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Hello,
I'm currently studying localized latent factor models and I'm trying to run the code.
I prepared the data according to the manual and tried to run the multicontext function, but an error occurred.

This is my setting and code.

setting = data.frame(
  name = 'uvw3-F',
  has.u = FALSE,
  has.gamma = FALSE,
  nFactors = 33,
  nLocalFactors = 3,
  is.logistic = FALSE
)

ans = run.multicontext(
              data.train = data.train, data.test=data.test,
              setting = setting,
              nSamples = 200,
              nBurnIn = 30,
              nIter = 30,
              out.dir="multi_results/");

max(obs$edge.context) is 11. So, I set the nLocalFactors = 3 and nFactors = 3*11 = 33.
But, The following error occurs

Error in run.multicontext(data.train = data.train, data.test = data.test,  : 
  Please check input parameter 'setting' when calling function run.multicontext: setting$nFactors must = setting$nLocalFactors * max(obs$edge.context).

Am I misunderstanding the setting? I'd appreciate it if you could tell me what the problem is.

Thank you for providing good research and code.

Hi,
Follow the tutorial and I got this issue:

R CMD SHLIB src/C/util.c src/C/factor_model_util.c src/C/pagerank.c src/C/hierarchical.c src/C/factor_model_multicontext.c src/C/factor_model_util2.cpp -o lib/c_funcs.so
clang++ -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -single_module -multiply_defined suppress -L/Library/Frameworks/R.framework/Resources/lib -L/usr/local/lib -o lib/c_funcs.so src/C/util.o src/C/factor_model_util.o src/C/pagerank.o src/C/hierarchical.o src/C/factor_model_multicontext.o src/C/factor_model_util2.o -L/Library/Frameworks/R.framework/Resources/lib -lRlapack -L/Library/Frameworks/R.framework/Resources/lib -lRblas -L/usr/local/lib/gcc/x86_64-apple-darwin13.0.0/4.8.2 -lgfortran -lquadmath -lm -Wall -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
ld: warning: directory not found for option '-L/usr/local/lib/gcc/x86_64-apple-darwin13.0.0/4.8.2'
ld: library not found for -lgfortran
clang: error: linker command failed with exit code 1 (use -v to see invocation)
make[1]: *** [lib/c_funcs.so] Error 1
make: *** [c_funcs] Error 1

Thanks!

Hi,
Follow the tutorial and I got this error:
Error in .Call("sum_margin", out, A, as.integer(nrow(A)), as.integer(ncol(A)), :
载入表里没有"C"字符名"sum_margin"

I have try my best to find the solution, but failed. Please give me some help, thanks. I run the code on my Mac with R version 3.3.2 .

Hi,

Following is the output of my make:
R CMD SHLIB src/C/util.c src/C/factor_model_util.c src/C/pagerank.c src/C/hierarchical.c src/C/factor_model_multicontext.c src/C/factor_model_util2.cpp -o lib/c_funcs.so
make[1]: Entering directory /home/Desktop/Latent-Factor-Models-master' make[1]: Nothing to be done forall'.
make[1]: Leaving directory /home/Desktop/Latent-Factor-Models-master' make: *** No rule to make targetsrc/arslogistic/arms.c', needed by `arslogistic'. Stop.

Should there be an arms.c somewhere?

Thanks!

I finally got it compiled (thanks to the solutions provided by others), but when I ran it, I got this error:

Error in dyn.load(sprintf("%slib/c_funcs.so", code.dir)) :
  unable to load shared object '/Users/patrickng/works/Latent-Factor-Models/lib/c_funcs.so':
  dlopen(/Users/patrickng/works/Latent-Factor-Models/lib/c_funcs.so, 6): Symbol not found: _compute_szuBv_c_single_dense
  Referenced from: /Users/patrickng/works/Latent-Factor-Models/lib/c_funcs.so
  Expected in: flat namespace

I am using R version 3.2.4 on Mac OSX. Wonder if anyone has seen this?

ans = fit.bst(obs.train=obs.train, x.obs.train=x.obs.train, x_src=x_src, x_dst=x_dst, x_ctx=x_ctx,out.dir = "/tmp/unit-test/simulated-mtx-uvw-10K", model.name="uvw", nFactors=3, nIter=10);

WARNING: You did not specify the following components in factor: gamma

WARNING: You did not specify the following components in param: h0, var_gamma

================= START fit.MCEM =====================================
Initial loglik: CD = -19358.42494, E = NA (0.01 sec)
Error in data.frame(Method = "MCEM", Iter = iter, nSteps = nSamples, CDlogL = loglik, :
arguments imply differing number of rows: 1, 0

Running src/LDA-RLFM/R/model/examples.R, I got following exception:

(B) Fit a model

dyn.load("c_funcs.so");
source("R/c_funcs.R");
source("R/utils.R");
source("R/model/MCEM_MStep.R");
source("R/model/fit.MCEM.R");

set.seed(2);
ans = fit.MCEM(

• nIter=5,         # Number of EM iterations
  

• nSamples=100,    # Number of samples drawn in each E-step: could be a vector of size nIter.
  

• nBurnIn=10,      # Number of burn-in draws before take samples for the E-step: could be a vector of size nIter.
  

• factor=data.train$factor,   # Initial factor values
  

• obs=data.train$obs,         # Observed rating
  

• feature=data.train$feature, # Feature values
  

• param=data.train$param,     # Initial parameter values
  

• corpus=data.train$corpus,   # The text corpus
  

• try=list(lambda=c(0.5,1,2,4,8), eta=c(0.5, 1, 2, 4)), # Values of lambda and eta that you want to try
  

• out.level=1,                # out.level=1: Save the factor & parameter values to out.dir/est.highestCDL and out.dir/est.last
  

• out.dir="/tmp/test/lda-rlfm", # out.level=2: Save the factor & parameter values of each iteration i to out.dir/est.i
  

• out.append=FALSE,
  

• debug=1,     # Set to 0 to disable internal sanity checking; Set to 100 for most detailed sanity checking
  

• verbose=1,   # Set to 0 to disable console output; Set to 100 to print everything to the console
  

• verbose.M=1, # Verbose setting for the M-step
  

• use.C=TRUE,  # Whether to use the C implementation (R implementation does not have full functionalities)
  

• lm=T         # Whether to use lm to fit linear regression (otherwise bayesglm will be used, which will be slow)
  

• );

WARNING: Some terms do not belong to any items in the corpus.

*** caught segfault ***
address 0x0, cause 'unknown'

Traceback:
1: .C("fillInTopicCounts", output$cnt_item_topic, output$cnt_topic_term, output$cnt_topic, output$z_avg, corpus_topic, corpus$item, corpus$term, corpus$weight, as.integer(nItems), as.integer(nrow(corpus)), as.integer(nTopics), as.integer(nTerms), as.integer(nCorpusWeights), as.integer(debug), DUP = FALSE)
2: getTopicCounts(corpus, factor$corpus_topic, nItems, nTopics, size$nTerms)
3: fit.MCEM(nIter = 5, nSamples = 100, nBurnIn = 10, factor = data.train$factor, obs = data.train$obs, feature = data.train$feature, param = data.train$param, corpus = data.train$corpus, try = list(lambda = c(0.5, 1, 2, 4, 8), eta = c(0.5, 1, 2, 4)), out.level = 1, out.dir = "/tmp/test/lda-rlfm", out.append = FALSE, debug = 1, verbose = 1, verbose.M = 1, use.C = TRUE, lm = T)
An irrecoverable exception occurred. R is aborting now ...

Thanks for any help!

The tutorial-BST.R gives the following error:

source("src/R/examples/tutorial-BST.R");
Loading required package: lattice
WARNING: You did not specify the following components in factor: gamma
WARNING: You did not specify the following components in param: h0, var_gamma
================= START fit.MCEM =====================================
Initial loglik: CD = -19358.42494, E = NA (0.00 sec)
test loss: 6.148298 (0.007 sec)

write a model & summary info on to disk (used 0.003 sec)

    Iteration 1

---

start E-STEP
Error in MCEM_EStep.multicontext.C(factor = factor, obs = obs, feature = feature, :
invalid mode (NULL) to pass to C or Fortran (arg 3)
In addition: Warning messages:
1: You did not specify the following components in factor: gamma
2: You did not specify the following components in param: h0, var_gamma

I am using R version 3.0.1 (2013-05-16) -- "Good Sport" and the C, FORTRAN code compiles without any warning message.
What are the possible reasons for this error? Thanks.

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