view gmm_baseline_experiments/external_libs/librosa/CHANGELOG.md @ 5:b523456082ca tip

Update path to dataset and reflect modified chunk naming convention.

Changes
=======

##v0.3.1

Bug fixes
    
  - Fixed bug #117: `librosa.segment.agglomerative` now returns a numpy.ndarray instead of a list
  - Fixed bug #115: off-by-one error in `librosa.core.load` with fixed duration
  - Fixed numerical underflow errors in `librosa.decompose.hpss`
  - Fixed bug #104: `librosa.decompose.hpss` failed with silent, complex-valued input
  - Fixed bug #103: `librosa.feature.estimate_tuning` fails when no bins exceed the threshold

Features

  - New function `librosa.core.get_duration()` computes the duration of an audio signal 
    or spectrogram-like input matrix
  - `librosa.util.pad_center` now accepts multi-dimensional input

Other changes

  - Adopted the ISC license
  - Python 3 compatibility via futurize
  - Fixed issue #102: segment.agglomerative no longer depends on the deprecated 
    Ward module of sklearn; it now depends on the newer Agglomerative module.
  - Issue #108: set character encoding on all source files
  - Added dtype persistence for resample, stft, istft, and effects functions

##v0.3.0

Bug fixes

  - Fixed numpy array indices to force integer values
  - `librosa.util.frame` now warns if the input data is non-contiguous
  - Fixed a formatting error in `librosa.display.time_ticks()`
  - Added a warning if `scikits.samplerate` is not detected

Features

  - New module `librosa.chord` for training chord recognition models
  - Parabolic interpolation piptracking `librosa.feature.piptrack()`
  - `librosa.localmax()` now supports multi-dimensional slicing
  - New example scripts
  - Improved documentation
  - Added the `librosa.util.FeatureExtractor` class, which allows librosa functions
    to act as feature extraction stages in `sklearn`
  - New module `librosa.effects` for time-domain audio processing
  - Added demo notebooks for the `librosa.effects` and `librosa.util.FeatureExtractor`
  - Added a full-track audio example, `librosa.util.example_audio_file()`
  - Added peak-frequency sorting of basis elements in `librosa.decompose.decompose()`

Other changes

  - Spectrogram frames are now centered, rather than left-aligned.  This removes the
    need for window correction in `librosa.frames_to_time()`
  - Accelerated constant-Q transform `librosa.cqt()`
  - PEP8 compliance
  - Removed normalization from `librosa.feature.logfsgram()`
  - Efficiency improvements by ensuring memory contiguity 
  - `librosa.logamplitude()` now supports functional reference power, in addition
    to scalar values
  - Improved `librosa.feature.delta()`
  - Additional padding options to `librosa.feature.stack_memory()`
  - `librosa.cqt` and `librosa.feature.logfsgram` now use the same parameter
    formats `(fmin, n_bins, bins_per_octave)`.
  - Updated demo notebook(s) to IPython 2.0
  - Moved `perceptual_weighting()` from `librosa.feature` into `librosa.core`
  - Moved `stack_memory()` from `librosa.segment` into `librosa.feature`
  - Standardized `librosa.output.annotation` input format to match `mir_eval`
  - Standardized variable names (e.g., `onset_envelope`).

##v0.2.1

Bug fixes

  - fixed an off-by-one error in `librosa.onset.onset_strength()`
  - fixed a sign-flip error in `librosa.output.write_wav()`
  - removed all mutable object default parameters

Features

  - added option `centering` to `librosa.onset.onset_strength()` to resolve frame-centering issues with sliding window STFT
  - added frame-center correction to `librosa.core.frames_to_time()` and `librosa.core.time_to_frames()`
  - added `librosa.util.pad_center()`
  - added `librosa.output.annotation()`
  - added `librosa.output.times_csv()`
  - accelerated `librosa.core.stft()` and `ifgram()`
  - added `librosa.util.frame` for in-place signal framing
  - `librosa.beat.beat_track` now supports user-supplied tempo
  - added `librosa.util.normalize()`
  - added `librosa.util.find_files()`
  - added `librosa.util.axis_sort()`
  - new module: `librosa.util()`
  - `librosa.filters.constant_q` now support padding
  - added boolean input support for `librosa.display.cmap()`
  - speedup in `librosa.core.cqt()`

Other changes

  - optimized default parameters for `librosa.onset.onset_detect`
  - set `librosa.filters.mel` parameter `n_mels=128` by default
  - `librosa.feature.chromagram()` and `logfsgram()` now use power instead of energy
  - `librosa.display.specshow()` with `y_axis='chroma'` now labels as `pitch class`
  - set `librosa.core.cqt` parameter `resolution=2` by default
  - set `librosa.feature.chromagram` parameter `octwidth=2` by default

## v0.2.0

Bug fixes

  - fixed default `librosa.core.stft, istft, ifgram` to match specification
  - fixed a float->int bug in peak_pick
  - better memory efficiency
  - `librosa.segment.recurrence_matrix` corrects for width suppression
  - fixed a divide-by-0 error in the beat tracker
  - fixed a bug in tempo estimation with short windows
  - `librosa.feature.sync` now supports 1d arrays
  - fixed a bug in beat trimming
  - fixed a bug in `librosa.core.stft` when calculating window size
  - fixed `librosa.core.resample` to support stereo signals

Features

  - added filters option to cqt
  - added window function support to istft
  - added an IPython notebook demo
  - added `librosa.features.delta` for computing temporal difference features
  - new `examples` scripts:  tuning, hpss
  - added optional trimming to `librosa.segment.stack_memory`
  - `librosa.onset.onset_strength` now takes generic spectrogram function `feature` 
  - compute reference power directly in `librosa.core.logamplitude`
  - color-blind-friendly default color maps in `librosa.display.cmap`
  - `librosa.core.onset_strength` now accepts an aggregator
  - added `librosa.feature.perceptual_weighting`
  - added tuning estimation to `librosa.feature.chromagram`
  - added `librosa.core.A_weighting`
  - vectorized frequency converters
  - added `librosa.core.cqt_frequencies` to get CQT frequencies
  - `librosa.core.cqt` basic constant-Q transform implementation
  - `librosa.filters.cq_to_chroma` to convert log-frequency to chroma
  - added `librosa.core.fft_frequencies`
  - `librosa.decompose.hpss` can now return masking matrices
  - added reversal for `librosa.segment.structure_feature`
  - added `librosa.core.time_to_frames`
  - added cent notation to `librosa.core.midi_to_note`
  - added time-series or spectrogram input options to `chromagram`, `logfsgram`, `melspectrogram`, and `mfcc`
  - new module: `librosa.display`
  - `librosa.output.segment_csv` => `librosa.output.frames_csv`
  - migrated frequency converters to `librosa.core`
  - new module: `librosa.filters`
  - `librosa.decompose.hpss` now supports complex-valued STFT matrices
  - `librosa.decompose.decompose()` supports `sklearn` decomposition objects
  - added `librosa.core.phase_vocoder`
  - new module: `librosa.onset`; migrated onset strength from `librosa.beat`
  - added `librosa.core.pick_peaks`
  - `librosa.core.load()` supports offset and duration parameters
  - `librosa.core.magphase()` to separate magnitude and phase from a complex matrix
  - new module: `librosa.segment`

Other changes

  - `onset_estimate_bpm => estimate_tempo`
  - removed `n_fft` from `librosa.core.istft()`
  - `librosa.core.mel_frequencies` returns `n_mels` values by default
  - changed default `librosa.decompose.hpss` window to 31
  - disabled onset de-trending by default in `librosa.onset.onset_strength`
  - added complex-value warning to `librosa.display.specshow`
  - broke compatibilty with `ifgram.m`; `librosa.core.ifgram` now matches `stft`
  - changed default beat tracker settings
  - migrated `hpss` into `librosa.decompose`
  - changed default `librosa.decompose.hpss` power parameter to `2.0`
  - `librosa.core.load()` now returns single-precision by default
  - standardized `n_fft=2048`, `hop_length=512` for most functions
  - refactored tempo estimator

## v0.1.0

Initial public release.