JiscMail Logo
Email discussion lists for the UK Education and Research communities

Help for CCPEM Archives


CCPEM Archives

CCPEM Archives


CCPEM@JISCMAIL.AC.UK


View:

Message:

[

First

|

Previous

|

Next

|

Last

]

By Topic:

[

First

|

Previous

|

Next

|

Last

]

By Author:

[

First

|

Previous

|

Next

|

Last

]

Font:

Proportional Font

LISTSERV Archives

LISTSERV Archives

CCPEM Home

CCPEM Home

CCPEM  April 2015

CCPEM April 2015

Options

Subscribe or Unsubscribe

Subscribe or Unsubscribe

Log In

Log In

Get Password

Get Password

Subject:

Re: Relion - ERROR!!! zero sum of weights - Refine 3D

From:

Sjors Scheres <[log in to unmask]>

Reply-To:

Sjors Scheres <[log in to unmask]>

Date:

Sat, 4 Apr 2015 19:28:00 +0100

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (529 lines)

Hi Tofayel,
Have you checked whether there are any "strange" particles, like all-0 or
with very strong pixels or so? This happens more often than one might
suspect, and can cause these problems.
Also, if you add up the particles in all groups from half1 and half1, then
you should get to 7000 again.
HTH,
S

> Hi Sjors and Relion Users,
>
> I am processing a dataset on ribosomes in Relion 1.3 and after sorting
> done at both 2D and 3D classification steps, I am left with around 7000
> particles. I went on to do Refine-3D and relion shows me an error which I
> have pasted below. However, I was going through the archives of ccpem
> mailing list and found out that this question was discussed earlier but
> failed to find out a consensus on the solution. Clearly, relion has some
> problem with some of the groups where particle_sumweight=nan or ZERO !!!
> Looked through previous iterations and all the star files if I had NaN
> assigned to any of the fields but none was found. I wanted to fish out the
> exact micrographs by looking at run*_it*_half1_model.star file and I did
> so. But the micrographs looks fine to me. I also figured out that in
> data_model_groups column, the _rlnGroupNrParticles doesnt add up to 7000
> particles. Clearly, I may be missing out on some important point about how
> grouping in done in relion but my understanding is , if we don't specify
> any group, relion assigns each micrograph to one group and thats how I get
> 164 groups (I started with 164 micrographs) but would also expect values
> in _rlnGroupNrParticles add up to 7000.
>
> Any help would be much appreciated !
>
>
> Auto-refine: Iteration= 19
>  Auto-refine: Resolution= 20.5714 (no gain for 1 iter)
>  Auto-refine: Changes in angles= 0.572653 degrees; and in offsets=
> 0.477056 pixels (no gain for 0 iter)
>  Estimating accuracies in the orientational assignment ...
>    7/   7 sec
> ............................................................~~(,_,">
>  Auto-refine: Estimated accuracy angles= 1.891 degrees; offsets= 1.571
> pixels
>  Auto-refine: Angular step= 0.9375 degrees; local searches= true
>  Auto-refine: Offset search range= 3.67425 pixels; offset step= 1.22475
> pixels
>  CurrentResolution= 20.5714 Angstroms, which requires orientationSampling
> of at least 6.54545 degrees for a particle of diameter 360 Angstroms
>  Oversampling= 0 NrHiddenVariableSamplingPoints= 21233664
>  OrientationalSampling= 1.875 NrOrientations= 150
>  TranslationalSampling= 2.4495 NrTranslations= 9
> =============================
>  Oversampling= 1 NrHiddenVariableSamplingPoints= 679477248
>  OrientationalSampling= 0.9375 NrOrientations= 1200
>  TranslationalSampling= 1.22475 NrTranslations= 36
> =============================
>  Estimated memory for expectation step  > 0.194003 Gb, available memory =
> 4 Gb.
>  Estimated memory for maximization step > 0.168626 Gb, available memory =
> 4 Gb.
>  Expectation iteration 19
> 3.02/10.47 min .................~~(,_,"> exp_thisparticle_sumweight= nan
>    [oo]
>  exp_part_id= 2489exp_iimage=1
>  group_id= 140 mymodel.scale_correction[group_id]= 0.974612
>  exp_ipass= 0
>  sampling.NrDirections(0, true)= 12288 sampling.NrDirections(0, false)= 29
>  sampling.NrPsiSamplings(0, true)= 192 sampling.NrPsiSamplings(0, false)=
> 6
>  mymodel.sigma2_noise[exp_ipart]=
>    0.00029
>    0.00017
>    0.00011
>    8.5e-05
>    0.00011
>    0.00011
>    0.00011
>     0.0001
>    0.00011
>     0.0001
>    9.5e-05
>    0.00011
>    0.00011
>    0.00011
>    9.4e-05
>    0.00011
>     0.0001
>    9.1e-05
>    8.8e-05
>    7.4e-05
>    6.4e-05
>    5.5e-05
>    4.8e-05
>    3.9e-05
>    3.4e-05
>    3.5e-05
>    3.2e-05
>    3.4e-05
>    3.2e-05
>    3.4e-05
>    3.3e-05
>      3e-05
>    2.8e-05
>    2.5e-05
>    2.4e-05
>    2.2e-05
>    2.1e-05
>    2.1e-05
>    2.3e-05
>    2.2e-05
>      2e-05
>      2e-05
>    1.8e-05
>    1.7e-05
>    1.5e-05
>    1.5e-05
>    1.5e-05
>    1.6e-05
>    1.5e-05
>    1.3e-05
>    1.2e-05
>    1.2e-05
>    1.2e-05
>    1.1e-05
>    1.1e-05
>      1e-05
>    9.7e-06
>    9.2e-06
>    9.6e-06
>    9.2e-06
>    8.5e-06
>      8e-06
>    7.7e-06
>    7.4e-06
>    7.3e-06
>      7e-06
>    6.9e-06
>    6.3e-06
>    6.1e-06
>    6.2e-06
>    5.9e-06
>    5.4e-06
>    5.3e-06
>    5.1e-06
>    5.1e-06
>    4.7e-06
>    4.5e-06
>    4.4e-06
>    4.4e-06
>      4e-06
>    3.9e-06
>    3.9e-06
>    3.7e-06
>    3.5e-06
>    3.4e-06
>    3.3e-06
>    3.3e-06
>    3.1e-06
>    2.9e-06
>    2.9e-06
>    2.7e-06
>    2.6e-06
>    2.5e-06
>    2.5e-06
>    2.4e-06
>    2.3e-06
>    2.3e-06
>    2.1e-06
>    2.1e-06
>      2e-06
>      2e-06
>      2e-06
>    1.9e-06
>    1.9e-06
>    1.7e-06
>    1.7e-06
>    1.7e-06
>    1.5e-06
>    1.6e-06
>    1.5e-06
>    1.4e-06
>    1.4e-06
>    1.4e-06
>    1.3e-06
>    1.3e-06
>    1.3e-06
>    1.3e-06
>    1.2e-06
>    1.2e-06
>    1.1e-06
>    1.1e-06
>    1.1e-06
>    1.1e-06
>      1e-06
>      1e-06
>    9.8e-07
>    9.6e-07
>      9e-07
>    9.2e-07
>    9.1e-07
>    8.8e-07
>    8.5e-07
>    8.2e-07
>    8.3e-07
>    8.1e-07
>    7.8e-07
>    7.6e-07
>    7.3e-07
>    7.4e-07
>    7.1e-07
>    6.9e-07
>    6.8e-07
>    6.7e-07
>    6.6e-07
>    6.4e-07
>    6.3e-07
>    6.2e-07
>    6.1e-07
>    6.1e-07
>    5.8e-07
>    5.8e-07
>    5.9e-07
>    5.8e-07
>    5.6e-07
>    5.5e-07
>    5.5e-07
>    5.3e-07
>    5.2e-07
>    5.2e-07
>    5.2e-07
>    5.1e-07
>    5.1e-07
>      5e-07
>    4.9e-07
>      5e-07
>    4.7e-07
>    4.7e-07
>    4.8e-07
>    4.8e-07
>    4.7e-07
>    4.6e-07
>    4.6e-07
>    4.5e-07
>    4.4e-07
>    4.5e-07
>    4.4e-07
>    4.3e-07
>    4.3e-07
>    4.2e-07
>    4.2e-07
>    3.8e-07
>
>  wsum_model.sigma2_noise[exp_ipart]=
>    0.00505
>   0.008294
>   0.008885
>     0.0105
>    0.02199
>    0.02241
>    0.03025
>    0.02976
>    0.03605
>    0.04888
>    0.03513
>    0.05765
>    0.05674
>    0.06473
>    0.06146
>    0.06058
>    0.08316
>    0.07294
>      0.068
>     0.0656
>    0.04934
>    0.05143
>    0.04654
>    0.03894
>    0.03511
>    0.03978
>    0.03836
>    0.03918
>    0.04001
>    0.04065
>    0.04533
>    0.04163
>    0.03614
>    0.03734
>    0.03787
>    0.03303
>    0.03379
>    0.03425
>    0.03926
>    0.03466
>    0.03528
>    0.03365
>    0.03082
>    0.03105
>     0.0288
>    0.03068
>    0.02896
>    0.03348
>    0.03103
>    0.02899
>    0.02711
>    0.02762
>    0.02841
>    0.02494
>    0.02458
>    0.02527
>    0.02241
>    0.02421
>    0.02179
>    0.02525
>    0.02277
>    0.02053
>    0.02133
>    0.01942
>    0.02277
>    0.01946
>    0.02045
>    0.01842
>    0.01772
>    0.02026
>    0.01784
>    0.01644
>     0.0181
>    0.01563
>    0.01669
>     0.0158
>    0.01571
>    0.01547
>    0.01436
>    0.01373
>    0.01335
>    0.01448
>     0.0136
>    0.01273
>    0.01241
>    0.01297
>      0.013
>    0.01181
>    0.01068
>    0.01209
>    0.01102
>    0.01043
>     0.0102
>    0.01051
>    0.00987
>   0.009272
>   0.009781
>   0.009298
>   0.009613
>   0.008501
>   0.008618
>   0.008227
>   0.008696
>   0.008679
>   0.007486
>   0.008003
>   0.008031
>   0.007193
>   0.007495
>   0.007211
>   0.007372
>   0.006475
>   0.006878
>   0.006456
>   0.006751
>   0.006632
>   0.006445
>   0.006353
>    0.00599
>   0.005952
>   0.006162
>   0.006017
>   0.005703
>   0.005698
>   0.005432
>   0.005284
>   0.005236
>   0.005386
>    0.00511
>   0.005097
>   0.004898
>   0.004766
>   0.004801
>   0.004767
>   0.004821
>   0.004455
>    0.00458
>   0.004311
>   0.004356
>   0.004669
>   0.004365
>   0.004334
>   0.004264
>   0.003941
>   0.004314
>   0.004089
>   0.003939
>   0.003849
>   0.003896
>   0.003935
>   0.003769
>   0.003948
>   0.003747
>   0.003863
>   0.003831
>   0.003606
>   0.003647
>   0.003594
>   0.003663
>   0.003462
>   0.003476
>   0.003862
>   0.003499
>   0.003513
>   0.003432
>   0.003445
>   0.003364
>   0.003358
>   0.003457
>   0.003516
>   0.003467
>   0.003608
>   0.003244
>   0.003466
>   0.003389
>   0.003315
>   0.003341
>   0.003351
>   0.003466
>   0.003308
>   0.002911
>
>  mymodel.avg_norm_correction= 0.955164
>  wsum_model.avg_norm_correction= 677.562
> written out Mweight.spi
>  exp_thisparticle_sumweight= nan
>  exp_min_diff2[exp_ipart]= 9.9e+100
> slave 3 encountered error: ERROR!!! zero sum of weights....
> File: src/ml_optimiser.cpp line: 3982
> +++ RELION: command line arguments (with defaults for optional ones
> between parantheses) +++
> ====== Continue options =====
>                          --continue : _optimiser.star file of the
> iteration after which to continue
> ====== General options =====
>                       --o (OLD_ctX) : Output rootname
>                        --iter (OLD) : Maximum number of iterations to
> perform
>                  --tau2_fudge (OLD) : Regularisation parameter (values
> higher than 1 give more weight to the data)
>             --flatten_solvent (OLD) : Switch on masking on the references?
>                --solvent_mask (OLD) : User-provided mask for the
> references
>               --solvent_mask2 (OLD) : User-provided secondary mask
>                         --tau (OLD) : STAR file with input tau2-spectrum
> (to be kept constant)
>           --particle_diameter (OLD) : Diameter of the circular mask that
> will be applied to the experimental images (in Angstroms)
>        --join_random_halves (false) : Join previously split random halves
> again (typically to perform a final reconstruction).
> ====== Re-align movie frames =====
>           --realign_movie_frames () : Input STAR file with the movie
> frames
>               --nr_frames_prior (5) : Number of movie frames to calculate
> running-average priors
>      --movie_frames_running_avg (3) : Number of movie frames in each
> running average
> ====== Orientations =====
>                --oversampling (OLD) : Adaptive oversampling order to
> speed-up calculations (0=no oversampling, 1=2x, 2=4x, etc)
>    --auto_local_healpix_order (OLD) : Minimum healpix order (before
> oversampling) from which auto-refine procedure will use local searches
>                   --sigma_ang (OLD) : Stddev on all three Euler angles for
> local angular searches (of +/- 3 stddev)
>                   --sigma_rot (OLD) : Stddev on the first Euler angle for
> local angular searches (of +/- 3 stddev)
>                  --sigma_tilt (OLD) : Stddev on the first Euler angle for
> local angular searches (of +/- 3 stddev)
>                   --sigma_psi (OLD) : Stddev on the in-plane angle for
> local angular searches (of +/- 3 stddev)
>                   --sigma_off (OLD) : Stddev. on the translations
>                --skip_align (false) : Skip orientational assignment (only
> classify)?
>               --skip_rotate (false) : Skip rotational assignment (only
> translate and classify)?
>             --skip_maximize (false) : Skip maximization step (only write
> out data.star file)?
> ====== Corrections =====
>                       --scale (OLD) : Switch on intensity-scale
> corrections on image groups
>                        --norm (OLD) : Switch on normalisation-error
> correction
> ====== Computation =====
>                             --j (1) : Number of threads to run in parallel
> (only useful on multi-core machines)
>                        --pool (OLD) : Number of images to be processed
> together
>   --dont_combine_weights_via_disc (false) : Send the large arrays of
> summed weights through the MPI network, instead of writing large files
> to disc
>                          --verb (1) : Verbosity (1=normal, 0=silent)
> ====== Expert options =====
>          --strict_highres_exp (OLD) : Resolution limit (in Angstrom) to
> restrict probability calculations in the expectation step
>                     --scratchdir () : Directory (with absolute path, and
> visible to all nodes) for temporary files
> --------------------------------------------------------------------------
> MPI_ABORT was invoked on rank 3 in communicator MPI_COMM_WORLD
> with errorcode 1.
>
> NOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.
> You may or may not see output from other processes, depending on
> exactly when Open MPI kills them.
>
>
> Thanking you,
> Tofayel
>


-- 
Sjors Scheres
MRC Laboratory of Molecular Biology
Francis Crick Avenue, Cambridge Biomedical Campus
Cambridge CB2 0QH, U.K.
tel: +44 (0)1223 267061
http://www2.mrc-lmb.cam.ac.uk/groups/scheres

Top of Message | Previous Page | Permalink

JiscMail Tools


RSS Feeds and Sharing


Advanced Options


Archives

April 2024
March 2024
February 2024
January 2024
December 2023
November 2023
October 2023
September 2023
August 2023
July 2023
June 2023
May 2023
April 2023
March 2023
February 2023
January 2023
December 2022
November 2022
October 2022
September 2022
August 2022
July 2022
June 2022
May 2022
April 2022
March 2022
February 2022
January 2022
December 2021
November 2021
October 2021
September 2021
August 2021
July 2021
June 2021
May 2021
April 2021
March 2021
February 2021
January 2021
December 2020
November 2020
October 2020
September 2020
August 2020
July 2020
June 2020
May 2020
April 2020
March 2020
February 2020
January 2020
December 2019
November 2019
October 2019
September 2019
August 2019
July 2019
June 2019
May 2019
April 2019
March 2019
February 2019
January 2019
December 2018
November 2018
October 2018
September 2018
August 2018
July 2018
June 2018
May 2018
April 2018
March 2018
February 2018
January 2018
December 2017
November 2017
October 2017
September 2017
August 2017
July 2017
June 2017
May 2017
April 2017
March 2017
February 2017
January 2017
December 2016
November 2016
October 2016
September 2016
August 2016
July 2016
June 2016
May 2016
April 2016
March 2016
February 2016
January 2016
December 2015
November 2015
October 2015
September 2015
August 2015
July 2015
June 2015
May 2015
April 2015
March 2015
February 2015
January 2015
December 2014
November 2014
October 2014
September 2014
August 2014
July 2014
June 2014
May 2014
April 2014
March 2014
February 2014
January 2014
December 2013
November 2013
October 2013
September 2013
August 2013
July 2013
June 2013
May 2013
April 2013
March 2013
February 2013


JiscMail is a Jisc service.

View our service policies at https://www.jiscmail.ac.uk/policyandsecurity/ and Jisc's privacy policy at https://www.jisc.ac.uk/website/privacy-notice

For help and support help@jisc.ac.uk

Secured by F-Secure Anti-Virus CataList Email List Search Powered by the LISTSERV Email List Manager