help elmat Elementary matrices and matrix manipulation. Elementary matrices. zeros - Zeros array. ones - Ones array. eye - Identity matrix. repmat - Replicate and tile array. linspace - Linearly spaced vector. logspace - Logarithmically spaced vector. freqspace - Frequency spacing for frequency response. meshgrid - X and Y arrays for 3-D plots. accumarray - Construct an array with accumulation. : - Regularly spaced vector and index into matrix. Basic array information. size - Size of array. length - Length of vector. ndims - Number of dimensions. numel - Number of elements. disp - Display matrix or text. isempty - True for empty array. isequal - True if arrays are numerically equal. isequaln - True if arrays are numerically equal, treating NaNs as equal. Matrix manipulation. cat - Concatenate arrays. reshape - Reshape array. diag - Diagonal matrices and diagonals of matrix. blkdiag - Block diagonal concatenation. tril - Extract lower triangular part. triu - Extract upper triangular part. fliplr - Flip matrix in left/right direction. flipud - Flip matrix in up/down direction. flip - Flip the order of elements. rot90 - Rotate matrix 90 degrees. : - Regularly spaced vector and index into matrix. find - Find indices of nonzero elements. end - Last index. sub2ind - Linear index from multiple subscripts. ind2sub - Multiple subscripts from linear index. bsxfun - Binary singleton expansion function. Multi-dimensional array functions. ndgrid - Generate arrays for N-D functions and interpolation. permute - Permute array dimensions. ipermute - Inverse permute array dimensions. shiftdim - Shift dimensions. circshift - Shift array circularly. squeeze - Remove singleton dimensions. Array utility functions. isscalar - True for scalar. isvector - True for vector. isrow - True for row vector. iscolumn - True for column vector. ismatrix - True for matrix. Special variables and constants. eps - Floating point relative accuracy. realmax - Largest positive floating point number. realmin - Smallest positive floating point number. intmax - Largest positive integer value. intmin - Smallest integer value. flintmax - Largest consecutive integer in floating point format. pi - 3.1415926535897.... i - Imaginary unit. inf - Infinity. nan - Not-a-Number. isnan - True for Not-a-Number. isinf - True for infinite elements. isfinite - True for finite elements. j - Imaginary unit. Specialized matrices. compan - Companion matrix. gallery - Test matrices. hadamard - Hadamard matrix. hankel - Hankel matrix. hilb - Hilbert matrix. invhilb - Inverse Hilbert matrix. magic - Magic square. pascal - Pascal matrix. peaks - A sample function of two variables. rosser - Classic symmetric eigenvalue test problem. toeplitz - Toeplitz matrix. vander - Vandermonde matrix. wilkinson - Wilkinson's eigenvalue test matrix. help tril tril Extract lower triangular part. tril(X) is the lower triangular part of X. tril(X,K) is the elements on and below the K-th diagonal of X . K = 0 is the main diagonal, K > 0 is above the main diagonal and K < 0 is below the main diagonal. See also triu, diag. Overloaded methods: gf/tril codistributed/tril gpuArray/tril sym/tril Reference page in Help browser doc tril doc help plot plot Linear plot. plot(X,Y) plots vector Y versus vector X. If X or Y is a matrix, then the vector is plotted versus the rows or columns of the matrix, whichever line up. If X is a scalar and Y is a vector, disconnected line objects are created and plotted as discrete points vertically at X. plot(Y) plots the columns of Y versus their index. If Y is complex, plot(Y) is equivalent to plot(real(Y),imag(Y)). In all other uses of plot, the imaginary part is ignored. Various line types, plot symbols and colors may be obtained with plot(X,Y,S) where S is a character string made from one element from any or all the following 3 columns: b blue . point - solid g green o circle : dotted r red x x-mark -. dashdot c cyan + plus -- dashed m magenta * star (none) no line y yellow s square k black d diamond w white v triangle (down) ^ triangle (up) < triangle (left) > triangle (right) p pentagram h hexagram For example, plot(X,Y,'c+:') plots a cyan dotted line with a plus at each data point; plot(X,Y,'bd') plots blue diamond at each data point but does not draw any line. plot(X1,Y1,S1,X2,Y2,S2,X3,Y3,S3,...) combines the plots defined by the (X,Y,S) triples, where the X's and Y's are vectors or matrices and the S's are strings. For example, plot(X,Y,'y-',X,Y,'go') plots the data twice, with a solid yellow line interpolating green circles at the data points. The plot command, if no color is specified, makes automatic use of the colors specified by the axes ColorOrder property. By default, plot cycles through the colors in the ColorOrder property. For monochrome systems, plot cycles over the axes LineStyleOrder property. Note that RGB colors in the ColorOrder property may differ from similarly-named colors in the (X,Y,S) triples. For example, the second axes ColorOrder property is medium green with RGB [0 .5 0], while plot(X,Y,'g') plots a green line with RGB [0 1 0]. If you do not specify a marker type, plot uses no marker. If you do not specify a line style, plot uses a solid line. plot(AX,...) plots into the axes with handle AX. plot returns a column vector of handles to lineseries objects, one handle per plotted line. The X,Y pairs, or X,Y,S triples, can be followed by parameter/value pairs to specify additional properties of the lines. For example, plot(X,Y,'LineWidth',2,'Color',[.6 0 0]) will create a plot with a dark red line width of 2 points. Example x = -pi:pi/10:pi; y = tan(sin(x)) - sin(tan(x)); plot(x,y,'--rs','LineWidth',2,... 'MarkerEdgeColor','k',... 'MarkerFaceColor','g',... 'MarkerSize',10) See also plottools, semilogx, semilogy, loglog, plotyy, plot3, grid, title, xlabel, ylabel, axis, axes, hold, legend, subplot, scatter. Overloaded methods: phytree/plot clustergram/plot HeatMap/plot channel.plot sfit/plot cfit/plot iddata/plot idnlhw/plot idnlarx/plot mpc/plot frd/plot dspdata.plot LinearModel/plot timeseries/plot wdectree/plot ntree/plot dtree/plot wvtree/plot rwvtree/plot edwttree/plot Reference page in Help browser doc plot doc plot j = -4 j = -4 j = -4; j = -4; h = 5; j = -4, h = 5, z = 12 j = -4 h = 5 z = 12 j = -4, h = 5; z = 12 j = -4 z = 12 pi ans = 3.141592653589793 format long format short pi ans = 3.1416 format long help format format Set output format. format with no inputs sets the output format to the default appropriate for the class of the variable. For float variables, the default is format SHORT. format does not affect how MATLAB computations are done. Computations on float variables, namely single or double, are done in appropriate floating point precision, no matter how those variables are displayed. Computations on integer variables are done natively in integer. Integer variables are always displayed to the appropriate number of digits for the class, for example, 3 digits to display the INT8 range -128:127. format SHORT and LONG do not affect the display of integer variables. format may be used to switch between different output display formats of all float variables as follows: format SHORT Scaled fixed point format with 5 digits. format LONG Scaled fixed point format with 15 digits for double and 7 digits for single. format SHORTE Floating point format with 5 digits. format LONGE Floating point format with 15 digits for double and 7 digits for single. format SHORTG Best of fixed or floating point format with 5 digits. format LONGG Best of fixed or floating point format with 15 digits for double and 7 digits for single. format SHORTENG Engineering format that has at least 5 digits and a power that is a multiple of three format LONGENG Engineering format that has exactly 16 significant digits and a power that is a multiple of three. format may be used to switch between different output display formats of all numeric variables as follows: format HEX Hexadecimal format. format + The symbols +, - and blank are printed for positive, negative and zero elements. Imaginary parts are ignored. format BANK Fixed format for dollars and cents. format RAT Approximation by ratio of small integers. Numbers with a large numerator or large denominator are replaced by *. format may be used to affect the spacing in the display of all variables as follows: format COMPACT Suppresses extra line-feeds. format LOOSE Puts the extra line-feeds back in. Example: format short, pi, single(pi) displays both double and single pi with 5 digits as 3.1416 while format long, pi, single(pi) displays pi as 3.141592653589793 and single(pi) as 3.1415927. format, intmax('uint64'), realmax shows these values as 18446744073709551615 and 1.7977e+308 while format hex, intmax('uint64'), realmax shows them as ffffffffffffffff and 7fefffffffffffff respectively. The HEX display corresponds to the internal representation of the value and is not the same as the hexadecimal notation in the C programming language. See also disp, display, isnumeric, isfloat, isinteger. Reference page in Help browser doc format pi ans = 3.141592653589793 pi = 5.0 pi = 5 pi pi = 5 sqrt(-1) ans = 0.000000000000000 + 1.000000000000000i i ans = 0.000000000000000 + 1.000000000000000i for i=1:10, pi=i, end pi = 1 pi = 2 pi = 3 pi = 4 pi = 5 pi = 6 pi = 7 pi = 8 pi = 9 pi = 10 i i = 10 j j = -4 help clear clear Clear variables and functions from memory. clear removes all variables from the workspace. clear VARIABLES does the same thing. clear GLOBAL removes all global variables. clear FUNCTIONS removes all compiled MATLAB and MEX-functions. clear ALL removes all variables, globals, functions and MEX links. clear ALL at the command prompt also clears the base import list. clear IMPORT clears the base import list. It can only be issued at the command prompt. It cannot be used in a function. clear CLASSES is the same as clear ALL except that class definitions are also cleared. If any objects exist outside the workspace (say in userdata or persistent in a locked program file) a warning will be issued and the class definition will not be cleared. clear CLASSES must be used if the number or names of fields in a class are changed. clear JAVA is the same as clear ALL except that java classes on the dynamic java path (defined using JAVACLASSPATH) are also cleared. clear VAR1 VAR2 ... clears the variables specified. The wildcard character '*' can be used to clear variables that match a pattern. For instance, clear X* clears all the variables in the current workspace that start with X. clear -REGEXP PAT1 PAT2 can be used to match all patterns using regular expressions. This option only clears variables. For more information on using regular expressions, type "doc regexp" at the command prompt. If X is global, clear X removes X from the current workspace, but leaves it accessible to any functions declaring it global. clear GLOBAL X completely removes the global variable X. clear GLOBAL -REGEXP PAT removes global variables that match regular expression patterns. Note that to clear specific global variables, the GLOBAL option must come first. Otherwise, all global variables will be cleared. clear FUN clears the function specified. If FUN has been locked by MLOCK it will remain in memory. Use a partial path (see PARTIALPATH) to distinguish between different overloaded versions of FUN. For instance, 'clear inline/display' clears only the INLINE method for DISPLAY, leaving any other implementations in memory. clear ALL, clear FUN, or clear FUNCTIONS also have the side effect of removing debugging breakpoints and reinitializing persistent variables since the breakpoints for a function and persistent variables are cleared whenever the program file changes or is cleared. Use the functional form of clear, such as clear('name'), when the variable name or function name is stored in a string. Examples for pattern matching: clear a* % Clear variables starting with "a" clear -regexp ^b\d{3}$ % Clear variables starting with "b" and % followed by 3 digits clear -regexp \d % Clear variables containing any digits See also clearvars, who, whos, mlock, munlock, persistent, import. Reference page in Help browser doc clear clear(pi) {Error using clear Argument must contain a string. } clear("pi") clear("pi") | {Error: The input character is not valid in MATLAB statements or expressions. } clear('pi') clear('i') pi ans = 3.141592653589793 i ans = 0.000000000000000 + 1.000000000000000i M=[1, 2, 3, 4] M = 1 2 3 4 help who who List current variables. who lists the variables in the current workspace. In a nested function, variables are grouped into those in the nested function and those in each of the containing functions. who displays only the variables names, not the function to which each variable belongs. For this information, use WHOS. In nested functions and in functions containing nested functions, even unassigned variables are listed. WHOS lists more information about each variable. who GLOBAL and WHOS GLOBAL list the variables in the global workspace. who -FILE FILENAME lists the variables in the specified .MAT file. who ... VAR1 VAR2 restricts the display to the variables specified. The wildcard character '*' can be used to display variables that match a pattern. For instance, who A* finds all variables in the current workspace that start with A. who -REGEXP PAT1 PAT2 can be used to display all variables matching the specified patterns using regular expressions. For more information on using regular expressions, type "doc regexp" at the command prompt. Use the functional form of who, such as who('-file',FILE,V1,V2), when the filename or variable names are stored in strings. S = who(...) returns a cell array containing the names of the variables in the workspace or file. You must use the functional form of who when there is an output argument. Examples for pattern matching: who a* % Show variable names starting with "a" who -regexp ^b\d{3}$ % Show variable names starting with "b" % and followed by 3 digits who -file fname -regexp \d % Show variable names containing any % digits that exist in MAT-file fname See also whos, clear, clearvars, save, load. Overloaded methods: Simulink.who Reference page in Help browser doc who help whos whos List current variables, long form. whos is a long form of WHO. It lists all the variables in the current workspace, together with information about their size, bytes, class, etc. In a nested function, variables are grouped into those in the nested function and those in each of the containing functions, each group separated by a line of dashes. In nested functions and in functions containing nested functions, even uninitialized variables are listed. whos GLOBAL lists the variables in the global workspace. whos -FILE FILENAME lists the variables in the specified .MAT file. whos ... VAR1 VAR2 restricts the display to the variables specified. The wildcard character '*' can be used to display variables that match a pattern. For instance, whos A* finds all variables in the current workspace that start with A. whos -REGEXP PAT1 PAT2 can be used to display all variables matching the specified patterns using regular expressions. For more information on using regular expressions, type "doc regexp" at the command prompt. Use the functional form of whos, such as whos('-file',FILE,V1,V2), when the filename or variable names are stored in strings. S = whos(...) returns a structure with the fields: name -- variable name size -- variable size bytes -- number of bytes allocated for the array class -- class of variable global -- logical indicating whether variable is global sparse -- logical indicating whether value is sparse complex -- logical indicating whether value is complex nesting -- struct with the following two fields: function -- name of function where variable is defined level -- nesting level of the function persistent -- logical indicating whether variable is persistent You must use the functional form of whos when there is an output argument. Examples for pattern matching: whos a* % Show variable names starting with "a" whos -regexp ^b\d{3}$ % Show variable names starting with "b" % and followed by 3 digits whos -file fname -regexp \d % Show variable names containing any % digits that exist in MAT-file fname See also who, clear, clearvars, save, load. Overloaded methods: Simulink.whos Reference page in Help browser doc whos who('M') Your variables are: M whos('M') Name Size Bytes Class Attributes M 1x4 32 double M=[1; 2; 3; 4] M = 1 2 3 4 whos('M') Name Size Bytes Class Attributes M 4x1 32 double v = [1 2 3 4] v = 1 2 3 4 v' ans = 1 2 3 4 v' ans = 1 2 3 4 v' * rand(4,4) {Error using * Inner matrix dimensions must agree. } v * rand(4,4) ans = 2.993125505133373 4.187749025342196 4.625464538532768 3.909039601286396 M = [1 2; 3, 4] M = 1 2 3 4 A = [M M] A = 1 2 1 2 3 4 3 4 A = [1 2 3; 4 5 6]; B = [-1 -1; -2 -2]; C = [A B; B B B] {Error using vertcat Dimensions of matrices being concatenated are not consistent. } C = [A B zeros(2,1); B B B] C = 1 2 3 -1 -1 0 4 5 6 -2 -2 0 -1 -1 -1 -1 -1 -1 -2 -2 -2 -2 -2 -2 rand(3) ans = 0.602843089382083 0.117417650855806 0.424166759713807 0.711215780433683 0.296675873218327 0.507858284661118 0.221746734017240 0.318778301925882 0.085515797090044 rand(3,1) ans = 0.262482234698333 0.801014622769739 0.029220277562146 rand(3,1,2) ans(:,:,1) = 0.928854139478045 0.730330862855453 0.488608973803579 ans(:,:,2) = 0.578525061023439 0.237283579771521 0.458848828179931 rand(3,4,2) ans(:,:,1) = 0.963088539286913 0.231594386708524 0.679135540865748 0.987982003161633 0.546805718738968 0.488897743920167 0.395515215668593 0.037738866239552 0.521135830804001 0.624060088173690 0.367436648544477 0.885168008202475 ans(:,:,2) = 0.913286827639239 0.261871183870716 0.136553137355370 0.653757348668560 0.796183873585212 0.335356839962797 0.721227498581740 0.494173936639270 0.098712278655574 0.679727951377338 0.106761861607241 0.779051723231275 help randn randn Normally distributed pseudorandom numbers. R = randn(N) returns an N-by-N matrix containing pseudorandom values drawn from the standard normal distribution. randn(M,N) or randn([M,N]) returns an M-by-N matrix. randn(M,N,P,...) or randn([M,N,P,...]) returns an M-by-N-by-P-by-... array. randn returns a scalar. randn(SIZE(A)) returns an array the same size as A. Note: The size inputs M, N, P, ... should be nonnegative integers. Negative integers are treated as 0. R = randn(..., CLASSNAME) returns an array of normal values of the specified class. CLASSNAME can be 'double' or 'single'. R = randn(..., 'like', Y) returns an array of normal values of the same class as Y. The sequence of numbers produced by randn is determined by the settings of the uniform random number generator that underlies RAND, randn, and RANDI. randn uses one or more uniform random values to create each normal random value. Control that shared random number generator using RNG. Examples: Example 1: Generate values from a normal distribution with mean 1 and standard deviation 2. r = 1 + 2.*randn(100,1); Example 2: Generate values from a bivariate normal distribution with specified mean vector and covariance matrix. mu = [1 2]; Sigma = [1 .5; .5 2]; R = chol(Sigma); z = repmat(mu,100,1) + randn(100,2)*R; Example 3: Reset the random number generator used by RAND, RANDI, and randn to its default startup settings, so that randn produces the same random numbers as if you restarted MATLAB. rng('default'); randn(1,5) Example 4: Save the settings for the random number generator used by RAND, RANDI, and randn, generate 5 values from randn, restore the settings, and repeat those values. s = rng z1 = randn(1,5) rng(s); z2 = randn(1,5) % z2 contains exactly the same values as z1 Example 5: Reinitialize the random number generator used by RAND, RANDI, and randn with a seed based on the current time. randn will return different values each time you do this. NOTE: It is usually not necessary to do this more than once per MATLAB session. rng('shuffle'); randn(1,5) See Updating Your Random Number Generator Syntax to use RNG to replace randn with the 'seed' or 'state' inputs. See also rand, randi, rng, RandStream, RandStream/randn Overloaded methods: RandStream/randn distributed/randn codistributor2dbc/randn codistributor1d/randn codistributed/randn gpuArray/randn Reference page in Help browser doc randn zeros(4) ans = 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ones(5) ans = 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 eye(6) ans = 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1:24 ans = Columns 1 through 16 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Columns 17 through 24 17 18 19 20 21 22 23 24 1:2:24 ans = 1 3 5 7 9 11 13 15 17 19 21 23 1:pi/12:pi ans = Columns 1 through 4 1.000000000000000 1.261799387799149 1.523598775598299 1.785398163397448 Columns 5 through 8 2.047197551196597 2.308996938995747 2.570796326794897 2.832595714594046 Column 9 3.094395102393195 1:24 ans = Columns 1 through 16 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Columns 17 through 24 17 18 19 20 21 22 23 24 M = [1 2 3; 4 5 6; 7 8 9] M = 1 2 3 4 5 6 7 8 9 diag(M) ans = 1 5 9 diag([1 2 3]) ans = 1 0 0 0 2 0 0 0 3 diag(diag(M)) ans = 1 0 0 0 5 0 0 0 9 M * eye(3) ans = 1 2 3 4 5 6 7 8 9 M .* eye(3) ans = 1 0 0 0 5 0 0 0 9 M M = 1 2 3 4 5 6 7 8 9 B = rand(3); M / B ans = -3.507947441095616 4.804876571953198 -0.936055892057272 -3.962351571685273 9.650584479768664 -2.119379985531626 -4.416755702274931 14.496292387584131 -3.302704079005980 M ./ B ans = 1.398528873826621 5.985102133870892 98.228783419999871 4.426146946947474 7.155677742352986 8.063711271287477 7.857024562712113 40.442884633339929 17.999192354992754 M M = 1 2 3 4 5 6 7 8 9 M(1,2) ans = 2 M(2,1) ans = 4 M(1,4) {Index exceeds matrix dimensions. } M(1,4) = 4 M = 1 2 3 4 4 5 6 0 7 8 9 0 M(4,4) = -1 M = 1 2 3 4 4 5 6 0 7 8 9 0 0 0 0 -1 M(6,6) = 10 M = 1 2 3 4 0 0 4 5 6 0 0 0 7 8 9 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 M(4,:) ans = 0 0 0 -1 0 0 M(:,1) ans = 1 4 7 0 0 0 M(:,-1) {Subscript indices must either be real positive integers or logicals. } M(:,end-1) ans = 0 0 0 0 0 0 M(:,end) ans = 0 0 0 0 0 10 M M = 1 2 3 4 0 0 4 5 6 0 0 0 7 8 9 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 M M = 1 2 3 4 0 0 4 5 6 0 0 0 7 8 9 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 M(1:3,1:3) ans = 1 2 3 4 5 6 7 8 9 M(1:2:5,1:2:5) ans = 1 3 0 7 9 0 0 0 0 M(1:2:end,1:2:end) ans = 1 3 0 7 9 0 0 0 0 M(end:-2:1,1:2:end) ans = 0 0 0 0 0 0 4 6 0 M M = 1 2 3 4 0 0 4 5 6 0 0 0 7 8 9 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 M(1:2,:) ans = 1 2 3 4 0 0 4 5 6 0 0 0 M([1 2],:) ans = 1 2 3 4 0 0 4 5 6 0 0 0 [1 2] ans = 1 2 1:2 ans = 1 2 M([1 2 1 1],:) ans = 1 2 3 4 0 0 4 5 6 0 0 0 1 2 3 4 0 0 1 2 3 4 0 0 M M = 1 2 3 4 0 0 4 5 6 0 0 0 7 8 9 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 M(2:3,2:3) ans = 5 6 8 9 M(3:-2:1,3:-2:1) ans = 9 7 3 1 M(.) M(.) | {Error: Unexpected MATLAB operator. } M(:) ans = 1 4 7 0 0 0 2 5 8 0 0 0 3 6 9 0 0 0 4 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 M M = 1 2 3 4 0 0 4 5 6 0 0 0 7 8 9 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 M(9) ans = 8 diag(M) ans = 1 5 9 -1 0 10 diag(M,-1) ans = 4 8 0 0 0 diag(M,+1) ans = 2 6 0 0 0 diag(diag(M,-1),1) ans = 0 4 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 M M = 1 2 3 4 0 0 4 5 6 0 0 0 7 8 9 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 diag(diag(M,-1),3) ans = 0 0 0 4 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 M' ans = 1 4 7 0 0 0 2 5 8 0 0 0 3 6 9 0 0 0 4 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 M M = 1 2 3 4 0 0 4 5 6 0 0 0 7 8 9 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 10 M = rand(5) M = Columns 1 through 4 0.479922141146060 0.805489424529686 0.028674152464106 0.500471624154843 0.904722238067363 0.576721515614685 0.489901388512224 0.471088374541939 0.609866648422558 0.182922469414914 0.167927145682257 0.059618867579639 0.617666389588455 0.239932010568717 0.978680649641159 0.681971904149063 0.859442305646212 0.886511933076101 0.712694471678914 0.042431137500742 Column 5 0.071445464600642 0.521649842464284 0.096730025780867 0.818148553859625 0.817547092079286 M > .6 ans = 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 1 1 1 1 1 1 0 1 B = (M > .6) B = 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 1 1 1 1 1 1 0 1 whos('B') Name Size Bytes Class Attributes B 5x5 25 logical B(2,2) ans = 0 B(2,2) = pi B = 0 1 0 0 0 1 1 0 0 0 1 0 0 0 0 1 0 1 1 1 1 1 1 0 1 whos('B') Name Size Bytes Class Attributes B 5x5 25 logical B * [1,2,3,4,5]' ans = 2 3 1 13 11 B B = 0 1 0 0 0 1 1 0 0 0 1 0 0 0 0 1 0 1 1 1 1 1 1 0 1 find(B == 1) ans = 2 3 4 5 6 7 10 14 15 19 24 25 help linspace linspace Linearly spaced vector. linspace(X1, X2) generates a row vector of 100 linearly equally spaced points between X1 and X2. linspace(X1, X2, N) generates N points between X1 and X2. For N = 1, linspace returns X2. Class support for inputs X1,X2: float: double, single See also logspace, colon. Overloaded methods: distributed/linspace codistributor2dbc/linspace codistributor1d/linspace codistributed/linspace gpuArray/linspace Reference page in Help browser doc linspace linspace( pi, 2*pi, 1 ) ans = 6.283185307179586 linspace( pi, 2*pi, 2 ) ans = 3.141592653589793 6.283185307179586 linspace( pi, 2*pi, 1 ) ans = 6.283185307179586 linspace( pi, 2*pi, 2 ) ans = 3.141592653589793 6.283185307179586 linspace( pi, 2*pi, 3 ) ans = 3.141592653589793 4.712388980384690 6.283185307179586 plot(linspace( pi, 2*pi, 3 )) plot(sin(linspace( pi, 2*pi, 3 ))) close all; plot(sin(linspace( pi, 2*pi, 3 ))) close all; plot(sin(linspace( pi, 2*pi, 30 ))) close all; plot(sin(linspace( pi, 2*pi, 300 ))) close all; plot(sin(linspace( pi, 3*pi, 300 ))) reshape( 1:24, 2, 3, 4) ans(:,:,1) = 1 3 5 2 4 6 ans(:,:,2) = 7 9 11 8 10 12 ans(:,:,3) = 13 15 17 14 16 18 ans(:,:,4) = 19 21 23 20 22 24 diary off