Objects			page : 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
ll.og	Abstraction		another scale-abstraction that takes a fifth value as logarithmic scaler.
Lmax	External		An object to compare two lists member by member and produce a list of the high values.
Lmean	External		An object to calculate the mean values between two lists, member by member. An object to calculate the mean values between two lists, member by member. The process is (x[i] +y[i])/2
Lmin	External		An object to compare two lists member by member and produce a list of the low value of each pair.
lookup~	External		Use a buffer~ for nonlinear distortion of a signal Use a buffer~ for nonlinear distortion of a signal. lookup~ allows you to use a table of samples (buffer~ object) to do waveshaping on a signal, in which the Y values of a input signal are used as X values to look up new signal values. Input values of -1 to +1 are mapped to table values between 0 (or the specified sample offset) and the size of the table.
lp.abbie	External		Generate random numbers from beta and arc sine distributions The beta distribution generates random numbers in the range 0 < x < 1. It has two parameters, a and b. These parameters are sometimes referred to in the literature as Éø and É¿ or ÉÀ and É—. The parameters control the shape of the distribution. Loosely speaking, values of a closer to zero increase the probability of small deviates (i.e., random values less than 0.5) being generated; values of b closer to zero increase the probability of large deviates (i.e., random values larger than 0.5).
lp.frrr~	External		Low-frequency noise Low-frequency noise is generated from a sequence of random values chosen at a constant rate slower than the sampling rate. In its simplest form, it functions as a noise generator passed through a sample-and-hold module. However, lp.frrr~ also allows the samples between the randomly generated values to be interpolated, either linearly or quadratically.
lp.gammer	External		Generate random numbers from Gamma and Erlang distributions The Gamma distribution has two parameters, generally referred to as order and location. It produces an asymmetrical distribution of positive random values, and is often used in musical contexts for generating rhythms. The order parameter must be positive, the location parameter may be zero or positive. The Erlang distribution is a special case of the Gamma function when the order parameter is an integer. This distribution is modeled on a process consisting of several independent exponentially-distributed sub-processes. In this case, the order parameter indicates the number of sub-processes. An Erlang distribution with order of one is equivalent to an exponential distribution.
lp.kg	External		Map I Ching values to nonstandard ranges One common way to consult the I Ching when there are less than 64 alternatives is to ask the I Ching how much weight to assign the individual choices. The I Ching is consulted for each of the choices wanted, and the hexagram values chosen are assigned as weights to each choice. Then a range of hexagram values proportional to the weight of each choice will be assigned. Thereafter, when a hexagram number is chosen from the I Ching, it is mapped to the choice with the relevant range. This process is computed for both "present" and "future" I Ching values. In lp.kg the choices are numbered starting at one.
lp.lll~	External		Parametric linear congruence "noise" "White" noise using the Linear Congruence algorithm, while allowing you to specify values for the LC parameters. See lp.lili for more information on parametric linear congruence. The lp.lll~ object works very much like lp.lili, except that the integral values produced are scaled to the range -1 < x. < 1 for signals. Note that the scaling factor is calculated relative to the mod parameter, so the maximum power range is always produced (except for LC cycles that get stuck at a constant… this can happen!). For many parameter combinations, this cycle of numbers generated may be very short. In other words, the result may be much closer to pitch than noise. There are many intermediate signals.
lp.lonnie	External		Generate random numbers from a log-normal distribution The log-normal distribution is derived from the normal (or "Gaussian") distribution. By definition, if the logarithm of a set of random variables has a normal distribution, then the variable has a log-normal distribution. Conceptually, one can think of the lognormal distribution is as the product of many independent uniform distributions (in contrast to the normal distribution, which is derived from the notion of summing independent uniform distributions). The log-normal distribution is often used to model characteristics such as income distribution, distribution of grain sizes in geological contexts, and distribution of weight or height in biological contexts. The log-normal distribution has two parameters: mean and standard deviation. Values from a log-normal distribution are positive and skewed to the right (i.e., the median is greater than the arithmetic mean.)
lp.pfishie	External		Generate random numbers from a Poisson distribution The Poisson distribution has one parameter, É…, which happens to be both the expected mean and variance. (Standard deviation is therefore É…). The Poisson distribution generates non-negative integers only. It is defined for positive real values of É…. The Poisson distribution was originally developed as an efficient means of approximating the Bernoulli distribution for special cases (to wit, when the product np is small even when n is large). It has gained considerable popularity for use in algorithmic composition, particularly due to the influence of Iannis Xenakis, who used it extensively.
lp.scampf	External		Scale, offset, and limit floating point values The core duty of lp.scampf is to multiply incoming values by a scaling factor and then to add an offset. In the following discussion this is referred to as mapping. Additionally, values may be constrained to a given range. Optionally, out-of-range values may be routed to a second outlet. If you prefer, you may specify that an arbitrary message be sent out the right outlet whenever mapped values exceed the specified range.
lp.scampi	External		Scale, offset, and limit integer values The core duty of lp.scampi is to multiply incoming values by a scaling factor and then to add an offset. In the following discussion this is referred to as mapping. Additionally, values may be constrained to a given range. Optionally, out-of-range values may be routed to a second outlet. If you prefer, you may specify that an arbitrary message be sent out the right outlet when mapped values exceed the specified range. Finally, you can specify how floating-point results are to be converted to integers. The options cover: conventional rounding, floor, ceiling, truncation (i.e., "to zero "), and "to infinity. "
lp.scamp~	External		Scale, offset, and limit signals This is your one-stop source for scaling, offsetting, and limiting signals to a different output range. The lp.scamp~ object wraps *~ and +~ into one convenient object with range-correction and splitting capabilities. The core duty of lp.scampf is to multiply incoming values by a scaling factor and then to add an offset. In the following discussion this is referred to as mapping. Additionally, values may be constrained to a given range. You can poll an lp.scamp~ object to find out how many samples were out of range.
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Libraries
BulkStore	debug: SELECT prenom, nom FROM auteurs RIGHT JOIN auteur_libraries USING (id_auteur) WHERE auteur_libraries.id_library='62'Tom Mays	bulk storage memory device for all values (any message)
FuzzyLib	debug: SELECT prenom, nom FROM auteurs RIGHT JOIN auteur_libraries USING (id_auteur) WHERE auteur_libraries.id_library='139'Alain Bonardi Isis Truck	When manipulating human knowledge such as perception, feelings, appreciation, veracity of facts, etc., the classical logic that recognize only two truth degrees (true or false) is not always the most suitable. To solve this problem, more than two degrees are considered in the non-classical logics. The fuzzy logic is one of these logics. In this logic, facts are represented through membership functions: when the membership value is equal to 1 the fact is exactly true; when it is equal to 0 the fact is exactly false; in between there is an uncertainty about the veracity of the fact. These membership functions are called "fuzzy subsets". They can be of different shapes: gaussian, trapezoidal, triangular, etc. Thus the aim of the fuzzy logic is to propose a theoretical framework for the manipulation - representation and reasoning - of such facts. The Fuzzy Lib library implements all the tools that are necessary to handle this manipulation: representation of a fuzzy subset (among them are the fuzzification, defuzzification and partitioning), reasoning process (generalized modus ponens, fuzzy implications, t-norms, t-conorms, etc.). This version 1 of the Fuzzy Lib enables to implement fuzzification, uncertain reasoning and defuzzification for any number of data in the framework of Max/MSP environment.
Litter Power Pro Package	debug: SELECT prenom, nom FROM auteurs RIGHT JOIN auteur_libraries USING (id_auteur) WHERE auteur_libraries.id_library='54'Peter Castine	The Litter Power package consists of over 60 external objects, including a number of new MSP noise sources, externals that produce values from a wide variety of random number distributions, and externals for mutation and cross-synthesis.
p.jit.gl.tools	debug: SELECT prenom, nom FROM auteurs RIGHT JOIN auteur_libraries USING (id_auteur) WHERE auteur_libraries.id_library='123' Pelado	the p.jit.gl tools are designed to provide for easier learning of and experimenting with the many attributes that are available to jitter's gl objects by making them a whole lot more transparent and accessible. patches expose jitter gl object's attributes to interfaces that allow you to immediately edit and change an attribute's value. many of the parameters are attached to blines, which provide smooth changes while rendering, and all settings can be saved and recalled as presets using the pattrs that are embedded in the patches.
Panaiotis Objects	debug: SELECT prenom, nom FROM auteurs RIGHT JOIN auteur_libraries USING (id_auteur) WHERE auteur_libraries.id_library='122' Panaiotis	The Mac version is UB. These Max objects have been enhanced since the documentation to the left was written. Help files for the objects provide information on enhancements. The matrix object has been substantially upgraded. It now combines features of unpack, spray, funnel, append, and prepend into one object. This makes a great object to place between controllers and jit objects because it acts like a multi-prepend. There are new configuration commands and enhancements to the old: even, odd, mod,and range, among others). Most commands can be applied to inlets of outlets. There is also a mute function that adds another layer of control. Matrixctrl support has been enhanced. See the help file for full details and examples. Most other objects now fully support floats. RCer and autocount will count in float values, not just integers. Notegen16 is a 16 channel version of its predecessor: notegen. It is more generalized and much more efficient.
SFA Max/MSP Library	debug: SELECT prenom, nom FROM auteurs RIGHT JOIN auteur_libraries USING (id_auteur) WHERE auteur_libraries.id_library='172'Stefano Fasciani	The SFA-MaxLib is a collection of Max/MSP objects developed in the context of the VCI4DMI. It includes functions and utilities in the form of FTM externals, FTM abstractions and Max abstractions. FTM is a shared library for Max/MSP developed by IRCAM, which provides a small and simple real-time object system and a set of optimized services to be used within Max/MSP externals. List of FTM Externals: sfa.eig - eigenvalues; sfa.inputcombinations - combination generator; sfa.levinson - levinson-durbin recursion; sfa.lpc2cep - lpc to cepstra conversion; sfa.rastafilt - rasta filter; sfa.rmd - relative mean difference; sfa.roots - polynomial roots; List of Abstractions: sfa.bark.maxpat - energy of the Bark bands from time domain frame;sfa.bark2hz_vect.maxpat - Herts to Bark conversion;sfa.barkspect.maxpat - energy of the Bark bands from spectrum; sfa.ceil.maxpat - ceil function; sfa.featfluxgate.maxpat - gated distance on stream of feature vectors; sfa.fft2barkmx.maxpat - utility sub-abstraction of sfa.bark; sfa.fft2barkmxN.maxpat - utility sub-abstraction of sfa.barkspect; sfa.hynek_eq_coeff.maxpat - hynek equalization coefficients; sfa.hz2bark.maxpat - Hertz to Bark conversion; sfa.hz2bark_vect.maxpat - Hertz to Bark conversion for vectors; sfa.hz2mel.maxpat - Hertz to Mel conversion; sfa.idft_real_coeff.maxpat - utility sub-abstraction of sfa.rasta-plp; sfa.maxminmem.maxpat - minimum and maximum of a stream of data; sfa.mfcc.maxpat - MFCC coefficients; sfa.modalphafilter.maxpat - 1st order IIR lowpass on a stream of vectors; sfa.nonlinfeqscale.maxpat - linear spectrum to Bark or Mel scale conversion; sfa.rasta-plp.maxpat - PLP and RASTA-PLP coefficients; sfa.spectmoments.maxpat - 4 spectral moments (centroid, deviation, skewness, kurtosis); sfa.3spectmoments+flatness.maxpat - 3 spectral moments (centroid, deviation, skewness) and the spectral flatness; sfa.spectralflux.maxpat - spectral flux on stream of spectrum vectors; sfa.spectralfluxgate.maxpat - gated spectral flux on stream of spectrum vectors; sfa.std.maxpat - standard deviation; sfa.win_to_fft_size.maxpat - smaller FFT size given frame size; sfa.GCemulator.maxpat – 3D gestural controller emulator;
suivi	debug: SELECT prenom, nom FROM auteurs RIGHT JOIN auteur_libraries USING (id_auteur) WHERE auteur_libraries.id_library='88' Ircam	Two externals performing score following on soloist performances using Hidden Markov Models (HMM) Suivi is based on FTM and requires the shared library FTMlib for Max/MSP. Both externals use an FTM track object - a sequence of time-tagged FTM values - to store the score of the soloist performance to be followed. Notes, trills and other elements of the score are represented by FTM score objects (FTM scoob class). For the moment, scores can be imported from standard MIDI files only. An editor for the FTM track class, which will also provide a graphical control interface for the score follower is under development as well as the import of MusicXML files. The suivi object set is distributed within the IRCAM Forum.