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Statistical Models

  • fluid.knnregressor The fluid.knnregressor object performs K-Nearest Neighbours regression, enabling the prediction of outputs by finding the weighted average of neighboring data points within datasets.
  • fluid.stats The fluid.stats object calculates the rolling mean and sample standard deviation for multichannel control inputs over a specified window.
  • commonality The commonality object calculates the 'Pitch Commonality' between three or more specified pitches.
  • anal The anal object calculates and stores transition probabilities between sequences of numbers, primarily for implementing Markov Chains.
  • fluid.standardize The fluid.standardize object rescales a FluidDataSet by transforming its data to have a mean of 0 and a standard deviation of 1 for each dimension.
  • gendyn~ The gendyn~ object implements Dynamic Stochastic Synthesis, generating waveforms where each point's amplitude and frequency evolve via a random walk.
  • fluid.pca fluid.pca performs Principal Component Analysis (PCA) on a fluid.dataset to reduce dimensionality, such as transforming 13 MFCC values into 2.
  • fluid.bufspectralshape The fluid.bufspectralshape object computes seven spectral shape descriptors (centroid, spread, skewness, kurtosis, rolloff, flatness, crest) from an audio source.
  • fluid.skmeans fluid.skmeans implements the K-means clustering algorithm with cosine similarity.
  • kalman The kalman object implements a simple, linear, one-dimensional Kalman filter.
  • prob The prob object generates a weighted series of random numbers based on a first-order Markov chain.
  • fluid.kmeans The fluid.kmeans object implements the K-means clustering algorithm, used to group data points from a fluid.dataset into a specified number of clusters.
  • brown The brown object generates pseudo-random numbers following a bounded Brownian motion, producing a control signal that takes small, random steps within a defined range.
  • fluid.normalize The fluid.normalize object normalizes a fluid.dataset or a single data point.
  • fluid.nmfmorph~ The fluid.nmfmorph~ object performs cross-synthesis between two audio sources using Nonnegative Matrix Factorization (NMF) and Optimal Transport (OT).
  • fluid.robustscale The fluid.robustscale object applies robust scaling to fluid.dataset objects.
  • fluid.bufstats The fluid.bufstats object calculates various statistical descriptors (e.g., mean, standard deviation, skewness, kurtosis, pitch) from segments within an audio buffer.
  • fluid.mds The fluid.mds object performs Multidimensional Scaling (MDS) for dimensionality reduction on a fluid.dataset.
  • histo The histo object records the frequency of received positive integers, creating a histogram.
  • markov The markov object generates sequences based on learned patterns, creating Markov chains of any order from floats, symbols, or lists.
  • fluid.bufnmfcross fluid.bufnmfcross reconstructs a target sound by using components learned from a source sound through Non-negative Matrix Factorization (NMF).
  • median The median object calculates the median value of a given list of numbers.