histogram.py

histogram.py is a Python utility designed to analyze and visualize audio files by generating histogram charts. These charts offer insights into the mastering process of albums, revealing details like compression and soft/hard clipping, which are often not captured by traditional dynamic range meters.

Installation

To use histogram.py, ensure you have Python 3.8+ installed along with the following packages:

pip install numpy matplotlib soundfile

Usage

You can run the script from the command line as follows:

python3 histogram.py [options]

Examples

1. Process a single file:

   python3 histogram.py path/to/audio.flac

2. Process a single album folder:

   python3 histogram.py path/to/album

3. Process all album folders recursively:

   python3 histogram.py /path/to/albums --recursive

4. Specify output image size and DPI:

   python3 histogram.py /path/to/audio.flac --size 12 8 --dpi 150

5. Display the histogram in a window:

   python3 histogram.py /path/to/audio.flac --window

6. Use custom regular expression for matching files:

   python3 histogram.py /path/to/directory --match "\.wav$"

Arguments

• input: Path to a file or directory (default: current working directory).
• -f, --filename: Name of the output image file (default: histogram.png).
• -r, --recursive: Recursively process directories.
• -c, --concurrency: Number of threads to use for processing (default: 1).
• -s, --size: Output image size in inches (default: [10.24, 6.4]).
• --dpi: DPI for the output image (default: 100).
• -m, --match: Regular expression to match files (default: (?i)\\.flac$).
• -w, --window: Display histogram in a window.
• -o, --overwrite: Overwrite existing image files.

Contributing

Feel free to open issues or submit pull requests if you have ideas for improvement or encounter any bugs.