.. toctree:: :maxdepth: 2 :caption: Contents: introduction user_guide api .. image:: logo.png :width: 7cm :align: center ==================== What is audiotoolbox ? ==================== **audiotoolbox** is a python package designed to generate and analyze acoustic stimuli for use in auditory research. It aims to provide an easy to use and intuitive interface. **auditools** provides the powerfull `Signal` class which extends the standard `numpy` array class with a fluent interface that provides methods and attributes often used in auditory signal processing. The commands: >>> import audiotoolbox as audio >>> sig = audio.Signal(n_channels=1, duration=1, fs=48000) >>> sig.add_tone(500).set_dbspl(60).add_fade_window(10e-3, 'cos') create a 1 second long signal with 1 channel at a sampling rate of 48kHz. A 500 Hz tone is then added to this signal, the level is set to 60dB SPL and a 10ms raised cosine fade-in and fade-out is added. The Signal class also provides method to quickly switch between the frequency and time-domain representation of the same signal: >>> sig.add_noise() >>> f_sig = sig.to_freqdomain() >>> f_sig[f_sig.freq.abs() > 1000] = 0 >>> sig = f_sig.to_timedomain() first adds gaussian white noise to the signal and then sets all spectral components above 1kHz to zero. All Signal classes are extensions of the standard `numpy` array, they can be used as drop-in replacements. As a consequence, the Signal class also inherits all methods of `numpy.ndarray`: >>> import numpy as np >>> sig = audio.Signal(n_channels=3, duration=1, fs=48000) >>> sig.add_uncorr_noise(0.5) >>> sig.var(axis=0) Signal([1., 1., 1.]) More information and a detailed documentation of the methods and functions provided by audiotoolbox can be found in the `api` and `introduction` sections. Installation ============ Using pip ---------- You can use pip to install audiotoolbox .. code-block:: bash pip install audiotoolbox From GitHub ----------- Or directly from GitHub 1. Clone the repository: `git clone https://github.com/Jencke/audiotoolbox.git` 2. Install the package: `pip install ./` 3. Optionally run the tests: `pytest` Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search`