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Code Block
languagebash --num-executors=600 

Example: In vivo images on hpf using registration chain

At time of writing, I used 4G of vmem, but this could likely be reduced to 2G.

  1. Login to hpf
  2. Start cluster and load modules
Code Block
qlogin -l vmem=4G,walltime=96:00:00
Please refer to the Pydpiper on the SickKids HPF page for details on which modules to load:

Pydpiper on the SickKids HPF

Note: Right now you also need to specify an lsq12 protocol, in addition to an nlin-protocol. Additionally, your csv file needs to have at least the following columns: group (aka how you want scans to be grouped, which is typically by mouse ID) and file).

Code Block
languagebash --pipeline-name=arghef_group2 --chain-csv-file Group2_LongitudinalFiles_cleaned_with_id_new.csv --num-executors 250 --lsq12-protocol /hpf/largeprojects/MICe/tools/protocols/linear/Pydpiper_testing_default_lsq12.csv --chain-common-time-point 12 --pride-of-models /hpf/largeprojects/MICe/tools/initial-models/pride_of_models_mapping.csv --latency-tolerance 1800


--chain-csv-file tells the pipeline how to group data. You need to have atleast three columns: timepoint, subject_id, filename (relative of full paths of the images being registered).
--chain-common-time-point is the timepoint to be registered together
--pride-of-models csvfile with at least two columns: time_point, and model_file. Each row is an init model so you can have a unique init model for each age.


Example: Basic registration pipeline at MICe on 20 56um brains


Please ensure you are using the latest quarantine. For a list of all quarantines see this page: Registration Quarantines (deprecated)

Code Block
languagebash \
--num-executors 20 \
--queue-type sge \
--init-model /axiom2/projects/software/initial-models/Pydpiper-init-model-basket-may-2014/basket_mouse_brain.mnc \
--pipeline-name test_registration \