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Nonstationary Extreme Value Analysis (NEVA) Toolbox

Nonstationary Extreme Value Analysis (NEVA) Software Package, Version 2.0
By: Linyin Cheng, PhD, University of California, Irvine
Release: 09/14/2014
Source Code: Matlab
The Nonstationary Extreme Value Analysis (NEVA) software package has been developed to facilitate extreme value analysis under both stationary and nonstationary assumptions. In a Bayesian approach, NEVA estimates the extreme value parameters with a Differential Evolution Markov Chain (DE-MC) approach for global optimization over the parameter space. NEVA includes posterior probability intervals (uncertainty bounds) of estimated return levels through Bayesian inference, with its inherent advantages in uncertainty quantification. The software presents the results of non-stationary extreme value analysis using various exceedance probability methods. We evaluate both stationary and non-stationary components of the package for a case study consisting of annual temperature maxima for a gridded global temperature dataset. The results show that NEVA can reliably describe extremes and their return levels.
NEVA includes two components:
(1) The Generalized Extreme Value (GEV) distribution for analysis of annual maxima (block maxima).
(2) The Generalized Pareto Distribution (GPD) for analysis of extremes above a certain threshold (i.e., peak-over-threshold (POT) approach).

Both NEVA GEV and NEVA GPD can be used for stationary (time-independent) and nonstationary (transient) extreme value analysis.

Reference Publication:

Cheng L., AghaKouchak A., Gilleland E., Katz R.W., 2014, Non-stationary Extreme Value Analysis in a Changing Climate , Climatic Change, doi: 10.1007/s10584-014-1254-5.
Download Reference Paper: http://amir.eng.uci.edu/publications/14_NEVA_CC.pdf

The toolbox includes a sample observation and simulation data sets. Run NEVA.m to see sample outputs.

Additional information:

http://amir.eng.uci.edu/neva.php

RLC circuit demo bundle

This demo bundle demonstrates how to model and analyze a dynamical system – the RLC circuit – in MATLAB, Simulink, and Simscape and how to seamlessly move between these modeling environments. The corresponding hardware experiment is analyzed with a low-cost data acquisition hardware platform.
Example files
RLC_symbolic.m: model and analyze circuit using symbolic math
RLC_nonlinear.m: model and analyze circuit using numeric math
RLC_nonlinear.pdf: documentation generated with MATLAB’s publish feature
RLC_simulink.slx: model and analyze circuit using graphical modeling
RLC_simscape.slx: model and analyze circuit using physical modeling
RLC_AnalogDiscovery.m: analyze hardware circuit using the DAQ toolbox
RLC_AnalogDiscovery.pdf: documentation generated with MATLAB’s publish feature

Support material
data_bode.mat: hardware measurement data file
data_step.mat: hardware measurement data file
Comp_Bode.fig: plot comparing theory and hardware experiment
Comp_Step.fig: plot comparing theory and hardware experiment
RLC_model.PNG: Simscape model screenshot
RLC_schematic.PNG: schematic for hardware experiment
license.txt

Note: these are the example files that will be used in a Webinar on experimenting in teaching that will be aired in November 2014. This Webinar discusses some of the teaching challenges and presents approaches and techniques to efficiently create, perform and evaluate experiments.

mouseGenGrid(range)

input range in a 4-element vectors to create x range and y range, e,g, [-100 100 - 200 200] will gen grid in x range of -100 to 100 and y range of -200 and 200, default is the parameters I used in my wind tunnel testing.
+ - to change grid density, click when holding shift to add points, without holding to toggle points.
Note that point can only be toggled when 'locked on' by the gray background grid.
I used it to generate grid for traverse measurements.
Support save and load grids.
It is my first submission derived from my research studies that require generating traverse measurement grid points. Not tested on other matlab version

CLPSO for variable weighting clustering

This Matlab code is written according to the interesting paper "Particle swarm optimizer for variable weighting in clustering high-dimensional data", which was published in the journal Machine Learning (2011). The creative work involved in the paper/code is fully devoted to the corresponding authors (Yanping Lu, et al). Note that I just code and share it for the purpose of learning. Further, some slight differences between the code and the corresponding paper may be found.

Cell2mat Function, 'CAT argumens dimension are not consistentt
I'm trying to convert a cell matrix to a double matrix. It appears that because this cell matrix which is 2048x1 has both positive and negative values, this function does not work.

This is the error appears:


Error in ==> cell2mat at 89
            m{n} = cat(1,c{:,n});

Error in ==> find_risetime at 3
num = cell2mat(num(12:end,1));

Anyone else run into this problem, were you successful in dealing with it, can you share your success story with me.

Thanks,
Fellow Matlab User
How to solve crash when running mex file
------------------------------------------------------------------------
            Abort signal detected at Fri Oct 24 08:54:34 2014
------------------------------------------------------------------------

Configuration:
  Crash Decoding : Disabled
  Current Visual : 0x24 (class 4, depth 24)
  Default Encoding : UTF-8
  GNU C Library : 2.15 stable
  MATLAB Architecture: glnxa64
  MATLAB Root : /usr/local/MATLAB/R2013a
  MATLAB Version : 8.1.0.604 (R2013a)
  Operating System : Linux 3.11.0-26-generic #45~precise1-Ubuntu SMP Tue Jul 15 04:02:35 UTC 2014 x86_64
  Processor ID : x86 Family 6 Model 62 Stepping 4, GenuineIntel
  Virtual Machine : Java 1.6.0_17-b04 with Sun Microsystems Inc. Java HotSpot(TM) 64-Bit Server VM mixed mode
  Window System : The XFree86 Project, Inc (40300000), display :19.0

Fault Count: 1


Abnormal termination:
Abort signal

Register State (from fault):
  RAX = 0000000000000000 RBX = 00007f81f26f6660
  RCX = ffffffffffffffff RDX = 0000000000000006
  RSP = 00007f82d0dc7f08 RBP = 00007f81f26f6660
  RSI = 000000000000756e RDI = 0000000000007540

   R8 = 00007f81f27057a7 R9 = 0000000000000000
  R10 = 0000000000000008 R11 = 0000000000000202
  R12 = 00007f82c68a6fa0 R13 = 00000000000000a3
  R14 = 00007f81f26f68d3 R15 = 0000000000000003

  RIP = 00007f82e28b64f5 EFL = 0000000000000202

   CS = 0033 FS = 0000 GS = 0000

Stack Trace (from fault):
[ 0] 0x00007f82e28b64f5 /lib/x86_64-linux-gnu/libc.so.6+00222453 gsignal+00000053
[ 1] 0x00007f82e28b9c5b /lib/x86_64-linux-gnu/libc.so.6+00236635 abort+00000379
[ 2] 0x00007f81f24e2429 /usr/local/lib/libglog.so.0+00042025
[ 3] 0x00007f81f24e3b7d /usr/local/lib/libglog.so.0+00047997
[ 4] 0x00007f81f24e5c7f /usr/local/lib/libglog.so.0+00056447 _ZN6google10LogMessage9SendToLogEv+00000655
[ 5] 0x00007f81f24e376c /usr/local/lib/libglog.so.0+00046956 _ZN6google10LogMessage5FlushEv+00000156
[ 6] 0x00007f81f24e651d /usr/local/lib/libglog.so.0+00058653 _ZN6google15LogMessageFatalD2Ev+00000013
[ 7] 0x00007f81f7b78847 /home/zhuzhu/share_zhuzhu/caffe-master/matlab/caffe/caffe.mexa64+00534599
[ 8] 0x00007f81f7b606aa /home/zhuzhu/share_zhuzhu/caffe-master/matlab/caffe/caffe.mexa64+00435882
[ 9] 0x00007f81f7b20405 /home/zhuzhu/share_zhuzhu/caffe-master/matlab/caffe/caffe.mexa64+00173061
[ 10] 0x00007f81f7b2141a /home/zhuzhu/share_zhuzhu/caffe-master/matlab/caffe/caffe.mexa64+00177178 mexFunction+00000225
[ 11] 0x00007f82daf1df8a /usr/local/MATLAB/R2013a/bin/glnxa64/libmex.so+00110474 mexRunMexFile+00000090
[ 12] 0x00007f82daf1a0f9 /usr/local/MATLAB/R2013a/bin/glnxa64/libmex.so+00094457
[ 13] 0x00007f82daf1af1c /usr/local/MATLAB/R2013a/bin/glnxa64/libmex.so+00098076
[ 14] 0x00007f82e48336b2 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_dispatcher.so+00562866 _ZN8Mfh_file11dispatch_fhEiPP11mxArray_tagiS2_+00000594
[ 15] 0x00007f82e42bdbf6 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+04262902
[ 16] 0x00007f82e42be37a /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+04264826
[ 17] 0x00007f82e42beeea /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+04267754
[ 18] 0x00007f82e4121bbd /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02575293
[ 19] 0x00007f82e414d412 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02753554
[ 20] 0x00007f82e414d53f /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02753855
[ 21] 0x00007f82e426a500 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+03921152
[ 22] 0x00007f82e40868ac /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+01939628
[ 23] 0x00007f82e4082993 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+01923475
[ 24] 0x00007f82e4083797 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+01927063
[ 25] 0x00007f82e40eee50 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02367056
[ 26] 0x00007f82e48336b2 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_dispatcher.so+00562866 _ZN8Mfh_file11dispatch_fhEiPP11mxArray_tagiS2_+00000594
[ 27] 0x00007f82e42bdbf6 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+04262902
[ 28] 0x00007f82e42be37a /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+04264826
[ 29] 0x00007f82e42beeea /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+04267754
[ 30] 0x00007f82e4121bbd /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02575293
[ 31] 0x00007f82e414d412 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02753554
[ 32] 0x00007f82e414d53f /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02753855
[ 33] 0x00007f82e426a500 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+03921152
[ 34] 0x00007f82e40868ac /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+01939628
[ 35] 0x00007f82e4082993 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+01923475
[ 36] 0x00007f82e4083797 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+01927063
[ 37] 0x00007f82e40eee50 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02367056
[ 38] 0x00007f82e48336b2 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_dispatcher.so+00562866 _ZN8Mfh_file11dispatch_fhEiPP11mxArray_tagiS2_+00000594
[ 39] 0x00007f82e42bdbf6 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+04262902
[ 40] 0x00007f82e42be37a /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+04264826
[ 41] 0x00007f82e42beeea /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+04267754
[ 42] 0x00007f82e4121bbd /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02575293
[ 43] 0x00007f82e414d412 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02753554
[ 44] 0x00007f82e414d53f /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02753855
[ 45] 0x00007f82e426a500 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+03921152
[ 46] 0x00007f82e4083868 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+01927272
[ 47] 0x00007f82e40eee50 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02367056
[ 48] 0x00007f82e48336b2 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_dispatcher.so+00562866 _ZN8Mfh_file11dispatch_fhEiPP11mxArray_tagiS2_+00000594
[ 49] 0x00007f82e40bddcb /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+02166219
[ 50] 0x00007f82e407b7cc /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+01894348
[ 51] 0x00007f82e4077e1d /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+01879581
[ 52] 0x00007f82e4078255 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwm_interpreter.so+01880661
[ 53] 0x00007f82db146fae /usr/local/MATLAB/R2013a/bin/glnxa64/libmwbridge.so+00139182
[ 54] 0x00007f82db147111 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwbridge.so+00139537
[ 55] 0x00007f82db147ce5 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwbridge.so+00142565 _Z8mnParserv+00000725
[ 56] 0x00007f82e4acb3d2 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwmcr.so+00447442 _ZN11mcrInstance30mnParser_on_interpreter_threadEv+00000034
[ 57] 0x00007f82e4aaa9ac /usr/local/MATLAB/R2013a/bin/glnxa64/libmwmcr.so+00313772
[ 58] 0x00007f82e4aaab88 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwmcr.so+00314248
[ 59] 0x00007f82d865b5c6 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwuix.so+00480710
[ 60] 0x00007f82d8668df2 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwuix.so+00536050
[ 61] 0x00007f82e5195862 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwservices.so+01845346
[ 62] 0x00007f82e519650f /usr/local/MATLAB/R2013a/bin/glnxa64/libmwservices.so+01848591 _Z25svWS_ProcessPendingEventsiib+00001615
[ 63] 0x00007f82e4aab5ef /usr/local/MATLAB/R2013a/bin/glnxa64/libmwmcr.so+00316911
[ 64] 0x00007f82e4aabf5c /usr/local/MATLAB/R2013a/bin/glnxa64/libmwmcr.so+00319324
[ 65] 0x00007f82e4aa5592 /usr/local/MATLAB/R2013a/bin/glnxa64/libmwmcr.so+00292242
[ 66] 0x00007f82e2c47e9a /lib/x86_64-linux-gnu/libpthread.so.0+00032410
[ 67] 0x00007f82e297473d /lib/x86_64-linux-gnu/libc.so.6+01001277 clone+00000109
Useful Figure Management Utilities

This package contains 3 trivial figure management utilities I can't live without:
SHOWMETHEFIGS Allow user to cycle between all figures by hitting any key
FILLSCREEN Set a figure size to completely fill the screen.

FIGSHIFT Cascades current figure window away from previous figure

How to add VC++ complier in matlab
My matlab version is 2010a and I have just installed VC++2010. But I can't find VC++ Complier using command "mex -setup".
Should I install any other software to support it?
My PC is win7 32bit.
Re: viewing a pdf as image in Matlab
Thank you Steven.I solved the problem through calling ghostscript from Matlab terminal.

Farid



"Steven Lord" <Steven_Lord@mathworks.com> wrote in message <m1oq23$sds$1@newscl01ah.mathworks.com>...
>
> "Seyedfarid Ghahari" <ghahari@gmail.com> wrote in message
> news:m1msqt$7ft$1@newscl01ah.mathworks.com...
> > Hello,
> >
> > I need to view a pdf file (which is one page image) in Matlab. Note that I
> > would not open pdf file in atlab through "winopen". Of course, it is
> > possible to save as pdf file as image (e.g., jpg) in adobe acrobat and
> > then read it in Matlab. But, I would like to use only Matlab for some
> > reason.
> >
> > I would be thankful if anybody can help.
>
> A PDF is not an image. It is a Portable _Document_ Format file (emphasis
> mine.) I don't believe there are any functions in MATLAB to import PDFs,
> because again they are full documents not simply image files.
>
> Your best options are probably going to be to use Adobe Acrobat or another
> conversion program to create an image from your PDF or perhaps there's a
> Java command that can import PDFs. [I'm not familiar with Java, so I don't
> know for certain if there is or what that command would be if it does
> exist.]
>
> --
> Steve Lord
> slord@mathworks.com
> To contact Technical Support use the Contact Us link on
> http://www.mathworks.com
Unlocking The Other Senses of Space
These days it's no surprise to come across a gallery of amazing astronomy images. The Hubble Space Telescope, the other NASA great observatories and space probes, the European Space Agency and European Southern Observatory, and many, many dedicated amateurs (among other sources) provide a steady flow of visual riches. Mind-boggling beauty shows up every day; I can barely keep up with it in my Twitter feed. But what of the other human senses? Our appreciation of the natural world is bolste
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