit depth and file size), and date information from the filename. Note however, that this function is intended for use only with audio files with a self-describing header.
- get_metadata_dir : Get metadata asociated with audio recordings in a directory. Metadata includes basic information of the audio file format (sample rate, number of channels, bit depth and file size), and date information from the filename. Note however, that this function is intended for use only with audio files with a self-describing header.

Parser
- read_raven_annot : Read raven annotations file (or labeling file) and return a Pandas Dataframe with the bounding box and the label of each region of interest (ROI). If the file exists but has no annotations, the function returns and empty dataframe.
- write_raven_annot : Write audio segmentation to text file in Audacity format, a file that can be imported and modified with Audacity. If the dataframe has no frequency delimiters, annotations are saved with standard Audacity format (temporal segmentation). If the dataframe has temporal and frequencial delimiters, the annotations are saved as spectral selection style (spectro-temporal selection). If the dataframe is empty, the function saves an empty file.

**In module sound :**

Transform the signal
- gain : Apply amplification or attenuation to the audio signal.

Minor changes
-------------------
- fix a bug in format_features
- add an argument in rand_cmap to change the seed
- fix a bug in entropy (when only zeros, entropy is 1)
- fix a bug in ADI and AEI calculation. The result is now similar to soundecology R package (see more details here :[https://github.com/scikit-maad/scikit-maad/issues/43]).
- add an optional argument to spectrogram to allow detrend to be off. This is interesting only when computing ADI and AEI
- update xeno-canto functions in order to be compliant with the new API.
- add an argument to overlay_rois in order to adapt the edge_color to the number of unique labels
- add warning in region_of_interest_index. default parameters are deprecated
- add new argument max_ratio_xy in region_of_interest_index. it defines the maximum ratio between the vertical axis (y) and horizontal axis (x) that is allowed for a ROI. This is very convenient to remove vertical spikes (e.g. rain). 10 seems a reasonable value to remove most of spikes due to light to medium rainfall.