lijia-xing / pmtk3 Goto Github PK

What steps will reproduce the problem?
1.
2.
3.

What is the expected output? What do you see instead?
 Attempted to access obsmat(:,3116); index out
of bounds because size(obsmat)=[2560,2560].

Error in ==> multinomial_prob at 19
  B(:,t) = obsmat(:, data(t));

Error in ==> dhmm_em>compute_ess_dhmm at 103
 obslik = multinomial_prob(obs, obsmat);

Error in ==> dhmm_em at 47
 [loglik, exp_num_trans, exp_num_visits1,
 exp_num_emit] = ...

Error in ==> Markov_Model at 72
[LL,prior_hat,A_hat,B_hat] = dhmm_em(signal+1,
prior,A1,B1, 'max_iter',4);


What version / revision of the product are you using? On what operating
system? Matlab R2011a, Windows 7


Please provide any additional information below.

I checked the multinomial_prob function from which the error seems to have been 
generated and found
for t=1:T
  B(:,t) = obsmat(:, data(t));
end
This doesn't make sense to me. Why does the observed value of my data have to 
be less than the dimensions of my output matrix? (Thats the root of the problem 
as far as I understand)

What steps will reproduce the problem?
1. Define a mrf using mrfCreate.  I used a simple 5x5 grid graph and define 
parameters nodePots and edgePots.

What is the expected output? What do you see instead?
I get an error saying
???  In an assignment  A(I) = B, the number of elements in B and
 I must be the same.

Error in ==> tabularFactorMultiply at 33
    ns(Ti.domain) = Ti.sizes;

The error seems to be in tabularFactorMultiply.m

What version / revision of the product are you using? On what operating system?
Latest april 2 version on Matlab 7.4 on Windows 7.

What steps will reproduce the problem?
1. run hmmDiscreteTest.m

What is the expected output? What do you see instead?

syntax error  [~,z] = max(pz,[],2)

What version / revision of the product are you using? On what operating
system?

pmtk3
Octave 3.2.4
Windows7

plotDecisionBoundary.m is broken in the current revision (r187)

What steps will reproduce the problem?
1.>> cd C:\pmtk3
>> initPmtk3


What is the expected output? What do you see instead?
>> initPmtk3
initializing pmtk3
downloading 38 packages to pmtk3/pmtksupportCopy from 
pmtksupport.googlecode.com - this may take a few minutes
downloading GGM-GWishart.............failed to download
downloading GPstuff-2.0..............failed to download
downloading SPAMS-1.02...............failed to download
downloading Sparsa...................failed to download
downloading boostingDemo.............failed to download
downloading bpca.....................failed to download
downloading dpMixWood................failed to download
downloading dpmixturesTeh07..........failed to download
downloading ekfukf1.2................failed to download
downloading export_fig...............failed to download
downloading exportfig................failed to download
downloading fastICA-2.5..............failed to download
downloading fastfit..................failed to download
downloading gaimc1.0-graphAlgo.......failed to download
downloading glmnet-matlab............failed to download
downloading gpml-matlab..............failed to download
downloading graphViz4Matlab..........failed to download
downloading l1ls.....................failed to download
downloading lars.....................failed to download
downloading libdai-0.2.6.............failed to download
downloading liblinear-1.51...........failed to download
downloading libsvm-mat-2.9.1.........failed to download
downloading lightspeed2.3............failed to download
downloading markSchmidt-9march2011...failed to download
downloading matbugs..................failed to download
downloading matlabRlink..............failed to download
downloading maxBranching.............failed to download
downloading mcmcdiag.................failed to download
downloading mplp-1.0.................failed to download
downloading netlab3.3................failed to download
downloading onlineEM.................failed to download
downloading pfColorTracker...........failed to download
downloading randraw..................failed to download
downloading rbpfSlam.................failed to download
downloading rjmcmcRbf................failed to download
downloading sparseBayes2.0...........failed to download
downloading svmLightWindows..........failed to download
downloading vblinlogreg..............failed to download
??? Error using ==> writeText at 31
could not open C:\pmtk3\pmtksupportCopy\pmtkSupportRoot.m

Error in ==> downloadAllSupport at 47
writeText(rootText, fullfile(destnRoot, 'pmtkSupportRoot.m'));

Error in ==> initPmtk3 at 49
    downloadAllSupport();

>> 

What version / revision of the product are you using? On what operating
system?
Matlab 7.9.0(R2009b)
Windows Vista

Please provide any additional information below.

What steps will reproduce the problem?
1. Create a condDiscreteProdCPD by any means with d > 1.
2. Run mkSoftEvidence on it and some observations.
3. Compare output with the brute-force for-loop implementation.

What is the expected output? What do you see instead?
The computed values for logB will be different. In particular, L(:,:,i) will be 
equal to zero for i not equal to d (the dimension of the observations).

What version / revision of the product are you using? On what operating
system?
The tarball from '23nov10'

Please provide any additional information below.
The exact error is clear: at line mkSoftEvidence.m, you'll see:
> L(:,:,d) = logT(:, Xobs(j, :), j);
Note that this is a for loop 'for j = 1:d', so the L(:,:,d) should instead be 
'L(:,:,j)'. This change fixes the issue.

What steps will reproduce the problem?
1. Download the current version (pmtk3-23nov10.zip)
2. run initPmtk3 
3. run testPmtk3

What is the expected output? What do you see instead?

Just downloaded pmtk3-23nov10.zip, and testPmtk3 produces:

parse error near line 53 of file 
/home/jpate/git/prosodicParsing/pmt3k/pmtk3-23nov10/toolbox/SupervisedModels/log
reg/logregFit.m

  syntax error

>>> [   weights       ....


Changing the "...." to "..." fixes the error.

What version / revision of the product are you using? On what operating
system?

$ uname -a
Linux PURPLE-HAZE 2.6.36-ARCH #1 SMP PREEMPT Sat Jan 8 14:15:27 CET 2011 x86_64 
Celeron(R) Dual-Core CPU T3000 @ 1.80GHz GenuineIntel GNU/Linux
$ octave -v
GNU Octave, version 3.2.4
Copyright (C) 2009 John W. Eaton and others.
This is free software; see the source code for copying conditions.
There is ABSOLUTELY NO WARRANTY; not even for MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE.

Octave was configured for "x86_64-unknown-linux-gnu".

Additional information about Octave is available at http://www.octave.org.

Please contribute if you find this software useful.
For more information, visit http://www.octave.org/help-wanted.html

Report bugs to <[email protected]> (but first, please read
http://www.octave.org/bugs.html to learn how to write a helpful report).


Please provide any additional information below.

Although I'm using octave, this just seems to be a typo with an extra "." 
(especially considering the output of svn diff -r2598 
toolbox/SupervisedModels/logreg/logregFit.m)

What steps will reproduce the problem?

 x=randn(100,20); y=randn(100,1); fit=glmnet(x,y);



What is the expected output? What do you see instead?

it shoudl return a struct. Instead  it returns

> x=randn(100,20); y=randn(100,1); fit=glmnet(x,y);
??? Invalid MEX-file 
'/Users/kpmurphy/pmtksupport/glmnet-matlab/glmnetMex.mexmaci64': 
dlopen(/Users/kpmurphy/pmtksupport/glmnet-matlab/glmnetMex.mexmaci64, 1):
Library not loaded: /usr/local/lib/libgfortran.2.dylib
  Referenced from: /Users/kpmurphy/pmtksupport/glmnet-matlab/glmnetMex.mexmaci64
  Reason: image not found.

Error in ==> glmnet at 254
    [a0,ca,ia,nin,rsq,alm,nlp,jerr] = glmnetMex(parm,x,y,jd,vp,ne,nx,nlam,flmin,ulam,thresh,isd,weights,ka);

254     [a0,ca,ia,nin,rsq,alm,nlp,jerr] = 
glmnetMex(parm,x,y,jd,vp,ne,nx,nlam,flmin,ulam,thresh,isd,weights,ka);


Please use labels and text to provide additional information.

it cannot find this fortran library:

/usr/local/lib/libgfortran.2.dylib

What steps will reproduce the problem?
1. model = mixexpFit(FGD,FGT,4);
2. >> yp=mixexpPredict(model,FGD);

What is the expected output? What do you see instead?
??? Reference to non-existent field 'Nclasses'.

Error in ==> mixexpPredict at 34
  yhat_k = zeros(N, model.Nclasses, K);

What version / revision of the product are you using? On what operating
system?
PMTK (r2776)/Windows (Matlab)

Please provide any additional information below.
yhat_k = zeros(N, model.Nclasses, K);
replace with 
yhat_k = zeros(N, model.nclasses, K);

dgmFit is supposed to handle missing local evidence, but currently crashes if 
you pass it a ragged array. 

What steps will reproduce the problem?

Edit dgmLogprobTest line 92 uncomment this line:


   %assert(approxeq(logZ7, logZ1, tol));

Then run dgmLogproTest.

What is the expected output? What do you see instead?

When trial=2, so all nodes are clamped, the logprob can be computed
by multiplying all the CPDs together, since the model is fully visible.
This should give the same result as the normalization constant for
inference. However, the assertion is violated.

Please use labels and text to provide additional information.

Bayes net probability of the evidence computation is failing.
Pretty fundamental... (seems to work if libdai on path - not sure
what the connection is, the libdai should not need to be called
if the model is fully visible)

What steps will reproduce the problem?
1. Run the initialization

What is the expected output? What do you see instead?

Process:         MATLAB [16789]
Path:            
/Applications/MATLAB_R2012a_Student.app/Contents/MacOS/StartMATLAB
Identifier:      com.mathworks.matlab
Version:         R2012a [7.14.0] (7.14.0)
Code Type:       X86-64 (Native)
Parent Process:  launchd [394]
User ID:         501

Date/Time:       2012-10-22 02:59:08.805 +0100
OS Version:      Mac OS X 10.8.2 (12C60)
Report Version:  10

Interval Since Last Report:          342359 sec
Crashes Since Last Report:           66
Per-App Interval Since Last Report:  74655 sec
Per-App Crashes Since Last Report:   30
Anonymous UUID:                      4A31AB5A-7A61-775E-2132-0CD351D2D0EC

Crashed Thread:  3

Exception Type:  EXC_BREAKPOINT (SIGTRAP)
Exception Codes: 0x0000000000000002, 0x0000000000000000

Dyld Error Message:
  Symbol not found: __gfortran_allocate64_array
  Referenced from: /Users/USER/*/glmnetMex.mexmaci64
  Expected in: /Applications/MATLAB_R2012a_Student.app/sys/os/maci64/libgfortran.3.dylib

What version / revision of the product are you using? On what operating
system?

Matlab Student Version R2012a 64-bit (maci64) on Mac OS 10.8.2 (Mountain Lion)

Please provide any additional information below.

The problem appears at the last step of the initialization "Compile mex", after 
pfColorTracker.

What steps will reproduce the problem?
1. Set len to 101 in hmmDiscreteFitTest
2. Run the demo

From Nachi Sahoo:

hmmFitEM.m, line 207-209: it is relying on a hard clustering
assignment to initialize transition probability matrix. Sometimes the
initial clustering gets a fewer number of clusters than the number of
states in hmm. So, the transition probability matrix formed on line
209 is smaller than it should be. One way to fix it is to change line
209 from
        A      = accumarray([z(1:end-1), z(2:end)], 1);
to
        A      = accumarray([z(1:end-1), z(2:end)], 1, [nstates,
nstates]);

Since, we'd know the number of states at this point. It ensures that
we'd have the correct sized transition matrix.

What steps will reproduce the problem?
1. pmtk3-3jan[[11]].zip


What is the expected output? What do you see instead?

It is 2012 now.


What version / revision of the product are you using? On what operating
system?

n/a


Please provide any additional information below.

What steps will reproduce the problem?
1. train separate models using positive discrete samples from different classes
2. cross-test for the highest likelihood using hmmLogprob

What is the expected output? What do you see instead?

hmmLogprob sometimes crashes when a model is tested on data that do not belong 
to the same class

What version / revision of the product are you using? On what operating system? 
pmtk3 nov 2010

Please provide any additional information below.

The problem is that the discretized positive samples in the training set might 
not include all the possible observations for a class, but hmmFit estimates the 
number of observations from the positive samples. So, if there are 8 
observation symbols, but a class makes use of only the first 6, the trained 
model also has 6 observation states, and cannot evaluate samples belonging to 
other classes, a crucial step for classification. 

Solution:
There should be an option to set the number of observations directly. 

What steps will reproduce the problem?
1. Fully  defined a HMM (hmmCreate)
2. Sampled training and test data  (hmmSample)
3. Trained a HMM (hmmFit)
4. Tested HMM (hmmLogprob)
-> Got a log likelihood greater than zero.

Things that look weird:

The state-transition matrix A of the trained model is not normalized: 
normalize(model.A)-model.A should be zero(..).

Could also be a numerical over-/underflow issue: I am using relative long 
sequencces.

Or my sampling HMM could be crap:

%d=1
nstates = 7;
pi = [1 0 0 0 0 0 0];
A = normalize(diag(ones(nstates, 1)) + ...
            diag(ones(nstates-1, 1), 1), 2);
sigma = [[0.05],[0.05],[0.05],[0.05],[0.05],[0.05],[0.05]];
mu = [0.7, 1.4, 2.1, 2.8, 3.5, 4.2, 4.9];
emission = condGaussCpdCreate(mu, sigma);

modelValid = hmmCreate('gauss', pi, A, emission);

What is the expected output? What do you see instead?
The log of a probality can't be greater than zero.

What version / revision of the product are you using? On what operating
system?
MATLAB 2009a


Please provide any additional information below.

- libsvm-mat-2.9.1 does not have .mexmaci64 binaries, and running 'make'
does not create them

What steps will reproduce the problem?

 x=randn(10,20); y=randn(10,1);
 model = svmFit(x, y, 'C', 1,'kernelParam', 1, 'kernel', 'rbf'); 



What is the expected output? What do you see instead?

It should return a model struct.
Instead I get this message

??? Undefined function or method 'libsvmTrain' for input arguments of type 
'double'.

Error in ==> svmlibFit at 89
model = libsvmTrain(y, X, options);

Error in ==> svmFit at 147
    model = fitFn(X, y, C, kernelParam, kernel, fitOptions{:});



Please use labels and text to provide additional information.


svmFit chooses which svm solver to use: it could be libsvm,
svmlight (windows only), or pure matlab (needs opt toolbox).

Currently this choice is made based on expected speed of the method,
not based on the OS the user is using. This should be improved.

What steps will reproduce the problem?
1. > initPmtk3Octave
2. > plotMFCC

What is the expected output? What do you see instead?

The specgram function does not run and no plot is produced.  I expected 
'signalToolboxInstalled' to be true, but it is not.

What version / revision of the product are you using? On what operating system?

I'm using a copy off trunk at http://pmtk3.googlecode.com/svn/trunk with Octave 
3.2.3 on Ubuntu 10.04.3 LTS.


Please provide any additional information below.

I investigated and found that the initPmtkOctave function unilaterally sets 
*ToolboxInstalled variables to 0.  Inspecting the normal init function, I 
learned how I *thought* things should work and made modifications such that it 
did.  My patch for this assumes that if the folder named in 'toolbox' exists in 
the path, then the toolbox must be installed.  This may or may not be the 
appropriate way to detect this in Octave.  If it is not, I'd be happy to 
improve the patch by making it more robust.

I also had make another change in order to get this to work correctly.  It 
seems restoredefaultpath() does not do what I expected, in that the signal 
processing toolbox is omitted from the path after this function is called.  But 
upon further reading, it appears the correct behavior is to set the path to its 
value /prior to any octaverc processing/ 
(http://octave.1599824.n4.nabble.com/octaverc-and-version-in-path-td1648598i20.h
tml).  So, given the fact that the toolkit paths are added in 
/etc/octave3.2.conf, I'm proposing restoredefaultpath() be removed.  Would this 
cause problems elsewhere?  If so, perhaps there is a way to trigger the path 
changes that come from the system-wide initialization file (and perhaps the 
user initialization files as well), so that restoredefaultpath() can still be 
used, but the add-on paths are included as well.

What steps will reproduce the problem?
1.Fitting a HMM on observations and setting the nr of States higher than 2
2. This is a Gauss or GaussMixTied
3. It works normal with 1xT(i)  sequences

What is the expected output? What do you see instead?
An error is generated at the next line with  generativeClassifierFit. Chol 
seems to be the problem in gaussLogprob at line 52

What version / revision of the product are you using? On what operating
system? Edition pmtk3 28feb 2011, Matlab R2007b, Ubuntu


Please provide any additional information below.
File is based on 
http://pmtk3.googlecode.com/svn-history/r2517/trunk/docs/tutorial/html/tutGenCla
ssif.html

What steps will reproduce the problem?
1. x = some_test_data 
2. mixModel = mixGaussFit(x, 2,  'verbose', true, 'maxIter', 
100,'nrandomRestarts',100);

What is the expected output? What do you see instead?
********** Random Restart 2 **********
initializing model for EM
??? Undefined function or variable 'd'.

Error in ==> mixGaussFit>initGauss at 41
    mu              = randn(d, nmix);

Error in ==> mixGaussFit>@(m,X,r)initGauss(m,X,r,initParams,prior) at 24
initFn = @(m, X, r)initGauss(m, X, r, initParams, prior);

Error in ==> emAlgo at 56
model = init(model, data, restartNum);

Error in ==> emAlgo at 38
        [models{i}, llhists{i}] = emAlgo(model, data, init, estep,...

Error in ==> mixGaussFit at 25
[model, loglikHist] = emAlgo(model, data, initFn, @estep, @mstep , ...

What version / revision of the product are you using? On what operating
system?
PMTK (r2774)/Windows (Matlab)

Please provide any additional information below.
Failure in 
function model = initGauss(model, X, restartNum, initParams, prior)
when restartNum ~= 1
mu              = randn(d, nmix);
regularizer     = 2; 
Sigma           = stackedRandpd(d, nmix, regularizer); 
model.mixWeight = normalize(rand(1, nmix) + regularizer); 

We need to define d from model or from data.

What steps will reproduce the problem?
1.modelEM = hmmFit(observed, nstates, 'discrete', ...
    'maxIter', 1000, 'verbose', true, 'convTol', 1e-7, 'nRandomRestarts', 3);
2.
3.

What is the expected output? What do you see instead?

??? Error using ==> normalize
Too many input arguments.

Error in ==> discreteFit at 32
model.T = normalize(bsxfun(@plus, counts, colvec(alpha-1)), 1);


What version / revision of the product are you using? On what operating
system?

pmtk3-3jan11. Windows 7. Matlab R2010a


Please provide any additional information below.

What steps will reproduce the problem?
1.initial installation of pmtk in matlab
2.
3.

What is the expected output? What do you see instead?
i get this error:
>> initPmtk3
initializing pmtk3
downloading 38 packages to pmtk3/pmtksupportCopy from 
pmtksupport.googlecode.com - this may take a few minutes
downloading GGM-GWishart.............Error using perl (line 80)
System error: Can't locate LWP/Simple.pm in @INC (@INC contains: /etc/perl 
/usr/local/lib/perl/5.14.2
/usr/local/share/perl/5.14.2 /usr/lib/perl5 /usr/share/perl5 /usr/lib/perl/5.14 
/usr/share/perl/5.14
/usr/local/lib/site_perl .) at 
/home/pajrul/pmtk3-3jan11/pmtkTools/supportTools/fetchfile.pl line 4.
BEGIN failed--compilation aborted at 
/home/pajrul/pmtk3-3jan11/pmtkTools/supportTools/fetchfile.pl line
4.
Command executed: perl 
/home/pajrul/pmtk3-3jan11/pmtkTools/supportTools/fetchfile.pl "
http://pmtksupport.googlecode.com/svn/trunk/GGM-GWishart/GGM-GWishart.zip"
/home/pajrul/pmtk3-3jan11/pmtksupportCopy/GGM-GWishart.zip

Error in downloadFile (line 13)
    status = perl(fetcher, source, dest);

Error in downloadAllSupport (line 21)
    ok     = downloadFile(source, dest);

Error in initPmtk3 (line 49)
    downloadAllSupport();


What version / revision of the product are you using? On what operating
system?
on matlab r2011b running on ubuntu 12.04

Please provide any additional information below.

In revision 33 of pmtk3, util/setSeed.m and util/restoreSeed.m were
removed. However, these functions are still used by util/Kfold.m

What steps will reproduce the problem?

1. > initPmtk3Octave
2. > isolatedWordClassificationWithHmmsDemo
3. /several errors occur/


What is the expected output? What do you see instead?

Output should match that shown in the tutorial.  Three separate errors -- two 
apparently related to Octave/Matlab compatibility issues and one typo -- 
prevent the demo from running to completion.

What version / revision of the product are you using? On what operating system?

I'm using a copy off trunk at http://pmtk3.googlecode.com/svn/trunk with Octave 
3.2.3 on Ubuntu 10.04.3 LTS.


Please provide any additional information below.

The errors are:

 * toolbox/LatentVariableModels/hmm/sub/hmmFitEm.m: Replace tilde (~)
   used to ignore output parameter.
 * toolbox/Algorithms/optimization/emAlgo.m: Delete extra '.' causing
   syntax error.
 * demos/isolatedWordClassificationWithHmmsDemo.m: Replaced call to
   display() with disp().

The first fix is a known issue:

  http://code.google.com/p/pmtk3/issues/detail?id=26

The third fix may not be the right thing to do.  Octave /has/ a display() 
function, and I can't imagine why it can't handle basic types.  I can 
demonstrate the error by entering

  octave:3> d=3.14
  d =  3.1400
  octave:4> display(d)
  error: display: not defined for class "double"
  error: called from:
  error:   /usr/share/octave/3.2.3/m/general/display.m at line 36, column 3

What steps will reproduce the problem?
1.Running the code on HMM with many states and sub-states.

What is the expected output? What do you see instead?
Expected: Positive transition and output matrix 
Obtained: small negative values (~10-18) Can these be due to numerical 
problems? 

What version / revision of the product are you using? On what operating
system?
The 2005 MIT release

Please provide any additional information below.

What steps will reproduce the problem?
 a=[1,2,3,4,5,6,1,2,3,4,5,6,6,5,4,3,2,1,1,2,3,31,31,2,32,12,4,5,60,0,2,1,3,4,5,81,32,2,1];

[model, loglikHist] = hmmFit(a, 2, 'discrete');

(This example is due to George Toderici)


What is the expected output? What do you see instead?

The penalizd log likelihood should go up, but instead it gives a warning that 
it does not.


Please use labels and text to provide additional information.


The problem is that the data involves a non consecutive set of integers, 
spanning 0 to 81. Internally this gets canonized to 1..12. However,there is 
still some residual problem. Perhaps the log prior on the transmat is not being 
added to the objective function.

What steps will reproduce the problem?
1.Some functionality that uses function
path = viterbi_path(prior, transmat, obslik)

What is the expected output? What do you see instead?

What version / revision of the product are you using? On what operating
system?
pmtk r2776

Please provide any additional information below.
Replace normalise function with normalize one on lines: 53, 64
http://code.google.com/p/pmtk3/source/browse/trunk/toolbox/LatentVariableModels/
hmm/sub/viterbi_path.m#53

What steps will reproduce the problem?
1.initPmtk3

What is the expected output? What do you see instead?
-pmtkSupportRoot.m failed to download

What version / revision of the product are you using? On what operating
system?
-pmtk3-2april2011 , Windows7  64 bits, Matlab 7.11.0 (R2001b)

Please provide any additional information below.

downloading 39 packages to pmtk3/pmtksupportCopy from 
pmtksupport.googlecode.com - this may take a few minutes
downloading GGM-GWishart.............done
downloading GPstuff-2.0..............done
downloading SPAMS-1.02...............done
downloading boostingDemo.............done
downloading bpca.....................done
downloading dpMixWood................done
downloading dpmixturesTeh07..........done
downloading ekfukf1.2................done
downloading export_fig...............done
downloading exportfig................done
downloading fastICA-2.5..............done
downloading fastfit..................done
downloading gaimc1.0-graphAlgo.......done
downloading glmnet-matlab............done
downloading gpml-matlab..............done
downloading graphViz4Matlab..........done
downloading l1ls.....................done
downloading lars.....................done
downloading libdai-0.2.6.............done
downloading liblinear-1.51...........done
downloading libsvm-mat-2.9.1.........done
downloading lightspeed2.3............done
downloading markSchmidt-9march2011...done
downloading matbugs..................done
downloading matlabRlink..............done
downloading maxBranching.............done
downloading mcmcdiag.................done
downloading mplp-1.0.................done
downloading netlab3.3................done
downloading onlineEM.................done
downloading pfColorTracker...........done
downloading pmtkSupportRoot.m........failed to download
downloading randraw..................done
downloading rbpfSlam.................done
downloading readme.txt...............failed to download
downloading rjmcmcRbf................done
downloading sparseBayes2.0...........done
downloading svmLightWindows..........done
downloading vblinlogreg..............done

What steps will reproduce the problem?
1. Fit a HMM model using MixGaussTied
2.
3.

What is the expected output? What do you see instead?

As the help describes, the model should output a matrix model.emission.M such 
that M(j,k) = p(Mt = k| St=j) where Mt is the mixture. Therefore, truly M's 
ROWS and not COLUMNS should sum to 1. This is necessary in order for the other 
equation in the help to be true, that is 
P(Xt |St =i) = Sum_m P(Mt = m  |St =i) gauss(Xt |mu(m), Sigma(m) ). 
Note then that in the above equation it is necessary for Sum_m P(Mt = m|St = i) 
= 1, otherwise we aren't normalizing the probability correctly. But note that 
this sum over index m, corresponds to summing ROW i of matrix M. However the 
output of this algorithm is always a matrix M that has its COLUMNS summing to 
1. But this makes no sense, because this is a sum over the mixture weight of 
certain component across states. Instead what we truly want is to have a matrix 
M, with each row telling us the mixing components of the mixture, and this 
components should sum to 1 for each state (i.e. for each row).

What version / revision of the product are you using? On what operating
system?
Linux, version from 3Jan11.

Please provide any additional information below.

What steps will reproduce the problem?
Run the initialization

What is the expected output? What do you see instead?

Matlab crashes gives this error message:

Process:         MATLAB [3801]
Path:            /Applications/MATLAB_R2012a.app/Contents/MacOS/StartMATLAB
Identifier:      com.mathworks.matlab
Version:         R2012a [7.14.0] (7.14.0)
Code Type:       X86-64 (Native)
Parent Process:  launchd [134]

Date/Time:       2012-09-16 00:31:51.371 -0400
OS Version:      Mac OS X 10.7.4 (11E53)
Report Version:  9

Interval Since Last Report:          79014 sec
Crashes Since Last Report:           4
Per-App Interval Since Last Report:  575374 sec
Per-App Crashes Since Last Report:   4
Anonymous UUID:                      6BFC8F52-6A0E-496B-9C3C-652CC662D37A

Crashed Thread:  3

Exception Type:  EXC_BREAKPOINT (SIGTRAP)
Exception Codes: 0x0000000000000002, 0x0000000000000000

Application Specific Information:
objc[3801]: garbage collection is OFF

Dyld Error Message:
  Symbol not found: __gfortran_allocate64_array
  Referenced from: /Users/USER/Documents/*/glmnetMex.mexmaci64
  Expected in: /Applications/MATLAB_R2012a.app/sys/os/maci64/libgfortran.3.dylib

What version / revision of the product are you using? On what operating
system?

Jan11 2012, version 3

Mac OS Lion (10.7.4)


Please provide any additional information below.

The problem seems to appear at the last step of the initialization  "Compile 
mex"

What steps will reproduce the problem?
1. Edit line 6 of mypath: p = tokenize(path, ';:');   so that it has a chance 
of working on macosx
2. Run whoCallsMe

What is the expected output? What do you see instead?
seg violation

What version / revision of the product are you using? On what operating
system?
MaxOSX 10.6.5

Please provide any additional information below.

What steps will reproduce the problem?
1. Running MATLAB 2012A on win7.
2. call model = hmmFitEm(X, 25, 'gauss'); where X = 1x8,000 vector of values 
between -3 and +3 on a grid with 0.25 spacing.
3. Following output seen:

Error using chol
Matrix must be positive definite.

Error in gaussLogprob (line 52)
    R    = chol(Sigma);

Error in mixGaussInferLatent (line 17)
  logPz(:, k) = logMix(k) + gaussLogprob(mu(:, k), Sigma(:, :, k), X);

Error in mixGaussFit>estep (line 52)
[weights, ll] = mixGaussInferLatent(model, data);

Error in emAlgo (line 62)
    [ess, ll] = estep(model, data);

Error in mixGaussFit (line 25)
[model, loglikHist] = emAlgo(model, data, initFn, @estep, @mstep , ...

Error in hmmFitEm>initWithMixModel (line 244)
    mixModel    = mixGaussFit(stackedData, nstates,  'verbose', false, 'maxIter', 10);

Error in hmmFitEm>initGauss (line 146)
        model = initWithMixModel(model, data);

Error in hmmFitEm>@(m,X,r)initFn(m,X,r,emissionPrior) (line 45)
initFn = @(m, X, r)initFn(m, X, r, emissionPrior);

Error in emAlgo (line 56)
model = init(model, data, restartNum);

Error in hmmFitEm (line 46)
[model, loglikHist] = emAlgo(model, data, initFn, @estep, @mstep, EMargs{:});


model = hmmFitEm(X, config.K, 'gauss');

What steps will reproduce the problem?

  Simply try to use conversation matrix NSTATESxNSTATES and a vector as pi0 that is <> NSTATES (not 1xNSTATES). This results in an error in hmmFwdBack.*: Can't multiply pi0 * A by MATLAB.

  Happened to me using isolatedWordClassificationWithHmmsDemo and changing nstates. Because pi0 is a fixed vector it wasn't and thus leads to the error.

What is the expected output? What do you see instead?

  hmmFit should assert(pi0 * A) is possible and else report correct size needed.

What version / revision of the product are you using? On what operating
system?
pmtk3: 24 October and MATLAB 2009a

What steps will reproduce the problem?
1. Set a weight vector in glmnetSet() produced options struct
2. Run cvglmnetMulticlass() with above options

What is the expected output? What do you see instead?
Should train a glmnet model. Instead, error occurs in cvglmnetMulticlass() line 
60 because the weight vector inside the CV loop has a different size w.r.t 
target vector y.

What version / revision of the product are you using? On what operating
system?
pmtk3-3jan11/pmtk3-2april2011, Win7 64bit

Please provide any additional information below.
Proposed MATLAB code to replace lines 57-62 in cvglmnetMulticlass.m:

weights = options.weights;
for i=1:nfolds
    which=foldid==i;
    if verbose, disp(['Fitting fold # ' num2str(i) ' of ' num2str(nfolds)]);end
    options.weights = weights(~which);
    cvfit = glmnet(x(~which,:), y(~which),family, options);
    predmat(which,:) = glmnetPredict(cvfit, type,x(which,:),options.lambda);
end
options.weights = weights;

>> loadData('data45')

downloading  http://pmtkdata.googlecode.com/svn/trunk/data45/data45.zip to 
F:\matlab_scripts\toolboxes\pmtk3-2april2011\pmtkdataCopy\data45.zip
??? Error using ==> loadData at 79
Cannot find
http://pmtkdata.googlecode.com/svn/trunk/data45/data45.zip 

What steps will reproduce the problem?

%% generate observation sequence and hidded state sequence using Matlab
%% HMM toolbox
TRANS = [.9 .1; .05 .95;];

EMIS = [1/6, 1/6, 1/6, 1/6, 1/6, 1/6;...
7/12, 1/12, 1/12, 1/12, 1/12, 1/12];

[seq,states] = hmmgenerate(10000,TRANS,EMIS);

%% test hmmFit function of pmtk3
[model, loglikHist] = hmmFit(seq, 2, 'discrete');
model.emission.T    % good
model.A             % good

%% test hmmFitFullyObs function of pmtk3
model = hmmFitFullyObs(states, seq, 'discrete');
model.emission.T    % problem: all elements of this matrix are "1"
model.A             % good


What is the expected output? What do you see instead?
All elements of model.emission.T generated by hmmFitFullyObs function are "1", 
which I think is not correct.

What version / revision of the product are you using? On what operating
system?
pmtk3-23nov10, Matlab 2009b, Win XP sp3


Please provide any additional information below.

What steps will reproduce the problem?
1. Download pmtk3-23nov10.zip or the current svn
2. run initPmtk3 then testPmtk3 in current Octave

What is the expected output? What do you see instead?

I expect to see the tests all pass. Instead, I receive the error message:

error: cov: x and y must have the same number of observations
error: called from:
error:   /usr/share/octave/3.2.4/m/statistics/base/cov.m at line 56, column 7
error: evaluating argument list element number 1
error: evaluating argument list element number 1
error:   
/home/jpate/git/prosodicParsing/pmt3k/pmtk3-23nov10/toolbox/LatentVariableModels
/ppca/sub/pcaPmtk.m at line 31, column 18
error:   
/home/jpate/git/prosodicParsing/pmt3k/pmtk3-23nov10/demos/bookDemos/Latent_facto
r_models_for_continuous_data/pcaDemo2d.m at line 12, column 28
error:   /home/jpate/git/prosodicParsing/pmt3k/pmtk3-23nov10/testPmtk3.m at 
line 75, column 

cov is different in octave and matlab, see:

http://www.mathworks.com/help/techdoc/ref/cov.html
http://octave.sourceforge.net/octave/function/cov.html



What version / revision of the product are you using? On what operating
system?

Again, this is with both a fresh svn clone and the .zip file in the Downloads 
page.

$ uname -a
Linux PURPLE-HAZE 2.6.36-ARCH #1 SMP PREEMPT Sat Jan 8 14:15:27 CET 2011 x86_64 
Celeron(R) Dual-Core CPU T3000 @ 1.80GHz GenuineIntel GNU/Linux
$ octave -v
GNU Octave, version 3.2.4
Copyright (C) 2009 John W. Eaton and others.
This is free software; see the source code for copying conditions.
There is ABSOLUTELY NO WARRANTY; not even for MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE.

Octave was configured for "x86_64-unknown-linux-gnu".

Additional information about Octave is available at http://www.octave.org.

Please contribute if you find this software useful.
For more information, visit http://www.octave.org/help-wanted.html

Report bugs to <[email protected]> (but first, please read
http://www.octave.org/bugs.html to learn how to write a helpful report).



Please provide any additional information below.

We see that line 32 of testPmtk3.m is commented out and the offending line 31 
is added in revision 2551 with

svn blame toolbox/LatentVariableModels/ppca/sub/pcaPmtk.m 

but there is no commit message. I tried uncommenting 32 and commenting out line 
31, and all tests from testPmtk3 pass.

What steps will reproduce the problem?
1.>> system('svn checkout http://pmtk3.googlecode.com/svn/trunk/ pmtk3')
Checked out revision 2659. 
ans =
     0
2.>> downloadAllSupport
downloading GGM-GWishart.............done
downloading SPAMS-1.02...............failed
downloading bpca.....................done
downloading dpmixturesTeh07..........done
downloading ekfukf1.2................done
downloading export_fig...............done
downloading exportfig................done
downloading fastICA-2.5..............done
downloading fastfit..................done
downloading gaimc1.0-graphAlgo.......done
downloading glmnet-matlab............done
downloading gpml-matlab..............done
downloading graphViz4Matlab..........done
downloading l1ls.....................done
downloading lars.....................done
downloading libdai-0.2.6.............done
downloading liblinear-1.51...........done
downloading libsvm-mat-2.9.1.........done
downloading lightspeed2.3............done
downloading markSchmidt-21june2010...done
downloading matbugs..................done
downloading matlabRlink..............done
downloading mcmcdiag.................failed
downloading mplp-1.0.................done
downloading netlab3.3................done
downloading onlineEM.................done
downloading randraw..................done
downloading sparseBayes2.0...........done
downloading svmLightWindows..........done
downloading vblinlogreg..............done

What is the expected output? What do you see instead?
downloading SPAMS-1.02...............failed
downloading mcmcdiag.................failed

What version / revision of the product are you using? On what operating
system?
revision 2659

Please provide any additional information below.
I think there are no ZIPped files on the paths
http://pmtksupport.googlecode.com/svn/trunk/SPAMS-1.02/
and
http://pmtksupport.googlecode.com/svn/trunk/mcmcdiag/

Thanks

What steps will reproduce the problem?
1. Follow the installation instruction: 
http://code.google.com/p/pmtk3/wiki/installation
2. Macintosh; matlab 7.9.0.529 (R2009b)
3. testPmtk3 crashes.

What is the expected output? What do you see instead?

I expected the demos to run. Instead I get:
??? Undefined function or variable 'p'.

Error in ==> LogisticLossSimple at 16
Xw = X .* repmat(rowvec(weights), 1, p);

Sure enough, LogisticLossSimple refers to an undefined variable 'p'.

What version / revision of the product are you using? On what operating
system?
pmtk3-24October2010.zip
MacOS 10.6.5


Please provide any additional information below.

Here's the command history in matlab:
>> initPmtk3
initializing pmtk3
downloading GGM-GWishart.............done
downloading SPAMS-1.02...............failed
downloading bpca.....................done
downloading dpmixturesTeh07..........done
downloading ekfukf1.2................done
downloading export_fig...............done
downloading exportfig................done
downloading fastICA-2.5..............done
downloading fastfit..................done
downloading gaimc1.0-graphAlgo.......done
downloading glmnet-matlab............done
downloading gpml-matlab..............done
downloading graphViz4Matlab..........done
downloading l1ls.....................done
downloading lars.....................done
downloading libdai-0.2.6.............done
downloading liblinear-1.51...........done
downloading libsvm-mat-2.9.1.........done
downloading lightspeed2.3............done
downloading markSchmidt-21june2010...done
downloading matbugs..................done
downloading matlabRlink..............done
downloading mcmcdiag.................failed
downloading mplp-1.0.................done
downloading netlab3.3................done
downloading onlineEM.................done
downloading randraw..................done
downloading sparseBayes2.0...........done
downloading svmLightWindows..........done
downloading vblinlogreg..............done
welcome to pmtk3
>> testPmtk3
Checking for matlabTools.........PASSED
Checking initialization..........PASSED
Checking pmtkSupport packages....PASSED
Checking pmtkData................downloading  
http://pmtkdata.googlecode.com/svn/trunk/crabs/crabs.zip to 
/Users/don/Documents/MATLAB/MurphySimulator/pmtk3/data/crabs.zip
unzipped and loaded crabs.mat
PASSED
Checking for graphviz............Please install or upgrade graphViz
Please install or upgrade graphViz
Please install or upgrade graphViz
Please install or upgrade graphViz
Please install or upgrade graphViz
FAILED
Testing selected code............



nll =
    6.9315
??? Undefined function or variable 'p'.

Error in ==> LogisticLossSimple at 16
Xw = X .* repmat(rowvec(weights), 1, p);

Error in ==> logregFit>@(w)LogisticLossSimple(w,X,y,weights) at 101
    loss = @(w) LogisticLossSimple(w, X, y, weights);

Error in ==> penalizedL2 at 13
    [nll,g] = gradFunc(w,varargin{:});

Error in ==> logregFit>@(w)penalizedL2(w,loss,lambdaVec(:)) at 133
    penloss = @(w)penalizedL2(w, loss, lambdaVec(:));

Error in ==> minFunc at 303
    [f,g] = funObj(x,varargin{:});

Error in ==> logregFit at 135
    [w, opt.finalObj, opt.exitflag, opt.output] = ...

Error in ==> logregL2FitTest at 19
model1 = logregFit(X, y01, 'lambda', lambda, 'preproc', pp, 'fitOptions', opts);

Error in ==> testPmtk3 at 66
logregL2FitTest;

What steps will reproduce the problem?
1. dgmLogprobTest - the final assertion (commented out) fails

What is the expected output? What do you see instead?


Please use labels and text to provide additional information.

I changed dgmInferNodes and insertClampedBels to handle
the case that single marginals are not returned as cell arrays.
It's something to do with this.

What steps will reproduce the problem?
1.x=[1 2 1 1 2; ...
     2 2 2 2 1; ...
     1 1 1 1 2 ]
2.model=markovFit(x);

What is the expected output? What do you see instead?
>> model.A
ans =
    0.5714    0.4286
    0.4000    0.6000
>> model.pi
ans =
    0.6667    0.3333
===========================but we have
??? Error using ==> plus
Matrix dimensions must agree.

Error in ==> markovFit at 27
model.pi = rowvec(normalize(histc(X(:, 1), 1:nstates)) + rowvec(pseudoCountsPi 
- 1));

What version / revision of the product are you using? On what operating
system?
PMTK (r2774), Matlab

Please provide any additional information below.
I think the simplest way is to change 
model.pi = rowvec(normalize(histc(X(:, 1), 1:nstates)) + rowvec(pseudoCountsPi 
- 1));
to 
model.pi = rowvec(normalize(histc(X(:, 1)', 1:nstates)) + rowvec(pseudoCountsPi 
- 1));

What steps will reproduce the problem?
1. Follow the tutorial on: 
http://pmtk3.googlecode.com/svn/trunk/docs/tutorial/html/tutFoundations.html
2. From this line on I get different outputs to the ones shown in the tutorial: 
m2 = gaussFit(X(1:50,:)); cond(m2.Sigma)
3. Later, this crashes: L = gaussLogprob(m3, X);
Saying: ??? Error using ==> chol
Matrix must be positive definite.

What is the expected output? What do you see instead?
An output for L is expected. I get an error.

What version / revision of the product are you using? On what operating
system?
R2011a (64bit) on Windows 7 64bit system

Please provide any additional information below.
Looking inside the gaussLogprob function, it says:

% Full covariance case
  if 0
       logp2 = -0.5*sum((X/Sigma).*X, 2);
       logZ2 = (d/2)*log(2*pi) + 0.5*logdet(Sigma);
       logp2 = logp2 - logZ2;
  end
  %   slightly faster version
  R    = chol(Sigma);
  logp = -0.5*sum((X/R).^2, 2);
  logZ = 0.5*d*log(2*pi) + sum(log(diag(R)));
  logp = logp - logZ;

Maybe the 'if 0' should be replaced by a test for positive definiteness.

Dear Sir / Madam,

I am using the matbugs interface you developed to run WinBugs from MatLab. 
However, in the last days, it start not to work as it appears  the following 
image (in WinBugs) when i run it from MATLAB. I suppose the question is the way 
both softwares are communicating but don’t know, exactly, where the erro ris. 
Could you help me on that? I install WinBUGS in folder ‘C:/JCM/WinBugs14’, 
then i run the matbugs.m, by running the schools example and the WinBugs 
feedback is the one in atachment (MATLAB2009b and WINDOWS7).

Sincere regards,

Jose Matos

What steps will reproduce the problem?
1. have matlabroot not contain MATLAB: in all caps
2. run initPmtk3
3.

What is the expected output? What do you see instead?

Instead of a successful initialization, the output is

>> initPmtk3
initializing pmtk3
??? Error using ==> catdirs at 24
All arguments must be strings.

Error in ==> addpath at 64
p = catdirs(varargin{1:n});

Error in ==> initPmtk3 at 12
addpath(genpathPMTK(fullfile(thisDir, 'localUtil')));


What version / revision of the product are you using? On what operating
system?
Revision: 2135
Please provide any additional information below.
For the time being case insensitive search might work for most people. i.e., 
change line 13 in genpathPMTK.m from 

if isempty(strfind(matlabroot, 'MATLAB'))

to 

if isempty(strfind(upper(matlabroot), 'MATLAB'))

What steps will reproduce the problem?

trainingData = data(:,4);
nHidStates = 4;

% Learn the model using EM with random restarts
nrestarts = 2;
modelEM = hmmFit(trainingData, nHidStates, 'discrete', ...
    'convTol', 1e-5, 'nRandomRestarts', nrestarts, 'verbose', false);

What is the expected output? What do you see instead?

It should create an hmm model. Instead it returns the error:

??? Undefined function or method 'logsumexp' for input arguments of type 
'double'.

Error in ==> normalizeLogspace at 12
L = logsumexp(x, 2);

What version / revision of the product are you using? On what operating system?

Matlab version R2010b on Windows XP running pmtk3.


Please provide any additional information below.

PMTK installation failed -- was unable to download during the installation 
process -- proxy should have worked.

What steps will reproduce the problem?
N/A
What is the expected output? What do you see instead?
N/A
Please provide any additional information below.

The attached file is a simple utility for converting factor graphs to pairwise 
MRF models (very similar to factorGraphToMrf2) due to mrfCreate not currently 
supporting general clique potentials. Intended to help with importing from 
formats external to pmtk3 (i.e. convert to factor graph representation and from 
there to mrf or mrf2 in order to be able to call different inference routines).

What steps will reproduce the problem?
1. run hmmNbestDemo.m
2. Undefined function or variable "xi_summed".
Error in hmmFwdBackMaxProduct (line 39)
 xi_summed = xi_summed + tmpXi./sum(tmpXi(:)); % inlined call to
 normalize
Error in hmmNbestDemo (line 17)
[ff, logmaxprob] = hmmFwdBackMaxProduct(initDist, transmat, softev);
3.

What is the expected output? What do you see instead?
no error, xi_summed seems to be uninitiated, ff is not assigned in 
hmmFwdBackMaxProduct.m

What version / revision of the product are you using? On what operating
system? pmtk3 2011dec15, windows 7, matlab 2012a


Please provide any additional information below.

I had trouble downloading data, and got errors with isOctave after running 
initPmtk3.m. The solution is to create the folders:

pmtk3-1nov12/pmtkTools/systemInfo
pmtk3-1nov12/pmtkdataCopy
pmtk3-1nov12/pmtkdataSmall

and then run initPmtk3

What steps will reproduce the problem?
1. See attached file mrfToMrf2Issue.m

What is the expected output? What do you see instead?

The function testMisconceptionMRFtoMRF2() should generate the same output as 
the testMisconceptionMRF(). Instead, the edge potentials in the mrf2 model 
appear to be getting set up incorrectly. 

What version / revision of the product are you using? On what operating
system?

pmtk3-3jan11.zip  - uploaded january 2012.
Matlab r2011a, Win 32 bit.
Windows 7 64bit.

Please provide any additional information below.

The attached updated file factorGraphToMrf2.m contains a proposed fix for the 
issue, which appears to be at line 34:

edgesWithPots = cell2mat(cellfuncell(@(f)f.domain, epots));

whereby a row vector is returned, which is inconsistent with edgeEnds - i.e. a 
column vector - when compared at line 35. 

The proposed fix is after line 32:
epots    = fg.factors(edgeFacNdx);

to add the following:

if isrowvec(epots)
    epots = epots';
end

What steps will reproduce the problem?
1. Download and install with initPmtk3
2. Evaluate [a b] = hmmFit({randn(1,50)}, 4, 'gauss')

What is the expected output? What do you see instead?
Expect no output. Instead, error obtained:

??? Invalid MEX-file
'C:\Users\fasiha\Documents\MATLAB\pmtk3-read-only\toolbox\LatentVariableModels\h
mm\sub\hmmFwdBack.mexw64':
Access is denied.

Error in ==> hmmFitEm>estep at 68
    [gamma, alpha, beta, logp] = hmmFwdBack(pi, A, Bi);

Error in ==> emAlgo at 62
    [ess, ll] = estep(model, data);

Error in ==> hmmFitEm at 46
[model, loglikHist] = emAlgo(model, data, initFn, @estep, @mstep, EMargs{:});

Error in ==> hmmFit at 69
[model, loglikHist] = hmmFitEm(data, nstates, type, varargin{:});

What version / revision of the product are you using? On what operating system?

SVN checkout r2778, Windows7, Matlab 2011a. 

Please provide any additional information below.

I had Cygwin available, so in the directory 
"pmtk3-read-only/toolbox/LatentVariableModels/hmm/sub", I ran "chmod 755 
*.mex*" to add the execute bit on all mex files. This fixes the problem.

I am not sure how to do this without Cygwin, or if it affects anyone else on 
Windows using a current checked out.