' + 106 | '' + 107 | _("Hide Search Matches") + 108 | "
" 109 | ) 110 | ); 111 | }, 112 | 113 | /** 114 | * helper function to hide the search marks again 115 | */ 116 | hideSearchWords: () => { 117 | document 118 | .querySelectorAll("#searchbox .highlight-link") 119 | .forEach((el) => el.remove()); 120 | document 121 | .querySelectorAll("span.highlighted") 122 | .forEach((el) => el.classList.remove("highlighted")); 123 | localStorage.removeItem("sphinx_highlight_terms") 124 | }, 125 | 126 | initEscapeListener: () => { 127 | // only install a listener if it is really needed 128 | if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; 129 | 130 | document.addEventListener("keydown", (event) => { 131 | // bail for input elements 132 | if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; 133 | // bail with special keys 134 | if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; 135 | if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { 136 | SphinxHighlight.hideSearchWords(); 137 | event.preventDefault(); 138 | } 139 | }); 140 | }, 141 | }; 142 | 143 | _ready(SphinxHighlight.highlightSearchWords); 144 | _ready(SphinxHighlight.initEscapeListener); 145 | -------------------------------------------------------------------------------- /docs/build/html/getting_started.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 |With Python >= 3.6, you can install libf0 using the Python package manager pip:
pip install libf0
93 | For development, testing, or generating the API documentation, clone the git repository and install:
99 |git clone https://github.com/groupmm/libf0.git
100 | cd libf0
101 | pip install -e .[dev,tests,docs]
102 | libf0 is a Python toolbox for fundamental frequency (F0) estimation in music recordings.
If you use this toolbox, please cite:
86 |Sebastian Rosenzweig, Simon Schwär, and Meinard Müller. libf0: A Python Library for Fundamental Frequency Estimation. In Late Breaking Demos of the International Society for Music Information Retrieval Conference (ISMIR), Bengaluru, India, 2022.
89 |To reference the original algorithms implemented in this toolbox, please cite:
92 |Alain De Cheveigné and Hideki Kawahara: YIN, a fundamental frequency estimator for speech and music, The Journal of the Acoustical Society of America 111.4 (2002): 1917-1930.
95 |Matthias Mauch and Simon Dixon: PYIN: A fundamental frequency estimator using probabilistic threshold distributions, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2014): 659-663.
98 |Justin Salamon and Emilia Gómez: Melody Extraction From Polyphonic Music Signals Using Pitch Contour Characteristics, IEEE Transactions on Audio, Speech, and Language Processing, vol. 20, no. 6, pp. 1759–1770, 2012.
101 |Arturo Camacho and John G. Harris: A sawtooth waveform inspired pitch estimator for speech and music. The Journal of the Acoustical Society of America, vol. 124, no. 3, pp. 1638–1652, 2008
104 |Meinard Müller. Fundamentals of Music Processing – Using Python and Jupyter Notebooks. Springer Verlag, 2nd edition, 2021. ISBN 978-3-030-69807-2. doi: 10.1007/978-3-030-69808-9.
107 |Slim and didactical implementation of a sawtooth waveform inspired pitch estimator (SWIPE). 100 | This version uses a log-frequency spectrogram instead of ERB filters. Furthermore, it is implemented more 101 | efficiently. See swipe() for the original implementation.
102 |A. Camacho and J. G. Harris, 105 | “A sawtooth waveform inspired pitch estimator for speech and music.” 106 | The Journal of the Acoustical Society of America, vol. 124, no. 3, pp. 1638–1652, Sep. 2008
107 |x (ndarray) – Audio signal
Fs (int) – Sampling rate
H (int) – Hop size
F_min (float or int) – Minimal frequency
F_max (float or int) – Maximal frequency
R (float) – resolution of the pitch candidate bins in cents (default = 10)
strength_threshold (float) – confidence threshold [0, 1] for the pitch detection (default value = 0)
f0 (ndarray) – Estimated F0-trajectory
t (ndarray) – Time axis
conf (ndarray) – Confidence / Pitch Strength
Compute a SWIPE’ kernel.
136 |f (float) – Frequency in Hz
F_coef_log_hz – Logarithmic frequency axis in Hz
k – Kernel
145 |ndarray
148 |Returns a set of prime numbers, adapted from http://rebrained.com/?p=458
156 |upto (int) – Find prime numbers up to this number
159 |A set of prime numbers including 1 & 2
162 |Sonification of trajectory with sinusoidal. Adapted from FMP notebook: C8/C8S2_FundFreqTracking.ipynb
99 |f0 (ndarray) – F0-trajectory
t (ndarray) – Time axis
audio_len (int) – Desired audio length in samples
confidence (None or ndarray) – Confidence values for amplitude control
Fs (int) – Sampling rate
smooth_len (int) – Smoothing filter length to avoid clicks in the sonification
x_soni – Sonified F0-trajectory
112 |ndarray
115 |Converts frequency in Hz to cents.
123 |F (float or ndarray) – Frequency value in Hz
F_ref (float) – Reference frequency in Hz (Default value = 55.0)
F_cents – Frequency in cents
132 |float or ndarray
135 |Converts frequency in cents to Hz.
143 |F_cents (float or ndarray) – Frequency in cents
F_ref (float) – Reference frequency in Hz (Default value = 55.0)
F – Frequency in Hz
152 |float or ndarray
155 || 92 | l | ||
| 96 | |
97 | libf0 | 98 | |
| 101 | |
102 | libf0.pyin | 103 | |
| 106 | |
107 | libf0.salience | 108 | |
| 111 | |
112 | libf0.swipe | 113 | |
| 116 | |
117 | libf0.swipe_slim | 118 | |
| 121 | |
122 | libf0.utils | 123 | |
| 126 | |
127 | libf0.yin | 128 | |
