updated check job status

clen_tools/detector-distance-refinement.py

@@ -14,6 +14,9 @@ python detector-distance-refinement.py -l <path to lst file generated by daq>
                                        -c cell_file
                                        -s sample size
 
+# other variables
+-f = fine only = only perform fine scan
+
 # output
 plot files of the analysis and a suggest for the clen
 """
@@ -26,6 +29,7 @@ import regex as re
 import numpy as np
 import matplotlib.pyplot as plt
 import time
+from tqdm import tqdm
 import argparse
 
 def h5_sample( lst, sample ):
@@ -75,7 +79,7 @@ def geom_amend( lab6_geom_file, clen ):
 def write_crystfel_run( clen, sample_h5_file, clen_geom_file, cell_file ):
 
     # crystfel file name
-    cryst_run_file = "{0}_cryst_run.sh".format( clen )
+    cryst_run_file = "{0}_run.sh".format( clen )
 
     # write file
     run_sh = open( cryst_run_file, "w" )
@@ -127,23 +131,31 @@ def make_step_range(centre_clen, step_size, steps):
     
     return step_range
 
-def check_job_status(username):
+def submit_job( job_file ):
-    # wait for jobs to complete
-    jobs_completed = False
-    while not jobs_completed:
-       # Get the status of the jobs using "squeue"
-       result = subprocess.run(['squeue', '--user', '{0}'.format(username)], stdout=subprocess.PIPE)
-       output = result.stdout.decode('utf-8')
 
-       # Check if there are no jobs running for the user
+    # submit the job
-       if '{0}'.format(username) not in output:
+    submit_cmd = [ "sbatch", "-p", "day", "--cpus-per-task=32", "--", job_file ]
-           jobs_completed = True
+    job_output = subprocess.check_output(submit_cmd)
-       else:
-           # Sleep for some time and check again
-           print("waiting for jobs to finish")
-           time.sleep(30)  # sleep for 30 seconds
 
-    print("All jobs completed.")
+    # scrub job id from - example Submitted batch job 742403
+    pattern = r"Submitted batch job (\d+)"
+    job_id = re.search( pattern, job_output.decode().strip() ).group(1)
+
+    return int(job_id)
+
+def wait_for_jobs( job_ids, total_jobs ):
+
+    with tqdm(total=total_jobs, desc="Jobs Completed", unit="job") as pbar:
+        while job_ids:
+            completed_jobs = set()
+            for job_id in job_ids:
+                status_cmd = ["squeue", "-h", "-j", str(job_id)]
+                status = subprocess.check_output(status_cmd)
+                if not status:
+                    completed_jobs.add(job_id)
+                    pbar.update(1)
+            job_ids.difference_update(completed_jobs)
+            time.sleep(30)
         
 def scrub_clen( stream_pwd ):
 
@@ -192,7 +204,6 @@ def find_streams( top_dir ):
     # return df of streams and clens
     return stream_df
 
-
 def scrub_us( stream ):
 
     # get uc values from stream file
@@ -207,6 +218,7 @@ def scrub_us( stream ):
         return np.nan
     
 def scrub_helper( top_dir ):
+
     # find stream files from process directory
     print( "finding stream files" )
     stream_df = find_streams( top_dir )
@@ -282,7 +294,6 @@ def find_clen_values(stats_df):
     
     return min_alpha_clen, min_beta_clen, min_gamma_clen, min_c_clen, min_alpha_val, min_beta_val, min_gamma_val, min_c_val
 
-
 def plot_indexed_std( stats_df, ax1, ax2 ):
 
     # indexed images plot
@@ -309,7 +320,6 @@ def plot_indexed_std( stats_df, ax1, ax2 ):
     color = "royalblue"
     ax2.plot(stats_df.clen, stats_df.std_c, color=color)
 
-
 def plot_indexed_std_alpha_beta_gamma( stats_df, ax1, ax2 ):
 
     # indexed images plot
@@ -354,6 +364,10 @@ def scan( cwd, lst, sample, lab6_geom_file, centre_clen, cell_file, step_size ):
     # make list of clen steps above and below the central clen
     step_range = make_step_range(centre_clen, step_size, steps)
     
+    # submitted job set and job_list
+    submitted_job_ids = set()
+    job_list = []
+
     # make directorys for results
     print( "begin CrystFEL anaylsis of different clens" )
 
@@ -377,14 +391,17 @@ def scan( cwd, lst, sample, lab6_geom_file, centre_clen, cell_file, step_size ):
         cryst_run_file = write_crystfel_run( clen, sample_h5_file, clen_geom_file, cell_file )  
 
         # run crystfel file
-        subprocess.call( [ "sbatch", "-p", "day", "--cpus-per-task=32", "--", "./{0}".format( cryst_run_file ) ] )
+        job_list.append( cryst_run_file )
+        job_id = submit_job( cryst_run_file )
+        submitted_job_ids.add( job_id )
         print( "done" )
 
         # move back to cwd
         os.chdir( cwd )
 
     #wait for jobs to complete
-    check_job_status(username)
+    wait_for_jobs(submitted_job_ids, len(job_list))
+    print("slurm processing done")
 
 def scrub_scan( scan_top_dir, scan ):
 
@@ -411,13 +428,17 @@ def scrub_scan( scan_top_dir, scan ):
 
     return suggested_clen
 
-def main( cwd, lst, sample, geom, centre_clen, cell_file ):
+def main( cwd, lst, sample, geom, centre_clen, cell_file, fine_only ):
 
+    # if statement to do coarse if fine_only==False
+    if fine_only == False:
         top_dir_coarse = "{0}/coarse".format( cwd )
 
         scan( cwd, lst, sample, geom, centre_clen, cell_file, step_size="coarse" )
 
         suggested_clen = scrub_scan( top_dir_coarse, scan="coarse" )
+    else:
+        suggested_clen = centre_clen
 
     top_dir_fine = "{0}/fine".format( cwd )
 
@@ -459,10 +480,16 @@ if __name__ == "__main__":
         type=int,
         default=500
     )
+    parser.add_argument(
+        "-f",
+        "--fine_only",
+        help="True = only do fine scan",
+        type=bool,
+        default=False
+    )
     args = parser.parse_args()
     # run main
-    username = os.getlogin()
     cwd = os.getcwd()
-    print( "current username = {0}".format( username ) )
     print( "top working directory = {0}".format( cwd ) )
-    main( cwd, args.lst, args.sample, args.geom, args.central_distance, args.cell_file )
+    main( cwd, args.lst, args.sample, args.geom, args.central_distance, args.cell_file, args.fine_only )
+