Software Listing of Author : "Durga Lal Shrestha"
- AHIST
- License: Shareware
- Price:


AHIST Alternative to Histogram. Motivation: to combine the good features of HIST and HISTC. USAGE: n = ahist(Y) n = ahist(Y,nbin) n = ahist(Y,xedges) [n,xc,index] = ahist(...) ahist(...) without output arguments produces a histogram bar plot of the results. INPUT: Y: Vector or Matrix of data. If Y is Matrix, AHIST works down the columns. nbin: Number of bins xedges: Matrix of edges for each column vector of data OUTPUT: n: Number of elements in each container. xc: The position of the bin centers in X index: Index matrix BIN. FEATURES: 1. Returns the index matrix (histc) 2. Either uses nbins (hist) or xedges (histc) 3. Returns centre of the bin (hist) 4. Plot histogram of each column of matrix in subplots WHY AHIST: 1. Note that in histc, the last bin counts any values of x that match edges(end). But...
- Publisher: Durga Lal Shrestha
- Date Released: 23-02-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts
- ami and correlation
- License: Freeware
- Price: 0.00


AMI computes and plots average mutual information (ami) and correlation of univariate or bivariate time series for different values of time lag. USAGE: [amis corrs] = ami(xy,nBins,nLags) INPUT: xy: either univariate (x) or bivariate ([x y]) time series data. If bivariate time series are given then x should be independent variable and y should be dependent variable. If univariate time series is given then autocorrelation is calculated instead of cross correlation. nBins: number of bins for time series data to compute distribution which is required to compute ami. nBins should be either vector of 2 elements (for bivariate) or scalar (univariate). nLags: number of time lags to compute ami and correlation. Computation is done for lags values of 0:nLags. OUTPUT: amis: vector of average mutual information for time lags of 0:nLags...
- Publisher: Durga Lal Shrestha
- Date Released: 12-01-2013
- Download Size: 31 KB
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- Platform: Matlab, Scripts
- AWAITBAR: alternative to waitbar
- License: Shareware
- Price:


AWAITBAR displays waitbar with abort button Clicking on the ABORT or the CLOSE button of the waitbar figure will abort the loop and close the waitbar. USAGE: H = awaitbar(x,message) creates and displays a waitbar of fractional length X with the message text in the waitbar figure. The handle to the waitbar figure is returned in H. x should be between 0 and 1. H = awaitbar(x,message,figTitle) displays title in the figure title H = awaitbar(x,message,figTitle,figPosition) positions the figure according to the value specified in figPosition abort = awaitbar(x) will update in the most recently created waitbar window. The output "abort" has value true when user click the abort button of the awaitbar. abort = awaitbar(x,H,...) will update in waitbar H FEATURES 1. Abort button to abort the loop and close the waitbar figure. 1. It...
- Publisher: Durga Lal Shrestha
- Date Released: 14-05-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts
- Data Cursor on Mouse Move
- License: Shareware
- Price:


Display and update the pixel value from image in the figure title bar on mouse movement. Usage: z=rand(10,10); h = image(z) set(gcf,'WindowButtonMotionFcn', {@getPixelOnMouseMove,h}); Now move the mouse over the image and see the pixel value in the figure title bar. Bugs and comments are welcome.
- Publisher: Durga Lal Shrestha
- Date Released: 16-02-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts
- GUI WAITBAR DEMO
- License: Shareware
- Price:


This simple demo shows how to attatch waitbar in GUI and displays other informaton like estimated time, elapsed time and percentage completed. Another demo within this GUI is a simple fun for testing your speed of mouse click on moving button in the GUI figure. You can change the speed of button movement by slider in the GUI. When you able to click the moving button which has caption 'Stop me', then it stops moving of this button and waitbar and also gives your score between 0 (worst) and 100 (best). The GUI also counts how many movements are in the left and right panels of the GUI. In total 100 movements, half of them should be in left panel.
- Publisher: Durga Lal Shrestha
- Date Released: 03-04-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts
- mweka Script
- License: Freeware
- Price: 0.00


The GUI executes various WEKA classifiers and displays the results in MATLAB. Here are some key features of "mweka": * Command line options for running weka * Demonstrate how to change classifier option using java class (similiar to GenericObjectEditor in weka) * Read and Write ARFF file to/from MATLAB * Able to select attributes from GUI to test with different input combinations * Show results graphically immediately * Easy to compare the results graphically for different runs * Bottom figures of the visualization panels show the dynamic zoom of the upper part
- Publisher: Durga Lal Shrestha
- Date Released: 16-05-2013
- Download Size: 1208 KB
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- Platform: Matlab, Scripts
- Plot Multi Dimensional Functions
- License: Shareware
- Price:


Usage: plotfunction(fcn,LB,UB,varargin) EXAMPLES: 1. plotfunction(@hosaki,[0 0],[5 5]); % Plot hosaki function in the range of 0 - 5 in both dimension. 2. LB = zeros(1,4);UB= 10*ones(1,4); xypar = [2 3]; plotfunction(@shekel,LB,UB,xypar); % Plot shekel function in the range of 0 - 10 in second and third dimension while keeping constant value (average of 0 and 10) in other dimensions. 3. baseValue = [3.2 4 4 6.8]; plotfunction(@shekel,LB,UB,xypar,baseValue); % Plot shekel function keeping constant value of 3.2 in first dimension and 6.8 in last dimension. Here values in second and thirs dimension is overwriten by range of LB and UB as done in example 2. 4. For example you have the following function f = parameterized_rosenbrock(x,a,b) x1 = x(1); x2 = x(2); f = a * (x2 - x1^2)^b + (1 - x1)^b; % Use the following to...
- Publisher: Durga Lal Shrestha
- Date Released: 03-01-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts
- Random Number from Empirical Distribution
- License: Shareware
- Price:


EMPRAND generates random numbers from empirical distribution of data. This is useful when you do not know the distribution type (i.e. normal or uniform), but you have the data and you want to generate random numbers form that data. The idea is to first construct cumulative distribution function (cdf) from the given data. Then generate uniform random number and interpolate from cdf. USAGE: [xr] = emprand(dist) generates single random number from given vector of data values dist. [xr] = emprand(dist,m) generates m by m matrix of random numbers. [xr] = emprand(dist,m,n) generates m by n matrix of random numbers. Examples: % Generate 1000 random normal numbers as data for EMPRAND dist = randn(1000,1); % Now generate 2000 random numbers from this data xr = emprand(dist,2000,1);
- Publisher: Durga Lal Shrestha
- Date Released: 26-04-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts
- Returns weighted percentiles of a sample
- License: Shareware
- Price:


The idea is to give more emphasis in some examples of data as compared to others by giving more weight. For example, we could give lower weights to the outliers. The motivation to write this function is to compute percentiles for Monte Carlo simulations where some simulations are very bad (in terms of goodness of fit between simulated and actual value) than the others and to give the lower weights based on some goodness of fit criteria. USAGE: y = WPRCTILE(X,p) % This is same as PRCTILE y = WPRCTILE(X,p,w) y = WPRCTILE(X,p,w,type) INPUT: X - vector or matrix of the sample data p - scalar or a vector of percent values between 0 and 100 w - positive weight vector for the sample data. Length of w must be equal to either number of rows or columns of X. If the weights are equal, then WPRCTILE is same as PRCTILE. type - an...
- Publisher: Durga Lal Shrestha
- Date Released: 22-02-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts
- rhist
- License: Shareware
- Price:


rhist is extension of MATLAB hist function to compute and plot relative frequency and density. N = HIST(Y) bins the elements of Y into 10 equally spaced containers and returns the relative frequency of elements in each container. If Y is a matrix, RHIST works down the columns. N = RHIST(Y,M), where M is a scalar, uses M bins. N = RHIST(Y,X), where X is a vector, returns the relative freqency of Y among bins with centers specified by X. The first bin includes data between -inf and the first center and the last bin includes data between the last bin and inf. N = RHIST(Y,M,Any_Character) returns relative frequency density of Y among bins.Any_Character is the any character inside single quotation or any numeric value. You can omit second optional argument using single quotation i.e. N = RHIST(Y,'',Any_Character) returns relative...
- Publisher: Durga Lal Shrestha
- Date Released: 20-02-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts
- Triangular pdf
- License: Shareware
- Price:


The files in this folder contains small routines for MATLAB to compute and plot triangular probability denstity function. There are following 4 files: tglpdf : Compute and plot triangular probability density function for given value of X (X can be scalar or matrix) tglcdf : Compute and plot triangular cumulative distribution function for given value of X (X can be scalar or matrix) invtglpdf: Compute the value of X from given value of probability density. This is inverse of tglpdf. invtglcdf: Compute the value of X from given value of cumulative distribution. This is inverse of tglcdf.
- Publisher: Durga Lal Shrestha
- Date Released: 05-04-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts

