File size: 3,265 Bytes
9f29b8f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 | ## Create python scripts to do a batch run for states in parallel
## This is setup to do a separate run for each sample type found in the metadf file
## then run "python3 run_batch_<date>.py
## it will create a jumble of text output but will run in parellel speeding things up a bit
import os
import importlib
import sys
hxex_path = os.path.join('/home/tuttle/data/HDX-MS/pyHXExpress') ### <- modify as needed using pyhxexpress.py file
sys.path.append(hxex_path)
import pyhxexpress as hxex ### <- modify as needed, this is set up for a pyhxexpress.py file
import numpy as np, pandas as pd
import config_fimh as config ### <- modify as needed
config_file_name = "config_fimh" ### <- set this so it updates value in output script
python_name = "python3" # <- set to e.g. python or python3 as appropriate
def hxex_reload():
importlib.reload(hxex)
importlib.reload(config)
hxex.config = config
hxex_reload()
hxex.config.Output_DIR = os.path.join(hxex.config.Data_DIR,'batchrun_'+str(config.date))
if not os.path.exists(hxex.config.Output_DIR): os.makedirs(hxex.config.Output_DIR)
print("saving output to ",hxex.config.Output_DIR)
metadf = hxex.get_metadf()
samples = metadf['sample'].unique()
### Create scripts for runs of each sample type
scripts = {}
for sample in samples:
run_dir = os.path.join(hxex.config.Output_DIR,str(sample)+"_run")
if not os.path.exists(run_dir): os.makedirs(run_dir)
filename = "run_"+str(sample)+"_"+config.date+".py"
write_file = os.path.join(run_dir,filename)
scripts[sample] = write_file
with open(write_file,"w") as p_file:
script_text = f'''
# run script for {sample}
import os
import importlib
import sys
hxex_path = os.path.join('{hxex_path}')
sys.path.append(hxex_path)
import pyhxexpress as hxex
import numpy as np, pandas as pd
import {config_file_name} as config
def hxex_reload():
importlib.reload(hxex)
importlib.reload(config)
hxex.config = config
hxex_reload()
hxex.config.Output_DIR = os.path.join("{run_dir}")
if not os.path.exists(hxex.config.Output_DIR): os.makedirs(hxex.config.Output_DIR)
print("saving output to ",hxex.config.Output_DIR)
metadf = hxex.get_metadf()
filtered = hxex.filter_df(metadf,samples="{sample}")
hxex.run_hdx_fits(filtered)
'''
#print(script_text)
p_file.write(script_text)
### Create the multiprocessing script that will pool each of the sample scripts
## based on https://medium.com/@rohitobrai11/multithreading-in-python-running-2-scripts-in-parallel-8258c4635182
mp_script_text = f'''
import threading
import subprocess
def run_script(script_name):
subprocess.run(["{python_name}", script_name])
scripts = {scripts}
if __name__ == "__main__":
script_thread = {{}}
for k,v in scripts.items():
script_thread[k] = threading.Thread(target=run_script, args=[v])
#print("value",v)
for k,v in scripts.items():
script_thread[k].start()
for k,v in scripts.items():
script_thread[k].join()
print("Batch scripts have finished executing.")
'''
#print(mp_script_text)
write_file = os.path.join(hxex.config.Output_DIR,'run_batch_'+config.date+'.py')
with open(write_file,"w") as p_file:
p_file.write(mp_script_text)
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