Test your AI Agents with the all-new Agent to Agent Testing Platform.Learn More

How to use scavenge method in prospector

Best Python code snippet using prospector_python

scr_scavenge.py

Source:scr_scavenge.py

...12from scrjob.scr_environment import SCR_Env13from scrjob.resmgrs import AutoResourceManager14from scrjob.launchers import AutoJobLauncher15# check for pdsh / (clustershell) errors in case any nodes should be retried16def scr_scavenge(nodeset_job=None,17                 nodeset_up='',18                 nodeset_down='',19                 dataset_id=None,20                 cntldir=None,21                 prefixdir=None,22                 verbose=False,23                 scr_env=None,24                 log=None):25  """This script is invoked to perform a scavenge operation26  scr_scavenge.py is a wrapper to gather values and arrange parameters needed for27  a scavenge operation.28  When ready, the scavenge parameters are passed to the Joblauncher class to perform29  the scavenge operation.30  The output of the scavenge operation is both written to file and printed to screen.31  This script returns 1 if a needed value or parameter could not be determined,32  and returns 0 otherwise33  """34  # check that we have a nodeset for the job and directories to read from / write to35  if nodeset_job is None or dataset_id is None or cntldir is None or prefixdir is None:36    return 137  bindir = scr_const.X_BINDIR38  # TODO: need to be able to set these defaults via config settings somehow39  # for now just hardcode the values40  if scr_env is None:41    scr_env = SCR_Env(prefix=prefixdir)42  if scr_env.param is None:43    scr_env.param = SCR_Param()44  if scr_env.resmgr is None:45    scr_env.resmgr = AutoResourceManager()46  if scr_env.launcher is None:47    scr_env.launcher = AutoJobLauncher()48  # lookup buffer size and crc flag via scr_param49  param = scr_env.param50  buf_size = os.environ.get('SCR_FILE_BUF_SIZE')51  if buf_size is None:52    buf_size = str(1024 * 1024)53  crc_flag = os.environ.get('SCR_CRC_ON_FLUSH')54  if crc_flag is None:55    crc_flag = '--crc'56  elif crc_flag == '0':57    crc_flag = ''58  start_time = int(time())59  # tag output files with jobid60  jobid = scr_env.resmgr.getjobid()61  if jobid is None:62    print('scr_scavenge: ERROR: Could not determine jobid.')63    return 164  # build the output filenames65  dset_dir = scr_env.dir_dset(dataset_id)66  output = os.path.join(dset_dir, 'scr_scavenge.pdsh.o' + jobid)67  error = os.path.join(dset_dir, 'scr_scavenge.pdsh.e' + jobid)68  if verbose:69    print('scr_scavenge: nodeset_up =   ' + nodeset_up)70    print('scr_scavenge: nodeset_down = ' + nodeset_down)71  # format up and down nodesets for the scavenge command72  nodeset_up, nodeset_down = scr_env.resmgr.get_scavenge_nodelists(73      upnodes=nodeset_up, downnodes=nodeset_down)74  if verbose:75    print('scr_scavenge: upnodes =          ' + nodeset_up)76    print('scr_scavenge: downnodes_spaced = ' + nodeset_down)77  # log the start of the scavenge operation78  if log:79    log.event('SCAVENGE_START', dset=dataset_id)80  print('scr_scavenge: ' + str(int(time())))81  # have the launcher class gather files via pdsh or clustershell82  consoleout = scr_env.launcher.scavenge_files(prog=bindir + '/scr_copy',83                                               upnodes=nodeset_up,84                                               downnodes_spaced=nodeset_down,85                                               cntldir=cntldir,86                                               dataset_id=dataset_id,87                                               prefixdir=prefixdir,88                                               buf_size=buf_size,89                                               crc_flag=crc_flag)90  # print outputs to screen91  try:92    os.makedirs('/'.join(output.split('/')[:-1]), exist_ok=True)93    with open(output, 'w') as outfile:94      outfile.write(consoleout[0])95    if verbose:96      print('scr_scavenge: stdout: cat ' + output)97      print(consoleout[0])98  except Exception as e:99    print(str(e))100    print('scr_scavenge: ERROR: Unable to write stdout to \"' + output + '\"')101  try:102    with open(error, 'w') as outfile:103      outfile.write(consoleout[1])104    if verbose:105      print('scr_scavenge: stderr: cat ' + error)106      print(consoleout[1])107  except Exception as e:108    print(str(e))109    print('scr_scavenge: ERROR: Unable to write stderr to \"' + error + '\"')110  # TODO: if we knew the total bytes, we could register a transfer here in addition to an event111  # get a timestamp for logging timing values112  end_time = int(time())113  diff_time = end_time - start_time114  if log:115    log.event('SCAVENGE_END', dset=dataset_id, secs=diff_time)116  return 0117if __name__ == '__main__':118  parser = argparse.ArgumentParser(add_help=False,119                                   argument_default=argparse.SUPPRESS,120                                   prog='scr_scavenge')121  parser.add_argument('-h',122                      '--help',123                      action='store_true',124                      help='Show this help message and exit.')125  parser.add_argument('-v',126                      '--verbose',127                      action='store_true',128                      default=False,129                      help='Verbose output.')130  parser.add_argument('-j',131                      '--jobset',132                      metavar='<nodeset>',133                      type=str,134                      default=None,135                      help='Specify the nodeset.')136  parser.add_argument('-u',137                      '--up',138                      metavar='<nodeset>',139                      type=str,140                      default=None,141                      help='Specify up nodes.')142  parser.add_argument('-d',143                      '--down',144                      metavar='<nodeset>',145                      type=str,146                      default=None,147                      help='Specify down nodes.')148  parser.add_argument('-i',149                      '--id',150                      metavar='<id>',151                      type=str,152                      default=None,153                      help='Specify the dataset id.')154  parser.add_argument('-f',155                      '--from',156                      metavar='<dir>',157                      type=str,158                      default=None,159                      help='The control directory.')160  parser.add_argument('-t',161                      '--to',162                      metavar='<dir>',163                      type=str,164                      default=None,165                      help='The prefix directory.')166  args = vars(parser.parse_args())167  if 'help' in args:168    parser.print_help()169  elif args['jobset'] is None or args['id'] is None or args[170      'from'] is None or args['to'] is None:171    parser.print_help()172    print('Required arguments: --jobset --id --from --to')173  else:174    ret = scr_scavenge(nodeset_job=args['jobset'],175                       nodeset_up=args['up'],176                       nodeset_down=args['down'],177                       dataset_id=args['id'],178                       cntldir=args['from'],179                       prefixdir=args['to'],180                       verbose=args['verbose'],181                       scr_env=None)...

optimization_run.py

Source:optimization_run.py

1#!/usr/bin/env python32import os3import sys4import random5import time6from random import seed, randint7import argparse8import platform9from datetime import datetime10# import imp11import glob12from time import sleep13import fileinput14import numpy as np15import pandas as pd16import subprocess17from small_script.myFunctions import *18from collections import defaultdict19parser = argparse.ArgumentParser(description="Compute phis under the optimization folder")20# parser.add_argument("DatabaseFolder", help="your database folder")21# parser.add_argument("OptimizationFolder", help="your optimization folder")22parser.add_argument("-m", "--mode", type=int, default=0)23parser.add_argument("-l", "--label", type=str, default="label")24parser.add_argument("-s", "--subMode", type=int, default=0)25parser.add_argument("-n", "--n_decoys", type=int, default=10)26args = parser.parse_args()27# if args.test:28#     do = print29# else:30#     do = os.system31with open('log_optimization_run.txt', 'a') as f:32    f.write(' '.join(sys.argv))33    f.write('\n')34from pyCodeLib import *35import warnings36warnings.filterwarnings('ignore')37scavenge_slurm = '''\38#!/bin/bash39#SBATCH --job-name=CTBP_WL40#SBATCH --account=commons41#SBATCH --partition=scavenge42#SBATCH --ntasks=143#SBATCH --threads-per-core=144#SBATCH --cpus-per-task=145#SBATCH --mem-per-cpu=1G46#SBATCH --time=04:00:0047#SBATCH --mail-user=luwei0917@gmail.com48#SBATCH --mail-type=FAIL49#SBATCH -o outs/slurm-%j.out50echo "My job ran on:"51echo $SLURM_NODELIST52srun {}\n'''53base_slurm = '''\54#!/bin/bash55#SBATCH --job-name=CTBP_WL56#SBATCH --account=ctbp-common57#SBATCH --partition=ctbp-common58#SBATCH --ntasks=159#SBATCH --threads-per-core=160#SBATCH --mem-per-cpu=1G61#SBATCH --time=1-00:00:0062#SBATCH --mail-user=luwei0917@gmail.com63#SBATCH --mail-type=FAIL64#SBATCH -o outs/slurm-%j.out65echo "My job ran on:"66echo $SLURM_NODELIST67srun {}\n'''68n_decoys = args.n_decoys69separateDecoysNum = -170# template = base_slurm71template = scavenge_slurm72def do(cmd, get=False, show=True):73    if get:74        out = subprocess.Popen(cmd,stdout=subprocess.PIPE,shell=True).communicate()[0].decode()75        if show:76            print(out, end="")77        return out78    else:79        return subprocess.Popen(cmd, shell=True).wait()80cd = os.chdir81def slurmRun(slurmFileName, cmd, template=scavenge_slurm, memory=1):82    with open(slurmFileName, "w") as out:83        out.write(template.format(cmd))84        # out.write(scavenge_slurm.format(f"python3 ~/opt/compute_phis.py -m 1 proteins_name_list/proteins_name_list_{name}.txt"))85    replace(slurmFileName, "#SBATCH --mem-per-cpu=1G", f"#SBATCH --mem-per-cpu={memory}G")86    a = getFromTerminal(f"sbatch {slurmFileName}")87    jobId = a.split(" ")[-1].strip()88    return jobId89def waitForJobs(jobIdList, sleepInterval=30):90    from datetime import datetime as dt91    if len(jobIdList) == 0:92        return93    previousJobNotFinished = True94    while previousJobNotFinished:95        print(f"Waiting for previous jobs {jobIdList}", dt.now())96        time.sleep(sleepInterval)97        previousJobNotFinished = False98        a = getFromTerminal("squeue -u wl45")99        for jobId in jobIdList:100            if jobId in a:101                previousJobNotFinished = True102    print("Continue Next Script")103if args.mode == 1:104    # time.sleep(36000)105    with open("protein_list") as f:106        content = f.readlines()107    pos = 0108    i = 0109    n = len(content)110    # n = 100  # for testing111    while pos < n:112        with open(f"proteins_name_list/proteins_name_list_{i}.txt", "w") as out:113            for ii in range(1):114                if pos < n:115                    out.write(content[pos])116                pos += 1117            i += 1118    print(i)119    n = i120    i = 0121    jobIdList = []122    for i in range(n):123        proteins = f"proteins_name_list/proteins_name_list_{i}.txt"124        # generate_decoy_sequences(proteins, methods=['shuffle'], num_decoys=[n_decoys], databaseLocation="../../../")125        jobId = slurmRun(f"slurms/run_{i}.slurm", f"python3 ~/opt/optimization_run.py -m 222 -l {proteins} -s {args.subMode}", template=template)126        # jobId = slurmRun(f"slurms/run_{i}.slurm", f"python3 ~/opt/compute_phis.py -m 0 proteins_name_list/proteins_name_list_{i}.txt")127        jobIdList.append(jobId)128        do(f"cat {proteins} >> iter0_complete.txt")129    # exit()130    waitForJobs(jobIdList, sleepInterval=300)131    with open(f"slurms/run_on_scavenge.slurm", "w") as out:132        out.write(base_slurm.format(f"python3 ~/opt/optimization_run.py -m 4 -s {args.subMode}"))133    replace(f"slurms/run_on_scavenge.slurm", "#SBATCH --mem-per-cpu=1G", "#SBATCH --mem-per-cpu=60G")134    do(f"sbatch slurms/run_on_scavenge.slurm")135if args.mode == 22:136    protein = args.label137    do(f"python3 ~/opt/compute_phis.py -m 0 {protein}")138    # do("python3 ~/opt/compute_phis.py -m 0 test_protein")139if args.mode == 222:140    proteins = args.label141    if args.subMode == 0:142        evaluate_phis_over_training_set_for_native_structures_Wei(proteins, "phi_list.txt",143                    decoy_method='shuffle', max_decoys=1e+10, tm_only=False, num_processors=1, separateDecoysNum=separateDecoysNum)144    if args.subMode == 1:145        evaluate_phis_over_training_set_for_decoy_structures_Wei(proteins, "phi_list.txt",146                    decoy_method='rosetta', max_decoys=1e+10, tm_only=False, num_processors=1, pickle=True, withBiased=False, mode=0)147if args.mode == 3:148    with open(f"slurms/run_on_scavenge.slurm", "w") as out:149        out.write(scavenge_slurm.format(f"python3 ~/opt/optimization_run.py -m 4"))150    replace(f"slurms/run_on_scavenge.slurm", "#SBATCH --mem-per-cpu=1G", "#SBATCH --mem-per-cpu=60G")151    do(f"sbatch slurms/run_on_scavenge.slurm")152if args.mode == 4:153    if args.subMode == 0:154        decoy_method = "shuffle"155    if args.subMode == 1:156        decoy_method = "rosetta"157    # complete_proteins = "iter0.txt"158    complete_proteins = "protein_list"159    # A, B, gamma, filtered_B, filtered_gamma, filtered_lamb, P, lamb = calculate_A_B_and_gamma_parallel(complete_proteins, "phi_list.txt", decoy_method='shuffle',160    #                                 num_decoys=1000, noise_filtering=True, jackhmmer=False, subset=None, read=2)161    A, B, gamma, filtered_B, filtered_gamma, filtered_lamb, P, lamb = calculate_A_B_and_gamma_wl45(complete_proteins, "phi_list.txt", decoy_method=decoy_method,162                                    num_decoys=n_decoys, noise_filtering=True, jackhmmer=False, read=False, mode=0, multiSeq=False)163# if args.mode == 44:164#     with open(f"slurms/run_on_scavenge.slurm", "w") as out:165#         out.write(base_slurm.format(f"python3 ~/opt/gg_server.py -d jun10 -m 4"))166#     replace(f"slurms/run_on_scavenge.slurm", "#SBATCH --mem-per-cpu=1G", "#SBATCH --mem-per-cpu=60G")...

__init__.py

Source:__init__.py

1from ew.static import cfg as ewcfg2from . import juviecmds34cmd_map = {56    # Crush a poudrin to get some slime.7    ewcfg.cmd_crush: juviecmds.crush,8    ewcfg.cmd_crush_alt1: juviecmds.crush,910    # move from juvenile to one of the armies (rowdys or killers)11    ewcfg.cmd_enlist: juviecmds.enlist,12    ewcfg.cmd_renounce: juviecmds.renounce,1314    # gives slime to the miner (message.author)15    ewcfg.cmd_mine: juviecmds.mine,1617    # flags a vein as dangerous18    ewcfg.cmd_flag: juviecmds.flag,1920    # scavenging21    ewcfg.cmd_scavenge: juviecmds.scavenge,22    ewcfg.cmd_scavenge_alt1: juviecmds.scavenge,23    ewcfg.cmd_scavenge_alt2: juviecmds.scavenge,24    25    # LOL26    ewcfg.cmd_juviemode: juviecmds.juviemode,2728    # gender??? OMG???29    ewcfg.cmd_identify: juviecmds.identify,
...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.