de.sciss.strugatzki.SelfSimilarity
The ceiling cross correlation value corresponding to the maximally bright color.
The ceiling cross correlation value corresponding to the maximally bright color. Should be less than or equal to 1, and greater than zero. The smaller the value, the earlier clipping occurs, and the more the colors are 'dragged' towards brighter values.
Whether the color scale should be inverted (true) or not (false).
Whether the color scale should be inverted (true) or not (false).
A warp factor (exponent) applied to the cross correlations before conversion to a color value.
A warp factor (exponent) applied to the cross correlations before conversion to a color value. Somewhat like a gamma correction. Values smaller than 1 produce brighter images, values greater than 1 produce darker images.
The color scheme to use for the image.
The color scheme to use for the image. Either of GrayScale and PsychoOptical
The size of the sliding window over which the features are correlated.
The size of the sliding window over which the features are correlated. That is, for a length of 1.0 second (given in sample frames, hence 44100 for a sample rate of 44100 Hz), at any given point in time, 0.5 seconds left of that point are correlated with 0.5 seconds right of that point.
The database folder is merely used to retrieve the normalization file,
given that normalize is true.
The database folder is merely used to retrieve the normalization file,
given that normalize is true.
A decimation factor to produce smaller image size.
A decimation factor to produce smaller image size. A factor of 1 means each frame step is performed, a factor of 2 means every second frame is skipped, a factor of 3 means only one in three frames is considered, and so forth.
The file to which the self similarity matrix image is written.
The file to which the self similarity matrix image is written.
The XML file holding the extractor parameters corresponding to the audio input file.
The XML file holding the extractor parameters corresponding to the audio input file. The audio input file's feature vector output file is determined from this meta file.
Whether to apply normalization to the features (recommended)
Whether to apply normalization to the features (recommended)
An option which restricts the calculation to a given span within the input file.
An option which restricts the calculation to a given span within the
input file. If None, the whole file is considered.
The balance between the feature of loudness curve and spectral composition (MFCC).
The balance between the feature of loudness curve and spectral composition (MFCC). A value of 0.0 means the segmentation is only performed by considering the spectral features, and a value of 1.0 means the segmentation is taking only the loudness into consideration. Values in between give a measure that takes both features into account with the given priorities.