Objects			page : 1 2 3 4
jit.streak	External		Probability lines The jit.streak object uses a specified probability to determine the chance that a given matrix cell's value will be extended to subsequent cells (with an optional scaling factor). The result is a streaky good time.
jit.textfile	External		Read and write a matrix as an ASCII text file The jit.textfile object maintains a text buffer, into which a text file or char matrix can be imported. The buffer can also be edited directly by double-clicking on the object to open an editor window. A bang to the object causes the text buffer to be sent out the left outlet as a matrix. In adapt mode, jit.textfile will analyze the file for carriage returns and deduce the probable width and height of the output matrix (always 1 plane 2 dimensional). String matrices can be output using the line message.
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.bernie	External		Generate random numbers from a Bernoulli distribution The Bernoulli distribution is based on a model of n independent trials, each of which has a probability p of succeeding. The result of a Bernoulli test is the number of successful trials, which must lie in the range 0 < x < n.
lp.ernie	External		Select items from an urn ("Finite urn" probability model) The lp.ernie object implements a very flexible general-purpose "finite urn" model. The typical finite urn model deals with colored balls in an urn. For instance, there might be three red balls, two black balls, and four white balls. Balls are removed one at a time. They are not replaced after removal. As balls are removed, the probabilities of picking each color change. The characteristics of the urn model are the concern with the changing probabilities and the fact that the total number of balls is known.
markov	Abstraction		probability based object Interface built around the prob-object of David Zicarelli. A table of transition probabilities (cf. prob.help) is sent to the right-most inlet and the start value into the middle. A bang into the left inlet outputs an element chosen from a one-dimensional markov matrix.
markov	External		Build a transition table of probabilities (Finite Markov chain)
markov-harmony	Abstraction		pitch generator An sequence of intervals that is generated by a one-dimensional markov chain. The transition probabilities of the intervals have to be sent to the right-most inlet following the conventions of the "prob"-object. The desired start interval must be sent to the middle inlet. A bang in the left inlet outputs one chosen interval.
modal_fuzzharm	External		The modal_fuzzharm object outputs a fuzzy logic chord harmonization based on incoming pitch classes. a.k.a. an auto-chord harmonizer. created by V.J. Manzo The modal_fuzzharm object outputs a fuzzy logic chord harmonization based on incoming pitch classes. The object integrates with several objects in the modal_object library including the modal_pc_match object to determine if the incoming note played is diatonic or chromatic and that notes relationship in the context of the specified tonic and mode. For example, is the incoming note scale degree 1? Is it chromatic scale degree #4? If so, how do we want to harmonize that note when we receive it? Double clicking the modal_fuzzharm object allows a user to see a table of chord symbols that the modal_triad object can interpret. The user can increase the probability weight to the table by clicking on one of the cells in the column for the desired chord/function listed in the top row. By default, all probabilities are set to zero. For example, if the incoming note matches scale degree one, you’d probably want to harmonize that note with the I chord, the IV chord and the vi chord since that scale degree one is present in all of these chords. Other chords may be used to harmonize that note as well, but you’d probably want the object to choose some chords more frequently than others, so we give them a higher table weight by clicking further down on the cells. A bang sent to the modal_fuzzharm object will choose one of the chords to harmonize that note with based on the weightings you’ve specified. The table can be opened and presets can be saved. In the help file for this object, the seven diatonic scale degrees all have modal_fuzzharm objects connected so that when one of these scale degrees is played, the note will be harmonized in any way the user specifies. A specified table file has been loaded for each modal_fuzzharm object when the help opens which illustrates some default probability settings that harmonize these notes with diatonic chord functions. created by V.J. Manzo www.vjmanzo.com | www.vincemanzo.com
MP3player (with buffer~)	External		simple mp3 (and other standard formats) player without jitter because the preloading of jit.qt.movie has several problems, I developed a supplementary solution for playing mp3 files within Max. it plays with buffer~. the interface is simple: just drag and drop the mp3 files to the "file" box, and start playback. You can scratch, fast-forward and control the speed/pitch without bounds.
Mutation	External		Mutates a List of integers The Mutation object mutates a list of numbers based on random probabilities. This object offers 5 different mutation modes.
mwc_bu	External		mwc_bu clears your max window when you send it a bang. Very usefull when debugging a patch. If you have any problem downloading the object... e-mail me and i will send it to you : tworowski@freesurf.fr. Thank you
nnLists	Javaclass (mxj)		Artificial neural network This is a Java implementation of a feed-forward back-propagation artificial neural network for Max/MSP/mxj. There is a JAR, NN.jar and an example mxj class nnLists which takes Max lists as input and output. This is probably sufficient for most purposes but specific classes could be written to deal with other data (e.g., Jitter matrices).
otudp_wrap	Abstraction		otudp wrapper with the use of an objectmapping file in the init folder using (for example) otudp becomes completely transparent on both platforms. (ok almost, otudp write has an outlet on OSX whereas udp-write on XP doesn't, that's not a problem if you don't deal with reading from the writing object).
ParticleFilter	Javaclass (mxj)		particle filter object tracking "ParticleFilter.java (mxj external) implements a (slightly simplified) version of the popular particle filtering tracking algorithm. Basically, particles of a given target sample the image. Those with high probability mass (i.e. over a target's pixel) are more likely to be sampled in the next frame. In this way, a target's particles tend to stick with it."
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Libraries
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.