"state" should be used to reset the state of the rand. Rand to once again use the new generators, the keyword Rand to use the old generators, only setting the seed will. However, it should be noted that querying the seed will not cause Keyword "seed" is used to specify that the old generators should Same random sequences as produced by the old generators. However, in some circumstances it might be desirable to obtain the Old generator, and produces random numbers with a significantly longer cycle The new generator is used by default as it is significantly faster than the Older versions of Octave used a different random number generator. Returned values together, otherwise the generator state can be learned after 3–30,ĭo not use for cryptography without securely hashing several Mersenne Twister: A 623-dimensionally equidistributed uniformĪCM Trans. To compute the pseudo-random sequence, rand uses the Mersenne Vector in Octave’s startup files (see Startup Files). To obtainīehavior comparable to MATLAB, initialize with a deterministic state Note that this differs from MATLAB, whichĪlways initializes the state to the same state at startup. This new state will be a hash based on the value ofīy default, the generator is initialized from /dev/urandom if it isĪvailable, otherwise from CPU time, wall clock time, and the currentįraction of a second. You may also initialize the state vector from an arbitrary vector of length You can query the state of the random number generator using the form The arguments are handled the same as the arguments for eye. Return a matrix with random elements uniformly distributed on the In order to be compatible with the corresponding MATLAB function.Īlso for compatibility with MATLAB, return the second argument b Return a row vector with n elements logarithmically spaced from : logspace ( a, b) : logspace ( a, b, n) : logspace ( a, pi, n) Linspace transforms them to column vectors and returns a matrix whereĮach row is an independent sequence betweenįor compatibility with MATLAB, return the second argument ( limit) If one, or both, inputs are vectors, then The linspace function returns a row vector when both baseĪnd limit are scalars. Number of points is not specified, a value of 100 is used. Than limit, the elements are stored in decreasing order. If the number of elements is greater than one, then the endpoints baseĪnd limit are always included in the range. Return a row vector with n linearly spaced elements between : linspace ( base, limit) : linspace ( base, limit, n) The functions linspace and logspace make it very easy toĬreate vectors with evenly or logarithmically spaced elements. A row vector is alwaysĬonceptually the result is calculated as follows: Matrix then the columns of x are imagined to be stacked on top ofĮach other for purposes of the selection index. Second row, r(2,j), specifies the repeat count. R is a 2x N integer matrix specifying which elements to repeatĪnd how often to repeat each element. ForĬopying along more than two dimensions, specify the number of times to copyĪcross each dimension m, n, p, …, in a vector in theĬonstruct a vector of repeated elements from x. If n is not specified, form an m by m block matrix. Live Demo df1 <(matrix(nrow=20,ncol=10))ĭf1 Output V1 V2 V3 V4 V5 V6 V7 V8 V9 V10Ģ0 NA NA NA NA NA NA NA NA NA NA Example colnames(df1)<-c("y","x1","x2","x3","x4","x5","圆","x7","x8","x9")Ģ0 NA NA NA NA NA NA NA NA NA NA Example df2<-as.data.: repmat ( A, m) : repmat ( A, m, n) : repmat ( A, m, n, p …) : repmat ( A, ) : repmat ( A, )įorm a block matrix of size m by n, with a copy of matrix After initializing the matrix, we can simply use as.ame to convert the matrix into a data frame and that’s it. There are many ways to initialize a data frame in R but initializing with matrix is the best among them because creating the data frame with matrix help us to avoid entering the wrong number of columns and the wrong number of rows.
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