Run

1. Rename the fits directory provided in the tutorial to fits_bk (the fitting in the next step will write to fits directory)

2. Run the fitting

   fit.py efitter_params.py
   

   The fitting runs will execute in the background and take two to three hours.

   The script will create the directory called fits with the following content:

   fits/
       search100000_metric_cam_inside0.6/ #directory with output for the given set of parameters
           emd_4151_binned.mrc/ #directory with all fits for this map for this parameters
   
               #directories with names as the PDB files
               Elp1.CTD.on5cqs.5cqr.model_ElNemo_mode7.pdb/
               Elp1_NTD_1st_propeller.pdb/
               Elp1_NTD_2nd_propeller.pdb/
               Elp2.pdb/
               Elp3.mono.pdb/
               config.txt
               emd_4151_binned.mrc
   

   Each of the .pdb directories should contain the following files:

   emd_4151_binned.mrc #link to the map file
   log_err.txt #error messages
   log_out.txt #output messages
   ori_pdb.pdb #link to the original PDB file
   solutions.csv #file with transformation matrices defining the fits
   

   Note

   The fitting is complete when each of the .pdb directories contains solutions.csv file.

   Inspect the log_out.txt files for status and log_err.txt for error messages.

3. Upon completion, calculate p-values:

   genpval.py fits
   

   This should create additional files in each .pdb directory:

   Rplots.pdf
   solutions_pvalues.csv
   

   The solutions_pvalues.csv is crucial for the global optimization step.