文件列表:

wmtsa-matlab-0.2.6\wmtsa\ChangeLog (20886, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\INSTALL (3825, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\LICENSE (1494, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\make.m (1881, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\startup.m (1495, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\TODO (442, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\VERSION (17, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\argterr.m (6443, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\colorspecname2rgb.m (1853, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\columnize.m (842, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\compare_struct_fieldnames.m (3096, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\compare_struct_fieldvalues.m (2567, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\encode_errmsg.m (3198, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\flipvec.m (1257, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\fuzzy_diff.m (2842, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\infomsg.m (3435, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\list2struct.m (2143, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\make.m (2209, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\nargerr.m (8547, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\nsigdig_diff.m (2805, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\numsigdig_diff.m (3271, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\parse_opts.m (2872, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\rgb2colorspecname.m (2604, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\set_default.m (1718, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\set_defaults.m (3500, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\set_infomsg_verbosity_level.m (3198, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\set_opts_defaults.m (1606, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\validate_opts.m (2898, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\verify_datatype.m (6731, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\wmtsa_err_table.m (3158, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\wmtsa_ismatrix.m (2799, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\wmtsa_isscalar.m (1286, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\wmtsa_isvector.m (3918, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\utils\yn.m (4052, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\third-party\suptitle.m (2499, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\Tests\wmtsa_tsensemble.m (186, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\Tests\utils\argterr_tcase.m (2336, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\Tests\utils\flipvec_tcase.m (2559, 2010-09-07)
wmtsa-matlab-0.2.6\wmtsa\Tests\utils\list2struct_tcase.m (1573, 2010-09-07)
... ...

WMTSA toolbox for MATLAB ------------------------ Version: 0.2.6 Date: 2006-08-23 Overview -------- WMTSA toolbox is an implemenation for MATLAB of the wavelet methods for time series analysis techniques presented in: Percival, D. B. and A. T. Walden (2000) Wavelet Methods for Time Series Analysis. Cambridge: Cambridge University Press. henceforth referenced as WMTSA. The WMTSA toolbox follows the terminology, symbology, algoritms and presentation of WMTSA whenever possible. Currently only the MODWT and its inverse transform have been fully implemented in the WMTSA toolbox. The DWT has been implemented but lacks plotting and analysis functions. What's New ---------- See ChangeLog for changes for the latest release. Installation ------------ See INSTALL file for instructions on how to install. Platform Compability -------------------- The WMTSA package has been developed using MATLAB 7.x on Linux platform. It has been compiled and tested on the following platforms: OS MATLAB Version -- -------------- Linux (Redhat EL 3.0 WS) 7.2 (R2006a) Linux (Redhat EL 4.0 x86_***) 7.2 (R2006a) Windows 2000 7.2 (R2006a) The distributed WMTSA package does not include compiled MEX function binaries for any platform. Binaries will be compiled during first launch of the wmtsa toolkit after installation. Required MATLAB toolboxes ------------------------- Statistics toolbox is now option. If available, the chi2inv and norminv functions are used; otherwise, the wmtsa/stats toolbox funcitons QGauss and QChisq functions are used. Directory organization --------------------- WMTSA functions are organized in subdirectories under the toolbox/wmtsa root as follows: dwt -- Core wavelet analysis transform, ANOVA plotting, utiility and support functions. odwt -- Object-oriented version of toolkit (Experimental) plotutils -- Plotting utiltiy functions. utils -- Utility functions for application support. stats -- Statistical functions. signal -- Signal processing functions. data -- Example datasets. Examples -- Examples from WMTSA Book and other sources illustrating use of the toolbox. third-party -- Functions from third-party sources. Documentation ------------- Each WMTSA function contains a standardized header which can be viewed by typing: help . The standardized header describes usage/syntax, input and output arguments, detailed description, alorigthm description, and references. For the current release, documentation is partial and incomplete. Your comments/corrections/questions are welcome and will be used to enhance the WMTSA toolbox and documentation. Examples -------- A set of examples illustrating the use of the WMTSA toolbox are under toolbox/wmtsa/Examples directory. The Figures subdirectory contains MATLAB scripts that replicate figures contained in WMTSA. To display a figure, type: figureXXX where XXX is the figure number. Reviewing the MATLAB scripts in the Figures directory will demonstrate how to use the WMTSA functions in MATLAB. The data subdirectory contains data (.dat) files used by the figure scripts. These data files originally from the WMTSA web site have been formatted for loading into MATLAB. Testing ------- Unit tests for testing proper functionality and verifying numerical accurarcy of the are included with toolkit and are found under the toolbox/wmtsa/Tests directory. There is a subdirectory for corresponding for each toolbox under toolbox/wmtsa. The unit tests utilize the MUnit toolbox for unit test, which is included with this distribution. To invoke unit tests: 1. Add MUnit toolkit to your path: addpath directory (e.g. XXX = dwt) 3. Run a test case: run_tcase(@YYY_tcase). For example: run_tcase(@modwt_functionality_tcase). Examining test cases illustrates the functionality of the wmtsa toolkit. License ------- The WMTSA toolkit for MATLAB is released under a BSD-style license contained in LICENSE file. Key Functions in the WMTSA Toolbox --------------------------------- Key WMTSA functions are identified via the following function prefaces: modwt_ = modwt transform and analysis imodwt_ = imdowt transform and analysis plot_modwt_ = plot modwt transform and analysis results. plot_imodwt_ = plot imodwt transform and analysis results. plot_ = plot function common for plotting MODWT and DWT results. Listed below are names, usage and brief descriptions of key WMTSA functions for analysis and plotting. For Analysis: ------------- % modwt -- Compute the (partial) maximal overlap discrete wavelet transform (MODWT) of a data series. % modwt_wvar -- Calculate wavelet variance from MODWT wavelet coefficients. % modwt_wcov -- Compute the wavelet covariance of two MODWT wavelet coefficient matrices. % modwt_wcor -- Compute the wavelet correlation of two MODWT wavelet coefficient matrices. % modwt_rot_cum_wsvar -- Calculate the rotated wavelet sample variance from MODWT wavelet coefficients. % modwt_cum_wav_svar -- Calculate cumulative sample variance of MODWT wavelet coefficients. % imodwt -- Calculate the inverse (partial) maximal overlap discrete wavelet transform (IMODWT). % imodwt_mra -- Calculate multi-resolution details and smooths via inverse maximal overlap discrete wavelet transform(IMODWT). % modwt_mra -- Calculate multi-resolution details and smooths of a time series via a single function call. For Plotting: ------------- % plot_modwt_coef -- Plot the MODWT wavelet and scaling coefficients and (optionally) the original time series. % plot_wvar -- Plot the wavelet variance and (optionally) confidence intervals. % plot_wcor -- Plot the wavelet correlation and (optionally) confidence intervals. % plot_wcov -- Plot the wavelet covariance and (optionally) confidence intervals. % plot_modwt_rcwsvar -- Plot the rotated cumlative sample variance of the MODWT wavelet coefficients. % plot_modwt_clcwsvar -- Plot the cumlative level of cumulative sample variance of MODWT wavelet coefficients. % plot_imodwt_mra -- Plot the IMODWT multiresoution analysis (detail and smooth) values and original time seies. Workflow -------- For analysis of a single signal: ------------------------------- X = vector series of observations | | V modwt | | V [WJt, VJ0t] ---> plot_modwt_coef | |-------------> modwt_wvar ---> plot_wvar | |-------------> modwt_cum_wav_svar ---> plot_modwt_cwsvar | |-------------> modwt_rot_cum_wav_svar.m ---> plot_modwt_rcwsvar | | V imodwt_mra | | V [DJt, SJ0t] ---> plot_imodwt_mra For analysis of a 2 signals: ---------------------------- X Y | | | | V V modwt modwt | | | | V V [WJXt] [WJYt] \ / \ / \ / \ / \ / \ / V modwt_wcor ---> plot_wcor modwt_wcov ---> plot_wcov Unit Testing ------------ We have developed a unit testing framework for MATLAB (munit) to unit test the toolkit. munit is similar to unit test frameworks developed for other languages (e.g. junit). A copy of munit is included with the WMTSA toolkit distribution. munit Unit test functions are located in the Test subdirectory. Under the Test directory is TestData subdirectory containing data for testing and verifying WMTSA toolkit functions. Note: Implementation of munit tests is still under development. Not all WMTSA toolkit functions have munit tests.

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