Reference based motion correction error: All movies must have the same number of frames

Motion Correction
20

Hi @parrot and others,

Here is a small script that @rposert devised as a work-around to this issue that you may find helpful. You will need to run this in a terminal using cryosparc-tools.

Steps:

  1. Reimport movies with Skip header check disabled if that was not initially done. This will output a set of ‘failed_movies’ whose frame count does not match the majority of the movies imported.
  2. Next, run the attached script, replacing the appropriate instance information, project number, workspace number, and job numbers (job_1 = new import movies, job_2 = patch CTF estimation with all movies). This will create a new external job in the appropriate workspace with a set of exposures containing only the number of expected frames.
  3. Create a Manually curate exposures job with the exposures output from the External Results job, and the particles stack you would like to perform RBMC on. Set the parameter Number of picked particles to `1,10000’. This will create an output of exposures where there is at least 1 particle present on the micrographs with the same number of frames.
  4. Connect the Exposures and Particles outputs from the Manually curate exposures job to the RBMC job and the volume associated with those particles.

This should alleviate the error with an inconsistent # of frames.

Script:

from cryosparc.tools import CryoSPARC

cs = CryoSPARC(
    license="xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx",
    host="localhost",
    base_port=39000,
    email="ali@example.com",
    password="password123"
)

project_number = "P317"
workspace_number = "W15"
job_1_number = "J1179"
job_2_number = "J1079"
project = cs.find_project(project_number)

# Movies with bad number of frames
imported_movies_job = project.find_job(job_1_number)
failed_movies = imported_movies_job.load_output("failed_movies")

# All exposures from patch CTF estimation
patch_ctf_job = project.find_job(job_2_number)
patch_ctf_exposures = patch_ctf_job.load_output("exposures")

good_exposures = patch_ctf_exposures.query(lambda row: row['movie_blob/import_sig'] not in failed_movies['movie_blob/import_sig'])

cs.save_external_result(
    project_number,
    workspace_number,
    good_exposures,
    type="exposure",
    name="desired_number_frame_exposures",
)
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