tag:www.mathworks.com,2005:/matlabcentral/fileexchange/feedMATLAB Central File Exchangeicon.pnglogo.pngMATLAB Central - File ExchangeUser-contributed code library2014-11-24T13:13:58-05:00224221100tag:www.mathworks.com,2005:FileInfo/483002014-10-29T15:46:10Z2014-11-24T18:05:49ZCompressible Flow RelationsCalculates various flow relations for compressible fluid flow<p>Note that while each sub function can run on its own, I recommend using the top level function compressible.m to avoid formatting confusion.
<br />This function solves for the relations associated with isentropic compressible flow, normal shock relations, isentropic flow with heat addition and friction, solutions for the Prandtl-Meyer function and Mach angle, and the Theta-Beta-Mach relation for oblique shocks. It does so for any value inputted and for any value of gamma, where gamma is the ratio of the specific heats. Also note that this function CAN handle vectors of inputs, and will return them in the same shape as the input if it can. This function can be used in three ways:
<br /> - If no input or output is specified, it will run a GUI that prompts the user to decide which table and input type, as well as the gamma that will be used. The GUI then displays the results in a table integrated into the figure.
<br /> - If inputs are included but not outputs, the function will print the results in the workspace.
<br />The above to methods are useful if these function is used to find values for reference or homework assignments. If the calculations are to be used within a function, the third option is:
<br /> - If inputs and outputs are included, the function will place the results into the output variables without printing or displaying anything. This use of the function allows for it to be integrated into a new function
<br />All formula derivations are from:
<br />Anderson, John D. Modern Compressible Flow: With Historical Perspective. New York: McGraw-Hill, 1982. Print.
<br />All code and formatting by Thomas Ransegnola. If there are errors, or you would like for something else to be added, please let me know at <a href="mailto:transegn@gmail.com">transegn@gmail.com</a></p>Tom Rhttp://www.mathworks.com/matlabcentral/fileexchange/authors/269262MATLAB 8.1 (R2013a)falsetag:www.mathworks.com,2005:FileInfo/485542014-11-24T18:05:31Z2014-11-24T18:05:31ZIterative Trimmed and Truncated Mean Algorithm filter (ITTM filter)ITTM filter for noise suppression and image processing.<p>The codes for the recently proposed iterative trimmed and truncated arithmetic mean (ITTM) are provided here. Here, trimming a sample means removing it and truncating a sample is to replace its value by a threshold. Simultaneously trimming and truncating enable the proposed filters to attenuate the mixed additive and exclusive noise in an effective way. The proposed trimming and truncating rules ensure that the output of the ITTM filter converges to the median. It offers an efficient method to estimate the median without time-consuming data sorting. Theoretical analysis shows that the ITTM filter of size n has a linear computational complexity O(n). Compared to the median filter and the iterative truncated arithmetic mean (ITM) filter, the proposed ITTM filter suppresses noise more effectively in some cases and has lower computational complexity.</p>Miao Zhenweihttp://www.mathworks.com/matlabcentral/fileexchange/authors/509251MATLAB 7.10 (R2010a)falsetag:www.mathworks.com,2005:FileInfo/482002014-10-20T17:05:16Z2014-11-24T17:32:30Zngunsu/matlab-eoh-siftEOHSIFT: Multispectral Image Feature Points<p>Matlab implementation of EOHSIFT
<br />Article URL: <a href="http://www.mdpi.com/1424-8220/12/9/12661">http://www.mdpi.com/1424-8220/12/9/12661</a>
<br />Bibtex @Article{s120912661, AUTHOR = {Aguilera, Cristhian and Barrera, Fernando and Lumbreras, Felipe and Sappa, Angel D. and Toledo, Ricardo}, TITLE = {Multispectral Image Feature Points}, JOURNAL = {Sensors}, VOLUME = {12}, YEAR = {2012}, NUMBER = {9}, PAGES = {12661--12672}, URL = {<a href="http://www.mdpi.com/1424-8220/12/9/12661">http://www.mdpi.com/1424-8220/12/9/12661</a>}, PubMedID = {23112736}, ISSN = {1424-8220}, DOI = {10.3390/s120912661} }</p>Cristhian Aguilerahttp://www.mathworks.com/matlabcentral/fileexchange/authors/514854MATLAB 8.1 (R2013a)falsetag:www.mathworks.com,2005:FileInfo/485532014-11-24T17:23:04Z2014-11-24T17:23:04Zfast iterative truncated arithmetic mean (FITM)filterFITM filter<p>The codes of the recently proposed ITM filter and the fast ITM (FITM) are given in this part. The ITM/FTIM filter outperforms the median filter in attenuating the single type of noise, such as Gaussian and Laplacian noise, and the mixed type of noise, such as the mixed Gaussian and impulsive noise. It also offers a way to estimate the median by a simple arithmetic computing algorithm.</p>Miao Zhenweihttp://www.mathworks.com/matlabcentral/fileexchange/authors/509251MATLAB 8.0 (R2012b)falsetag:www.mathworks.com,2005:FileInfo/333812011-10-19T23:19:21Z2014-11-24T17:14:14ZJSONlab: a toolbox to encode/decode JSON files in MATLAB/OctaveJSONlab is an open-source JSON/UBJSON encoder and decoder (parser) for MATLAB and Octave.<p>** JSONLAB v1.0 RC1 (Optimus) is released on 09/17/2014. Binary JSON format (UBJSON) is supported! **
<br />JSONlab is a component of iso2mesh toolbox (<a href="http://iso2mesh.sf.net">http://iso2mesh.sf.net</a>). For the latest information regarding JSONlab, please visit its homepage at <a href="http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab">http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab</a></p>
<p>JSON (JavaScript Object Notation) is a highly portable, human-readable and "fat-free" text format to represent complex and hierarchical data. It is as powerful as XML, but less verbose. JSON format is widely used for data-exchange in applications, and is essential for the wild success of Ajax and Web2.0.</p>
<p>UBJSON (Universal Binary JSON) is a binary JSON format, specifically optimized for compact file size and better performance while keeping the semantics as simple as the text-based JSON format. Using the UBJSON format allows to wrap complex binary data in a flexible and extensible structure, making it possible to process complex and large dataset without accuracy loss due to text conversions.</p>
<p>We envision that both JSON and its binary version will serve as part of the mainstream data-exchange formats for scientific research in the future. It will provide the flexibility and generality achieved by other popular general-purpose file specifications, such as HDF5, with significantly reduced complexity and enhanced performance.</p>
<p>JSONlab is a free and open-source implementation of a JSON/UBJSON encoder and a decoder in the native MATLAB language. It can be used to convert a MATLAB data structure (array, struct, cell, struct array and cell array) into JSON/UBJSON formatted strings, or to decode a JSON/UBJSON file into MATLAB data structure. JSONlab supports both MATLAB and GNU Octave (a free MATLAB clone).</p>
<p>JSONlab provides two functions, loadjson.m -- a MATLAB->JSON decoder,
<br />and savejson.m -- a MATLAB->JSON encoder, for the text-based JSON, and
<br />two equivallent functions -- loadubjson and saveubjson for the binary
<br />JSON. The savejson, loadubjson and saveubjson functions were written by
<br />Qianqian Fang, while the loadjson.m script was derived from the previous works by the following people:</p>
<p>- Nedialko Krouchev: <a href="http://www.mathworks.com/matlabcentral/fileexchange/25713">http://www.mathworks.com/matlabcentral/fileexchange/25713</a>
<br /> date: 2009/11/02
<br />- FranÃ§ois Glineur: <a href="http://www.mathworks.com/matlabcentral/fileexchange/23393">http://www.mathworks.com/matlabcentral/fileexchange/23393</a>
<br /> date: 2009/03/22
<br />- Joel Feenstra: <a href="http://www.mathworks.com/matlabcentral/fileexchange/20565">http://www.mathworks.com/matlabcentral/fileexchange/20565</a>
<br /> date: 2008/07/03</p>
<p>Please find detailed online help at <a href="http://iso2mesh.sourceforge.net/cgi-bin/index.cgi?jsonlab/Doc">http://iso2mesh.sourceforge.net/cgi-bin/index.cgi?jsonlab/Doc</a></p>Qianqian Fanghttp://www.mathworks.com/matlabcentral/fileexchange/authors/33904MATLAB 7.4 (R2007a)JSONlab is platform independent.falsetag:www.mathworks.com,2005:FileInfo/484442014-11-24T16:18:24Z2014-11-24T16:18:24ZBinomial Inverse (Binary Search)Binomial inverse cumulative distribution function via binary search<p>X = binoinv_bs(Y,N,P) returns the inverse of the binomial cdf with parameters N and P. Since the binomial distribution is discrete, BINOINV_BS returns the least integer X such that the binomial cdf evaluated at X, equals or exceeds Y. BINOINV_BS utilizes a binary search of BINOCDF to find the inverse of the binomial distribution, which may be faster than BINOINV for large N.
<br />
<br />The size of X is the common size of the input arguments. A scalar input functions as a constant matrix of the same size as the other inputs.
<br />
<br />Note that X takes the values 0,1,2,...,N.
<br />
<br />See also binoinv, binocdf, binofit, binopdf, binornd, binostat, icdf.</p>Nade Sritanyaratanahttp://www.mathworks.com/matlabcentral/fileexchange/authors/491655MATLAB 8.3 (R2014a)falsetag:www.mathworks.com,2005:FileInfo/464192014-04-30T15:56:31Z2014-11-24T16:17:02ZrotationMatrix.zip3D rotation matrix class<p>The class RotationMatrix allows to handle a 3D rotation matrix with different parametrizations:
<br />- a [3x3] rotation matrix
<br />- Euler angles
<br />- exponential map
<br />- quaternions
<br />Once a RotationMatrix instance has been created from one of the parametrizations above, all the parametrizations can be obtained interchangeably. </p>
<p>Example:</p>
<p>% create a rotation matrix from its exponential map
<br />r = RotationMatrix(rand([3,1]), 'exponentialMap');</p>
<p>% get the corresponding matrix/quaternion representation
<br />aMatrix = r.GetRotationMatrix();
<br />aQuaternion = r.GetQuaternion();</p>
<p>Additional static methods are provided for building a rotation matrix from different parametrizations.</p>
<p>See RotationMatrixTest.m for further examples.</p>Alberto Crivellarohttp://www.mathworks.com/matlabcentral/fileexchange/authors/461125MATLAB 8.2 (R2013b)MATLABfalsetag:www.mathworks.com,2005:FileInfo/485522014-11-24T15:35:13Z2014-11-24T15:45:56ZTupper's self-referential formulasolve the special N in Tuppers' formula, if the image provided.<p>wiki:Tupper's self-referential formula.
<br /><a href="http://en.wikipedia.org/wiki/Tupper%27s_self-referential_formula">http://en.wikipedia.org/wiki/Tupper%27s_self-referential_formula</a>
<br />Note:Wiki may provide a wrong answer.
<br />inspired by the following website:
<br /><a href="http://www.matrix67.com/blog/archives/301">http://www.matrix67.com/blog/archives/301</a>
<br /><a href="http://www.matrix67.com/blog/archives/4447">http://www.matrix67.com/blog/archives/4447</a>
<br /><a href="http://bbs.pediy.com/showthread.php?t=56002">http://bbs.pediy.com/showthread.php?t=56002</a></p>Mineralterhttp://www.mathworks.com/matlabcentral/fileexchange/authors/285004MATLAB 8.2 (R2013b)falsetag:www.mathworks.com,2005:FileInfo/466082014-05-14T14:02:52Z2014-11-24T13:04:12ZfrcolocColocalization of Fluorescence and Raman Microscopic Images for Training Data Collection<p>This colocalization scheme unveils statistically significant overlapping regions by identifying correlation between fluorescence color channels and clusters from unsupervised machine learning methods like hierarchical cluster analysis (HCA) performed on Raman or CARS spectral images. The scheme works as a pre-selection to gather appropriate spectra which can be used as training data to establish a supervised classifier (e.g. Random Forest) to automatically identify subcellular compartments.
<br />A dataset for testing can be downloaded here: <a href="http://www2.rz.rub.de:8234/imperia/md/content/pure/supplement.zip">http://www2.rz.rub.de:8234/imperia/md/content/pure/supplement.zip</a></p>Sascha D. Kraußhttp://www.mathworks.com/matlabcentral/fileexchange/authors/255204MATLAB 8.3 (R2014a)falsetag:www.mathworks.com,2005:FileInfo/485512014-11-24T11:22:35Z2014-11-24T11:22:35ZThe X CollectionCollection of programs that ease interaction with Excel files.<p>The X collection is a set of Matlab programs that make it easier for the user to interact with Excel sheets. Matlab offers already many ways of exchanging data with Excel. For instance xlsread and xlswrite allow the programmer to read data from and write data into Excel worksheets. But these programs are inefficient when a large number of read and write operations have to be repeated because they build a cobnbection to the Excel COM server and then release this connection again with every operation.
<br />The X collection splits that up. The programmer creates a connection to Excel (with XConnect), then does whatever he or she has to do (XWrite, XRead, XOpenBook, XGetSheet, XSaveBook etc), and then releases the Excel connection again (XDisconnect). Depending on the type of work, the gain in speed range from none to huge.
<br />The following programs are included: XConnect, XDisconnect, XListOpenBooks, XGetBook, XNewBook, XOpenBook, XSaveBook, XSaveAllBooks, XCloseBook, XCloseAllBooks, XListSheets, XGetSheet, XAddSheet, XRead, XWrite, XWriteDates, XDateFmt, XRangeAddress</p>
<p>Their meanings should be more or less obvious. They all come with help, so that you user should be abvle to figure out how to use these programs fairly easily.
<br />There is also an example script (example.m) that demonstrates many of these programs.
<br />Should you need help with this, please contact me. If you find this contribution useful, please comment below.</p>Yvan Lengwilerhttp://www.mathworks.com/matlabcentral/fileexchange/authors/28060MATLAB 8.4 (R2014b)Microsoft Excel installationfalse