# Using the current working directory is IMPORTANT with the default settings for Job()
#$ -cwd
#$ -m e
# $Id$
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(inputfiles=dict(density='analysis/water.pickle',
bulk='analysis/bulk.pickle',
psf='inp/XXX.psf',
dcd='trj/rmsfit_XXX.dcd'),
outputfiles=dict(
density='analysis/water.pickle',
hopdcd='trj/hoptraj.dcd',
hoppsf='trj/hoptraj.psf',
))
#
#------------------------------------------------------------
job.stage()
# commands
import hop.utilities
hop.utilities.matplotlib_interactive(False)
from hop.interactive import *
from hop.sitemap import Density
#$ -j y
# Using the current working directory is IMPORTANT with the default settings for Job()
#$ -cwd
#$ -m e
# $Id$
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(inputfiles=dict(psf = '1IFC/inp/XXX.psf',
dcd = '1IFC/trj/rmsfit_XXX.dcd'),
outputfiles=dict(water = '1IFC/analysis/water.pickle',
bulk = '1IFC/analysis/bulk.pickle',
dx = '1IFC/analysis/*.dx',
))
#
#------------------------------------------------------------
job.stage()
F = job.filenames
V = job.variables
# commands
import hop.utilities
hop.utilities.matplotlib_interactive(False)
from hop.interactive import *
* creates hopping graph
* exports xgml file
* initial analysis and statistics
"""
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(inputfiles=dict(
hopdcd='trj/hops.dcd',
hoppsf='trj/hops.psf',
density='analysis/water.pickle',
),
outputfiles=dict(
xgmmlfiles='analysis/*.xgmml',
hopgraph='analysis/hopgraph.pickle',
survivaltimes='analysis/survival_times/*.png',
))
#
#------------------------------------------------------------
job.stage()
# commands
import hop.utilities
hop.utilities.matplotlib_interactive(False) # no X11 available
from hop.interactive import build_hoppinggraph_fromfiles
"\tSTATE=%(STATE)s topdir=%(topdir)s\n"\
"\tpsf=%(psf)s\n"\
"\tdcd=%(dcd)s" % locals()
job = Job(
variables=dict(
trj=STATE, # compute hop traj for trj = apo | holo HOP_TARGET
survival_times_dir=survival_times_dir,
),
inputfiles=dict(
dens_apo=APO_DIR('analysis',
'water_' + ID + '.pickle'), # is modified!
dens_holo=HOLO_DIR('analysis', 'water_' + ID + '.pickle'),
psf=psf,
dcd=dcd,
),
outputfiles=dict(
equiv_graph=FIGS_DIR('equivalence_graph_1.png'),
saved_apo=APO_DIR('analysis', '*.pickle'),
saved_holo=HOLO_DIR('analysis', 'water_remapped_1IFC.pickle'),
hopdcd=TRJ_DIR('hoptrj.dcd'),
hoppsf=TRJ_DIR('hoptrj.psf'),
hopgraph=ANALYSIS_DIR('hopgraph_' + ID + '.pickle'),
xgmml=ANALYSIS_DIR('*.xgmml'),
survivaltimes=os.path.join(survival_times_dir, '*.png'),
),
)
#
#------------------------------------------------------------
job.stage()
F = job.filenames
#$ -v PYTHONPATH=/home/oliver/Library/python-lib #$ -v LD_LIBRARY_PATH=/opt/intel/cmkl/8.0/lib/32:/opt/intel/itc60/slib:/opt/intel/ipp41/ia32_itanium/sharedlib:/opt/intel/ipp41/ia32_itanium/sharedlib/linux32:/opt/intel/fc/9.0/lib:/opt/intel/cc/9.0/lib #$ -r n #$ -j y # Using the current working directory is IMPORTANT with the default settings for Job() #$ -cwd #$ -m e # $Id$ from staging.SunGridEngine import Job #------------------------------------------------------------ # EDIT THE inputfiles AND outputfiles DICTIONARIES. #------------------------------------------------------------ # record input and output files relative to top_dir = cwd job = Job(variables=dict(), inputfiles=dict(), outputfiles=dict()) # #------------------------------------------------------------ job.stage() F = job.filenames V = job.variables # commands import hop.utilities # must come first (for reasons unknown) hop.utilities.matplotlib_interactive(False) # no X11 available import hop.analysis job.unstage() job.cleanup()
def TRJ_DIR(*args):
return os.path.join(GSBP_MD_DIR, *args)
psf_files = glob.glob(TRJ_DIR('*_gsbp_*.psf'))
psf_files.sort()
#ifabp_apo_gsbp_15_0.psf ifabp_apo_gsbp_gcmc_1.psf
psf = psf_files[-1]
dcd_files = glob.glob(TRJ_DIR('rmsfit_*_1.dcd'))
dcd_files.sort()
dcd = dcd_files[-1]
job = Job(inputfiles=dict(psf=psf, dcd=dcd),
outputfiles=dict(dx='analysis/*.dx',
water_saved='analysis/water_' + id + '.pickle',
bulk_saved='analysis/bulk_' + id + '.pickle'))
#
#------------------------------------------------------------
job.stage()
# commands
import hop.utilities
hop.utilities.matplotlib_interactive(False)
from hop.interactive import *
density = make_density(job.filenames['psf'],
job.filenames['dcd'],
job.filenames['water_saved'],
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(variables=dict(),
inputfiles=dict(
psf="",
trj="",
hoppsf="",
hoptrj="",
density="",
),
outputfiles=dict(
fig_distance="figs/site_distance.pdf",
fig_orbit="figs/site_orbit.pdf",
fig_distance2="figs/site_distance2.pdf",
fig_orbit2="figs/site_orbit2.pdf",
fig_occupancy="figs/site_occupancy.pdf",
fig_orbitoccupancy="figs/site_orbitoccupancy.pdf",
saved="analysis/siteanalysis.pickle",
))
#
#------------------------------------------------------------
job.stage()
F = job.filenames
V = job.variables
# commands
# $Id: markovsampling.py 2044 2008-07-22 19:21:12Z oliver $
"""Run 20 independent Pscans to check convergence of MCMC model with Ntotal."""
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(variables=dict(
repeats=20,
parameter='Ntotal',
pvalues=[
3e3, 5e3, 8e3, 1e4, 3e4, 5e4, 8e4, 1e5, 3e5, 5e5, 8e5, 1e6, 5e6, 1e7,
3e7
],
),
inputfiles=dict(hopgraph='analysis/hopgraph.pickle'),
outputfiles=dict(
scan='analysis/pscan_Ntotal.pickle',
scanfig='figs/pscan_Ntotal.pdf',
))
#
#------------------------------------------------------------
job.stage()
F = job.filenames
V = job.variables
# commands
import hop.utilities # must come first (for reasons unknown)
hop.utilities.matplotlib_interactive(False) # no X11 available
#---------------- EDIT JOB NAME ------------------- #$ -N gsbpRMSfit #-------------------------------------------------- #$ -S /usr/bin/python # Importing the whole environment is important for setting up Charmm: #$ -V #$ -v PYTHONPATH=/home/oliver/Library/python-lib #$ -v LD_LIBRARY_PATH=/opt/intel/cmkl/8.0/lib/32:/opt/intel/itc60/slib:/opt/intel/ipp41/ia32_itanium/sharedlib:/opt/intel/ipp41/ia32_itanium/sharedlib/linux32:/opt/intel/fc/9.0/lib:/opt/intel/cc/9.0/lib #$ -r n #$ -j y # Using the current working directory is IMPORTANT with the default settings for Job() #$ -cwd #$ -m e # $Id$ # """RMS-fit a GSBP trajectory (with fixed atoms and gaps in the protein) to a reference structure. This requires a sequence alignment, the reference, and the trajectory. All intermediate steps such as creating the initial aligned frame (using MDAnalysis) are performed, as is the actual fitting using Charmm with the CONSFIX=1 ORIENT=1 options. Currently, this is geared towards GSBP_MD simulations. Set GSBP_MD_DIR in the environment or with qsub -v GSBP_MD_DIR=./GSBP_MD_1 rmsfit_gsbp.py It automatically find the psf file for the dcd in GSBP_MD_DIR, but other values have to be set in Job() as usual. """ from staging.SunGridEngine import Job
# $Id$
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(
inputfiles=dict(
psf='inp/XXX.psf',
dcd='trj/rmsfit_XXX.dcd',
bulkdensity='analysis/bulk.pickle', # remove if needs computing
),
outputfiles=dict(TAP_dcd='trj/TAP_rmsfit_XXX.dcd',
dx='analysis/*.dx',
waterdensity='analysis/water_TAP.pickle',
bulkdensity_saved='analysis/bulk.pickle'),
variables=dict(
water_selection="name OH2",
rho_cut=2.72,
rho_cut_bulk=0.6,
))
#
#------------------------------------------------------------
job.stage()
F = job.filenames
V = job.variables
# commands
#$ -j y
# Using the current working directory is IMPORTANT with the default settings for Job()
#$ -cwd
#$ -m e
# $Id$
from staging.SunGridEngine import Job
# from staging.Local import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(inputfiles=dict(hg_apo = '1IFC/analysis/hopgraph.pickle',
hg_holo = '2IFB/analysis/hopgraph.pickle'),
outputfiles=dict(cg = 'analysis/cg_1IFC_2IFB.pickle',
png = 'fig/*.png') )
#
#------------------------------------------------------------
job.stage()
# commands
import hop.utilities # must come first (for reasons unknown)
hop.utilities.matplotlib_interactive(False) # no X11 available
import hop.sitemap,hop.graph
class Struct:
pass
"""Align coordinate to reference, using a fasta alignment to find the
common atoms."""
from staging.SunGridEngine import Job
#from staging.Local import Job
job = Job(inputfiles=dict(
sequence='sequences/1IFC_R151IFC.fasta',
ref_psf='coord/1ifc_xtal.psf',
ref_pdb='coord/1ifc_xtal.pdb',
trj_psf='GSBPsetup/ifabp_apo_gsbp_15_0.psf',
trj_pdb='GSBPsetup/ifabp_apo_gsbp_15_0.pdb',
),
outputfiles=dict(
fit_pdb='GSBPsetup/rmsfit_ifabp_apo_gsbp_15_0.pdb', ))
job.stage()
from MDAnalysis import Universe
import hop.trajectory
print "Setting up the Universes..."
ref = Universe(job.filenames['ref_psf'], pdbfilename=job.filenames['ref_pdb'])
trj = Universe(job.filenames['trj_psf'], job.filenames['trj_pdb'])
ref_resids = [a.resid for a in ref.selectAtoms('name CA')]
target_resids = [a.resid for a in trj.selectAtoms('name CA')]
print "Alignment and selection string..."
selection = hop.trajectory.fasta2select(job.filenames['sequence'],
ref_resids=ref_resids,
# see http://gonzo.med.jhmi.edu/woolfwiki/index.php/Making_proteins_whole_in_LAMMPS_trajectories
#
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(inputfiles=dict(
HEADER='str/header.str',
PSF='inp/ifabp_apo_100mM_charmm.psf',
DCD='trj/ifabp_apo_100mM_0-20ns_dt1ns.dcd',
REF_PDB='coord/1ifc_xtal.pdb',
),
outputfiles=dict(
DCD_RMS='trj/rmsfit_ifabp_apo_100mM_0-20ns_dt1ns.dcd',
RESINDEX='inp/ifabp_apo_100mM_charmm.resindex',
LOG_1='log/1_remap.log',
LOG_2='log/2_unfold.log',
LOG_3='log/3_remap.log',
LOG_4='log/4_orient.log',
))
#
#------------------------------------------------------------
job.stage()
#------------------------------------------------------------
# python script proper starts here
# (build commandlines using python named string interpolation)
#
#$ -j y
# Using the current working directory is IMPORTANT with the default settings for Job()
#$ -cwd
#$ -m e
# $Id$
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(inputfiles=dict(dens_apo='1IFC/analysis/water.pickle',
dens_holo='2IFB/analysis/water.pickle'),
outputfiles=dict(
saved_apo='1IFC/analysis/water.pickle',
saved_holo='2IFB/analysis/water_remapped_1IFC.pickle',
graph='figs/equivalence_graph.png',
sitestats_apo='1IFC/figs/sitestats.pdf',
sitestats_holo='2IFB/figs/sitestats.pdf'))
#
#------------------------------------------------------------
job.stage()
# commands
import hop.utilities # must come first (for reasons unknown)
hop.utilities.matplotlib_interactive(False) # no X11 available
import hop.sitemap
TOP_DIR('analysis', 'water_remapped*_' + id + '.pickle'))
if len(density_files) == 0:
density_files = glob.glob(TOP_DIR('analysis', 'water_' + id + '.pickle'))
density_files.sort()
# 2IFB/analysis/water_1.pickle 2IFB/analysis/water_remapped_1IFC_1.pickle
density = density_files[-1] # pick remapped if available
job = Job(variables=dict(),
inputfiles=dict(
psf=psf,
trj=dcd,
hoppsf=TRJ_DIR('hoptrj.psf'),
hoptrj=TRJ_DIR('hoptrj.dcd'),
density=density,
),
outputfiles=dict(
fig_distance=TOP_DIR('figs', 'site_distance_' + id + '.pdf'),
fig_orbit=TOP_DIR('figs', 'site_orbit_' + id + '.pdf'),
fig_distance2=TOP_DIR('figs', 'site_distance2_' + id + '.pdf'),
fig_orbit2=TOP_DIR('figs', 'site_orbit2_' + id + '.pdf'),
fig_occupancy=TOP_DIR('figs', 'site_occupancy_' + id + '.pdf'),
fig_orbitoccupancy=TOP_DIR('figs',
'site_orbitoccupancy_' + id + '.pdf'),
saved=TOP_DIR('analysis', 'siteanalysis_' + id + '.pickle'),
))
#
#------------------------------------------------------------
job.stage()
F = job.filenames
V = job.variables
# commands
ref_dir = os.path.join(top_dir, 'FABP', 'I-FABP', '1IFC', 'coord')
ref_psf = os.path.join(ref_dir, '1ifc_xtal.psf')
ref_pdb = os.path.join(ref_dir, '1ifc_xtal.pdb')
trj_dir = os.path.join(top_dir, 'FABP', 'I-FABP', '1IFC', 'GSBP', 'NVT')
trj_psf = os.path.join(trj_dir, 'inp', 'ifabp_gsbp_15_0.psf')
trj_dcd = os.path.join(trj_dir, 'trj', 'ifabp_gsbp_15_1.dcd')
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(inputfiles=dict(
sequence=seq_fasta,
ref_psf=ref_psf,
ref_pdb=ref_pdb,
trj_psf=trj_psf,
trj_dcd=trj_dcd,
),
outputfiles=dict(fit_dcd='trj/rmsfit_*.dcd', ))
#
#------------------------------------------------------------
job.stage()
from MDAnalysis import Universe
import hop.trajectory
print "Alignment and selection string..."
selection = hop.trajectory.fasta2select(seq_fasta, is_aligned=True)
print "Setting up the Universes..."
#$ -j y
# Using the current working directory is IMPORTANT with the default settings for Job()
#$ -cwd
#$ -m e
# $Id$
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(variables=dict(state='apo'),
inputfiles=dict(hopgraph='analysis/hopgraph.pickle'),
outputfiles=dict(
scan='analysis/pscan.pickle',
occupancy_pdf='figs/mcmc_occupancy.pdf',
correl_pdf='figs/mcmc_occupancy_correl.pdf',
))
#
#------------------------------------------------------------
job.stage()
F = job.filenames
V = job.variables
# commands
import hop.utilities # must come first (for reasons unknown)
hop.utilities.matplotlib_interactive(False) # no X11 available
import hop.MCMC
from pylab import *
# Using the current working directory is IMPORTANT with the default settings for Job()
#$ -cwd
#$ -m e
# $Id$
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(inputfiles=dict(HEADER='str/header.str',
PSF='inp/crbp_apo.psf',
DCD='trj/1opa_salt_ewald_shake_10ang_prod.dcd',
REF_PDB='coord/rmsfit_1opa_a_xtal.pdb',
),
outputfiles=dict(DCD_RMS='trj/rmsfit_1opa_salt_ewald_shake_10ang_prod.dcd',
CHARMM_LOG='log/rmsfit.log',
))
#
#------------------------------------------------------------
job.stage()
# commands
import os
# This setup requires my canonical filesystem layout under CHARMM:
if not 'CHARMM' in os.environ: # get sane value for CHARMM top dir
os.environ['CHARMM'] = os.path.join(os.environ['BIO_D'],'Library','Charmm')
os.environ['CHARMM_TOP'] = os.path.join(os.environ['CHARMM'],'toppar')
# Using the current working directory is IMPORTANT with the default settings for Job()
#$ -cwd
#$ -m e
# $Id$
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(variables=dict(state='apo'),
inputfiles=dict(hopgraph='analysis/hopgraph.pickle'
),
outputfiles=dict(scan = 'analysis/pscan.pickle',
occupancy_pdf = 'figs/mcmc_occupancy.pdf',
correl_pdf = 'figs/mcmc_occupancy_correl.pdf',
))
#
#------------------------------------------------------------
job.stage()
F = job.filenames
V = job.variables
# commands
import hop.utilities # must come first (for reasons unknown)
hop.utilities.matplotlib_interactive(False) # no X11 available
import hop.MCMC
from pylab import *
# Using the current working directory is IMPORTANT with the default settings for Job()
#$ -cwd
#$ -m e
# $Id$
from staging.SunGridEngine import Job
#------------------------------------------------------------
# EDIT THE inputfiles AND outputfiles DICTIONARIES.
#------------------------------------------------------------
# record input and output files relative to top_dir = cwd
job = Job(inputfiles=dict(dens_apo = '1IFC/analysis/water.pickle',
bulk_apo = '1IFC/analysis/bulk.pickle',
dens_holo = '2IFB/analysis/water.pickle',
bulk_holo = '2IFB/analysis/bulk.pickle',
),
outputfiles=dict(scan = 'analysis/scan.pickle',
scan_pdf = 'figs/scan.pdf',
))
#
#------------------------------------------------------------
job.stage()
F = job.filenames
# commands
import hop.utilities # must come first (for reasons unknown)
hop.utilities.matplotlib_interactive(False) # no X11 available
import hop.analysis
import numpy