def get_em2d_restraint(assembly,
images_selection_file,
restraint_params,
mode="fast",
n_optimized=1):
""" Sets a restraint for comparing the model to a set of EM images
"""
model = assembly.get_model()
# Setup the restraint
sc = em2d.EM2DScore()
r = em2d.Em2DRestraint(model)
r.setup(sc, restraint_params)
names = em2d.read_selection_file(images_selection_file)
names = [base.get_relative_path(images_selection_file, x) for x in names]
log.debug("names of the images %s", names)
srw = em2d.SpiderImageReaderWriter()
imgs = em2d.read_images(names, srw)
r.set_images(imgs)
ps = atom.get_leaves(assembly)
lsc = container.ListSingletonContainer(ps)
r.set_particles(lsc)
if (mode == "coarse"):
r.set_coarse_registration_mode(True)
elif (mode == "fast"):
r.set_fast_mode(n_optimized)
elif (mode == "complete"):
pass
else:
raise ValueError("Em2DRestraint mode not recognized")
return r
def get_em2d_restraint( assembly,
images_selection_file,
restraint_params,
mode="fast",
n_optimized=1):
""" Sets a restraint for comparing the model to a set of EM images
"""
model = assembly.get_model()
# Setup the restraint
sc = em2d.EM2DScore()
r = em2d.Em2DRestraint()
r.setup(sc, restraint_params)
names = em2d.read_selection_file(images_selection_file)
names = [base.get_relative_path(images_selection_file, x) for x in names]
log.debug("names of the images %s", names)
srw = em2d.SpiderImageReaderWriter()
imgs = em2d.read_images(names, srw)
r.set_images(imgs)
ps = atom.get_leaves(assembly)
lsc = container.ListSingletonContainer(ps)
r.set_particles(lsc)
if (mode == "coarse"):
r.set_coarse_registration_mode(True)
elif (mode == "fast"):
r.set_fast_mode(n_optimized)
elif(mode == "complete"):
pass
else:
raise ValueError("Em2DRestraint mode not recognized")
return r
def get_experiment_params(fn_params):
"""
Imports the configuration file
@param fn_params configuration file
@return Experiment Class with all the infomation from the config file
"""
name, ext = os.path.splitext(fn_params)
import imp
foo = imp.load_source(name, fn_params)
exp = foo.Experiment()
# convert to absolute paths
exp.fn_pdbs = [base.get_relative_path(fn_params, fn) for fn in exp.fn_pdbs]
if hasattr(exp, "sampling_positions"):
exp.sampling_positions.read = base.get_relative_path(fn_params, exp.sampling_positions.read)
if hasattr(exp, "benchmark"):
if hasattr(exp.benchmark, "fn_pdb_native"):
exp.benchmark.fn_pdb_native = base.get_relative_path(
fn_params, exp.benchmark.fn_pdb_native)
if hasattr(exp.benchmark, "fn_pdbs_native"):
fns = []
for fn in exp.benchmark.fn_pdbs_native:
fns.append( base.get_relative_path(fn_params, fn) )
exp.benchmark.fn_pdbs_native = fns
if hasattr(exp, "dock_transforms"):
for i in range(len(exp.dock_transforms)):
exp.dock_transforms[i][2] = base.get_relative_path(fn_params, exp.dock_transforms[i][2])
if hasattr(exp, "em2d_restraints"):
for i in range(len(exp.em2d_restraints)):
exp.em2d_restraints[i][1] = base.get_relative_path(fn_params, exp.em2d_restraints[i][1])
return exp
def get_experiment_params(fn_params):
"""
Imports the configuration file
@param fn_params configuration file
@return Experiment Class with all the infomation from the config file
"""
name, ext = os.path.splitext(fn_params)
import imp
foo = imp.load_source(name, fn_params)
exp = foo.Experiment()
# convert to absolute paths
exp.fn_pdbs = [base.get_relative_path(fn_params, fn) for fn in exp.fn_pdbs]
if hasattr(exp, "sampling_positions"):
exp.sampling_positions.read = base.get_relative_path(
fn_params, exp.sampling_positions.read)
if hasattr(exp, "benchmark"):
if hasattr(exp.benchmark, "fn_pdb_native"):
exp.benchmark.fn_pdb_native = base.get_relative_path(
fn_params, exp.benchmark.fn_pdb_native)
if hasattr(exp.benchmark, "fn_pdbs_native"):
fns = []
for fn in exp.benchmark.fn_pdbs_native:
fns.append(base.get_relative_path(fn_params, fn))
exp.benchmark.fn_pdbs_native = fns
if hasattr(exp, "dock_transforms"):
for i in range(len(exp.dock_transforms)):
exp.dock_transforms[i][2] = base.get_relative_path(
fn_params, exp.dock_transforms[i][2])
if hasattr(exp, "em2d_restraints"):
for i in range(len(exp.em2d_restraints)):
exp.em2d_restraints[i][1] = base.get_relative_path(
fn_params, exp.em2d_restraints[i][1])
return exp
