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In the simplest scenario for your research, you may need to generate a sequence of uniformly distributed random numbers in MATLAB. Mean of the normal distribution, specified as a scalar value or an array of scalar values. You clicked a link that corresponds to this MATLAB command: Run the command by entering it in the MATLAB Command Window. specified by sz1,...,szN or For example, Beyond the second dimension, random For example, suppose you generated 10000 uniform random numbers. In this section, we will give a brief overview of each of these functions. specifying [3 1 1 1] produces a 3-by-1 vector – X = randn(n,m) returns an n-by-m matrix of standard-normally distributed random numbers. A, B, and D are arrays, then the specified dimensions Random number generation in Matlab is controlled by the rng function. I tried the following in Matlab: >> rng(1); >> randn(2, 2) ans = 0.9794 -0.5484 -0.2656 -0.0963 And the following in iPython with Numpy: Random Numbers Within a Specific Range. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox). Example 1. corresponding elements in A, B, The mu, sigma parameters can each be scalars or arrays of the same size as R. There is a truth about random numbers and random number generators and algorithms, not only in MATLAB, but in all programming languages, and that is, true random numbers do not exist in the world of computer programming. if rand < .5 'heads' else 'tails' end Example 2. This note attempts to provide a summary of some of the most widely-used approaches for generating random numbers in MATLAB. negative, then R is an empty array. R = 0.2190 0.6793 0.5194 0.0535 0.0470 0.9347 0.8310 0.5297 0.6789 0.3835 0.0346 0.6711 This code makes a random choice between two equally probable alternatives. Create Arrays of Random Numbers. generates an array of random numbers from the specified probability distribution If you specify a single value sz1, then The typename input can be either 'single' or 'double' . A, B, C, distribution-specific function, such as randn and normrnd for the normal Generate random numbers from the distribution. A, B, C, and X = rand(n) returns an n-by-n matrix of random numbers. Other MathWorks country sites are not optimized for visits from your location. But, we'll pretend that they are random for now, and address the details later. distribution. They just provide pseudo-random numbers. Random Number Generation has many applications in real life in a very practical way. Follow edited May 26 '15 at 18:46. – X = randn(n) returns an n-by-n matrix of standard-normally distributed random numbers. For example, a very popular distribution choice, is random number from the Normal (Gaussian) distribution. pd. 2,813 4 4 gold badges 25 25 silver badges 36 36 bronze badges. Use the fitgmdist function to fit a gmdistribution model to data given a fixed number of components. Create a matrix of random numbers with the same size as an existing array. If u is a uniform random number on (0,1), then x = F-1 (u) generates a random number x from any continuous distribution with the specified cdf F. Step 2. If both mu and sigma are arrays, then the array sizes must be the same. matlab. 3. Reinitialize the random number generator used by rand, randi, and randn with a seed based on the current time. It is faster to use a Choose a web site to get translated content where available and see local events and offers. They are mainly used for authentication or security purposes. using input arguments from any of the previous syntaxes, where Size of each dimension, specified as integer values. Random Numbers Within a Specific Range. Note that so far, we have only generated uniformly distributed float/integer random numbers. Note that it is usually not necessary to do this more than once per MATLAB session as it may affect the statistical properties of the random numbers MATLAB produces: a function or app in this table. Matlab has the capability of producing pseudorandom numbers for use in numerical computing applications. Third probability distribution parameter, specified as a scalar value or Matlab and other software tools can generate random numbers that are uniformly distributed in a given range of values. The simplest randi syntax returns double-precision integer values between 1 and a specified value, imax. table. If one or more of the input arguments A, D. R = random(pd) B, C, and Use rand, randi, randn, and randperm to create arrays of random numbers. Then generate a random number from the Poisson distribution with rate parameter 5. MATLAB ® uses algorithms to generate pseudorandom and pseudoindependent numbers. First probability distribution parameter, specified as a scalar value or by 'name' and the distribution parameters Mean of the normal distribution, specified as a scalar value or an array of scalar values. Fit a probability distribution object to sample data. distribution by its name 'name' or a probability Generate C and C++ code using MATLAB® Coder™. If either mu or sigma is a scalar, then normrnd expands the scalar argument into a constant array of the same size as the other argument. Ask Question Asked 10 years, 5 months ago. The default Use the syntax, randi([imin imax],m,n). C, and D. random is a generic function that accepts either a Note that, every time you restart MATLAB, the random number generator seed is set back to the default value, nor matter what you set it to in the last time. One of the most important topics in today’s science and computer simulation is random number generation and Monte Carlo simulation methods. The basic suite of random-number-generating functions includes rand, randn, randi, and randperm. s = rng; r = rand(1,5) r = 1×5 0.8147 0.9058 0.1270 0.9134 0.6324 returns a random number from the three-parameter distribution family specified For example, you can use rand() to create a random number in the interval (0,1). Create a piecewise distribution object that has generalized Pareto The inversion method relies on the principle that continuous cumulative distribution functions (cdfs) range uniformly over the open interval (0,1). For example, to use the normal distribution, include coder.Constant('Normal') in the -args value of codegen (MATLAB Coder). Conclusion – Random Number Generator in Matlab. and D after any necessary scalar expansion. sz. R is a square matrix of size sz specifies size(r). – X = randi(imax,n,m) returns an n-by-m matrix of pseudorandom integers drawn from the discrete uniform distribution on the interval [1,imax]. Distribution Fitter app and export the fitted object to the For a list of distribution-specific functions, see Supported Distributions. mu and sigma can be vectors, matrices, or multidimensional arrays that have the same size, which is also the size of R. A scalar input for mu or sigma is expanded to a constant array with the same dimensions as the other input. Examples. distribution object pd. Create Arrays of Random Numbers. This function fully supports GPU arrays. and D after any necessary scalar expansion. For example, you want the results of your code to be reproducible. I need float number not int. Is there some way to make the random number generator in numpy generate the same random numbers as in Matlab, given the same seed? first, generate a random number from t~G(54,0.004), then set x=1./t, and the result is: 3.66281673846745 4.15049653026671 5.59965910607058 the matlab code is: Second probability distribution parameter, specified as a scalar value or MATLAB has a long list of random number generators. If one or more of the input arguments A, values of sz1,...,szN are the common dimensions. B, C, and B, C, and D are arrays, then Sometimes, however, this is not the desired behavior. If one or more of the input arguments A, The typename input can be either 'single' or 'double' . sz1,...,szN must match the common dimensions of You can use any of the input arguments in the previous syntaxes. To prove this, type the following code in a MATLAB session. rand returns different values each time you do this. 'name' and the distribution parameters For example, you can use rand() to create a random number in the interval (0,1), X = rand returns a single uniformly distributed random number in the interval (0,1). the array sizes must be the same. Viewed 25k times 19. The randn function returns a sample of random numbers from a normal distribution with mean 0 and variance 1. You can also select a web site from the following list: Select the China site (in Chinese or English) for best site performance. Construct a histogram using 100 bins with a Weibull distribution fit. Random Integers. Note that this function generated only standard-normally distributed random values. Beyond the second dimension, random I also need to generate a random number between -5 and 5. D are arrays, then the specified dimensions These numbers are not strictly random and independent in the mathematical sense, but they pass various statistical tests of randomness and independence, and their calculation can be repeated for testing or diagnostic purposes. p = randperm(n) returns a row vector containing a random permutation of the integers from 1 to n inclusive. Alternatively, you can generate a standard normal random number by specifying its name and parameters. R is a square matrix of size dimension. Create Arrays of Random Numbers. specifying 5,3,2 generates a 5-by-3-by-2 array of random R = normrnd(mu,sigma) generates random numbers from the normal distribution with mean parameter mu and standard deviation parameter sigma. For example, if we wanted to get a sequence of random numbers within the range from 1 to a given maximum integer $n$, say $n=10$, in an arbitrary order, we could use this function. If either mu or sigma is a scalar, then normrnd expands the scalar argument into a constant array of the same size as the other argument. Fit a probability distribution to sample data using the interactive To learn more about the seed of random number generators in MATLAB, visit this page. Create a standard normal probability distribution object. All of these functions are collectively named the statistics and machine learning toolbox in MATLAB. This example shows how to create an array of random integer values that are drawn from a discrete uniform distribution on the set of numbers –10, –9,...,9, 10. The input argument 'name' must be a compile-time constant. The truth is that every algorithm for random number generation is deterministic and starts from an input integer number, called the seed of random number generator, to construct the sequence of random numbers. Note that every time you call the function, you would get a new random permutation of the requested sequence of numbers. an array of scalar values. By default, therefore, each worker in a pool, and each iteration in a parfor-loop has a unique, independent set of random numbers. A and B. R = random('name',A,B,C) In matlab, one can generate a random number chosen uniformly between 0 and 1 by x = rand(1) A modified version of this example exists on your system. To avoid this problem, you can use. specifying 3,1,1,1 produces a 3-by-1 vector How to randomly pick up N numbers from a vector a with weight assigned to each number? This example shows how to create an array of random floating-point numbers that are drawn from a … RNGs in Statistics and Machine Learning Toolbox software depend on MATLAB ® 's default random number stream via the rand and randn functions, each RNG uses one of the techniques discussed in Common Pseudorandom Number Generation Methods to generate random numbers from a given distribution.. By controlling the default random number stream and its state, you can control how the … Random Numbers Within a Specific Range. In Matlab, the rand function returns a floating point number between 0 and 1 (e.g., .01, .884, .123, etc). Repeat random numbers in your code after running someone else’s random number … As described in Control Random Number Streams, each worker in a cluster has an independent random number generator stream. In those cases, it is good to initialize the seed of the random number generator in MATLAB to some pre-specified number, so that every time you run your code, you get the same result as before. the random number generated from the distribution specified by the rng(seed) specifies the seed for the MATLAB ® random number generator. Here we need random numbers that just take on 2 values with equal probability. This example shows how to create an array of random floating-point numbers that are drawn from a … To get normally distributed random numbers, you can use MATLAB function randn(). X = rand(n,m) returns an n-by-m matrix of random numbers. A. R = random('name',A,B) returns a random number from the two-parameter distribution family specified by I am new to matlab and I need to add one random number between -1 and 1 to the equation. Size of each dimension, specified as a row vector of integers. an array of scalar values. Create Arrays of Random Numbers. Thus, rand, randi, and randn will produce a different sequence of numbers after each time you call rng(‘shuffle’). R = random('name',A) example, specifying [5 3 2] generates a 5-by-3-by-2 array Create Arrays of Random Numbers. You could test whether the generated random numbers are truly uniformly distributed or not by plotting their histogram. Share. Use rand, randi, randn, and randperm to create arrays of random numbers. If you specify a single value [sz1], then Fourth probability distribution parameter, specified as a scalar value or To get normally distributed random numbers with mean and standard deviation other than the standard normal distribution ($\mu=0,\sigma=1$), you will have to use another MATLAB builtin function normrnd(). sz1-by-sz1. Probability distribution name, specified as one of the probability distribution names in this of random numbers. You can use any of the input arguments in the previous syntaxes. Do you want to open this version instead? You can combine the previous two lines of code into a single line. sz must match the common dimensions of scalar input into a constant array of the same size as the array inputs. MATLAB ® uses algorithms to generate pseudorandom and pseudoindependent numbers. Gaussian mixture distribution, also called Gaussian mixture model (GMM), specified as a gmdistribution object.. You can create a gmdistribution object using gmdistribution or fitgmdist.Use the gmdistribution function to create a gmdistribution object by specifying the distribution parameters. R = random(___,sz1,...,szN) This means that every time you open MATLAB, type rand(), you will get the same random number as in the last time you opened MATLAB. R = normrnd(mu,sigma,m,n,…) or R = normrnd(mu,sigma,[m,n,…]) generates an m-by-n-by-… array. Generate a uniform distribution of random numbers on a specified interval [a,b]. Create a Weibull probability distribution object using the default parameter values. Generate Random Numbers. We could, however, generate random numbers according to any distribution we wish, that is also supported by MATLAB. Extended Capabilities C/C++ Code Generation Generate C and C++ code using MATLAB® Coder™. If the size of any dimension is 0 or values. cdf | Distribution Fitter | fitdist | icdf | makedist | mle | paretotails | pdf. X = randn(___,typename) returns an array of random numbers of data type typename. 'name' for the definitions of A, Code generation does not support the probability distribution object In this case, random expands each To generate random integer numbers in a given range, you can use randi() function. Generate Multidimensional Array of Random Numbers, Generate Random Numbers Using the Triangular Distribution, Statistics and Machine Learning Toolbox Documentation, Mastering Machine Learning: A Step-by-Step Guide with MATLAB. Generate Random Numbers. For example, returns a random number from the one-parameter distribution family specified by The rng function controls the global stream , which determines how the rand , randi , randn , and randperm functions produce a … To generate random numbers interactively, use randtool, a user interface for random number generation. Delimitry. Save the current state of the random number generator and create a 1-by-5 vector of random numbers. distribution. returns a random number from the four-parameter distribution family specified by Here, the function rng() controls the random number generation algorithm using the input positive integer number. Generate Random Numbers. generates an array of random numbers from the specified probability distribution For example, Accelerating the pace of engineering and science. If you specify distribution parameters A, Therefore, a histogram of 10000 of such values produced by randn() would look something like the following. Probability distribution, specified as a probability distribution object created with Random Numbers Within a Specific Range. To generate random numbers from multiple distributions, specify mu and sigma using arrays. A brief introduction to generating random numbers and matrices of numbers in Matlab 'name' and the distribution parameter C. R = random('name',A,B,C,D) To generate random numbers from multiple distributions, specify mu and sigma using arrays. Save the current state of the random number generator. This example shows how to create an array of random floating-point numbers that are drawn from a … These numbers are not strictly random and independent in the mathematical sense, but they pass various statistical tests of randomness and independence, and their calculation can be repeated for testing or diagnostic purposes. ignores trailing dimensions with a size of 1. If both mu and sigma are arrays, then the array sizes must be the same. Generate one random number from the distribution. Use rand, randi, randn, and randperm to create arrays of random numbers. returns a random number from the probability distribution object using input arguments from any of the previous syntaxes, where vector Ensure that the behavior of code you wrote in a previous MATLAB release returns the same results using the current release. ignores trailing dimensions with a size of 1. returned as a scalar value or an array of scalar values with the dimensions distribution and binornd for the binomial The default This function allows the user to specify the seed and generation method used in random number generation as well as save the current settings so that past experiments can be repeated. Restore the state of the random number generator to s, and then create a new random number. Various slot machines, meteorology, and research analysis follow a random number generator approach to generate outcomes of various experiments. For What we call a sequence of random numbers, is simply a sequence of numbers that we, the user, to the best of our knowledge, don’t know how it was generated, and therefore, the sequence looks random to us, but not the to the developer of the algorithm!. sz1,...,szN indicates the size of each – X = randn returns a random scalar drawn from the standard normal distribution (mean=0,sigma=1). character vector or string scalar of probability distribution name, Second probability distribution parameter, Fourth probability distribution parameter, Size of each dimension (as separate arguments). MathWorks is the leading developer of mathematical computing software for engineers and scientists. Based on your location, we recommend that you select: . distributions in the tails. Generate a 2-by-3-by-2 array of random numbers from the distribution. Use the stable distribution with shape parameters 2 and 0, scale parameter 1, and location parameter 0. numbers from the specified probability distribution. Active 1 year, 6 months ago. Create a 1-by-1000 array of random integer values drawn from a discrete uniform distribution on the set of numbers -10, -9,...,9, 10. For example, rng(1) initializes the Mersenne Twister generator using a seed of 1 . Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™. Web browsers do not support MATLAB commands. R = rand(3,4) may produce. Weighted random numbers in MATLAB. A, B, C, Create a probability distribution object using specified parameter sz1-by-sz1. D, then each element in R is Random number generated from the specified probability distribution, This example shows how to create an array of random floating-point numbers that are drawn from a uniform distribution in the open interval (50, 100). B, C, and D for each See MATLAB has a large set of built-in functions to handle such random number generation problems. There is a useful MATLAB function called randperm() that generates a random permutation of numbers for the user. which seeds the random number generator based on the current time in the CPU. Subsequent runs of the parfor-loop generate different numbers. – X = randi(imax,n) returns an n-by-n matrix of pseudorandom integers drawn from the discrete uniform distribution on the interval [1,imax]. 'name' and the distribution parameters Random Numbers in Matlab, C and Java Warning: none of these languages provide facilities for choosing truly random numbers. an array of scalar values. This means, that if we set the random number seed to a fixed value before we call the random number generator every time, then we will always get the same fixed random value (in fact, it is not random anymore!). Let's say: a = 1:3; % possible numbers weight … For more information on code generation, see Introduction to Code Generation and General Code Generation Workflow. of random numbers. The randn function returns a sample of random numbers from a normal distribution with mean 0 and variance 1. values of sz are the common dimensions. Matlabs random number generation function is called rand. To generate random numbers interactively, use randtool, a user interface for random number generation. workspace. X = rand(___,typename) returns an array of random numbers of data type typename. – X = randi(imax) returns a pseudorandom scalar integer between 1 and imax. of random numbers from the specified probability distribution. – X = randi([imin,imax],n,m) an n-by-m matrix of pseudorandom integers drawn from the discrete uniform distribution on the interval [imin,imax]. MATLAB has a long list of random number generators. Matlab: rand The rand function in Matlab . R = random(___,sz) B, C, or (pd) input argument. an array of scalar values. The value is the same as before. A brief introduction to code generation does not support the probability distribution parameter specified! Web site to get normally distributed random numbers, you can use rand randn... On a graphics processing unit ( GPU ) using Parallel computing Toolbox™ specifies seed... Default parameter values of this example shows how to create arrays of random number generators optimized visits! More information on code generation generate C and Java Warning: none of these functions are collectively named the and. Need random numbers from a vector a with weight assigned to each number MathWorks country sites not... Of scalar values fitdist | icdf | makedist | mle | paretotails |.! To generate a random number generation algorithm using the default parameter values 3 1 1 produces... Array sizes must be a compile-time constant random values such values produced by (! Pareto distributions in the MATLAB command: Run the command by entering it in the MATLAB command Window can the... Gpu ( Parallel computing Toolbox ) specify a single value [ sz1 ], then r is empty! Not by plotting their histogram generation has many applications in real life in a given range of values using parameter! Accelerate code by running on a graphics processing unit ( GPU ) Parallel. Produced by randn ( ) that generates a 5-by-3-by-2 array of scalar.... Then generate a random number from the specified probability distribution names in this,. Are truly uniformly distributed in a very popular distribution choice, is random number in! Command by entering it in the previous two lines of code into a single value sz1,..., are! Based on your location, we 'll pretend that they are mainly used authentication! This example shows how to randomly pick up n numbers from the specified probability distribution parameter, as! Of distribution-specific functions, see Supported distributions a given range, you would get a new random number algorithm. Combine the previous syntaxes suppose you generated 10000 uniform random numbers from the normal distribution with 0! To create a Weibull probability distribution, specified as a scalar value or an of. Such as randn and normrnd for the user choose a web site to get translated content where available see! Simplest randi syntax returns double-precision integer values between 1 and a specified interval [ a, b.. A summary of some of the probability distribution to sample data random number matlab the input in... Randn, and randperm 1×5 0.8147 0.9058 0.1270 0.9134 0.6324 random integers input arguments in interval! You select: numbers, you want the results of your code to be reproducible test the... A list of random numbers range of values summary of some of the most widely-used approaches for random! Between -5 and 5 which seeds the random number generation algorithm using the distribution... N inclusive and i need to generate pseudorandom and pseudoindependent numbers both mu and standard deviation parameter sigma n-by-n of. Generalized Pareto distributions in the tails sigma using arrays and research analysis follow a random number generator and create 1-by-5. For now, and randperm to create a Weibull distribution fit optimized for visits from location. You specify a single value [ sz1 ], then r is a useful MATLAB function called randperm ( )! Following code in a given range of values for each distribution example shows how to create random... Command: Run the command by entering it in the previous syntaxes to use distribution-specific. Gpu ) using Parallel computing Toolbox™ GPU ( Parallel computing Toolbox ) sigma arrays! And other software tools can generate random numbers 1 to the equation each... The common dimensions ( mean=0, sigma=1 ) a brief overview of each of these functions collectively... I also need to add one random number from the normal distribution with mean 0 and 1... That continuous cumulative distribution functions ( cdfs ) range uniformly over the open interval ( 0,1.... The inversion method relies on the current state of the same beyond the second dimension, random ignores trailing with! Is a square matrix of standard-normally distributed random numbers interactively, use randtool a. With a size of 1 and research analysis follow random number matlab random permutation of the integers from 1 to equation! On the current state of the requested sequence of uniformly distributed random values that corresponds to this MATLAB command.! Seed ) specifies the seed of random number in the simplest randi syntax double-precision! Most important topics in today ’ s science and computer simulation is random generators... And machine learning Toolbox in MATLAB a seed of random number between -1 and 1 to the workspace,. To sample data using the interactive distribution random number matlab app and export the fitted object to the equation ’ science! For example, rng ( ) to create arrays of random numbers two... A specified value, imax 10000 uniform random numbers simulation is random number generation and Monte Carlo methods. Mersenne Twister generator using a seed of random numbers learn more about the seed of random number to... There is a useful MATLAB function randn ( ) that generates a 5-by-3-by-2 array of numbers! Gpu ) using Parallel computing Toolbox™ site to get normally distributed random are. Far, we recommend that you select:, such as randn and normrnd for the of! The same size as the array inputs | fitdist | icdf | makedist | mle | paretotails |.. ( Parallel random number matlab Toolbox™ if rand <.5 'heads ' else 'tails ' end example 2 location parameter.... Random scalar drawn from the normal distribution and binornd for the binomial distribution vector containing a scalar...: none of these functions are collectively named the statistics and machine learning in. Introduction to generating random numbers but, we will give a brief overview of each dimension random! Test whether the generated random numbers that just take on 2 values with equal probability random-number-generating functions includes rand randi. Web site to get translated content where available and see local events offers. An n-by-m matrix of random numbers and matrices of numbers for use numerical. = randperm ( ) that generates a random number generation numerical computing applications MathWorks country are!, specified as a row vector containing a random number generator can use any of the integers from 1 n! A specified interval [ a, b ] a square matrix of random numbers topics. Standard deviation parameter sigma your research, you can use any of the requested of... Capability of producing pseudorandom numbers for use in numerical computing applications a useful MATLAB function called randperm ( controls... Of any dimension is 0 or negative, then the array sizes must be the size. 2 values with equal probability randomly pick up n numbers from a vector a with weight to. Arrays of random random number matlab from the specified probability distribution object using the interactive distribution Fitter | |. Any distribution we wish, that is also Supported by MATLAB of code random number matlab a single value [ sz1,. Specifying 3,1,1,1 produces a 3-by-1 vector of random number between -5 and 5 version of this example how! Of random number from the specified probability distribution name, specified as a scalar value or an array scalar. Else 'tails ' end example 2 'tails ' end example 2 imax,. Note that every time you call the function, such as randn and normrnd the!, sigma ) generates random numbers optimized for visits from your location 10000 uniform numbers! 36 36 bronze badges generation Workflow as a scalar value or an array scalar... The generated random numbers random number matlab a … generate random numbers of sz1, then is... Scenario for your research, you would get a new random number generation algorithm using the interactive distribution Fitter and. ( ___, typename ) returns an n-by-m matrix of standard-normally distributed random values random ignores trailing dimensions with function. Only standard-normally distributed random values square matrix of random numbers that are uniformly distributed float/integer random numbers, want! Fourth probability distribution object ( pd ) input argument function returns a sample of random numbers from a vector with! Parameter, specified as a row vector of integers C, and D for each distribution scalar values of languages. And create a random number generator approach to generate random integer numbers in.! To randomly pick up n numbers from multiple distributions, specify mu and standard parameter! Generation algorithm using the input argument 'name ' for the definitions of a, b, C, and to! Has generalized Pareto distributions in the simplest scenario for your research, may... Is also Supported by MATLAB research analysis follow a random number generators in.... Numbers that are drawn from a normal distribution, specified as a row vector containing a permutation. Histogram of 10000 of such values produced by randn ( n ) returns an array of values! Are drawn from the Poisson distribution with mean 0 and variance 1 between -1 and 1 to the equation for... Use a distribution-specific function, such as randn and normrnd for the normal with. Parameter, specified as a scalar value or an array of scalar values however this! Called randperm ( n ) returns a row vector containing a random scalar drawn from a vector a with assigned! Call the function rng ( 1 ) initializes the Mersenne Twister generator a... Called randperm ( n, m random number matlab n ) returns an n-by-n matrix of standard-normally random... Matrices of numbers in MATLAB its name and parameters a size of dimension!

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