$ singularity exec ./best-latest.sif /bin/bash -c 'best inputData "$BEST_DATA_DIR/test-data.mat" outputDirName best-outputs memMethod cMEM sensorsTypes EEG+MEG reconstructionWindow "0.7 0.71" baselineWindow "0 0.5"'
/bin/bash: warning: setlocale: LC_ALL: cannot change locale (en_US.UTF-8)
*** Trying defaults values for: 
  Columns 1 through 4

    'baseline'    'normalization'    'clusteringMethod'    'mspWindow'

  Columns 5 through 7

    'mspThresholdMethod'    'mspThreshold'    'neighborhoodOrder'

  Columns 8 through 11

    'spatialSmoothing'    'activeMeanInit'    'activeProbaInit'    'lambdaInit'

  Columns 12 through 14

    'activeProbaThres...'    'activeVarCoef'    'inactiveVarCoef'

  Columns 15 through 18

    'noiseCovMethod'    'optimMethod'    'frequencies'    'waveletType'

  Columns 19 through 22

    'vanishingMoments'    'coefShrinkage'    'useParallel'    'maxWorkers'

*** Extra inputs: 
        inputData: '/usr/local/Multi_FunkIm/best_cbrain-mcv97/data/test-data.mat'
        memMethod: 'cMEM'
    outputDirName: 'best-outputs'

*** List of options: 
Pipeline: 
	cMEM

Data definition: 
          DataTypes: {'EEG'  'MEG'}
        TimeSegment: [0.7000 0.7100]
    BaselineSegment: [0 0.5000]
           Baseline: [328x1001 double]
      normalization: 'adaptive'
            verbose: 1

Clustering: 
        MSP_R2_threshold: 0.9500
      neighborhood_order: 4
              MSP_window: 10
           clusters_type: 'static'
    MSP_scores_threshold: 0

Model: 
    active_mean_method: 2
          alpha_method: 3
       alpha_threshold: 0
        initial_lambda: 1

Solver: 
              NoiseCov: []
       NoiseCov_method: 2
    NoiseCov_recompute: 1
     spatial_smoothing: 0.6000
       active_var_mult: 0.0500
     inactive_var_mult: 0
          Optim_method: 'fminunc'
      covariance_scale: 1
       parallel_matlab: 1

Starting parallel pool (parpool) using the 'local' profile ...
Warning: The system time zone setting, 'US/Eastern', does not specify a single time zone unambiguously. It will be treated as 'America/New_York'. See the <a href="matlab:doc('datetime.TimeZone')">datetime.TimeZone property</a> for details about specifying time zones.
> In verifyTimeZone (line 34)
  In datetime (line 543)
  In parallel.internal.cluster/DefaultProperties/getNewJobPropStruct (line 17)
  In parallel.internal.types.JobProp>iGetDefaults (line 62)
  In parallel.internal.types.JobProp (line 56)
  In parallel.internal.cluster.CJSSupport>iGetJobPropMap
  In parallel.cluster/CJSCluster (line 657)
  In parallel.cluster.Local (line 504)
  In parcluster (line 59)
  In parallel.internal.pool.argumentsParser>iGetClusterAndNumWorkers (line 163)
  In parallel.internal.pool.argumentsParser (line 48)
  In parallel.internal.pool.doParpool (line 13)
  In parpool (line 98)
  In BEst>runMEM (line 775)
  In BEst (line 10)
Preserving jobs with IDs: 1 2 because they contain crash dump files.
You can use 'delete(myCluster.Jobs)' to remove all jobs created with profile local. To create 'myCluster' use 'myCluster = parcluster('local')'.
Connected to the parallel pool (number of workers: 6).


===== pipeline cMEM
cMEM, be_main_source ... done.
cMEM, be_main_leadfields ... done.
cMEM, stable clustering ...
cMEM, stable clustering: dimension of the signal subspace 9, for inertia > 0.95
cMEM, stable clustering: dimension of the signal subspace 8, for inertia > 0.95
MEM : New noise covariance is computed using baseline
MEM : New noise covariance is computed using baseline
cMEM, MULTIMODAL data ... ... MEG found 
Sample   1( 0,0.701):
		218 clusters,
		127 iter.
		Entropy drop:-103.8
Sample   9( 0,0.709):
		218 clusters,
		128 iter.
		Entropy drop:-145.7
Sample   8( 0,0.708):
		218 clusters,
		113 iter.
		Entropy drop:-119.2
Sample   3( 0,0.703):
		218 clusters,
		125 iter.
		Entropy drop:-154.5
Sample   2( 0,0.702):
		218 clusters,
		128 iter.
		Entropy drop:-171.9
Sample  11( 0,0.711):
		218 clusters,
		126 iter.
		Entropy drop:-289.2
Sample  10( 0,0.710):
		218 clusters,
		124 iter.
		Entropy drop:-211.6
Sample   5( 0,0.705):
		218 clusters,
		125 iter.
		Entropy drop:-113.9
Sample   4( 0,0.704):
		218 clusters,
		130 iter.
		Entropy drop:-193.1
Sample   7( 0,0.707):
		218 clusters,
		121 iter.
		Entropy drop:-160.1
Sample   6( 0,0.706):
		218 clusters,
		134 iter.
		Entropy drop:-104.9
cMEM, Elapsed CPU time is 13.67 seconds.
Bye.