Software Listing of Author : "Gautam Vallabha"

Doing linear tests (like ANOVA or t-tests) on proportional data (values between 0 and 1) is difficult since the distributions of these values are not strictly Gaussian, especially when the proportions are near 0 or 1. The Rationalized Arcsine Transform linearizes the proportions and converts them to "rational arcsine units". The linear tests can then be performed on the RAU values. (p=0.5 roughly corresponds to a rau of 50). RAU(p) computes the rationalized arcsine transform for a proportion value p (0 <= p <= 1). p can also be a vector of proportion values.

  • Platform: Matlab, Scripts

Calculates the correlation coefficient for 2-d directional and circular data, e.g., if you have one set of 2-d movements and want to compare them to a second (paired) set of 2-d movements. The input to the function is two Nx2 matrices (each matrix specifies the x,y coordinates of N data points).

  • Platform: Matlab, Scripts

This m-file implements a simple data acquisition gui with multiple channels and custom triggering It demonstrates how to: 1) Use nested functions to simplify data acquisition programs 2) Use a simple GUI (a couple of pushbuttons) to start and stop data acquisition. 3) Wait for an event/trigger (like a button press) and log pre-event or pre-trigger data from multiple synchronized channels. 4) Record pretrigger data based on custom criteria. In this m-file the triggering event is a button click. However, the event could be any custom criterion (e.g., the data amplitude is greater than a threshold *and* a toggle button is enabled). Requires: the Data Acquisition Toolbox (TM) and the Winsound adapter. It does not depend on any hardware-specific capabilities.

  • Platform: Matlab, Scripts

obj = findInstrument('STR') returns an interface object to an instrument whose model name, vendor name or VISA resource matches any part of the string STR. findInstrument requires the Instrument Control Toolboxd-OC?D? and a VISA adaptor, and currently only works with USB and GPIB instruments. -------------- EXAMPLES (See the published MATLAB file for sample outputs) % see a list of all the available instruments findInstrument; % find an instrument by model number obj = findInstrument('34405'); fopen(obj) query(obj,'*IDN?') fclose(obj) % find an instrument by model number, using Agilent VISA obj = findInstrument('34405', 'agilent'); % find an instrument by model number and % create a device object obj = findInstrument('33120'); fgen = icdevice('agilent_33120a.mdd', obj); % find an instrument by matching a...

  • Platform: Matlab, Scripts

MATLAB supports Agilent arbitrary waveform generators through the Instrument Control Toolbox. This example demonstrates how you can use MATLAB to develop a GUI application for configuring an Agilent N8241A Arbitrary Waveform Generator. The GUI allows you to configure sinusoids and pulse trains of varying frequency, and to step automatically through a sequence of frequency values. It also has a "simulate" mode that allows you to explore the GUI without an actual instrument (the generated waveforms and AWG status are displayed a separate figure window). To run the application, save the files in the associated ZIP file, and do one of the following: >> agilentFcnGen('simulate'); % to run the application with a simulated AWG >> agilentFcnGen(visaResourceString); % give the VISA resource string of the AWG You may use this application...

  • Platform: Matlab, Scripts

ScopeMath (fileid 13165) is a MATLAB-based GUI that uses the Instrument Control Toolbox to retrieve waveforms from an oscilloscope and analyze them in various ways. ScopeMath_Simple is a simplified version that demonstrates how to set up a similar GUI for your own purposes. It shows how to: 1) Create the GUI 2) Connect to the instrument 3) Get data from the instrument, and 4) Clean up the resources when exiting the program. For more information on the Instrument Control Toolbox, see http://www.mathworks.com/products/instrument/

  • Platform: Matlab, Scripts

MOUSEINPUT_TIMEOUT returns continuous mouse locations with timeout OUT = MOUSEINPUT_TIMEOUT returns the sequence of mouse locations between a button press and a button release in the current axes. It does not timeout. OUT is an Nx2 matrix, where OUT(1,:) is the location at button press and OUT(END,:) is the location at button release. OUT = MOUSEINPUT_TIMEOUT(T) times out after a period of T seconds. T can be a fractional value (T=inf indicates no timeout). If the mouse-button has not been pressed during that time, OUT is []. If the timeout occurs during a mouse movement, OUT contains the mouse locations before the timeout. OUT = MOUSEINPUT_TIMEOUT(T,AH) records the mouse movement from the axes specified by axes handle AH. Note: MOUSEINPUT_TIMEOUT differs from GINPUT in two ways. (1) It does not return information about which...

  • Platform: Matlab, Scripts

PLOT_GAUSSIAN_ELLIPSOIDS plots 2-d and 3-d Gaussian distributions. H = PLOT_GAUSSIAN_ELLIPSOIDS(M, C) plots the distribution specified by mean M and covariance C. The distribution is plotted as an ellipse (in 2-d) or an ellipsoid (in 3-d). By default, the distributions are plotted in the current axes. H is the graphics handle to the plotted ellipse or ellipsoid. PLOT_GAUSSIAN_ELLIPSOIDS(M, C, SD) uses SD as the standard deviation along the major and minor axes (larger SD => larger ellipse). By default, SD = 1. PLOT_GAUSSIAN_ELLIPSOIDS(M, C, SD, NPTS) plots the ellipse or ellipsoid with a resolution of NPTS (ellipsoids are generated on an NPTS x NPTS mesh). By default, NPTS = 50 for ellipses, and 20 for ellipsoids. PLOT_GAUSSIAN_ELLIPSOIDS(M, C, SD, NPTS, AX) adds the plot to the axes specified by the axis handle AX.

  • Platform: Matlab, Scripts

[DATA TIME] = readFlukeFile(FILENAME), reads a CSV file with recorded measurements from a Fluke multimeter. It returns DATA (a vector of measurement values) and TIME (a vector of measurement times). The "time" of each measurement is the elapsed time in seconds since the start of the recording session. The expected workflow is the following: 1. Configure the Fluke multimeter to record a series of measurements 2. Use FlukeViewForms (TM) to download the measurements, and export them to a CSV file 3. Use readFlukeFile to read the CSV file Example: [data time] = readFlukeFile('sampledata.csv'); plot(time, data); xlabel('time in seconds'); NOTE: This entry requires FlukeViewForms (which is available with many of the Fluke models). To communicate with a Fluke 45 multimeter (which supports SCPI commands), see...

  • Platform: Matlab, Scripts

The RealTime Pacer block slows down ("paces") simulation time so that it synchronizes with real elapsed time. The degree of slowdown is controllable via a Speedup parameter. 1) The block is implemented using an M S-function, so it works on any supported Simulink platform. It does not support code generation. 2) The block uses the MATLAB PAUSE function to slow down the simulation. The PAUSE command gives up the processor during the pause, so system performance does not degrade. 3) The M-S function illustrates how to use nested functions to simplify the code. The matching between simulation time and elapsed real time is approximate, with expected differences on the order of 10 to 30 milliseconds. This limitation is due to difficulties of precise timing with a multitasking operating system. -------- RELATED FX ENTRIES The following...

  • Platform: Matlab, Scripts
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